Type 2 diabetes mellitus (T2DM) is known to be associated with increased cardiovascular risk. The aim of this study was therefore to investigate the independent effects of hyperglycaemia, hypoglycaemia, and glucose variability on microvascular and macrovascular disease in T2DM. 1c measurement, as well as 72-hour continuous glucose monitoring. Macrovascular disease was defined as one or more of the following: history of ischaemic heart disease (IHD), cerebrovascular accident (CVA), ABI < 0.9, or abnormal CIMT.  Subjects with T2DM of <10 years duration and on stable antiglycaemic treatment underwent carotid intima-media thickness (CIMT), ankle-brachial index (ABI), albumin-creatinine ratio (ACR), and HbAp = 0.006) and duration of blood glucose (BG) < 3.9 mmol/L (OR 1.12 (95% CI 1.014–1.228), p = 0.024) were independent predictors of macrovascular disease. BSA (OR 12.6 (95% CI 1.70–93.54), p = 0.013) and duration of BG < 3.9 mmol/L (OR 1.09 (95% CI 1.003–1.187), p = 0.041) were independent predictors of abnormal CIMT. Area under the curve for BG > 7.8 mmol/L  was the sole independent predictor of albuminuria in generalised linear regression.  The study population comprised 121 subjects with T2DM . The mean age was 62.6 years, and the mean DM duration was 3.7 years. Macrovascular disease was present in 71 patients (58.7%). In multivariate logistic regression analysis, body surface area (BSA) (OR 18.88 (95% CI 2.20–156.69),  This study demonstrates that hypoglycaemia is associated with the occurrence of atherosclerotic disease while hyperglycaemia is associated with microvascular disease in a Caucasian population with T2DM of recent duration. Diabetes is known to be associated with both microvascular and macrovascular disease . Whilst 1c with cardiovascular events, including mortality [1c, it is likely that the hypoglycaemic group also had more hyperglycaemia, which might conceivably have contributed to increased intima-media thickness.One possible explanation for this discrepancy is the detrimental effect of hypoglycaemia. Östgren and colleagues have recently reported a U-shaped relationship of HbAortality . A recenortality . Furtherortality , 7 The tortality , 9 and tortality . Howeverortality , this isortality , whilst ortality . Furtherortality . HoweverAnother possible explanation of the failure of clinical trials to demonstrate a beneficial effect of glycaemic control is that none of them targeted reducing fluctuations in blood glucose. Indeed, many forms of treatment may increase blood glucose fluctuations. Acute fluctuations in blood glucose have been shown to be associated with increased mortality . This ma1c and fructosamine served as additional glycaemic indexes.The aim of this study was therefore to investigate the independent effects of hyperglycaemia, hypoglycaemia, and glucose variability on microvascular and macrovascular disease in type 2 diabetes. Urinary albumin-creatinine served as a marker of microvascular disease. Ankle-brachial index, carotid intima-media thickness, and documented cardiovascular disease served as markers of macrovascular disease. 72-hour continuous glucose monitoring was used to assess hypoglycaemia, hyperglycaemia, and glucose variability. HBAThe study was cross-sectional in nature; data collection was performed over a one-year period, from April 2015 to April 2016. Patients were randomly selected from the list of outpatients attending the Diabetes Centre, Mater Dei Hospital, Malta, during the year 2014. The inclusion criteria were subjects who were diagnosed with type 2 DM according to World Health Organization criteria within the last ten years and were on stable antiglycaemic treatment. Patients suffering from dementia or mental illnesses with the consequent inability to give an informed consent with regard to participation in the study were excluded from the study. Other exclusion criteria included recent admission to hospital with a diabetes-related complication such as hyperglycaemic hyperosmolar ketoacidosis, liver failure, or kidney failure, as well as any other factors that result in glycaemic fluctuations. The study protocol was approved by the University of Malta Research Ethics Committee. All participants gave written informed consent.The presence of history of ischaemic heart disease and of cerebrovascular disease was ascertained by use of a questionnaire and by review of medical notes. Height and weight were measured using a calibrated balance and a stadiometer, with the subjects wearing light clothing and without shoes. Body mass index (BMI) was calculated as weight divided by height squared. Waist circumference was measured to the nearest 0.5 cm in the horizontal plane at the midpoint between the lowest rib and the iliac crest . The wai1c (measured using high-performance liquid chromatography) and fructosamine were taken as markers of glycaemic control. Urine albumin was measured by an immunoturbidometric technique . Creatinine was measured by a kinetic colorimetric test using the Jaffe reaction (Roche Diagnostics). Albumin-creatinine ratio (ACR) was assessed in all patients as a marker of microvascular disease. Body surface area was provided by the Esaote machine used to perform CIMT by inputting weight and height.All subjects underwent routine blood investigations in the fasting state on the day of the clinical examination. No medication was taken on the morning of the examination. Patients who were treated with insulin discontinued injections after 22:00 on the day preceding the examination. Estimated glomerular filtration rate (eGFR) was calculated using the Modified Diet in Renal Disease (MDRD) formula . Haemoglobin ASeventy-two-hour subcutaneous continuous glucose monitoring (CGM) was performed in all study participants on an ambulatory basis using the iPro2 continuous glucose-monitoring system . Participants were advised to pursue their normal daily living without alterations in their usual diet, exercise, and medications taken. Data from the iPro2 were uploaded online via the CareLink iPro software. The following parameters were extracted for each patient: mean blood glucose (MBG), standard deviation of blood glucose (SD), the highest and lowest blood glucose values, the number of high and low excursions, the area under the curve when the blood glucose was higher than 7.8 mmol/L (AUC > 7.8), the area under the curve when the blood glucose was lower than 3.9 mmol/L (AUC < 3.9), the duration (%) when the blood glucose was higher than 7.8 mmol/L, the duration (%) when the blood glucose was lower than 3.9 mmol/L, and the duration (%) when the blood glucose was between 3.9 mmol/L and 7.8 mmol/L.Carotid intima-media thickness (CIMT) was assessed in both common carotid arteries in each participant using the Esaote Quality intima media thickness (QIMT®). The common carotid artery was utilised since, according to the Mannheim consensus, it increases the accuracy and reproducibility of the measurements obtained. The Esaote QIMT utilises a radio frequency signal to enable measurement of the CIMT with high spatial resolution. The QIMT tool automatically provides accurate measurements of all the parameters which are independent from both the investigator and device settings. Results were categorised as normal or abnormal using age-specific cut-offs, which have been validated in large worldwide databases . Further2. PAD was defined as an ABI of ≤0.9. The mean arterial pressure was the average arterial pressure during a single cardiac cycle and pulse pressure the difference between the systolic and diastolic blood pressure readings. Macrovascular disease was defined as the presence of one or more of the following: history of ischaemic heart disease (IHD) or cerebrovascular accident (CVA), ABI < 0.9, or abnormal CIMT.eGFR was defined as being low if it was <60 mL/min/1.73mt-test for normally distributed variables. For nonparametric variables, the Mann–Whitney U test was used for comparison of 2 groups. Categorical variables were compared using the χ2 test. The Pearson test was used to test correlation of normally distributed variables, and the Spearman test was used for comparison of non-normally distributed variables.All data were analysed using SPSS version 24.0 for Windows. Results are presented as mean ± standard deviation (SD) or median (interquartile range (IQR)). Continuous variables were checked for normality of distribution using the Kolmogorov-Smirnov method. Comparisons of continuous variables between two groups were made using independent sample p value was <0.1 in univariate analysis. Predictors were removed from the model if their p value exceeded 0.05.Univariate followed by multivariate analyses  were performed to identify independent determinants of both the occurrence of macrovascular disease and abnormal CIMT in the study population. Variables were entered into the regression model if their p value < 0.1 in univariate analysis being included in the multivariate model; however, a generalised linear model was performed as multivariate analysis in view that ACR exhibited a gamma distribution (a right-skewed distribution). All tests were two-sided, and a p value of <0.05 was considered to be statistically significant.With regard to ACR, univariate followed by multivariate analysis was again performed with variables with a f2 = 0.15) at α = 0.05.Sample size was determined so as to have statistical power of 90% to detect a moderate effect size , a median fasting plasma glucose of 7.08 mmol/L, and a mean blood glucose (MBG) during CGM of 7.9 mmol/L. Hyperglycaemic episodes were more prevalent than hypoglycaemic episodes as shown by the number of high and low excursions, the AUC > 7.8 mmol/L and AUC< 3.9 mmol/L, as well as duration of BG > 7.8 mmol/L, between 3.9 and 7.8 mmol/L, and < 3.9 mmol/L. However, none of the study participants reported hypoglycaemic episodes, indicating that all these episodes were subclinical. There were no patients with missing data.The study population comprised 121 T2DM subjects of Caucasian origin. The baseline characteristics are outlined in p value < 0.1 and were thus included in the multivariate model: body surface area (BSA), smoking pack years, HDL cholesterol, triglycerides, ESR, lowest blood glucose (BG) value, AUC for BG < 3.9 mmol/L, and duration of BG < 3.9 mmol/L. In multivariate logistic regression analysis, BSA (OR 18.88 (95% CI 2.20–156.69), p = 0.006) and duration of BG < 3.9 mmol/L (OR 1.12 (95% CI 1.014–1.228), p = 0.024) were shown to be independent predictors of macrovascular disease. The relation between presence of cardiovascular disease and duration of BG < 3.9 mmol/L is shown in Seventy-two subjects exhibited macrovascular disease. Univariate followed by multivariate analysis was performed to identify predictors of macrovascular disease in the study population. The results of univariate analysis are shown in Tables 3p value < 0.1: age, DM duration, smoking pack years, BSA, white cell count, eGFR, ESR, and duration of BG < 3.9 mmol/L. These variables were consequently included in the multivariate model.In the study population, 64 subjects had abnormal CIMT (composite of increased CIMT and presence of carotid plaque). In univariate analysis, the following variables had a p = 0.013) and duration of BGM < 3.9 mmol/L (OR 1.09 (95% CI 1.003–1.187), p = 0.041) were independent predictors of abnormal CIMT. The relation between abnormal CIMT and duration of BG < 3.9 mmol/L is shown in Binary logistic regression analysis revealed that BSA (OR 12.6 (95% CI 1.70–93.54), p value < 0.1 in univariate analysis: low eGFR (<60 mL/min/1.73m2), white cell count, HDL cholesterol, triglycerides, uric acid, BMI, WI, MBG, SD, AUC for BG > 7.8 mmol/L, duration of BG > 7.8 mmol/L, duration of BG between 3.9 and 7.8 mmol/L, and highest BG value recorded. Generalised linear regression model revealed AUC for BG > 7.8 mmol/L  to be the sole independent predictor of albuminuria.The following had 1c below 7.5% (58 mmol/L) [The present study found that the duration of blood glucose < 3.9 mmol/L was significantly and independently associated with abnormal CIMT and with the composite of abnormal CIMT, ABI, coronary artery disease, and cerebrovascular disease in subjects with type 2 diabetes. This suggests that hypoglycaemia may predispose to atherosclerosis. These findings are consistent with those of the Diabetes Control and Complications Trial (DCCT), which reported that the rate of severe hypoglycaemic episodes in subjects with type 1 diabetes was associated with increased coronary calcium score in those with a HbA mmol/L) . It is, 1c, fructosamine, AUC > 7.8 mmol/L, and duration > 7.8 mmol/L) or of glucose fluctuations (as assessed by standard deviation of blood glucose during CGM) with macrovascular disease. However, duration of blood glucose > 7.8 mmol/L was independently associated with ACR. These observations may be related to the short median duration of diabetes in our patients. Our findings are consistent with clinical trial data which have shown that lowering blood glucose for a few years is effective in reducing microvascular but not macrovascular disease [We did not find significant associations of any of the hyperglycaemic indexes  trial was associated with increased mortality  and why Hypoglycaemia can promote atherogenesis in a number of ways. Acute hypoglycaemia has been shown to result in decreased nitric oxide bioavailability, increased oxidative stress , plateleBody surface area was also found to be independently associated with atherosclerotic markers. This is probably related to insulin resistance and/or hyperinsulinaemia.The patients with macrovascular disease were on average younger than those without macrovascular disease. This could be due to the cross-sectional nature of our study. Macrovascular disease shortens life expectancy resulting in a lower average age of subjects with macrovascular disease compared to subjects without. Furthermore, macrovascular disease was associated with hypoglycaemia, which is also known to decrease survival . Duratio1c [A limitation of our study is that we have no information on antecedent glycaemic indexes. This problem is inherent to the study area as it is not practical or ethical to perform CGM over a number of years and not alter management in order to keep glycaemic parameters stable. However, we tried to reduce the impact of this limitation in a number of ways. Firstly, we only recruited patients with stable control, namely, not needing escalation of treatment. Secondly, we studied patients with short duration of diabetes because such patients are less likely to have variation in their glycaemic parameters over the course of their disease. Thirdly, we performed blind, rather than real-time, CGM so that patients did not alter their behaviour as result of the glucose readings. Additionally, patients were instructed not to change their usual routines. In this way, the CGM data are more likely to be representative of the patients' usual glycaemic profile. Furthermore, many glycaemic indices such as HbA1c  and hypo1c  have beeIn conclusion, the study suggests that mild asymptomatic hypoglycaemia in subjects with type 2 diabetes is associated with atherosclerotic disease. This cannot be explained by an association of hypoglycaemia with hyperglycaemia or glucose fluctuations. Hyperglycaemic load, as measured by AUC for BG > 7.8 mmol/L, was associated with microalbuminuria.


Patients with cardiovascular disease are at an increased risk of chronic kidney disease (CKD). However, data on incident CKD in patients with multiple vascular comorbidities are insufficient. In this study, we identified the predictors of CKD stages 3–5 in patients at risk of cardiovascular disease and used their estimated glomerular filtration rate (eGFR) to construct a nomogram to predict the 5-year risk of incident CKD.2 for ≥3 months. Time-dependent area under the receiver operating characteristic curve (AUC) was used to evaluate the discrimination ability of the model. Calibration curves were applied to determine the calibration ability and adjusted for the competing risk of death. Internal validation of predictive accuracy was performed using K-fold cross-validation.Ambulatory data on 622 adults with preserved kidney function and one or more cardiovascular disease risk factors who attended outpatient clinics at a tertiary care hospital in Al-Ain, United Arab Emirates were obtained retrospectively. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation and assessed every 3 months from baseline to December 12, 2017. Fine and Gray competing risk regression model was used to identify the independent variables and construct a nomogram to predict incident CKD at 5 years, which is defined as eGFR < 60 mL/min/1.73 mOf the 622 patients, 71 had newly developed CKD stages 3–5 over a median follow-up of 96 months . Baseline eGFR, hemoglobin A1c, total cholesterol, and history of diabetes mellitus were identified as significant predictors of CKD stages 3–5. The nomogram had good discrimination in predicting the disease stages, with a time-dependent AUC of 0.918  at 5 years, after internal validation by cross-validation.This study demonstrated that incident CKD could be predicted with a simple and practical nomogram in patients at risk of cardiovascular disease and with preserved kidney function, which in turn could help clinicians make more informed decisions for CKD management in these patients.The online version of this article (10.1186/s12882-019-1494-8) contains supplementary material, which is available to authorized users. Cardiovascular disease (CVD) is the leading cause of death worldwide  and an iHowever, despite the increasing CVD prevalence, data on CKD progression in patients at risk of CVD are limited , 9. TherThis is a retrospective cohort study of United Arab Emirates (UAE) nationals who visited the outpatient clinics at Tawam Hospital between April 1, 2008, and December 31, 2008, and had either CVD or one or more CVD risk factors. Tawam Hospital is a state-funded tertiary care facility located in Al Ain, UAE. This medical center and its outpatient clinics serve a population of approximately 770,000, the majority of whom are UAE nationals . The stu2, systolic blood pressure (SBP) ≥120 mmHg, diastolic blood pressure (DBP) ≥80 mmHg, serum glycosylated hemoglobin A1c (HbA1c) ≥5.7%, serum triglycerides (TG) ≥2.26 mmol/L, or serum total cholesterol (TC) ≥6.21 mmol/L.Sociodemographic data and clinical information were manually extracted from 1118 patients’ ambulatory electronic medical records (EMRs) that were available for review. Inclusion criteria for this study were UAE nationals ≥18 years old with any of the following conditions at baseline: HTN, CVD, DM, dyslipidemia, history of smoking, body mass index (BMI) ≥25 kg/m2, 6 were renal transplant recipients, and 39 had missing data on baseline serum creatinine (SCr), TG, or HbA1c levels) . Obesity was defined as BMI ≥30 kg/m2. Patients receiving antihypertensive medications were considered as having HTN. Similarly, patients with dyslipidemia were those taking lipid-lowering medications, and patients with DM were those receiving antidiabetic medications. Smoking history was positive if there was a current or any history of smoking tobacco. Patients were considered to have vascular disease if they had a diagnosis of coronary heart disease , cerebrovascular accident, or peripheral arterial disease. All-cause mortality was defined as death from any cause.BMI was calculated as weight (kg) divided by height  was used to measure fasting lipid profile and SCr level by standard methods, while HbA1c levels were assessed using the automated analyzer Integra 400 Plus . The recommended manufacturer’s reference intervals for SCr level were 53–115 μmol/L and 58–96 μmol/L for men and women, respectively.The baseline clinical variables and demographic data recorded in the patients’ EMRs and retrieved for analysis were age; sex; history of DM, HTN, dyslipidemia, smoking, and CVD; SBP; DBP; BMI; TC; TG; HbA1c; and eGFR. The baseline characteristics of patients who did and did not develop CKD stages 3–5 were compared using the independent samples t-test for normally distributed continuous variables, the Mann-Whitney U test for non-normally distributed continuous variables, and Fisher’s exact test (two-tailed) for categorical variables. We did not use any method of data imputation, and missing covariate and dependent variable data were excluded from the analysis.2, 90–99 mL/min/1.73 m2, and ≥ 100 mL/min/1.73 m2).Time of follow-up for each patient was calculated from the baseline visit in 2008 to either incident CKD, death, or the last outpatient clinic visit, whichever occurred first. Considering the potential bias due to the competing risk of non-CKD death, we used the Fine and Gray regression model to adjust for the risk estimates of non-CKD death as a competing risk . The unaP > 0.2 were removed. Second, all significant variables were included to develop the multivariate model. Third, we constructed two CKD risk prediction models: one based on all remaining variables and the other using backward-stepwise selection. For each model, sub-distribution hazard ratios (SHRs) and 95% confidence intervals (95% CIs) were calculated to estimate the relative risk. The proportional hazards assumption was assessed by examining plots of the scaled Schoenfeld residuals against time failure for the predictors. Multicollinearity was evaluated by examining tolerance.Using the cmprsk package in R software , we consMoreover, two important components of predictive accuracy, i.e., discrimination and calibration, were used to evaluate the performance of the models . The evaP values were two-tailed, and P values < 0.05 were considered statistically significant.All statistical analyses and data manipulations were performed using R software version 3.5.2  and IBM®SPSS® software, version 25 . All 2. Moreover, patients with CKD stages 3–5 event were older at baseline; more frequently had a history of CVD, DM, HTN, and dyslipidemia; and had a higher SBP, TG, and HbA1c, but had a lower DBP, TC, and eGFR, than patients without CKD stages 3–5 event.Table 2, between 90 and 99 mL/min/1.73 m2, and ≥ 100 mL/min/1.73 m2, respectively , 7.8% , and 1.1%  for patients with a baseline eGFR between 60 and 89 mL/min/1.73 m5.9–40.2%P ≤ 0.2) were entered into the multivariate prediction model; four variables were retained after backward-stepwise selection  in the multivariate model after stepwise selection and 0.904  in the full multivariate model. Thus, the time-dependent AUC values of the multivariate model after stepwise selection were better than those of the full multivariate model . The patient’s corresponding probability for developing CKD stages 3–5 at 5 years would be 65%.The nomogram could be applied in the clinical setting  [2/year) [Several studies have shown that older age, DM, smoking, obesity, dyslipidemia, and HTN are independent risk factors for developing CKD stages 3–5 , 26–32. with DM)  comparedwith DM)  or with [2/year) . Thus, f[2/year) .Identification and risk stratification of CVD patients at risk of developing CKD stages 3–5 are important issues in clinical practice, particularly in outpatient clinics that provide care to patients with multiple vascular comorbidities. Furthermore, active detection of CKD risk and early treatment of risk factors may avoid complications associated with the subsequent CKD stages . However2, which were obtained ≥3 months apart. This could help account for intra-individual variability in eGFR and lead to a more accurate representation of kidney function. In addition, we used the CKD-EPI equation to define the outcome, which is more accurate than the Modification of Diet in Renal Disease Study equation according to most studies [One of the strengths of this study is that the diagnosis of CKD stages 3–5 was based on two consecutive readings of eGFR < 60 mL/min/1.73 m studies , 42–44. This study has several limitations. First, other risk factors, such as albuminuria, were not explored. A number of studies have described the significance of albuminuria in predicting the development of kidney failure , 45–47; This study demonstrated that in patients at high cardiovascular risk, eGFR, HbA1c, TC, and a history of DM are significant predictors of CKD stages 3–5. A simple and practical nomogram with good accuracy was constructed for predicting 5-year risk of developing CKD stages 3–5 based on competing risk model among patients with vascular comorbidities. This user-friendly risk prediction tool could help healthcare providers make better-informed decisions regarding CKD prevention and management in at-risk patients.Additional file 1:HbA1c glycosylated hemoglobin A1c, eGFR estimated glomerular filtration rate. (TIF 60 kb)Nomogram to predict the development of chronic kidney disease stages 3–5 at 5 years with a worked example. Instruction for use: locate a patient characteristic, such as history of diabetes, HbA1c, eGFR, and cholesterol levels, on the corresponding axis to determine the points the patient receives for each characteristic. Add the points of each characteristic and locate the sum on the total points axis. Draw a line straight down to identify the patient’s probability of developing CKD stages 3–5 at 5 years. Additional file 2:ID identification, DM diabetes mellitus, HbA1c glycosylated hemoglobin A1C, CVD cardiovascular disease, HTN hypertension, SBP systolic blood pressure, DBP diastolic blood pressure, BMI body mass index, eGFR estimated glomerular filtration rate, CKD chronic kidney disease. (XLSX 54 kb)Use of estimated glomerular filtration rate to predict incident chronic kidney disease in patients at risk of cardiovascular disease: a retrospective study dataset.


Background: Antares is an algorithm for pulse wave analysis (PWA) by oscillometric blood pressure (BP) monitors in order to estimate central (aortic) blood pressure (cBP). Antares aims to enable brachial cuff-based BP monitors to be type II-devices, determining absolute cBP values independently of potential peripheral BP inaccuracies. The present study is an invasive validation of the Antares algorithm in the custo screen 400. Methods: We followed entirely the 2017 ARTERY protocol for validation of non-invasive cBP devices, the 2013 American National Standards Institute, Inc./Association for the Advancement of Medical Instrumentation/International Organization for Standardization (ANSI/AAMI/ISO) 81060-2 and 2018 AAMI/European Society of Hypertension (ESH)/ISO validation standard protocols. In total, 191 patients undergoing cardiac catheterization were included, of which 145 patients entered analysis. Invasive cBP recordings were compared to simultaneous non-invasive cBP estimations using the Antares algorithm, integrated into an oscillometric BP monitor. Results: Mean difference between invasive and non-invasively estimated systolic cBP was 0.71 mmHg with standard deviation of 5.95 mmHg, fulfilling highest validation criteria. Conclusion: Antares is the first algorithm for estimation of cBP that entirely fulfills the 2017 ARTERY and AAMI/ESH/ISO validation protocols. The Antares algorithm turns the custo screen 400 BP monitor into a type II-device. Integration of Antares into commercially available BP monitors could make it possible to measure PWA parameters in virtually every practice in future. BasicalFor the first time, in 2017 a worldwide consensus paper under the leadership of the ARTERY society was published as a task force consensus statement on protocol standardization for the validation of non-invasive central pressure devices [The existing devices were categorized as type I or type II devices. Type I means that an estimate of central BP relative to the measured brachial BP is given in order to concentrate on a relatively accurate pressure difference between central and peripheral sites. Type II means that these devices estimate the intra-arterial central BP, what could be understood as the “true” central BP, despite the known inaccuracy of peripheral BP measurements compared to invasive measurements .The ANSI/AAMI/ISO 81060-2:2013  was developed by the International Organization for Standardization (ISO)/TC 121/SC 3, the International Electrotechnical Commission (IEC)/SC 62D Joint Working Group (JWG) 7 on non-invasive BP monitoring equipment and the AAMI Sphygmomanometer Committee. The objective of the standard is to provide minimum labeling, performance, and safety requirements for the clinical validation of medical electrical equipment used for estimation of the arterial blood pressure by utilizing a cuff. Most, but not all, of the ANSI/AAMI/ISO 81060-2:2013 recommendations are included in the ARTERY Society task force consensus statement on protocol standardization for validation of non-invasive central BP devices . 2018 a Antares is an algorithm for calculating central blood pressure values, which can be integrated into an oscillometric device at the upper arm. Antares aims to enable an oscillometric BP monitor to act as a type II-device, thereby providing “true” invasive central BP values. Antares was developed by Redwave Medical GmbH, Jena, Germany.The study aims is to invasively validate the central blood pressure calculation of the Antares algorithm according to the ARTERY validation protocol as well as the 2013 ANSI/AAMI/ISO 81060-2 and the 2018 AAMI/ESH/ISO standard using an oscillometric BP monitor at the upper arm.We followed entirely the 2017 ARTERY society task force consensus statement on protocol standardization for the validation of non-invasive central blood pressure devices, the 2013 ANSI/AAMI/ISO 81060-2 and the 2018 AAMI/ESH/ISO standard.In total, 191 patients undergoing cardiac catheterization for clinical reasons were included in the study. According to the criteria of the 2013 AAMI protocol, 14 patients were excluded due to high variation of invasive BP readings (five patients with standard deviation (SD) in invasive systolic BP (SBP) >10 mmHg, three patients with SD in invasive mean arterial pressure (MAP) >6 mmHg and six patients with SD in invasive diastolic BP (DBP) >6 mmHg). Also, 22 patients were excluded due to severe arrhythmia during the measurements. In one study center, the first 10 measurements had to be excluded due to a systemic error in zeroing. This resulted in 145 patients being available for the analysis. All patients who entered the analysis were Caucasians. 107 patients were within a heart rate of 60–100/min (73.8%).Study centers: The measurements were performed in three German study centers: Greifswald, Bad Oeynhausen, and Bad Berka .Most patients were included in Bad Berka (63 patients), followed by Bad Oeynhausen (50 patients) and Greifswald (32 patients). In all cases, the invasive recording was performed simultaneously to the non-invasive recording. Out of the 145 patients included in the analysis, 100 cardiac catheters were performed radially, and 45 were done femorally. The study was conducted in compliance with the Declaration of Helsinki. Ethics approval was obtained from the local ethics committees. All participants gave their informed consent for inclusion before they participated in the study.Study setting: All measurements were performed in the cardiac catheterization laboratory, with constant temperature, without excessive ambient noise from monitoring devices. The invasive and non-invasive measurements were performed at the end of each cardiac catheter examination and were completely simultaneous. Thus, the patient was adapted to the environment and without disturbing influences. Data acquisition was done in a period of undisturbed rest, free from acute hemodynamic interventions, free from acute medication changes and without talking.Non-invasive central BP device measurement: All non-invasive measurements were performed with the custo screen 400 device , with the integrated Antares algorithm to calculate central BP on a connected laptop. The familiarization with the equipment took only a few minutes in each study center because it is the process of a normal blood pressure measurement. The oscillometric device in its original version is built for 24 h-ambulatory blood pressure monitoring. The custo screen 400 is validated for peripheral blood pressure measurement according to ESH-IP 2010 [-IP 2010 . Cuff siThe Antares software version 2.0, developed by Redwave Medical GmbH, Jena, Germany, was applied in the oscillometric device. Acquisition of the oscillometric pulse waves took place during the deflation of the cuff. Cuff deflation speed was 4 mmHg/s with a linear deflation via a regulated valve. Redwave Medical is patent holder for pulse wave analysis (PWA) in pulse waves that are recorded during inflation and deflation of a cuff (patent no DE 10 2017 117 337 B4). Generally speaking, it means that the pulse waves generated during a normal oscillometric BP measurement procedure can be taken for PWA with no need for altering the standard BP pump operation. The recorded pulse waves were analyzed for non-invasive estimation of central BP using the Antares algorithm. In order to be independent of the potential error of peripheral BP measurement, a recalibration of the brachial BP waveforms was performed by the Antares algorithm internally. The recalibrated mean arterial pressure and diastolic pressure were used for calibration as an internal preprocessing step. The Antares algorithm receives a cuff pressure signal in deflation stage as input signal and separates the pulsatile signal component from the inherent cuff pressure. The single pulse waves are identified. Weighted, multiple transformation of each pulse wave is based on several analytical steps, which could be referred to as adaptive transfer function. Grid points are then identified to calculate hemodynamic parameters such as cBP. The residuum, defined as spread between actual and expected deflating cuff pressure, is calculated. Arrhythmia and other disturbing artifacts are identified based on the residuum and the shape of the pulse wave. The integration of Antares in the software of a blood pressure monitor aims to enable a brachial cuff-based BP monitor to be a type II-device with relatively accurate absolute central BP values independently from the peripheral BP measurement.Invasive central BP measurement: The invasive central BP measurements and the non-invasive measurements were performed by following exactly the same protocol with one exception: the invasive recording time in Greifswald was 20 s, while in Bad Oeynhausen and Bad Berka it was 90 s. All invasive measurements were performed using fluid-filled catheters. In the majority of measurements (90%), a 5 French Judkins right or left 3.5 standard diagnostic coronary catheter of 100 cm length was used. A mix of multiple catheters was used in the remaining 10%. The test to determine frequency response involves a rapid flush like a rectangular pulse (at least 180 mmHg). After a sudden release, the flush bag pressure decreases rapidly and forces an overshooting of the baseline. The natural frequency was calculated from the time between 2nd and 3rd oscillation (one cycle). The damping coefficient was calculated from the ratio of the amplitudes of those two consecutive oscillations. The routinely checked natural frequency and damping coefficients of the systems were 21.9 Hz (15–29 Hz) and 0.21 (0.14–0.29), respectively, which surpasses the recommended guidelines [idelines . The datFlushing was performed before each invasive measurement using sodium chloride 0.9%. At the beginning of the invasive procedure, zeroing was performed precisely, having in mind that inaccuracy in zeroing will cause severe BP aberration. For calibration of each transducer the zero reference level for pressure measurement was set at midchest height, which was also used for balancing. Both calibration and balancing were checked before each measurement was performed. In an undefined number of cases repeated zeroing was performed according to the examiner’s experience. The correct catheter position was confirmed by X-ray at the end of the standard procedure, because the invasive measurement was performed at the end of each heart catheterization. Sample rates at which waveforms were invasively recorded were 500 Hz in Greifswald, 2000 Hz in Bad Oeynhausen, and 240 Hz in Bad Berka. Waveform data processing was performed with the use of a Philips Allura Xper FD20 system in Greifswald, Siemens Sensis Axiom system in Bad Oeynhausen and General Electric MacLab IT system in Bad Berka.The invasive pressure waves were analyzed semi-automatically over the whole period of the recording; meaning 20 s in Greifswald, and 90 s in Bad Oeynhausen and Bad Berka, respectively. To determine the invasive systolic BP, the peak of every recorded pulse wave; for invasive diastolic BP the lowest signal point; and for invasive mean arterial pressure (MAP) the area under the curve was taken for the calculation. The pulse waves of the invasive recordings were visually checked and in that case cleared if they differed greatly from the mean . As an example please see Figure 2a where, over 90 s, a total of two pulse waves had to be excluded. All other pulse waves were included in the analysis of central BP, what means that in the end several extrasystoles still were included. A measurement was considered severe arrhythmia if more than 30% of pulse waves had to be deleted, and the recording of that patient was withdrawn from the analysis. The values for each pulse wave were averaged and additionally the standard deviation was calculated. According to the AAMI protocol, recordings with a SD—within the invasive pressure—of more than 10 mmHg for systolic BP, 6 mmHg for diastolic BP, and 6 mmHg for MAP were withdrawn from the analysis. Nitroglycerin was injected at the beginning of the heart catheterization with a time difference of at least 10 minutes until the invasive and non-invasive recordings of the pulse waves were performed. No other medication was given closely prior to the recordings of the pulse waves.p < 0.05 level.All patient data and measurement results were stored in a database . Statistical analysis was performed using IBM SPSS 22 software . Data are presented as means ±standard deviation. The Pearson correlation coefficient was used to assess the strength of linear correlation between invasive and estimated central BP. Furthermore, the regression equation y = ax + b was used to create a trend line in the scatter plots to evaluate the relationship between the pressures. The agreements between invasive and estimated central BP were compared using Bland–Altman analysis. Statistical significance was declared at the two-side r2 = 0.86. The mean difference was 0.71 mmHg and SD was 5.95 mmHg. For diastolic BP, the correlation was r2 = 0.71, mean difference 2.96 mmHg and SD 5.21 mmHg. For MAP, correlation was r2 = 0.84, mean difference 0.19 mmHg and SD 3.78 mmHg. The corresponding scatter plots and Bland–Altman plots revealed good limits of agreement. The trend lines illustrate no significant over-or underestimations for systolic BP, MAP or diastolic BP. The coefficient of determination of estimated central systolic BP to invasively measured central systolic BP was The mean standard deviation of the invasive central systolic blood pressure for all 145 patients was 4.08 mmHg (SD 1.62), for central mean arterial pressure 2.83 mmHg (SD 1.19), and for central diastolic blood pressure 2.31 mmHg (SD 1.06 mmHg). As stated above, patients with high invasive blood pressure SD were excluded from the analysis. The study confirmed that the Antares algorithm turns the oscillometric custo screen 400 blood pressure monitor into a type II-device for non-invasive estimation of true central BP fulfilling entirely the 2017 ARTERY validation protocol  as well This validation study, which is comparing the invasively measured central BP with the non-invasive estimation using a regular oscillometric BP device, shows a level of agreement that faces the highest requirements as defined as the mean value of differences within five mmHg and standard deviation of less than 8 mmHg . We did According to the 2013 ANSI/AAMI/ISO 81060-2 protocol, the ranges of the invasively measured BP as reference blood pressure for comparison of the estimated central BP were for central systolic BP 10 mmHg and for diastolic BP 6 mmHg. In this way, a hemodynamic stability can be assumed. The residual pressure fluctuations may reflect a physiologic pressure range. Patients with arrhythmia in more than 30% of the recorded pulse waves were excluded. Again, this procedure is undertaken in order to achieve acceptable hemodynamic stability. To set the maximum for arrhythmic pulse waves to 30% of all invasively recorded pulse waves means that a relatively high number of patients with a certain degree of arrhythmia were still included in the calculation. Nevertheless, the level of agreement with a mean difference for estimated systolic BP of 0.71 mmHg and SD of 5.95 mmHg could be reached. Moreover, the data are pooled from three different study sites that could bear another potential error. Still, the measured BP is within the best acceptable range. “Best acceptable range” means for the 2017 ARTERY standard that the device tested passes the validation criteria with mean difference < 5 mmHg, SD < 8 mmHg without fail criteria, for the 2017 AAMI protocol that mean difference is below 5 mmHg with SD below 8 mmHg, for the 2018 AAMI/ESH/ISO protocol if an estimated probability of a tolerable error (≤ 10 mmHg) is at least 85%, and for the British Hypertension Society (BHS) if it passes grade A criteria. Consequently, for all named protocols, the results of the Antares algorithm to estimate cBP are within the best acceptable range. Thus, when implemented into the device, it may be concluded that the Antares algorithm is robust and could be used in the real world in order to non-invasively estimate the central BP.All invasive measurements were performed using fluid-filled catheters. The biggest advantage of using fluid-filled catheters is that they can be easily integrated into everyday clinical practice. This allows achieving a sufficient number of patients included in the invasive measurement, is cost-effective and, furthermore, enhances the probability to show results that can be verified by other working groups easily. One disadvantage compared to micromanometer-tipped catheters is that they are susceptible to false pressures due to damping and altered frequency response. For the given fluid-filled catheters, the coefficient of damping and frequency response were within a generally accepted range . AnotherThe invasive and non-invasive measurements were performed at the end of each cardiac catheter simultaneously. There was no lag of time between those measurements. However, 100% synchronization via R-peak was not done. To the best of our knowledge this should be acceptable because following the 2013 AAMI protocol, physiologic pressure fluctuations already were taken into account and should be covered by the length of the invasive measurements . It cannot be completely ruled out that this procedure introduces a systematic error when comparing periods of different length. From a clinical point of view it may be advantageous to compare the estimated cBP with the invasive measurement procedure that comes as close as possible to the “true” central pressure. To average the cBP of an invasive recording of 90 s might be closer to the “true” cBP than a shorter period of 20 or 30 s. Therefore we followed the 2013 AAMI protocol and used the concept of hemodynamic stability of an entire invasive measurement, which timewise envelops the oscillometric measurement.Though the development of the recalculated “new” brachial BP was done based on invasive comparisons , the method of recalculation of the brachial BP is not invasively validated itself, but considered preprocessing only. Accordingly, the recalculated values are not displayed as discussed above. Thus, it has to be concluded that an exact estimation of aorta-to-brachial systolic BP amplification cannot be gauged using the Antares algorithm. This is partly because it is the nature of a type II-device instead of providing a type I-device. The decision to have a type II-device was reinforced by findings that type II-devices have proved better risk stratification for hypertension-related end organ damage and outcome then type I-devices ,16,17,18The AAMI protocols as well the ARTERY protocol suggest that an indicative range for invasive central systolic BP may be below/equal 100 mmHg in 5% of the readings and above/equal 160 mmHg in 5% of the readings, and invasive central diastolic BP may be below/equal 60 mmHg in 5% of the readings and above/equal 85 mmHg in 5% of the readings. In the validation protocols this BP criterion is categorized as “may”, which means that this criterion provides further guidance and is not a “must” or “should” recommendation. Although we have measured invasively in total 191 patients and could use data of 145 patients for the analysis, we could include in the extreme BP ranges only three patients for central SBP below/equal 100 mmHg and 17 patients for central DBP of above/equal 85 mmHg. The corresponding Bland–Altman plots have a good level of accordance without any significant trend. However, it has to be stated that further invasive comparisons have to show if within these extreme BP ranges Antares works to a similarly robust degree as shown for the other ranges.With the integrated Antares algorithm, the oscillometric blood pressure device studied here proofs to serve as a type II-device for estimation of true central BP. Antares fulfills entirely the 2017 ARTERY validation protocol as well as the 2013 ANSI/AAMI/ISO and the 2018 AAMI/ESH/ISO validation protocols including the criteria for high accuracy devices for estimation of central BP. Whether Antares can be integrated reliably with similar robust results in other oscillometric devices has yet to be proven.The integration of a feature for measuring central blood pressure in commercially available blood pressure monitors could make it possible to measure these parameters in every practice in the future. The existing knowledge about the significance of central blood pressure could then finally be applied more widely in clinical practice.


Tacrolimus is an important immunosuppressive agent with high intra- and inter-individual pharmacokinetic variability and a narrow therapeutic index. As tacrolimus extensively accumulates in erythrocytes, hematocrit is a key factor in the interpretation of tacrolimus whole blood concentrations. However, as hematocrit values in pediatric kidney transplant patients are highly variable after kidney transplantation, translating whole blood concentration targets without taking hematocrit into consideration is theoretically incorrect. The aim of this study is to evaluate the potential impact of hematocrit correction on tacrolimus target exposure in pediatric kidney transplant patients.Data were obtained from 36 pediatric kidney transplant patients. Two hundred fifty-five tacrolimus whole blood samples were available, together responsible for 36 area under the concentration-time curves (AUCs) and trough concentrations. First, hematocrit corrected concentrations were derived using a formula describing the relationship between whole blood concentrations, hematocrit, and plasma concentrations. Subsequently, target exposure was evaluated using the converted plasma target concentrations. Ultimately, differences in interpretation of target exposure were identified and evaluated.In total, 92% of our patients had lower hematocrit (median 0.29) than the reference value of adult kidney transplant patients. A different evaluation of target exposure for either trough level, AUC, or both was defined in 42% of our patients, when applying hematocrit corrected concentrations.A critical role for hematocrit in therapeutic drug monitoring of tacrolimus in pediatric kidney transplant patients is suggested in this study. Therefore, we believe that hematocrit correction could be a step towards improvement of tacrolimus dose individualization.The online version of this article (10.1007/s00467-018-4117-x) contains supplementary material, which is available to authorized users. CYP3A5 polymorphisms [Calcineurin inhibitors (CNIs) are the cornerstone of immunosuppressive therapy after kidney transplantation. Tacrolimus was introduced in the 1990s as an alternative to ciclosporin and is now widely used to prevent rejection after solid-organ transplantation in both adult and pediatric transplant recipients . Tacroliorphisms –9, age [orphisms  and hemaorphisms , 7 were For pediatric kidney transplant patients, little is known about the optimal targets for tacrolimus exposure. Furthermore, both whole blood trough concentrations and area under the concentration-time curves (AUCs) are used to adjust the tacrolimus dosing regimen of the individual patient. As it stands, it is unknown what the best pharmacokinetic parameter to predict treatment outcome is, and the relationship between blood trough concentrations and AUCs in pediatric patients remains a matter of debate . As refeHematocrit is a confounder for interpretation of tacrolimus exposure in whole blood. Several population pharmacokinetic studies have indeed identified hematocrit as a key factor for interpretation of tacrolimus whole blood concentrations in both the adult and pediatric population , 14, 15.Hematocrit values tend to change significantly in the first months after transplantation , 20. ChaThe aim of our study was to evaluate the potential impact of hematocrit correction on tacrolimus target exposure in pediatric kidney transplant patients.To evaluate the impact of hematocrit correction on tacrolimus dose individualization in pediatric kidney transplant patients, we performed a retrospective cohort study at our tertiary referral center  in the Netherlands.0–12 h or AUC0–8 h was available. A subset of our study population has previously been described by Martial et al. [Step 1: Derivation of hematocrit corrected target exposurePediatric kidney transplant patients aged 1–18 years) undergoing therapeutic drug monitoring for tacrolimus between 2012 and 2017 were included when an AUCl et al. . Patient–18 yearsl et al. , 24. In l et al.  or a tril et al. . As foodCwb) can be calculated from plasma concentrations, using the fraction of hematocrit (fHCT) for weighting with the following equation (Eq. 1), in which Bmax is the maximum binding concentration of 418 μg/L and Kd is the dissociation constant of 3.8 μg/L [As tacrolimus dose individualization in children is guided by measurement of whole blood concentrations , we deri3.8 μg/L :\documenEquation 1 can be rearranged to calculate the plasma concentrations if the whole blood concentration and fraction hematocrit are known, with the following equation (Eq. 2):fHCT of 0.35 L/L in the adult population, based on hematocrit values found in previous studies conducted in adult kidney transplant recipients [For calculation of the plasma target concentrations we assumed a cipients , 26–28.Subsequently, whole blood target trough concentrations were converted to plasma target trough concentrations using the aforementioned Eq. 2. The target ranges for converted plasma trough concentrations and whole blood trough concentrations with different hematocrit values are shown in Table R squared coefficient of 0.93, Supplementary Fig. y = 0.0218x1.0772, where y and x represent the plasma target AUC and whole blood target AUC, respectively. The target ranges for whole blood AUCs and converted plasma AUCs are shown in Table Step 2: Derivation of hematocrit corrected trough concentrations and AUCs of the patientsWhole blood target AUCs cannot be directly converted to plasma target AUCs, due to the non-linear binding of tacrolimus and thus a varying blood-to-plasma ratio during a dosing interval. Therefore, the individual whole blood concentrations on which the target AUCs are based should be converted to plasma concentrations, and subsequently, the plasma target AUC can be calculated. In the literature, however, these individual whole blood concentrations for the AUC targets are not available. Therefore, we simulated the steady-state whole blood pharmacokinetics of tacrolimus in 1000 virtual adult patients, based on a previously validated population pharmacokinetic model for tacrolimus  with the0–12 h was based.Step 3: Evaluation of target exposureWhole blood trough concentrations of the patients were converted to plasma trough concentrations using the aforementioned Eq. 2. Whole blood AUCs were converted to plasma AUCs by converting the individual concentrations of different time points on which the total AUCStep 4: Evaluation of differences in interpretation of target exposureSubsequently, whole blood AUCs and trough concentrations of the patients as well as predicted plasma AUCs and trough concentrations of the patients were compared with the corresponding target concentrations.Finally, to evaluate the impact of hematocrit correction in TDM of tacrolimus, differences in the interpretation of target exposure were identified by comparing the evaluation of target exposure for whole blood concentrations with and without hematocrit correction.n = 6), respectively [K × height (cm)/serum creatinine (μmol/L)) with a k value of 36.5 [A validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) bioanalytical assay was used to determine tacrolimus whole blood concentrations. The range of the assay was 1–300 μg/L. Intra-assay precision and accuracy was 3.4%, 2.2%, 3.0% and 102%, 94%, and 94%, respectively, at 3.04, 6.23, and 13.0 μg/L . Whole blood trough concentrations were evaluated using the target concentrations according to our local hospital protocol. As shown in Table A total of 37 children (age range 1.8–17.1 years) were eligible for inclusion in this study. One patient was excluded because the closest hematocrit value was 18 days before sampling. Data on a total of 255 tacrolimus whole blood concentrations were available, together providing 36 AUCs. Patient characteristics are presented in Table 0–12 h (range 62–354 h μg/L) and whole blood trough concentration (range 2.0–25.7 μg/L) were converted to the corresponding plasma AUC0-12h (range 2.0–16.0 h μg/L) and plasma trough concentration (range 0.06–1.02 μg/L). Figure 0–12 h, and whole blood and predicted plasma trough concentration of the individual patient.For every individual patient, a whole blood AUCFurthermore, Fig. Using the hematocrit corrected target levels, a different evaluation for target exposure for either the trough level, AUC or both, was defined in a total of 42% (15/36) of our pediatric kidney transplant patients. In Table Tacrolimus is a key immunosuppressive agent in the majority of pediatric kidney transplant patients. This study shows the importance of hematocrit correction in tacrolimus target evaluation in this population. Using hematocrit corrected target concentrations, a different interpretation of tacrolimus exposure was found in 42% of our patients. As tacrolimus has a narrow therapeutic index, indicating that small variations in drug exposure can have a relevant impact on graft survival and toxicity, the results of this study suggest that using hematocrit corrected targets could prevent incorrect dose adjustments of tacrolimus based on whole blood concentrations. As the majority of our patients had a lower hematocrit value than the reference value of adult kidney transplant patients of 0.35 L/L, which causes an underestimation of the pharmacologically active concentration, toxicity in particular may be prevented.Currently, therapeutic target ranges for tacrolimus exposure in pediatric kidney transplant patients are based on empirical observations in adult transplant patients, as reference values based on clinical trials in pediatric patients are lacking , 12. EspThe importance of hematocrit correction in adult kidney transplant patients has been highlighted previously , 27, 32.The challenge for clinicians to attain the optimal target exposure in the individual patient after kidney transplantation has been previously described by Ekberg et al. and Størset et al., who found 50% and 42%, respectively, of tacrolimus trough concentrations outside the target range during the first 6–8 weeks post transplantation , 33. OurTo our knowledge, this is the first study investigating the role of hematocrit in the interpretation of tacrolimus whole blood exposure in pediatric kidney transplant patients in clinical practice. As the optimal strategy for TDM is still under debate, both AUC and trough concentrations are currently used in the clinical setting. Reported correlations between tacrolimus AUC and trough concentration are variable, indicating that trough concentrations alone may be a poor predictor of exposure . A pharmAn important limitation of our study is its retrospective design, which may cause information bias. Although the observed whole blood concentrations were evaluated retrospectively, the exact time of dose administration was known in 35/36 of our patients. For one patient, the approximate time of dose administration was recorded in the medical file. As all patients were admitted to the hospital during the time of sampling and medication was administered by the nursing staff, we believe that the adherence to the medication is good and therefore full compliance was presumed. Due to the retrospective design of this study, laboratory values of 15 patients were unavailable on the day of sampling; therefore, these variables were imputed by choosing value closest to the day of sampling with a maximum of 2 days for hematocrit. This, however, is a limitation of our study and ideally all samples would be paired.Bmax) and affinity constant (Kd) were obtained from a previously conducted study in adult liver transplant patients [Bmax and Kd in 40 liver transplant recipients using the same equation [In this study, values for the binding capacity High Resolution Image (TIF 128 kb)


Hip fracture in elderly patients is a serious health concern due to the associated morbidity and mortality. Although acute kidney injury after hip fracture is known to be a significantly poor prognostic factor for morbidity and mortality, the literature regarding the risk factors for acute kidney injury after hip fracture is insufficient. This study aimed to investigate the incidence and associated risk factors for acute kidney injury in patients with femoral neck fracture.A total of 248 patients who underwent an operation for femoral neck fracture between January 2011 and January 2015 were retrospectively analyzed. Acute kidney injury was defined according to the Kidney Disease: Improving Global Outcomes guidelines.n = 44). Risk factors for acute kidney injury included diabetes mellitus, pre-existing renal disease, preoperative blood urea nitrogen (BUN), preoperative estimated glomerular filtration rate (eGFR), preoperative haemoglobin (Hb) level, type of operation, postoperative creatinine level and intraoperative hypotension (P <  0.05). After controlling for confounding variables, intraoperative hypotension was only the independent risk factor for acute kidney injury (P = 0.012).The incidence of acute kidney injury was 17.7% (Acute kidney injury was found to occur frequently after surgery for femur neck fracture. Surgeons should be aware of acute kidney injury when planning the management of patients with femoral neck fracture and consider that the duration of intraoperative hypotension is a risk factor for acute kidney injury. Hip fracture in elderly patients is a serious health concern due to the associated morbidity and mortality –4. ComplWhile several studies have reported that the postoperative development of AKI is associated with high morbidity and mortality after orthopedic operation, data regarding the risk factors for AKI after hip fracture are insufficient. Furthermore, the definition of AKI applied in the existing studies did not correspond to that specified by the KDIGO guidelines. Therefore, the purpose of this study was to investigate the incidence of and associated risk factors for AKI according to KDIGO guidelines in patients with femoral neck fracture.This study was approved by our institutional review board. We retrospectively reviewed 312 patients who underwent surgery for femoral neck fracture between January 2011 and January 2015. All fractures were operated on by a single expert orthopedic surgeon. Of these, 24 patients were excluded due to insufficient medical records, and 36 patients were excluded as they were less than 65 years old. Finally, 248 patients (66 men and 182 women) were enrolled in this study. The mean age of the patients at operation was 77.6 years  and the patients were followed for an average of 21.32 days .Demographic and clinical data including past medical history were thoroughly reviewed. The American Society of Anesthesiologists (ASA) score was determined to evaluate the general comorbidity of patients. Use of medications, such as angiotensin-converting enzyme inhibitors (ACE-Is), non-steroidal anti-inflammatory drugs, and contrast nephrotoxic antibiotics, which are known to affect renal function, was recorded, and preoperative hemoglobin (Hb) levels, electrolyte levels including blood urea nitrogen (BUN), and serum creatinine (SCr) were measured.Additionally, intraoperative risk factors for AKI were assessed on the basis of the type of operation, operation time, intraoperative blood loss, and the presence of intraoperative hypotension (systolic blood pressure < 80 mmHg or a mean blood pressure < 55–60 mmHg) that persisted for more than 5 min .AKI was diagnosed if any one of the following conditions was present, according to KDIGO 2012 : an incrP-value < 0.05 was considered statistically significant.Patients were subdivided into 2 groups according to the presence or absence of AKI: the AKI and non-AKI groups. Quantitative variables are expressed as means ± standard deviation (SD) and qualitative variables as number and percentage. Student’s t-test was used for the comparison of quantitative variables and Fisher’s exact test was used for qualitative variables. We performed multivariable logistic regression analysis using the significant variables revealed by the univariate analysis as the independent variables and the presence of AKI as the dependent variable. The stepwise backward elimination method was used for multivariable logistic regression and the final model was selected according to the Akaike’s information criterion (AIC) value. All statistical analyses were conducted using SPSS software  and a n = 44) and the AKI group had a significantly higher rate of medical comorbidities, including diabetes (P <  0.001), pre-existing renal disease (P <  0.001), and medication with an ACE inhibitor (P = 0.037) than the non-AKI group. Preoperatively, the AKI group had a significantly lower preoperative Hb (P <  0.001), BUN (P <  0.001), preoperative (P = 0.034) and postoperative creatinine (P <  0.001), eGFR (P <  0.001), proteinuria (P = 0.029), ESR (P <  0.001), and CRP (P = 0.012) levels.The demographic and clinical characteristics of patients are presented in Table P = 0.028). In a subgroup analysis according to the type of operation, including bipolar hemiarthroplasty (BH), total hip replacement (THR), and osteosynthesis, the prevalence of AKI was significantly different (Fig. P = 0.42, Table The type of operation differed significantly between the AKI and non-AKI groups (ent Fig. . The incUnivariable logistic regression analysis showed that type of operation, diabetes mellitus, pre-existing renal disease, ACE inhibitor, preoperative Hb level, preoperative BUN level, preoperative eGFR, postoperative Cr level and intraoperative hypotension were the significant risk factors for postoperative AKI. According to multivariable logistic regression analysis controlling for confounding variables, the presence of intraoperative hypotension was the only significant risk factor for postoperative AKI Table .Table 3MAKI develops in 7.5% of patients undergoing noncardiac surgery  and the Bipolar hemiarthroplasty, rather than THR, was significantly associated with an increased risk of AKI in this study, although THR leads to massive blood loss and prolonged operating time because of its invasive and meticulous surgical technique. One possible explanation is that the patients who underwent bipolar hemiarthroplasty were typically older and less ambulatory, owing to the presence of underlying disease. Several studies have demonstrated that the incidence of AKI increases with age and is most common in elderly patients , 15. AddThe use of hypotensive anesthesia is generally recommended in the orthopedic department for decreasing intraoperative blood loss, transfusion requirements, and operation time, improving the quality of the surgical field, and preventing deep vein thrombosis. However, it may lead to intraoperative dehydration and hypotension and dehydration may in turn cause endothelial injury and the subsequent local release of endothelin, angiotensin II, and catecholamines, all of which cause vasoconstriction and exacerbate ischemia in the kidney , 18. A cThe major limitation of this study was that it did not investigate the total duration of intraoperative hypotension. Although the duration of hypotension required to incur damage is unclear, interest in the effects of the duration of intraoperative hypotension on AKI has recently increased , 19. In In conclusion, AKI was found to occur frequently after surgery for femur neck fracture. Surgeons should be aware of acute kidney injury when planning the management of patients with femoral neck fracture and consider that the duration of intraoperative hypotension is a risk factor for acute kidney injury.


Predicting immediate and subsequent graft function is important in clinical decision-making around kidney transplantation, but is difficult using available approaches. Here we have evaluated urinary microRNAs as biomarkers in this context. Profiling of 377 microRNAs in the first urine passed post-transplantation identified 6 microRNAs, confirmed to be upregulated by RT-qPCR in an expanded cohort . Receiver operating characteristic analysis showed Area Under the Curve 0.94 for this panel. To establish whether this early signal was sustained, miR-21 was measured daily for 5 days post-transplant, and was consistently elevated in those developing Delayed Graft Function . The biomarker panel was then evaluated in an independent cohort, sampled at varying times in the first week post-transplantation in a separate transplant center. When considered individually, all miRs in the panel showed a trend to increase or a significant increase in those developing delayed Graft Function  with Area Under the Curve 0.75 for the panel. In conclusion, combined measurement of six microRNAs had predictive value for delayed graft function following kidney transplantation. Due to the increasing number of patients on the waiting list, new ways have been identified to increase the organ donor pool4. These have included the use of ‘marginal’ and ‘extended criteria’ donors (defined by the United Network for Organ Sharing (UNOS) as donors older than 60 years, or donors between age 50–59 with two or more criteria from higher terminal Creatinine >1.5 mg/dl, hypertension and death due to CVA)6. However, these innovations have also increased the impact of Ischemia Reperfusion Injury (IRI) on the kidney graft, increasing rates of delayed graft function  and primary non-function. DGF increases length of hospital stay and risk of acute rejection episodes, and is associated with poorer long-term outcomes7.Kidney transplantation is the treatment of choice for many patients with end stage renal failure. It improves quality of life, prolongs survival and is more cost effective in comparison to dialysis8. Risk of DGF may be predicted based on donor and recipient characteristics9. Graft function is intensively monitored post-transplantation, but separating ischemia-mediated DGF from other causes of graft dysfunction, and predicting extent and tempo of recovery of graft function, is difficult. Invasive biopsy of the kidney graft is frequently employed in order to differentiate DGF from other possible causes of graft dysfunction including acute rejection, and carries increased risk in the immediate post-transplant period10. Identifying a non-invasive biomarker of the extent of IRI and hence DGF, would improve prediction of outcome and tailored management for transplant patients. Development of such a biomarker would also facilitate testing of new approaches to attenuate IRI and reduce the risk of DGF.Early ischemic injury, frequently manifesting as DGF, is also an important and potentially modifiable contributor to poor long term survival following kidney transplantation13. These small non-coding RNAs regulate various physiological and pathophysiological processes, and have an important role in acute kidney injury14. They are found in many biological samples including tissue, serum, and urine15. Because of their tissue-specific expression, microRNAs show promise as biomarkers, and their expression levels in urine may reflect intra-renal events16. Our laboratory has shown that microRNAs play a key role in renal proximal tubular cell recovery from acute kidney injury17 and has developed robust laboratory-based methodologies for the isolation and quantification of urinary microRNAs18.Recently, microRNAs have emerged as essential post-transcriptional regulators of gene expression21. Lorenzen et al. found that urinary miR-210 abundance was a sensitive discriminator for non-treated versus treated acute rejection19. A panel of urinary microRNA changes have also been reported in patients experiencing chronic allograft dysfunction21. However, to our knowledge no studies have evaluated the microRNA profile of DGF in kidney transplantation.The urinary microRNA profile shows promise for detection of acute rejection within the kidney graftThe aim of this study was to test whether by quantifying urinary microRNAs it is possible to predict those who will go on to develop DGF following kidney transplantation. Our approach was to perform unbiased profiling and confirmatory analysis in a discovery cohort from a single center. The resultant signature predictive of DGF was then validated in a second cohort of 47 patients transplanted at an independent center.7. To maximize capacity for results to translate into a test deliverable in clinical practice, total urinary microRNA quantification was performed, rather than sub-fractionation to study exosomes or other sub-compartments. To minimize sample variation in the profiling and discovery cohort, all patients were recruited in a single center, and the first urine passed post-transplantation was sampled from the urinary catheter immediately post-operatively. Pre-analytic sample handling and processing was adherent to the stated standard operating procedure, based on our previous work to define optimal handling and processing of urine samples for microRNA analysis.Consecutive transplant recipients were recruited in a single transplant center at the time of transplantation, and with allocation to DGF or no DGF group at day 7 dependent on outcome. DGF was defined as requirement for Renal Replacement Therapy in the first 7 days post-transplantationHLA-incompatible transplantations were not included in the analysis, and all of the transplants included were from ABO-compatible donor-recipient pairs. Immunosuppression comprised Basiliximab or Anti Thymocyte Globulin and Methyl Prednisolone, followed by triple maintenance therapy . The same immunosuppressant protocol was employed for live and cadaveric recipients, however other differences in live versus cadaveric donor kidneys might influence post-transplantation urinary microRNA profile. In particular, the expected differences in pre-transplantation ischemic time were observed Table  so in th22. The other three led to graft loss, and comprised one CD-DGF loss at three months due to further deterioration in a recipient with poor post-transplant baseline function, and two LD-No DGF losses (at 13 and 20 months) due to severe rejection, in both cases there was possible noncompliance with immunosuppressive medication. In all cases, biopsies followed a clinical suspicion of rejection, and no protocol biopsies were undertaken in patients in this cohort. Mean estimated glomerular filtration rate (eGFR) (±SEM) at 6 months post-transplantation was 55.33 (±3.17) ml/min and there was no significant difference in eGFR between the 3 groups (p > 0.9)  was significantly up-regulated with ≥5-fold change in the ‘CD-DGF’ group compared with both ‘LD-No DGF’ and ‘CD-No DGF’ groups, at ‘first-pass urine’ post-transplantation Fig. . ExpressThe above data identified a panel of microRNAs that were predictive of DGF when measured in urine collected immediately post-transplantation. In order to determine whether urinary microRNAs are more generally useful as a biomarker of DGF in clinical practice, we next evaluated urinary expression profile of miR-21 in this cohort for the 5 consecutive days after kidney transplantation. miR-21 in urine was significantly up-regulated in the ‘CD-DGF’ group compared with both the ‘No DGF’ groups during the first five days post-transplantation (p < 0.05)  was recruited and their urine samples collected in the first week post-transplantation. Of the 47 patients recruited, 13 28%) developed DGF and 34 (72%) had no DGF  and subsequently confirmed these findings using measurement of specific microRNAs by RTqPCR. These alterations in miR detection were then tested in an independent cohort of patients transplanted at a separate center, and were further shown to be evident through the five days following transplantation. These data suggest that urinary miR profile may be a useful measure of renal injury that manifests subsequently as delayed graft function.25. Amongst these, the most is known in terms of kidney injury about the role of miR-21. Increased levels of miR-21 have been found in the urine and plasma of patients sustaining AKI of various etiologies28, and abundant data demonstrates mechanistic importance of miR-21 in the kidney following ischemic injury, where miR-21 may serve both to limit acute injury by inhibition of apoptosis and inflammatory pathways but also in the longer term may promote fibrosis (reviewed in29). In addition, our recent work showed that miR-21 measured in hypothermic machine perfusate of kidneys placed on the Lifeport® perfusion system correlated with estimated GFR at 6 and 12 months post-transplantation30. In the current study, consistent with its possible role as a sentinel for ischemic injury in the donor kidney, we found that elevated miR-21 was detectable throughout the first five days post-transplantation in patients developing DGF. Importantly, however, miR-21 as a single biomarker was outperformed by a combined analysis of the signature derived from unbiased profiling.Recent studies have begun to uncover the likely functions of microRNAs in the kidney, and there is accumulating evidence that microRNAs play a key role in responses to acute kidney injury of various etiologies31). Previous data supports miR-10a as a biomarker in mouse models of AKI32. MiR-29a is abundant in kidney, where it is linked to matrix deposition in response to the profibrotic cytokine Transforming Growth Factor Beta-133 as well as, outside the kidney, to regulation of the immune system and tumorigenesis (reviewed in34). MiR-221 regulates angiogenesis and is highly expressed in multiple cancers, where it has been proposed as both a biomarker and therapeutic target35. MiR-429 is part of the miR-200 family, strongly implicated in retention of an epithelial phenotype and downregulated in cancer-associated epithelial to mesenchymal transition36 while MiR-9 is implicated in brain development37.The functions of other microRNAs identified in the present study in the context of kidney transplantation are currently unclear. Many of the known roles of these microRNAs are in cancer and development, potentially reflecting shared underlying actions but also potentially affected by the critical mass of research focus and studies in the field to date. MiR-10a is abundantly expressed in normal mouse kidney, where its function is unknown. It targets Hox genes, transcription factors with key developmental roles, and is found at increased levels in diverse tumors . The microRNA panel that we describe had very high discriminatory capacity in the discovery set (AUC 0.94) which was reduced in a second, independent validation cohort (AUC 0.75). In part, this reflects the inherently higher predictive value for a biomarker panel in the sample set from which it is defined. Important concepts for validation are replication in an independent cohort, and to seek clinical as well as statistical validation (reviewed in40). In the current study, the validation cohort was chosen to reflect how the test might be used in standard care, with sampling at variable times in the immediate post-transplant period. A consequence is greater variability in microRNA levels, as reflected in Fig. ROC analysis is a commonly used approach to depict the trade-offs between sensitivity and specificity for a given test. The ROC curve can be summarized by the area under the curve (AUC ROC) which equates to the probability that if a random case and control from the population are compared, the case will have the higher value . The first sample was taken immediately post-transplant, i.e. ‘first-pass urine’. Recruitment took place until there were at least 10 patients per group: living donor kidney transplant without DGF (LD-No DGF), cadaveric donor kidney transplant without DGF (CD-No DGF), and cadaveric donor kidney transplant with DGF (CD-DGF). All patients gave informed consent for samples to be collected and stored in the Wales Kidney Research Tissue Bank. Urine samples were centrifuged at 2000 g for 10 minutes at 4 °C to remove debris. The supernatant was divided into aliquots of 350 μl for RNA extraction. Samples were stored at −80 °C until RNA extraction experiments. For subsequent validation, a second cohort of 47 patients undergoing transplantation at a second center (Newcastle Institute of Transplantation) was recruited. Patients in this validation cohort gave a single spot sample of urine in the first five days following transplantation. All subjects gave informed consent for sample collection (Research Ethics Committee reference 11/NE/0352 and 09/WSE02/48).41. In brief, urine was centrifuged at 2000 g for 10 mins at 4 °C before addition of carrier RNA  at 1 μg/750 μL w/v, and synthetic Caenorhabiditis elegans cel-miR-39  to final concentration 0.5pM, before proceeding as per the miRNeasy extraction protocol.RNA was extracted using miRNeasy Mini Kits  as per the manufacturer’s instructions, with minor modifications as per the protocol recently established in this laboratory377 unique microRNAs and 4 controls were measured by Taqman Low Density Array  with Reverse Transcription followed by pre-amplification Megaplex PreAmp primers, according to the manufacturer’s recommendations (Life technologies). TLDA (Human MicroRNA Panel Card A v.2.0) was performed using a 7900-HT Fast Real-Time PCR System, according to the manufacturer’s recommendations (Life Technologies).−ΔΔCT method42. Taqman microRNA gene expression assay ID numbers were hsa-miR-9 (000583), hsa-miR-10a (000387), hsa-miR-21 (000397), hsa-miR-29a (000412), hsa-miR-221 (000524), hsa-miR-429 (001024), hsa-miR-506 (001050), hsa-miR-574-3p (002349) and miR-cel-39 (000200).cDNA was generated using a High Capacity Reverse Transcription Kit with specific stem loop primers for the TaqMan miRNA assays (Life Technologies). RT-qPCR was performed on a ViiA7 Fast Real-Time PCR System (Life Technologies). The amplification of a single PCR product was confirmed by melt curve analysis. Selected microRNAs  were quantified by Taqman miRNA assay, according to the manufacturer’s instructions and their expression normalized to miR-cel-39. The relative changes in gene expression were analyzed by the 2The clinical and research activities being reported are consistent with the Principles of the Declaration of Istanbul as outlined in the ‘Declaration of Istanbul on Organ Trafficking and Transplant Tourism’. Demographic data were collected on the donors  and recipients , HLA mismatch, duration of hospital stay, and eGFR at 3, 6, 9 and 12 months.t test. Significance level was pre-specified as p-value < 0.05.Statistical analyses were performed using GraphPad Prism version 6. ROC analysis was conducted using R software. Categorical Data were expressed as median (and range) and analyzed by Mann-Whitney U test. Continuous data were reported as mean (±SEM) and analyzed by unpaired Student’s


The prevalence of pressure ulcers particularly in the frail older adult population continues to be high and very costly especially in those suffering from chronic diseases and has brought a higher awareness to comprehensive, preventive and therapeutic measures for treatment of pressure ulcers. Internal risk factors highlighted by comorbidities play a crucial role in the pathogenesis of pressure ulcers.Focusing on the impact of common chronic diseases (comorbidities) in aging on pressure ulcers  and the significant complicating conditions e.g., anemia, infectious diseases, malnutrition, hospitalization, incontinence and polypharmacy, frailty and disability becomes important in developing a more complete, inclusive and multidisciplinary approach to prevention of PU in older patients.To describe chronic and acute conditions which are risk factors in elderly patients for developing PU.We present an overview of comorbidities seen with PU in three diverse patient locations.The inclusion criteria are sites , older patients, chronic diseases and pressure ulcers grade 2 and over.Using a recently developed conceptual framework accepted by European and National Pressure Ulcer Advisory Panels, we examined chronic diseases to identify the risk factors of chronic conditions and complicating conditions which potentially influence risk for PU development.Multiple chronic diseases and complicating factors which associated with immobility, tissue ischemia, and undernutrition are caused to PU in community settings, hospitals, and nursing facilities. Life expectancy of older adultshas significantly increased due to better living conditions and improved medical treatment. In Western countries, the average life expectancy increased for women from 70 years to 82 and for men to 80 years . In contSarcopenia and frailty occur as biological changes at the cellular level as well as physiological changes characterized by reduced muscle strength, weight loss, and physical inactivity. Frailty often results in dependency, polypharmacy, disability, geriatric syndromes, institutionalization and early death .Multiple factors act together synergistically to cause PU in the functionally impaired frail older population. The pathogenesis of PU is a multifactorial process involving inflammatory factors, hormonal changes, reduced immune protection, impaired blood perfusion and degenerative changes . A comprDisability and geriatric syndromes are various clinical and functional conditions frequently occurring in older persons affecting activities of daily living  and quality of life  .Some PUs in older adults may be unavoidable, meaning that PU will occur despite optimal care and monitoring. Unavoidable PUs will occur particularly in patients suffering from chronic diseases with an extended duration, stretching a patient’s deterioration to the limit of functional organ failure . A consensus of NPUAP multi-disciplinary experts in 2010 considered certain situations such as hemodynamic instability  causing inadequate peripheral perfusion and severe undernutrition  to be triggers for unavoidable ulcers .Pressure ulcers in these patients are the final end of the pathway of accumulating comorbidities of high severity with complicating conditions affecting some frail or disabled elderly patients.The prevalence of PU particularly in older adults continues to be disturbingly high especially in those suffering from chronic diseases and frailty, bringing a higher awareness to applied preventive and therapeutic measures . An overColeman et al. 2014 . recentlThe etiological mechanisms by which stress and internal strain interact with damaged skin and subcutaneous tissue resulting in pressure ulcer development include localized ischaemia, reperfusion injury, impaired lymphatic drainage and sustained cell deformation .Pressure ulcers are typically accompanied by severe complications including pain, depression and infections. These complications induce further health deterioration, with prolonged patient suffering, longer hospitalization, early mortality and increased cost . PressurIdentifying the impact of comorbidities is of critical importance in understanding the development of pressure ulcers. Comorbidities can be defined as concurrence of multiple chronic diseases in the same patient. The population with comorbidities differs from those with individual chronic diseases due to the interaction between the multiple conditions, leading to the need for a comprehensive and multidisciplinary approach and long term continuing care. Chronic medical conditions are significantly more prevalent among older adults. Eighty-one percent of Americans over sixty-five have more than one chronic condition Many of these people have five or more chronic conditions, associated with higher rates of ED visits and hospitalizations as well as more prescriptions . Older aThe common age-related chronic diseases are identified as cardio-vascular, diabetes, lung, renal, musculoskeletal, neurodegenerative diseases. Exploring the impact of these diseases provides insight into multidimensional effects on older patients regarding clinical symptoms, complications, consequences and effectiveness of treatment. Progression of these diseases can be manifested through impaired motor, sensory, immune and hormonal systems and lead to frailty, disability, geriatric syndromes and isolation. The combined effect of these impaired systems and organs may result in associated complicating conditions including; malnutrition, anemia of chronic disease, recurrent infection, polypharmacy and hospitalization. The significance of comorbidity risk factors in the pathogenesis of PU requires further investigation, recognizing the insolvability of PU prevention solely with external relief devices.The inclusion criteria for the literature review are studies of PU risk factors in the community, in acute hospitals and in long term facilities, A medline search was done of PU risk factors and older adults and community; and PU risk factors, older adults and hospital; and PU risk factors, older adults and long term care. We further searched under PU and “chronic conditions” and “pressure ulcer risk factors” with specific common chronic diseases: diabetes, congestive heart failure, cardiovascular disease, stroke, peripheral vascular disease, chronic kidney disease, chronic pulmonary disease/COPD, dementia/neurodegenerative disease, osteoarthritis, osteoporosis, obesity. After reviewing this literature, we did a search of pressure ulcer risk factors and specific associated problems: incontinence, anemia, malnutrition, polypharmacy. We excluded studies looking only at stage 1 ulcers or medical-device related ulcers and excluded studies including only spinal cord injury patients.Advanced heart disease with low cardiac output and/or decreased oxygenation, results in hypotension, decreased blood perfusion and peripheral ischemia contributing to the appearance of PU .Atherosclerosis is the primary physiological process affecting the vascular system in older adults. Well-known risk factors for atherosclerosis include smoking, high blood pressure, hyperlipedemia, diabetes and sedentary lifestyle. The accelerated atherosclerosis process decreases blood perfusion to essential organ targets such as the heart, brain, eyes, kidneys, legs and soft tissue skin predisposed to local ischemia. Reduced perfusion to skin and soft tissue may contribute toPU development. Cardiovascular disease is an often cited risk factor for PU among ICU hospital patients . Among hIn our review, we did not find consistent associations between hypertension and PU.Peripheral vascular disease (PVD) is distinguished by arterial, venous and/or lymphatic insufficiencies, particularly prominent with the onset of PU. Heel ulcers are associated with peripheral arterial disease among hospitalized patients . AnotherDirect causal risk factors from Coleman’s theoretical model associating PU and vascular diseases are primarily poor perfusion due to local ischemia, delayed reperfusion of ischemic tissue and impaired lymphatic drainage, all reducing tissue tolerance and the threshold to develop PU. Indirect causal factors might be diabetes and poor nutrition. Other potential indirect factors in the Coleman model might include side-effects of cardiac, diuretic and cholesterol medication (causing hypotension and muscle pain), old age and other factors relating to general health status including acute illness. Edema or dehydration as a result of congestive heart failure (CHF), could cause structural changes of the skin layers, promoting the development of PU.In patients with advanced vascular disease, PU prevention might include stroke prevention and edema management as well as good nutrition and muscle strengthening.Patients with cerebrovascular accidents (CVA) are prone to be immobilized and to develop PU. Typically, stroke results from atherosclerotic cerebrovascular disease. Therefore, poor perfusion and medication side effects could also contribute to PU after stroke, particularly during hospitalizations. Stroke also increases risk for falls and injuries leading to more hospitalizations and disability. Post-stroke infection such as pneumonia is also common and may predispose to PU.In a study of stroke patients in Thailand living in the community, PU prevalence was very high and was associated with malnutrition, friction, and moisture . A studyIn an outpatient setting, Margolis et al.  found thp < .001). 1013 (43.8%) patients with pressure ulcers suffered from CHFcompared to the patients without pressure ulcers of whom only 28.4% suffered from CHF (p < .001).In a retrospective study of over 50,000 patients, Lyder et al.  found thIn patients after stroke, PU prevention might include usual rehabilitation therapy, occupational therapy assessment, secondary stroke prevention, fall prevention screening and assessment, and assessment and management of continence.The prevalence of diabetes in the last several decades has increased  and is ep < .001) compared to the patients without pressure ulcers of whom only 33.4% suffered from diabetes. In populations of hospitalized hip fracture patients . Khor . Khor  reportedIn a study of palliative care patients across multiple settings, infection was associated with PU .Infection prevention strategies for vulnerable older adults include appropriate vaccinations, hand washing, avoidance of indwelling catheters. There are specific guidelines for preventing post-operative infections and ventilator associated pneumonia.Many of the chronic conditions discussed here are associated with urinary and/or fecal incontinence, either due to advanced disease or due to side effects of medications.In a study in a California hospital, 73% of patients with PU had fecal or urinary incontinence . In a reFor high risk older adults, continence screening and assessment can be helpful.Older adults who take at least 5 medications are likely to be experiencing adverse effects from their medications due to drug-drug interactions and drug-disease interactions. Several types of medications are associated with PUs including sedatives , vasopreMany pressure ulcers develop during acute hospitalizations. Incidence rates vary among studies and there seems to be regional variability. Hospitalized patients spend more time in bed than they would in the community. Moreover, they often receive new medications which may be sedating or reduce appetite. One-third of hospitalized older female patients experience functional impairment from their hospital stay and only half will recover to their pre-hospital function . AcutelyThe main objective of this article was to detail the chronic and acute disease risk factors for frail elderly patients developing PU.Multiple chronic conditions impair mobility, and also have a cumulative vascular, inflammatory, immune, hormonal and degenerative effect on the development and treatment of pressure ulcers. Different locations of pressure ulcers (sacrum v. heel) may have different disease associations. For example, heel ulcers seem more strongly associated with diabetes and PVD than sacral ulcers.Identifying the key risk factors and impact of comorbidities and associated geriatric conditions on the susceptibility of the elderly patient is of critical importance for the prevention of pressure ulcers.The authors of this overview used the Coleman conceptual framework focusing on pathways for risk factors in PU development identified with comorbidities. The Coleman conceptual model does not list chronic conditions other than diabetes as causal factors for PU. However, many of the chronic conditions discussed here fit into the Coleman model. These are particularly important as rates of diabetes, dementia, and severe obesity are expected to increase dramatically in the coming decades.Direct PU causal factors associated with comorbidities include immobility, skin/pressure ulcer status and poor perfusion. Indirect factors are moisture, sensory perception, diabetes, low albumin and poor nutrition. Other potential factors include old age, medication, pitting edema and other factors relating to general health status including infection, acute illness, raised body temperature and chronic wounds See Fig. .Fig. 1CoThe direct risk factor associating PU and cardiovascular diseases is primarily poor perfusion occurring in all medical settings. Diabetes directly influences PU by risk factors of poor perfusion and skin changes and indirectly by lack of sensation perception in all medical settings. Direct risk factors associating PU and Chronic Pulmonary Disease (CLD) include immobility and poor perfusion. The primary direct causal factor associating PU and neurodegenerative disorders is likely immobility and the indirect causal factor of poor nutrition in both community and LTC settings. Effects seem strongest for diabetes, stroke, and advanced dementia. For heel ulcers, peripheral vascular disease and diabetes are particularly strong causal factors. PU may be unavoidable in patients with these conditions, given circumstances such as reduced mobility and undernutrition.Among chronic diseases, diabetes, stroke, and advanced dementia seem to be most strongly associated with PU development. Immobility patients with low BMI, low albumin and haemoglobin, high inflammatory markers (CRP and ESR)associated with these conditions and with hemodynamic instability  and chronic complications may be most likely to lead to unavoidable PU (9).The population with comorbidities differs from those with individual chronic diseases due to the interaction between the multiple conditions, leading to the need for a comprehensive and multidisciplinary approach and chronic continuing care. Complicating conditions are identified with the progression of diseases to later advanced stages where the modifying impact of comorbidities on the aging process becomes strongly prevalent in contributing to development of PU.It is important to understand the PU risk factors coming directly from multiple chronic diseases, complicating factors, functional impairment and disability and the unavoidable PU Fig. . UnderstAppreciating PU as a dreaded complication from advanced chronic comorbidities and associated health conditions can help guide treatment goals. Thus the patient, family, and health care team are empowered to improve prevention and optimize treatment of the wounds  together with more traditional interventions such as pressure relief devices and repositioning serving as the optimal treatment for pressure ulcers), and to change the treatment priorities to control the symptoms of PU (unavoidable PU) and ultimately enhance the quality of life for the elderly patient.


To the Editor:VT) was set, adequate control of the VT was difficult during NIV. In an observational study [VT at 6–8 mL/kg, the actual VT was 9.8 mL/kg during application (75% of patients had VT > 8 mL/kg). Similarly, the LUNG-SAFE study [VT was 8.73 mL/kg in ARDS patients managed with NIV. Physiologically, VT during NIV is the consequence of both the ventilation-inspiratory pressure support and the spontaneous respiratory muscle activity. Thus, even with the inspiratory pressure set at a low level, patients may still spontaneously breathe with a high VT because of a strong respiratory effort to alleviate tachypnea/dyspnea. Second, differences in ARDS severity remain an important cause of inconsistent findings. In a propensity-matched analysis, Bellani et al. [2/FIO2 < 150 mmHg, the mortality of the NIV group was significantly higher than that of the invasive ventilation group. This may be due to the fact that tidal hyperinflation during NIV may be more significant as the lung in patients with severe ARDS is stiffer, which is a significant risk factor for ventilation-induced lung injury. In the study by He et al. [VT ventilation is more significant in mild than in severe ARDS. Thus, whether NIV should be considered when treating ARDS still requires investigation. Third, there are different NIV approaches. In 2016, Patel et al. [p < 0.001). However, in the helmet group, the positive end-expiratory pressure (PEEP) was significantly higher  and the supported pressure was lower  than in the mask group. Higher PEEP and lower pressure support are supposed to be associated with lower driving pressure. Thus, whether the benefit of helmet NIV was a result of a more protective ventilation strategy remains unclear. Finally, we suggest that further studies should incorporate mechanical indexes  into NIV application to obtain more positive results.The benefits of noninvasive ventilation (NIV) in acute respiratory distress syndrome (ARDS) have long been debated. In a recent well-designed trial, He et al.  found thal study , CarteauFE study  also repe et al.  found th