Understanding hospital-acquired pressure injury (HAPrI) etiology is essential for developing effective preventive interventions. Pressure injuries are classified based on the degree of visible tissue damage; the two most commonly identified HAPrI stages in critical care patients are stage 2 and deep tissue injury (DTI). Some experts speculate that stage 2 and DTI have different etiologies, with stage 2 injuries formed from the “outside in” as a result of tissue deformation, decreased perfusion, and subsequent ischemia caused by external pressure and/or shear forces, whereas DTI emerges from the “inside out” due to inadequate perfusion to the deeper tissues causing tissue ischemia.The purpose of this study was to compare risk profiles of intensive care unit (ICU) patients who developed stage 2 injuries versus DTIs.2χ test. Risk profile variables included demographic characteristics, Braden Scale scores, vasopressor infusions, hypotension, surgical factors, length of stay, BMI, laboratory values, diabetes, Charlson Comorbidity Index, and the levels of sedation or agitation. The distributions of potential risk variables between patients with stage 2 injuries and DTIs were summarized and compared. A logistic regression model with the least absolute shrinkage and selection operator method was developed to identify the critical risk factors for distinguishing stage 2 and DTI patients.This was a retrospective cohort study to compare the risk profiles of patients in the ICU with stage 2 injuries and DTIs using electronic health record data. Eligible patients were admitted to the surgical or cardiovascular ICU at an academic medical center in the United States between 2014 and 2018. Anatomic locations were examined, and differences in anatomic patterns were compared using the χ21=8.43, P=.03). The multivariate model showed that patients who developed stage 2 HAPrIs had a longer length of stay in the ICU than those with DTIs  but were less likely than patients with DTIs to experience a diastolic blood pressure <50 mmHg  or receive an epinephrine infusion .A total of 244 patients developed a stage 2 injury or DTI during the study period. Of those, 38 patients with medical device–related pressure injury were excluded. The final study sample consisted of 206 patients (n=146 stage 2 and n=60 DTI). Compared with DTIs, stage 2 HAPrIs were more likely to be located on a bony prominence (n=206, Stage 2 injuries and DTIs have different risk factors and different anatomic patterns. Patients who developed DTIs were more likely to experience low diastolic blood pressure and receive epinephrine, a potent vasopressor. Stage 2 injuries were more likely to occur on the bony prominences, whereas DTIs commonly occurred on the fleshy parts of the body such as the buttock. The United States has an estimated cost burden exceeding US $26 billion for hospital-acquired pressure injury (HAPrI) treatment , althougUnderstanding the etiology of HAPrI is foundational for developing effective preventive interventions. The National Pressure Injury Advisory Panel and the European Pressure Ulcer Advisory Panel provide a pressure injury (PrI) classification staging system  along with common descriptions of the extent of the visible skin and tissue damage for the purpose of clinical practice, audits, and research . Stage 2This was a retrospective cohort study of electronic health record (EHR) data to establish risk factor profiles of ICU patients comparing stage 2 injuries and DTIs. The institutional review board of the University of Utah approved the study (IRB_00111380).Eligible patients were those who were admitted to the surgical or cardiovascular ICU at an academic medical center in the United States between 2014 and 2018. Inclusion criteria were age >18 years and development of a nonmedical device–related stage 2 injury or DTI during the ICU stay. Exclusion criteria were pediatric patients (<18 years old) and the absence of an ICU-acquired stage 2 injury or DTI. Patients with a medical device–related PrI were included in the study only if they also developed a nonmedical device–related PrI of stage 2 or a DTI . PatientCritical care nurses at this institution conduct a head-to-toe skin assessment each shift and document results in the EHR, noting the location and stage of any HAPrI, which is then confirmed by a certified wound care nurse. Patients unable to reposition independently are repositioned every 2 hours, and skincare protocols are employed to encourage nurses to keep the skin as clean and dry as possible. All of the ICU beds are pressure redistribution/low air loss beds; bariatric pressure redistribution/low air loss beds are used for patients with obesity.Data were obtained using a combination of a query of the institution’s critical-care datamart cross-referenced with data maintained by the institution’s quality department, along with a manual review of the EPIC EHR system when necessary. Data extracted were limited to the first ICU stay for patients with multiple ICU stays. To capture HAPrI risk factors, only data from the timeframe between ICU admission and HAPrI detection were included.Stage 2 injury and DTI were defined according to the National Pressure Injury Advisory Panel definitions ; a PrI wt tests (or Wilcoxon rank-sum tests) for continuous variables and with the 2χ test (or Fisher exact test) for categorical variables. Variance inflation factors (VIFs) were calculated to detect if multicollinearity was present among the list of potential predictors. If none of the potential predictors had a VIF exceeding 5, we treated all predictors as independent predictors. We employed a logistic regression model with the least absolute shrinkage and selection operator (LASSO) method [All statistical analyses were performed in R version 3.6.1. . First, the distributions of potential risk variables between patients with stage 2 injuries and DTIs were summarized and compared using ) method  to identP values. Instead, by imposing a penalty in the regression model fitting, the LASSO approach shrinks the coefficients of unimportant predictors to zero while retaining the important coefficients [Unlike other variable selection approaches—such as the stepwise approach—the LASSO approach does not select important risk factors based on ficients . The optA total of 244 patients developed a stage 2 injury or DTI during the study period. Of those, 38 patients with a medical device–related PrI were excluded. The final study sample consisted of 206 patients (n=146 stage 2 and n=60 DTI). Univariate relationships between study variables and HAPrI stage are presented in 2χ1=8.43, P=.03). Among the 146 stage 2 HAPrIs, 93 (63.7%) were located on the sacrum or the coccyx and 11 (7.5%) were located on other bony prominences . Among the 60 DTIs, 30 (50%) were found on a bony prominence , whereas the other 30 (50%) occurred on fleshy parts of the body, particularly the buttock .Compared with DTIs, stage 2 HAPrIs were more likely to be located on a bony prominence  to the deeper tissues . ICU patIn this exploratory study, low diastolic blood pressure had the strongest correlation with the development of a DTI. This finding is consistent with a prior study aimed at identifying risk factors for DTI in ICU patients , which fThe finding that epinephrine, a potent vasopressor, was associated with DTI is further evidence for the importance of tissue perfusion in DTI etiology. Vasopressor drugs are administered to improve organ perfusion in patients with hypotension; however, the alpha-adrenergic properties of certain vasopressors, including epinephrine, cause arterial vasoconstriction and therefore decrease blood flow to the vessels in the muscles and peripheral tissues. Although it is well established that vasopressor drugs are risk factors for HAPrI, likely as a result of their indication (severe illness and hypotension) and the mechanism of action  ,9,24, thThis study showed that stage 2 HAPrIs were more likely than DTIs to be located on a bony prominence, whereas DTIs were mostly located on the fleshy parts of the body (primarily the buttock). This finding has important clinical implications for routine nursing care because routine skin assessment usually involves checking the bony prominences and not the fleshy areas [The differences in anatomic patterns, with stage 2 injuries mostly occurring on the bony prominences and DTIs mainly occurring on the fleshy areas, suggest a potential etiological difference between stage 2 injuries and DTIs. Stage 2 HAPrIs are likely primarily caused by pressure (tissue compression) between a surface  and a bony prominence, or pressure combined with shear force ,16,24.The study is limited by its small sample size, and therefore the results are considered exploratory. We were limited to the data contained in the EHR, and consequently unable to accurately obtain variables difficult to capture retrospectively, such as repositioning frequency. Moreover, these data are based on a single study site and therefore may not be generalizable to other institutions.Results from this exploratory study performed in surgical and cardiovascular ICU patients showed that deep tissue and stage 2 HAPrIs have different risk factors and different anatomic patterns. Patients who developed DTIs were more likely than patients with stage 2 HAPrIs to experience low diastolic blood pressure and to have received epinephrine, a potent vasopressor. Stage 2 HAPrIs were more likely to occur on the bony prominences, whereas DTIs commonly occurred on the fleshy parts of the body such as the buttock. Future research is needed to elucidate the detailed etiologic differences between stages, which will lead to identifying effective preventive interventions.


The most common cause of portal hypertension is liver cirrhosis. Portal hypertension causes many complications in cirrhotic patients; a significant complication is the formation of varices and the subsequent life-threatening variceal bleeding due to elevated portal venous pressures. Hepatic venous pressure gradient (HVPG) is the gold standard for measuring portal hypertension and guides management. Pharmacological treatments lower the HVPG, preventing the progression of varices and subsequent variceal bleeding. The pharmacological treatments frequently used in primary and secondary prophylaxis of a variceal bleed are nonselective beta (β)-adrenergic blockers. Propranolol was the first nonselective β-adrenergic blocker used for lowering HVPG and has been well studied. However, in the past decade, clinical trials have shown that carvedilol has been more effective. This study aims to establish whether carvedilol is more effective than propranolol in reducing the hepatic venous pressure gradient and decreasing the risk of variceal bleeding in adult cirrhotic patients. A systematic review has been conducted to gather relevant clinical trials comparing drugs and their effects on HVPG. Four databases: PubMed ), Google Scholar, the Cochrane Library, and ScienceDirect, were analyzed, and records from January 1, 1999, to January 1, 2023, were chosen. There were a total of 1,235 potentially eligible records across the four databases. Using the eligibility criteria for this systematic review, seven studies of 533 patients were included. Across all seven clinical trials, it was found that carvedilol reduced HVPG more than propranolol and decreased the risk of variceal bleeding in adult cirrhotic patients. Liver cirrhosis and its complicationsLiver cirrhosis is a severe and potentially life-threatening condition, with an estimated global prevalence of 0.27% to 0.45% and a mortality rate of 14.6% to 44.2% over five years, depending on the severity of the disease and the underlying cause [Portal hypertension and variceal bleeding Portal hypertension is an increase in hepatic vascular resistance to portal blood flow. The most common cause of portal hypertension is liver cirrhosis. It is defined by an increased portal venous pressure gradient above 5 millimeters of mercury (mmHg) . The patHepatic venous pressureThe gold standard method of measuring portal hypertension is the hepatic venous pressure gradient (HVPG), which is used to assess the severity of portal hypertension and guide its management. The HVPG is calculated by measuring the difference between the wedged hepatic venous pressure (WHVP) and the free hepatic venous pressure (FHVP). To measure the WHVP, a catheter is inserted into the hepatic vein and advanced to a hepatic venous branch, which is wedged to occlude the venous flow temporarily. The pressure measured at this point represents the WHVP. To measure the FHVP, the catheter is withdrawn close to the inferior vena cava (IVC), around 1 cm to 2 cm inside the hepatic vein. The pressure measured at this point represents the FHVP. The difference between the WHVP and the FHVP is the HVPG, which reflects the pressure gradient between the portal vein and the inferior vena cava. An HVPG of less than or equal to 5 mmHg is normal; 6-9 mmHg is mild portal hypertension; 10-19 mmHg is moderate portal hypertension; and ≥20 mmHg indicates severe portal hypertension -15. In pPharmacological management to decrease portal hypertension in cirrhotic patientsThere are pharmacological and interventional approaches to reducing portal hypertension, and the focus of this systematic review will be based on the pharmacological approach. Pharmacological therapy aims at decreasing hepatic vascular resistance by preserving or increasing portal blood flow and correcting hyperdynamic circulation and pathological angiogenesis while striving to reduce the hepatic venous pressure gradient to less than 12 mmHg, or 20% of the baseline . PatientPrimary prophylaxis prevents a variceal bleed in patients with a high risk of a variceal bleed . The recNonselective β-adrenergic blockers are the drugs of choice for preventing bleeding from esophageal varices . This isMethodsThe findings of this systematic review implement the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines .Eligibility CriteriaThe Population, Intervention, Control, and Outcomes (PICO) criteria were used as the primary framework for the eligibility criteria. The literature selected for this systematic review is based on all the components of the PICO criteria, as follows:Population: Selection of studies with adult cirrhotic patients ≥19 years old from all ethnicities and genders; Intervention: Carvedilol for reducing HVPG and lowering the risk of a variceal bleed; Comparison: Propranolol for reducing HVPG and lowering the risk of a variceal bleed; and Outcomes: Studies displaying evidence of which drug, carvedilol or propranolol, lowered HVPG and reduced the risk of a variceal bleedInclusion and Exclusion CriteriaThe inclusion criteria in this systematic review included studies investigating whether carvedilol is more effective than propranolol in reducing the hepatic venous pressure gradient and decreasing the risk of variceal bleeding in adult cirrhotic patients. There were no gender or ethnic restrictions on the population of the studies. Papers of all languages with English translations, free full-text articles published between 1999 and 2023, randomized controlled trials, non-randomized control trials, meta-analyses, literature, and systematic reviews were included in the study. Case studies, case reports, gray literature, animal studies, and editorials were excluded from this systematic review.Search StrategyThe online search used PubMed, Google Scholar, the Cochrane Library, and ScienceDirect. Keywords that have been utilized for the websites mentioned above include "carvedilol," "propranolol," "non-selective adrenergic beta-agonists," "portal hypertension," "hepatic venous pressure gradient," "esophageal and gastric varices", "gastrointestinal hemorrhage", and "liver cirrhosis." The Medical Subject Headings Search (MeSH) targeted the keywords presented in this systematic review. The Boolean method combined the keywords to search the databases mentioned above uniformly; MeSH concepts, key terms, and search results from each database are shown in Tables Data Selection and ExtractionTwo researchers (LD and MT) independently selected and extracted relevant studies. Disagreements over eligibility between the two researchers were resolved by discussing the study design, intervention implemented, outcomes measured, and relevance to inclusion and exclusion criteria. A third researcher (TS) was solicited when a uniform consensus could not be reached. Across all databases, there were a total of 1,235 potential eligible records. Based on the eligibility criteria, a total of seven studies consisting of 533 patients formed the basis of this review. The studies included seven randomized controlled trials. From the studies included, the following data were retrieved: (i) the surname of the principal author and the publication date; (ii) a study overview ; and (iii) general features of the study population .Study Quality AppraisalEach study used in this systematic review was assessed for the potential risk of bias. Clinical trials were evaluated using the revised Cochrane risk of bias 2 (RoB 2) tool. With the latest Cochrane RoB 2 tool, each randomized controlled trial was assessed for potential biases based on five risks of bias. Each risk of bias was scored as either low, high, or moderate. Subsequently, the overall risk of bias was also reported as low, moderate, or high . Table 3ResultsThe various search strategies across the databases identified 1,235 records. Out of 1,235 records, 726 originated from PubMed ), 492 from Google Scholar, two from the Cochrane Library, and 15 from ScienceDirect. No other resource was used. A total of three duplicates were removed online using EndNote before screening the articles. The remaining 1,232 records were thoroughly screened for relevance based on titles and abstracts, after which 1,000 records were excluded due to their irrelevance to the topic, research objectives, inclusion, and exclusion criteria. Hence, 232 articles were sought for retrieval, and after thoroughly checking again for relevance to the research topic, inclusion and exclusion criteria, and free full texts, a further 213 were removed.A total of 19 reports were assessed for eligibility, and 12 were removed. Two reports were removed as they contained no data of interest; seven were removed as they did not address the research topic; and three were removed because they needed more population of interest. Therefore, seven reports were included in this systematic review and all seven were randomized control trials. The complete PRISMA flow diagram is shown in Figure Table DiscussionClinical Trial ResultsIn the seven clinical trials that were chosen for this systematic review, all have displayed that carvedilol reduced HVPG more than propranolol, hence reducing the risk of variceal bleeding. Agarwala et al., in a randomized controlled trial, found that of the 36 patients that received carvedilol, only three had a first variceal bleed during the six-month follow-up. Of 32 patients receiving propranolol, 10 had first variceal bleeding during the six-month follow-up . Regarding rebleeding after the first variceal bleed, out of 21 patients taking carvedilol, three had rebleeding, compared to 10 out of 22 in the propranolol group . Furthermore, this study highlights that carvedilol is more effective in lowering the risk of variceal bleeding than propranolol and can be used as both primary and secondary prophylaxis for variceal bleeding . In BañaGupta et al. studied the effect of carvedilol versus propranolol on HVPG in 59 cirrhotic patients after having their first variceal bleeding . Patients were followed up after one month, and it was found that HVPG was reduced significantly in both groups (p = 0.001); the number of HVPG responders was significantly higher in the carvedilol group (22/29) as compared to the propranolol group (14/28), p = 0.04. Hence, carvedilol effectively reduces portal pressure in cirrhotic patients with esophageal bleeding . In SharCarvedilol’s Effects on Hemodynamics Other than HVPGMean arterial pressure (MAP) is the average blood pressure during a single cardiac cycle. The hemodynamic target in cirrhotic patients is a systolic blood pressure above 90 mmHg with a pulse above 55 beats per minute. In patients with decompensated cirrhosis, carvedilol can be used at low doses if the systolic blood pressure is above 90 mmHg . NonseleStudies have shown that reducing MAP can lead to a reduction in HVPG, reducing the risk of variceal bleeding and improving overall outcomes in cirrhotic patients. Tripathi et al.'s randomized controlled trial of 213 cirrhotic patients with portal hypertension found that using nonselective β-adrenergic blockers lowered MAP and was associated with a significant reduction in HVPG and a lower risk of variceal bleeding compared to placebo . Lee et Carvedilol's Side Effect Profile Compared with Propranolol While carvedilol seems like an effective alternative to propranolol, it is important to discuss its side effect profile. The two main concerns about the clinical use of carvedilol in cirrhotic patients include hypotension and new-onset or worsening ascites. Hypotension in cirrhotic patients using carvedilol would manifest as fatigue, weakness, dizziness, and orthostatic hypotension. Orthostatic hypotension was reported by Bañares et al., where 14/65 patients taking carvedilol experienced orthostatic hypotension compared with the 9/60 propranolol-treated patients. This calls for caution when used in clinical practice . In the Regarding worsening ascites, Bañares et al. noted a significant increase in plasma volume and body weight in cirrhotic patients receiving carvedilol and not propranolol. Additionally, an increase in diuretic dosage was needed in seven carvedilol patients compared with two propranolol patients because of new-onset or worsening ascites or ankle edema. The new onset/worsening ascites have been attributed to a possible increase in sodium retention  and the LimitationsThis study is limited because the acquired results were from single-center studies with small study populations and varying follow-up courses. Notably, there is significant heterogeneity in the results reported between the studies due to differences in the dose and frequency of carvedilol and propranolol.Liver cirrhosis is the most common cause of portal hypertension. Portal hypertension has devastating consequences in cirrhotic patients, such as the development of varices and subsequent variceal bleeding. Portal hypertension is measured through the hepatic venous pressure gradient. Pharmacological management with nonselective β-adrenergic blockers is used in cirrhotic patients to lower portal hypertension and as primary and secondary prophylaxis for variceal bleeding. Propranolol was the oldest and most commonly used nonselective β-adrenergic blocker to lower portal hypertension and reduce the risk of variceal bleeding. Clinical trials have shown that carvedilol is more effective than propranolol in reducing HVPG and the risk of variceal bleeding. Given the clinical trial results, carvedilol should be considered an effective alternative to propranolol in cirrhotic patients with portal hypertension and varices. However, large-scale multicenter studies with extended follow-up periods are warranted to assess this thoroughly.


Postmenopausal women are at increased risk of coronary artery disease (CAD). Diabetes Mellitus is a major risk factor for CAD. The stiffening of the aorta is associated with increased cardiovascular morbidity and mortality. We aimed to investigate the relation of aortic elasticity parameters to CAD severity assessed by SYNTAX score (SS) in diabetic postmenopausal women. The study prospectively included 200 consecutive diabetic postmenopausal women with CAD who underwent elective coronary angiography. Patients were classified into 3 groups based on SS, low-SS ≤ 22, intermediate-SS ≥ 23– ≤ 32, and high-SS ≥ 33. Echocardiographic aortic elasticity parameters, including aortic stiffness index (ASI), aortic strain (AS) (%) and aortic distensibility (AD) were obtained in all patients.P-values  and cut-off values , respectively.Patients in the high SS group were older age and had a higher aortic stiffness. After adjusting different co-variates AD, AS, and ASI could be used as independent predictors of high SS with the following In diabetic postmenopausal women, the simple echocardiography-derived aortic elasticity parameters might predict the severity and complexity of angiographic coronary lesions assessed by the SS. Ischemic heart disease is the major cause of morbidity and mortality in diabetic women, and this risk increases in women who have attained menopause , 2. WomeThe study prospectively included 200 consecutive postmenopausal women with type 2 DM presenting to Tanta University, Cardiology department during the period from September 2022 till December 2022 and were referred for elective coronary angiography for diagnosis of CAD based on patients’ symptoms, positive stress test, and electrocardiographic evidence of ischemia.Informed consent was taken from all patients, and the study was approved by the local ethical committee.The diagnosis of diabetes was based on the clinical history of pre-existing DM , fasting plasma glucose ≥ 126 mg/dL, 2-h plasma glucose ≥ 200, a random plasma glucose ≥ 200 mg/dL or HbA1c ≥ 6.5% any time .Menopause is defined as women with the absence of a menstrual period for at least 12 consecutive months and not using a hormonal contraceptive .Exclusion criteria were: Poor echogenic window, patients presenting with acute coronary syndrome, left ventricular ejection fraction (LVEF) < 50%, use of hormone replacement therapy, those without significant CAD , normal coronary angiography, patients on hemodialysis, collagen vascular diseases, congenital heart disease, more than mild valvular stenosis or regurgitation, prior percutaneous coronary intervention, history of coronary artery bypass surgery, prosthetic heart valves, atrial fibrillation, atrial flutter.As the flowchart shows in Fig. Blood pressure (BP) measurements were obtained just before starting the echocardiographic study. Blood pressure values were obtained in the sitting position after at least 5 min of rest in a quiet room. BP was measured three times with mercury sphygmomanometers at 1–2 min intervals. Systolic and diastolic BP was recorded as the average of the last two BP measurements, and the difference between them was defined as pulse pressure .Coronary angiography was performed using the standard techniques through the femoral or radial approach. The SS was computed from the diagnostic coronary angiogram as the sum of the points for each significant coronary lesion (defined as diameter stenosis > 50% in vessels with minimum diameter > 1.5 mm). Patients were divided according to the SS into three groups: Low‑SS ≤ 22, intermediate‑SS ≥ 23– ≤ 32, and high‑SS ≥ 33 Two dimensional transthoracic echocardiographic and Doppler studies were performed using the commercially available GE Vivid 7 echocardiograph with a 2.5 MHz transducer. LVEF was evaluated using the modified Simpson formula In the parasternal long-axis view the systolic and diastolic inner diameters of the ascending aorta were measured by M-mode tracing 3 cm distal to the aortic valve.The aortic systolic diameter (AoS) was measured at the maximal anterior motion of the aortic valve, whereas the diastolic diameter (AoD) was measured at the peak of the QRS complex on the simultaneously recorded electrocardiogram. The measurements were averaged over 3 consecutive cardiac cycles. Aortic elasticity indices were calculated according to these formulas:n experienced echocardiographer performed all measurements. In randomly selected 15 patients intra-observer and inter-observer variability of aortic elasticity indices were evaluated using intraclass correlation coefficients by repeated analysis by the same investigator or independently by two separate investigators.Statistical analyses were performed using the IBM SPSS software package version 20.0. . The Kolmogorov- Smirnov test was used to test for the normal distribution of continuous data. The obtained quantitative data were presented as mean, standard deviation (SD), and qualitative data were expressed as numbers and percentages. Results were analyzed using one-way analysis of variance (ANOVA) when comparing between more than two means, and the Post Hoc test was used for multiple comparisons between different groups. A Chi-square (X2) test of significance was used in order to compare proportions between two qualitative parameters.P value < 0.05 is considered as statistically significant.Univariate and multivariable logistic regression analyses were performed to detect potential independent predictors of high SS. Receiving operator characteristics (ROC) curve was used to detect optimal cut-off values of aortic elasticity parameters for predicting a high SS. A In addition, the power of the sample size was calculated by G Power tool  with 0.05 alpha and 0.25 effect size. The calculated power value was 0.89 according to post hoc-type power analysis.This cross-section study included two hundred postmenopausal female patients who attended the cardiology department for elective coronary angiography.Patients were classified into three groups according to the severity of coronary artery disease as measured by the SS: low, intermediate, and high SS groups.The clinical, hemodynamic, laboratory and echocardiographic parameters of the aortic stiffness of the three groups were analyzed Table . There iP-values of , respectively  respectively, ASI (0.001 and 0.001) respectively and AD (0.001 and 0.001) respectively and AS (0.001 and 0.001) respectively. However, there was no statistically significant difference regarding these parameters in low and intermediate SS groups.On the other hand, there was a statistically significant difference between the three groups regarding age, systolic blood pressure, diastolic blood pressure, pulse pressure, AD, AS, and ASI with P-values of  respectively.In the same context, the post hoc test showed that there is a statistically significant increase in age with the increase in SS with a statistically significant difference between low and intermediate, low and high as well as intermediate and high score groups with P-values of 0.001 for both.There were statistically significant differences between patients with high and low SS as well as patients with intermediate and high SS regarding the systolic and diastolic blood pressure at enrollment with P-values of  respectively  with sensitivity , specificity  and the area under the curve of  respectively Figs. .Fig. 2ThIntra-observer and inter-observer variability for aortic elasticity indices measurements ranged from 0.93 and 0.96.Menopause is associated with an increased incidence, progression, and severity of metabolic syndrome ; Large sSmulyan et al. observed in their study that structural alterations of the blood vessel caused age-related variations in pulse wave velocity in women; however, they did not expressly take into account the influence of menopause in their study. Palmiero et al.  in theirAlso, after adjusting for different cardiovascular risk factors in the SWAN study, arterial stiffness was found to be increased by 7.5% within one year of the final menstrual period; they used the carotid-femoral pulse wave velocity as a marker for aortic stiffness .On contrary to these findings and to the findings in our study, the cross-sectional study by, Lodon et al. showed that menopause reduces the age-related rise in arterial stiffness, although their sample size was too small .Saltiki et al. . examineIn a retrospective analysis of the Women's Angiographic Vitamin and Estrogen (WAVE) trial Ahmad et al.  discoverAfter menopause, both the prevalence and mortality of CAD in women rise. Age, abdominal obesity, and in particular (DM), combined with ovarian function loss and the resulting lack of endogenous estrogens, accelerate the development of atherosclerosis. It is generally known that estrogen positively affects some of the main CAD risk factors .The hallmark of the current study is that the increased aortic stiffness as measured by AD, ASI, and the AS was related to more aggressive coronary atherosclerosis and high SS in diabetic postmenopausal women. In our cohort, this finding was not dependent on other traditional cardiometabolic risk factors such as smoking status, history of hypertension, BMI, HBA1c, and lipid profile levels as these factors did not show any significant difference between the studied groups.Moreover, in the multivariate analysis, after adjusting different variables that can affect the severity of coronary artery disease, the parameters mentioned above were found to be independent predictors of a high SS.Aortic elasticity plays a vital role in maintaining blood flow during diastole. It regulates the pulsatile flow of blood from the heart and makes a steady state of flow to different body organs . ArteriaIt is difficult to ignore the impact of age when analyzing how menopause affects arterial stiffness. However, it has been documented that estrogen deficit in postmenopausal women worsens the effects of aging on arterial stiffness. Additionally, the renin-angiotensin system is also activated, atherogenic inflammatory cytokines are produced, and collagenase activity is decreased by estrogen deficiency .Estrogen receptors α and β are present in the human vasculature, and estradiol is thought to keep the elasticity of the aorta through vasodilatation and vascular matrix formation . There iMany studies used the carotid-femoral pulse-wave velocity  and anklSimilar to our study Karakurt et al.  found thThe limitation of this study includes the small sample size as we calculated the sample size to the whole study population for each group; we can not exclude the influence of age on our results.In diabetic postmenopausal aortic elasticity parameters evaluated by echocardiography might predict high SS.


During the follow-up, 18 patients had a CV event, and 37 patients had a renal event. In the univariate cox regression analysis, systolic AOBP was found to be predictive of the primary outcome , and after adjustment for eGFR, smoking status, diabetes, and a history of CV disease and systolic and diastolic AOBP were also found to be predictive of the primary outcome . Conclusions: In patients with CKD, AOBP appears to be prognostic of CV risk or risk for kidney disease progression and could, therefore, be considered a reliable means for recording BP in the office setting.Background: The aim of this study was to evaluate the prognostic value of automated office blood pressure (AOBP) measurement in patients with hypertension and chronic kidney disease (CKD) stage 3–5 not on dialysis. Methods: At baseline, 140 patients were recruited, and blood pressure (BP) measurements with 3 different methods, namely, office blood pressure (OBP), AOBP, and ambulatory blood pressure measurement (ABPM), were recorded. All patients were prospectively followed for a median period of 3.4 years. The primary outcome of this study was a composite outcome of cardiovascular (CV) events  or a doubling of serum creatine or progression to end-stage kidney disease (ESKD), whichever occurred first. Results: At baseline, the median age of patients was 65.2 years; 36.4% had diabetes; 21.4% had a history of CV disease; the mean of estimated glomerular filtration rate (eGFR) was 33 mL/min/1.73 m The incidence of end-stage kidney disease (ESKD) keeps rising in many industrialized nations, regardless of the widespread use of treatments to limit the progression of CKD . It has se study . Hypertese study . HoweverSimilarly to the general population, the diagnosis of hypertension in patients with CKD is based on office blood pressure measurements (OBP) and, in recent decades, ambulatory blood pressure measurements (ABPM). The latter method was found to be more accurate, not only in the identification of hypertension but also in the prediction of CVD risk , despiteAOBP correlates better than OBP with left ventricular mass  and micrThe participants of this study were recruited at the nephrology clinics of two Greek hospitals, Athens General Hospital Evangelismos and University General Hospital of Alexandroupoli. The inclusion criteria were patients with hypertension who were under treatment, had CKD stage 3–5 (according to the CKD-EPI equation), were not on dialysis, and were between 18 and 85 years of age. Exclusion criteria included acute kidney injury within the previous 2 months; kidney transplantation; pregnancy; hemodialysis or peritoneal dialysis; a change in antihypertensive therapy during the previous 15 days; and serious non-cardiovascular diseases such as cancer or liver cirrhosis. Those unable to attend follow-up office visits were omitted as well.All eligible individuals received a medical interview, anthropometric measurements, and blood and urine tests at the start of the study. Specifically, laboratory data  were collected during the initial study visit. Each participant’s history of smoking, hyperlipidemia, and risk factors for CVD had been assessed. Serum creatinine concentrations were measured, and the estimated glomerular filtration rate (eGFR) was obtained by using the CKD-EPI equation adjusted for body surface area. This study was conducted in conformity with the principles of the Declaration of Helsinki. All participants gave their informed consent, and the study was authorized by the hospitals’ ethical committees and scientific boards.All BP readings  were taken in hospital outpatient settings. OBP was computed as the mean of two consecutive measurements by using a certified digital oscillometric BP electronic instrument  and a medium–large stable bladder, 22–42 cm. BP measurements were obtained at 1 min intervals from 8:30 to 10:30. Before assessing OBP, participants were instructed to stay seated for 5 min and to avoid speaking; a doctor from the research team was present throughout. Systolic blood pressure (SBP) lower than 140 mm Hg and diastolic blood pressure (DBP) lower than mm Hg were deemed acceptable levels for OBP . After tFor 24 h ABPM monitoring, a certified electronic Microlife WatchBP O3, bladder size 22–32 cm, or 32–42 cm, was employed. The device was set to take a reading every 15 min during the day (06:00–23:00) and every 30 min during the night (00:00–06:00) (23:00–06:00). At the time of measurement, participants were told to immobilize their arm and record their day activities and sleep duration in a notebook. SBP lower than 135 mm Hg and DBP lower than 85 mm Hg were accepted values of normality for ABPM in adults during daytime (awake); night-time (asleep) SBP and DBP lower than 120 and 70 mm Hg, respectively; and 24 h SBP and DBP lower than 130 and 80 mm Hg, respectively .The Microlife WatchBP Office device, which was validated for OBP measurement by the International Protocol , was useBeginning with the initial study visit, participants attended follow-up meetings every six months to monitor BP management, antihypertensive therapy, and primary outcomes. The primary outcome of this study was a composite outcome of a CV event, serum creatine doubling, or development of ESKD, whichever came first. CV events comprise fatal or nonfatal CV events, such as myocardial infarction; coronary heart disease, including coronary intervention, hospitalization for heart failure (HF), stroke, and intermittent claudication; and peripheral arterial disease interventions, whichever happened first. Renal events were defined as serum creatinine levels doubling or the progression to ESKD. The endpoint of ESKD was met on the first day of dialysis treatment.2 test, and continuous variables were compared by using Student’s t test. We utilized Cox proportional hazard models to assess the relationship between the initial BP values  and the onset of a CV or renal event. The correlation between OBP, AOBP, and ABPM values and the primary outcome was evaluated by using hazard ratios and their 95% confidence intervals per 1 mm Hg increase in systolic and diastolic BP. In the Cox regression analysis, two models were conducted: the first model was univariate-unadjusted, and the second model was multivariate-adjusted for baseline covariates known to influence renal and CV outcomes, such as smoking status , diabetes, eGFR, and a history of CVD. Moreover, by using the Cox regression analysis, we developed survival curves, which were adjusted for smoking status , diabetes, eGFR, and a history of CVD, in various groups of patients based on normal and high levels of BP assessed at baseline by using the three distinct techniques, OBP, AOBP, and ABPM. All p values are two-sided, and p < 0.05 denotes statistical significance. All statistical analyses were performed by using version 20.015 of the MedCalc statistical tool.The Kolmogorov–Smirnov test was utilized to examine the data for normality. Normally distributed continuous variables are expressed as the mean standard deviation, non-normally distributed continuous variables are expressed as the median (interquartile range), and categorical variables are expressed as a percentage. Categorical variables were compared by using the χ(n = 9), changes in antihypertensive treatment 2 weeks before the study (n = 8), and acute kidney injury on top of CKD in the last two months (n = 4). Six patients were lost to follow-up. The median age of the patients was 68 (57–76) years, and 50 (35.7%) were women. In total, 51 patients (36.4%) had diabetes, 30 patients (21.4%) had a history of CVD, 83 patients (59.3%) were receiving drugs for hyperlipidemia, and 19 patients (13.6%) were current smokers. The number of patients with CKD stages 3a, 3b, 4, and 5 was 39 (28%), 42 (30%), 47 (33.5%), and 12 (8.5%), respectively, with a mean eGFR of 33 ± 14 mL/min/1.73 m2. Demographic, clinical, and treatment information on the 140 patients included in the cohort is presented in We included 140 of 161 eligible patients. The reasons for exclusion were inadequate ABPM recordings At baseline, the mean systolic/diastolic OBP, AOBP, and daytime ABPM were 151/81 mm Hg, 134/77 mm Hg, and 132/77 mm Hg, respectively . The meaCompared with patients without an event, patients who experienced CV or renal events during the follow-up period had lower eGFRs; higher levels of iPTH and albuminuria; higher systolic daytime, night-time and 24 h ABPM values; and higher numbers of antihypertensive drugs used .From the Cox regression analysis, neither the systolic nor the diastolic OBP measurements were predictive of the primary outcome by using the unadjusted model; however, the diastolic OBP readings were found to be predictive of the primary outcome according to the adjusted model . Progressing with the analysis, the systolic AOBP readings were predictive of CV or renal events by using the unadjusted and adjusted models . The diastolic AOBP readings were not predictive of the primary outcome when fitted to the unadjusted model but were predictive according to the adjusted model . Systolic daytime ABPM appeared to be predictive of the primary outcome by using the unadjusted model  but was not predictive with the adjusted model, and diastolic daytime ABPM was not found to be predictive by using the unadjusted model but was predictive with the adjusted model . Systolic night-time and 24 h ABPM were predictive according to the unadjusted model  and the adjusted model . On the other hand, diastolic night-time and 24 h ABPM were not predictive when fitted to the unadjusted model but were predictive according to the adjusted model . All the results are presented in p = 0.050 and p = 0.003, respectively). On the other hand, high systolic OBP and daytime and 24 h ABPM were of no prognostic importance. Regarding normal and high baseline diastolic BP, which were measured via the three methods, fitting the adjusted survival curves, it emerged that only high diastolic night-time ABPM was related to the primary outcome of this study (p = 0.004) (= 0.004) .With this prospective cohort study, we were the first to investigate the prognostic effect of AOBP measurements in hypertensive patients with stage 3 to 5 CKD who were not on dialysis. As a result, high systolic AOBP readings were found to be a significant factor for predicting the composite outcome of CV or renal events even after adjustment for smoking status, eGFR, diabetes, and a history of CVD. Furthermore, diastolic AOBP measurements were also found to be prognostic for CV or renal events when fitted to the adjusted model. Taken together, these results suggest that high systolic and diastolic AOBP readings are significant risk factors for the prognosis of hypertensive patients with CKD stage 3–5 in terms of CV and kidney disease.These findings are partially in line with those of the study of Myers et al. (2015) in a non-CKD population in which the prognostic values of AOBP readings for the development of future CV events were compared . IncludeIn a second study, which was similarly conducted in a non-CKD population (6.183 CHAP participants 66 years old on antihypertensive treatment at baseline), the association between obtained AOBP at baseline and CV events was investigated . The ave2) in the SPRINT trial, patients were randomly allocated to an SBP goal of 120 mm Hg  or 140 mm Hg  [In the SPRINT study, 9361 patients with an SBP of 130 mm Hg or more and a high CV risk were randomly given an SBP goal of less than 120 mm Hg (intensive therapy) or less than 140 mm Hg (standard therapy) [ = 1316) ; 112 indIn a comparison of OBP and AOBP, it has been demonstrated that AOBP reduces the white coat effect, prevents speaking during the rest and measurement periods, and eliminates observer error and bias ,23,24. I2) for whom BP measurements were obtained with the 3 different methods: OBP, AOBP, and ABPM [In our study comparing the mean SBP measurements with the three different methods, namely, OBP, AOBP, and ABPM, we found that the mean difference in systolic BP between AOBP and OBP was 17 mm Hg, while the difference in mean SBP between AOBP and daytime ABPM was only 2 mm Hg. These results are in concordance with the results of a cross-sectional study that included 91 CKD patients (mean eGFR 45 mL/min per 1.73 m2) [Regarding the prognostic role of the other two methods of BP measurement that were implemented in our study, systolic OBP was not predictive of the primary outcome, while diastolic OBP appeared to be prognostic of CV or renal events only when the adjusted model was applied. Systolic and diastolic ABPM were revealed to be prognostic of CV or renal events. These results are consistent with the findings of Minutolo et al. (2011), who investigated the prognostic role of daytime systolic and diastolic BP in comparison with OBP in 436 individuals with CKD  in the current study was always the same; meanwhile, a random order could be a more accurate method to compare the three techniques. In addition, home BP measurements could be employed to compare in-office and out-of-office BP measurement techniques comprehensively. Finally, our findings are based on a single BP measurement with the three different methods in two consecutive days at the beginning of the study. However, repeated measurements over time and longitudinal change could provide more a precise ability to predict outcomes.In conclusion, systolic and diastolic AOBP measurements perform well in the prediction of CV or renal risk in CKD hypertensive patients not on dialysis. The findings of this study affirm the role of AOBP as the reference technique for the assessment of BP in the office setting in patients with CKD. These results are in line with the KDIGO 2021 Clinical Practice Guideline for the Management of Blood Pressure in Chronic Kidney Disease , which p


Kidney transplantation is the first-choice treatment for end-stage renal disease (ESRD). Kidney transplant recipients (KTRs) are at higher risk of experiencing a life-threatening event requiring intensive care unit (ICU) admission, mainly in the late post-transplant period (more than 6 months after transplantation). Urosepsis and bloodstream infections account for almost half of ICU admissions in this population; in addition, potential side effects related to immunosuppressive treatment should be accounted for cytotoxic and ischemic changes induced by calcineurin inhibitor (CNI), sirolimus/CNI-induced thrombotic microangiopathy and posterior reversible encephalopathy syndrome. Throughout the ICU stay, Acute Kidney Injury (AKI) incidence is common and ranges from 10% to 80%, and up to 40% will require renal replacement therapy. In-hospital mortality can reach 30% and correlates with acute illness severity and admission diagnosis. Graft survival is subordinated to baseline estimated glomerular filtration rate (eGFR), clinical presentation, disease severity and potential drug nephrotoxicity. The present review aims to define the impact of AKI events on short- and long-term outcomes in KTRs, focusing on the epidemiologic data regarding AKI incidence in this subpopulation; the pathophysiological mechanisms underlying AKI development and potential AKI biomarkers in kidney transplantation, graft and patients’ outcomes; the current diagnostic work up and management of AKI; and the modulation of immunosuppression in ICU-admitted KTRs. Kidney transplantation (KT) is the best therapeutic option for patients with end-stage renal disease (ESRD) and is associated with a better quality of life and lower mortality compared to patients on chronic dialysis . AdvanceAKI is estimated to occur in one fifth of the adult general population with acute illness, further increasing during ICU stay . Kidney Furthermore, the recent COVID-19 pandemic contributed to a boost in AKI incidence : it is eAKI consists of an abrupt worsening of the renal function, characterized by an increase in serum creatinine by at least 0.3 mg/dL within 48 h, an increase in serum creatinine to 1.5 times from baseline within a week or urinary output inferior to 0.5 mL/kg/h for 6 h, according to KDIGO criteria . AKI is Infections and severe sepsis are universally considered the prominent cause of ICU admission for AKI in KTRs. Their incidence varies according to the timing after transplantation, with a prevalence of opportunistic infections and activation of latent infection during the first 12 months, while community-acquired infections predominate in the late post-transplant period  29]. In. In29]. Escherichia coli and Klebsiella pneumoniae are described as the principal infectious agents in KTRs with UTIs, although an increased incidence of infections due to multi-resistant organisms  and fungi (Candida species) have reported in recent years [2 [95% CI: −3.23 to −1.35]) and graft loss at 1 year  recurrences did not exert a cumulative detrimental effect on allograft survival or on acute rejection frequency [Urosepsis and urinary tract infections (UTIs) are the most frequent infectious complications and the main causes of AKI in this population, mostly occurring within the first six months post-transplantation, presumably due to the intense immunosuppressive treatment regimen, the presence of ureteral stents and the unique anatomical configuration of the graft, including a shorter ureter, lacking anti-reflux properties and denervation that may hinder an early diagnosis ,32. Urosnt years ,34,35. Ant years . It is arequency ,37,38. Arequency . Human urequency . Microbirequency ,41,42.Escherichia coli) as the prevalent community-acquired pathogen [The second infectious cause of AKI in KTRs admitted in ICU is bloodstream infections with a cumulative incidence estimated between 10% and up to 40% of cases ,43. Discpathogen ,47.Cytomegalovirus (CMV) is ascribed as the leading viral pathogen in KTRs, particularly in the first months after kidney transplantation. CMV infection incidence is estimated to range between 40% and 80% . CMV hasEscherichia coli) with subsequent release in the bloodstream of gut-derived uremic toxins (p-cresyl sulfate and indoxyl sulfate), aberrant short chain fatty acids and lipopolysaccharides, thus paving the way for inflammation-driven AKI and progression to CKD [Finally, chronic immunosuppressive therapy may lead to intestinal disturbances and gut microbiome modifications with consequent bacterial translocation. This iatrogenic dysbiosis may favor the proliferation of pathobionts  are the milestone of immunosuppressive therapy in kidney transplantation, albeit burdened by a certain side effect. Dysregulation of vasoconstrictor factors, such as endothelin and thromboxane A2, associated with the reduced release of vasoactive molecules, including nitric oxide, prostacyclin and prostaglandin E2 in turn associated with both the renin–angiotensin–aldosterone system and sympathetic nervous system upregulation, led to abnormal vasoconstriction of the afferent arteriole and progressive allograft dysfunction ,59. AcutFinally, antimicrobials are routinely implemented, mostly in combinations, in the ICU setting, therefore acting as potent triggers for drug-induced AKI. The nephrotoxicity of aminoglycosides has been widely reported in literature, and they are acknowledged to upregulate reactive oxygen species (ROS) production on epithelial cells at the level of the S1 and S2 segments of the proximal tubule in a dose-dependent manner . ToxicitKTRs are exposed to additional potential conditions associated with a high risk for AKI, such as ischemia–reperfusion injury, surgical complications, acute antibody mediated or T-cell mediated rejection, side effects from immunosuppressive therapy, urinary tract infections (UTIs) and sepsis ,75,76. HFurthermore, the use of immunosuppressive drugs naturally exposes recipients to a higher risk of contracting infectious diseases: in the context of sepsis, the risk of AKI onset is not only related to hemodynamic alteration and reduced renal blood flow, but due to direct pathogen effects on renal tissue. Several studies have also shown that E. coli infections result in site-specific endothelial dysfunction at the renal proximal tubule through bacterial attachment to the apical tubular cells membrane, with consequent local reduction in peritubular blood flow and increased endothelial permeability ,82,83. SWith the advent of the COVID-19 pandemic, KTRs have been exposed to a new risk factor for the development of AKI, as they are more susceptible to severe forms of infection with worse clinical outcomes due to the limited humoral and cellular response to vaccine in this population . In thisSARS-CoV-2 can promote the development of AKI through multiple pathophysiological mechanisms. An indirect mechanism has been firstly reported as the consequence of severe hemodynamic alterations in the context of COVID-19 pneumonia with consequent cardiac dysfunction, decreased cardiac output and hypoperfusion . Common The overproduction of proinflammatory cytokines  induced endothelial dysfunction and other inflammatory pathways similar to those involved in sepsis and leading to multi-organ dysfunction . AnotherIn addition, a mechanism of the direct infection of renal cells by SARS-CoV-2 has been hypothesized, as the presence of SARS-CoV-2 was observed in various renal districts, but especially at the glomerular level . InteresFinally, it is noteworthy to report the other causes of AKI in kidney transplantation should be taken into account; the need to revise the immunosuppressive regimen, such as by modifying and/or stopping immunosuppressive drugs, may lead to changes in the immunological status with donor-specific antibodies (DSA) formation and, consequently, the development of humoral rejection .Classical AKI criteria are known to present several limitations in assessing kidney disease in the acute setting. Serum creatinine is still the gold standard for defining kidney dysfunction, but it represents a late marker, not able to early identify kidney injury. In addition, several factors may affect creatinine values, particularly in the acute setting of ICU patients; the creatinine production rate varies according to age, gender, muscle mass, diet, and nutritional state. Moreover, a prolonged ICU stay significantly affects muscle mass and, consequently, creatinine values.Over the years, many biomarkers related to AKI have been studied, aiming not only to diagnose AKI at an early stage but also to identify potential therapeutic targets for treatment ,104. NGAMore recently, Castellano and colleagues analyzed the role of anti-senescence protein Klotho in the kidney transplant setting: Klotho levels were significantly reduced in DGF patients, suggesting that Klotho deficiency may play a significant role in DGF-associated chronic allograft dysfunction due to its pleiotropic functions  . AnotherOverall, all of the listed biomarkers have rationales for their application in clinical practice; however, most of them are not well characterized and are based on studies with limited simple sizes. Considering the complexity of the pathophysiology of AKI and kidney transplant setting and the high cost of production and validation, further investigations are required before their routinary application in clinical practice.Transcriptomic biomarkers have also been investigated over the years, among which microRNAs (miRNAs) have been studied in kidney disease and organ transplantation. miRNA dysregulation related to genetic events or inhibition of regulatory enzymes have been reported to be involved in the pathogenesis of several disease, including kidney disease . Their fSeveral miRNAs play a crucial role in the patient with AKI. For example, increased urinary levels of miR-494, which inhibits the expression of the activating transcription factor 3 (ATF3) gene involved in the NF-κB pathway, have been shown in patients with AKI before the rise in serum creatinine . In addiSeveral miRNAs have been evaluated in the setting of kidney transplantation, with a specific focus on ischemia–reperfusion injury. The upregulation of miR-146a has been described in urine samples of kidney transplant recipients from deceased donors compared to those from living donors, suggesting its role as diagnostic marker for ischemia–reperfusion injury . MicroRNOverall, although several molecules have been proposed as diagnostic and/or predictive biomarkers for AKI and kidney transplantation, their application in the clinical practice is still lacking due to limited data on the discriminatory performance of such markers. A better characterization of this condition may lead to the identification of new molecules that can not only uniquely identify acute kidney damage and better discriminate different causes of AKI in the transplant setting but can also serve as potential therapeutic targets.Long-term graft and patient outcomes are a matter of major concern among KTRs admitted to the ICU. AKI has a higher prevalence in KTRs, and it is associated with an increased risk of graft loss and death by all causes . While IKTRs with AKI showed an increased risk of cardiovascular disease and mortality with respect to KTRs without AKI. A recent retrospective, single-center cohort study reported that AKI is associated with a 38% increased risk of major adverse cardiovascular events (MACE) and an 86% increased risk of cardiovascular mortality . HoweverFinally, limited data are available to date about the application in the AKI and kidney transplant setting of novel therapeutic approaches  characterized by the ability of reducing proteinuria and increased cardio- and renal protection in the general population . RecentlDespite the great efforts made in achieving a better understanding of the pathophysiological mechanisms involved in AKI, the management of such a condition is still limited to general measures, including volume resuscitation, hemodynamic management for optimization of hypovolemic conditions and early initiation of a sepsis care bundle with prompt antibiotic treatment in the case of sepsis and septic shock, taken for unselected critically ill patients ,133,134.The diagnostic work-out depends on the clinical conditions and the suspected underlying cause of AKI, as well as on the duration and severity of renal impairment. A regular monitoring of the kidney function and electrolyte plasma levels is mandatory for a proper management of the transplanted patient admitted to the ICU. As a general rule, any increase in serum creatinine exceeding 20% from baseline deserves an attentive evaluation to rule out any possible causes of acute illness and requires a nephrological consultation . In addiRRT initiation may be required in half of KTRs with severe AKI. In this case, when a previous dialysis access is not available, a new vascular access should be placed, taking care to avoid the placement of a femoral catheter on the same side of the graft. Hemodynamic instability and the need for optimal volume status control are the leading factors for the use of continuous renal replacement therapies (CRRT) instead of the intermittent modalities. The choice of the most appropriate CRRT modalities is subordinated to the patient’s characteristics, healthcare providers’ expertise and cost-effectiveness of the treatment; thus, a multidisciplinary approach involving intensivists, nephrologists and transplant teams is strongly recommended . There iThe optimal management of immunosuppressive therapy in KTRs admitted to the ICU may be pivotal in assessing clinical outcomes. There are several different immunosuppressive protocols with different combination of drugs, based on the individual risk of rejection as well as potential side effects to a specific drug. The foremost recommended combination of immunosuppressants for maintenance treatment includes a CNI, an anti-metabolite  and low-dose oral prednisone . NonetheNo consensus is available to date on the optimal management of immunosuppression in such conditions, and specific therapeutic adjustments, taking into consideration the underlying etiology of AKI in the ICU setting, are required. In conclusion, AKI following ICU admission in KTRs represents a major concern for nephrologists, as those patients are at higher risk of allograft loss and mortality. Sepsis represents the main cause of ICU admission and AKI development with pathophysiological mechanisms similar to non-transplant patients with sepsis; however, the immunological status of KTRs increases the risk of progression to severe forms of diseases and mortality that affect up to 30% of KTRs admitted in ICU. In this scenario, an optimal management should include volume status optimization, hemodynamic monitoring and prompt and appropriate antibiotic treatment; in addition, immunosuppression should be carefully managed according to patients’ condition and required a strong collaboration between nephrologists and intensivists.


H. pylori infection. We found elevated FCAL values in 39 (17.1%) of 228 IBS patients with food intolerance/malabsorption and H. pylori infection. Within these, fourteen patients were lactose intolerant, three showed fructose malabsorption, and six had histamine intolerance. The others had combinations of the above conditions: five patients had LIT and HIT, two patients had LIT and FM, and four had LIT and H. pylori. In addition, there were individual patients with other double or triple combinations. In addition to LIT, IBD was suspected in two patients due to continuously elevated FCAL, and then found via histologic evaluation of biopsies taken during colonoscopy. One patient with elevated FCAL had sprue-like enteropathy caused by the angiotensin receptor-1 antagonist candesartan. When screening for study subjects concluded, 16 (41%) of 39 patients with initially elevated FCAL agreed to voluntarily control FCAL measurements, although symptom-free and -reduced, following the diagnosis of intolerance/malabsorption and/or H. pylori infection. After the initiation of a diet individualized to the symptomatology and eradication therapy (when H. pylori was detected), FCAL values were significantly lowered or reduced to be within the normal range.Inflammatory bowel disease (IBD) involves two clinically defined entities, namely Crohn’s disease and ulcerative colitis. Fecal calprotectin (FCAL) is used as a marker to distinguish between organic IBD and functional bowel disease in disorders of the irritable bowel syndrome (IBS) spectrum. Food components may affect digestion and cause functional abdominal disorders of the IBS spectrum. In this retrospective study, we report on FCAL testing to search for IBD in 228 patients with disorders of the IBS spectrum caused by food intolerances/malabsorption. Included were patients with fructose malabsorption (FM), histamine intolerance (HIT), lactose intolerance (LIT), and  Crohn’s disease and ulcerative colitis are inflammatory bowel diseases (IBD), which are idiopathic disorders causing inflammation in the gastrointestinal (GI) tract. GI endoscopy, including histologic evaluation of the GI mucosa, are the golden standard, but is an invasive test for the diagnosis, management, and surveillance of IBD. Additionally, endoscopy is associated with considerable costs, perils, and burdens to patients and health systems . TherefoHelicobacter pylori (H. pylori) may cause symptoms across the IBS spectrum [Epidemiological and clinical studies indicate that specific nutrients in westernized diets pose a risk for the development and unfavorable disease courses of IBD . So far,spectrum . Accordispectrum  across tH. pylori infection, and that FCAL may be lowered significantly with individualized diets adapted to the symptomatology.Although the clinical usefulness of FCAL determinations has been demonstrated, there are limitations . Our resH. pylori were performed. The patients’ complaints included diarrhea, soft stools, bloating, and chronic abdominal pain. The initial stool tests for FCAL determinations were performed before patients received their individual diagnoses and in advance of their change in dietary behavior. In patients with initially elevated FCAL, control FCAL measurements were arranged via invitation by phone 3 to 6 months after diagnosis and following dietary behavior change.At presentation, all patients had symptoms of IBS spectrum disorders; therefore, tests for food intolerances/malabsorption and 2) lactose breath tests were started. An H2 breath test was used at first presentation to examine whether the patient had LIT, and at second presentation to examine whether the patient had FM. Lactose H2 breath tests were performed with Gastrolyzer  using 200 mL water and, 50 g of lactose after fasting. End-expiratory exhalation of H2 was measured every 30 minutes (min) for a period of 120 min. Blood glucose was determined with a glucose oxidase method, every 60 min for a period of 120 min. A lactose intolerance was diagnosed when the H2 increased > 20 parts per million (ppm) or the blood glucose increase was <20 mg/dL. FM was tested using H2 breath tests and with a drink containing 25 g of fructose . FM was present with the exhalation of H2 > 20 parts per million (ppm) compared to fasting H2. Before, the breath tests no antibiotics or laxatives were allowed and no colonoscopy was performed within 4 weeks prior to the breath test. In the morning at the first presentation, blood drawings were performed after overnight fasting (>12 h) and hydrogen .The Liaison XS chemiluminescence technology immunoassay was used to determine the quantitative measurement of calprotectin in stool samples . To identify HIT, systematic anamneses with a standardized questionnaire concerning abdominal complaints of HIT, and the response to a histamine-reduced diet was used. Diamine oxidase (DAO) in serum was determined using the radio extraction assay DAO Rea 100 . Antibodies against tissue transglutaminase were determined using anti-tTG IgA ELISA to consider celiac disease . An enzyme-linked IgA immunosorbent assay, anti-tTG IgA ELISA , or histologic evaluation of gastric mucosal biopsies were used to detect H. pylori. After the diagnosis of individual food intolerance/malabsorption, patients received written information regarding their personal food malabsorption/intolerance or the combinations thereof. A registered dietician helped improve a diet individually tailored to each patient’s symptomatology.In a retrospective analysis of outpatients’ charts, we identified 228 FCAL determinations in consecutive patients  with food intolerance/malabsorption and/or H. pylori infections with the number and percentage of patients with elevated FCAL. After contact via phone, 16 patients with previously elevated FCAL > 50 μg/g, came for a control of FCAL after 3 to 6 months. p < 0.001) from the initial measurement to the second control FCAL test.As a nonparametric statistical test for pairwise comparison of FCAL evaluations, the Wilcoxon test demonstrated a significant statistical difference , 13 had HIT (33.3%), 8 had FM (20.5%), and 6 patients had an H. pylori infection (15.4%). One patient had a sprue-like enteropathy.The numbers and percentages of individual food intolerance/malabsorption and Originally, IBS was determined according to the Rome consensus meetings, but performed validation studies advocate a simpler determination of classic IBS symptoms . NonetheFCAL concentrations reflect the activity of inflammatory cells, including neutrophils, in the intestinal mucosa. It is clinically used as a marker to quantify intestinal inflammation, as its concentrations significantly increase in patients with IBD. Subsequently, the correlation of FCAL with clinical disease activity helps to distinguish suspected or confirmed IBD . This waNonetheless, the gut infiltration of neutrophil leucocytes in IBD is not specific. Overall, the exact etiology of IBD as of IBS is still uncertain. It is suggested that abnormal activation of the immune system, genetic susceptibility, and altered intestinal flora—due to mucosal barrier defects—may play a role in the development of these disorders. Nevertheless, both conditions influence the gut microbiota . GeneralH. pylori (which is classified as a carcinogen) on GI microbial diversity and composition [H. pylori-only patients. Patients infected with H. pylori had high FCAL levels only in combination with food intolerance/malabsorption.In particular, lactose intolerance (LIT) appears as a documented reason for IBS spectrum complaints . Relatioposition  and on eposition . HoweverH. pylori, need to be considered for etiological clarification [H. pylori infection, and that the introduction of individualized diets significantly lowered FCAL values.To date, dietary management in disorders of the IBS spectrum is insufficient. Approximately half of adult LIT patients not only require reduced lactose intake, but also need additional diet adjustments to improve their GI symptoms . Howeverfication . In thisFCAL is clinically used to guide diagnostic and therapeutic decisions as a well-studied inflammatory biomarker due to its stability, assay reproducibility, and low cost. Currently, FCAL concentrations < 50 μg/g are considered normal. FCAL concentrations higher than 200 μg/g may indicate the presence of an endoscopic active state of IBD . HoweverThere is a complex relationship between diets, symptoms, and intestinal inflammation , and theWe demonstrated that food intolerance/malabsorption might have caused mucosal infiltration of neutrophils in patients with elevated FCAL values. This inflammation seems to have caused abdominal symptoms of the IBS spectrum in food intolerance/malabsorption. Subsequently, in patients who were symptom-free due to good adherence to their individualized food-reduction and/or elimination diets , FCAL levels were clearly reduced, or returned to within normal range. Targeted dietary intervention using reduction or exclusion diets for single or possibly combined food intolerance/malabsorption reduced intestinal inflammation and contributed to symptom relief with significant FCAL reduction.


Chronic kidney disease (CKD) is a global health concern. This study aims to identify key factors associated with renal function changes using the proposed machine learning and important variable selection (ML&IVS) scheme on longitudinal laboratory data. The goal is to predict changes in the estimated glomerular filtration rate (eGFR) in a cohort of patients with CKD stages 3–5.A retrospective cohort study.A total of 710 outpatients who presented with stable nondialysis-dependent CKD stages 3–5 at the Shin-Kong Wu Ho-Su Memorial Hospital Medical Center from 2016 to 2021.This study analyzed trimonthly laboratory data including 47 indicators. The proposed scheme used stochastic gradient boosting, multivariate adaptive regression splines, random forest, eXtreme gradient boosting, and light gradient boosting machine algorithms to evaluate the important factors for predicting the results of the fourth eGFR examination, especially in patients with CKD stage 3 and those with CKD stages 4–5, with or without diabetes mellitus (DM).Subsequent eGFR level after three consecutive laboratory data assessments.Our ML&IVS scheme demonstrated superior predictive capabilities and identified significant factors contributing to renal function changes in various CKD groups. The latest levels of eGFR, blood urea nitrogen (BUN), proteinuria, sodium, and systolic blood pressure as well as mean levels of eGFR, BUN, proteinuria, and triglyceride were the top 10 significantly important factors for predicting the subsequent eGFR level in patients with CKD stages 3–5. In individuals with DM, the latest levels of BUN and proteinuria, mean levels of phosphate and proteinuria, and variations in diastolic blood pressure levels emerged as important factors for predicting the decline of renal function. In individuals without DM, all phosphate patterns and latest albumin levels were found to be key factors in the advanced CKD group. Moreover, proteinuria was identified as an important factor in the CKD stage 3 group without DM and CKD stages 4–5 group with DM.The proposed scheme highlighted factors associated with renal function changes in different CKD conditions, offering valuable insights to physicians for raising awareness about renal function changes. Chronic kidney disease (CKD), characterized by decreased glomerular filtration rate, is a global health concern with a high prevalence rate 10–15%); moreover, this disease is highly associated with morbidity and mortality, leading to financial and medical burdens 0–15%; mo. The graTimely intervention for delaying the progression of CKD to ESKD may not only improve the quality of life of patients but also reduce the associated morbidity and mortality , 7. As tMachine learning (ML) methods excel in analyzing unstructured data and complex patterns, whereas traditional statistical methods often require human intervention and expertise in model selection, hypothesis formulation, and result interpretation . In the 2  scheme in a CKD cohort with longitudinal laboratory data. In the context of longitudinal data analysis, it is crucial to prioritize the examination of the rate and variation of biochemical data rather than solely relying on baseline data. This study employed five effective ML algorithms, namely, stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), random forest (RF), eXtreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). Using these algorithms, we developed an integrated multistage ML-based predictive scheme for all four subgroups according to eGFR and presence of DM to predict eGFR changes and subsequently evaluate and integrate relatively important risk factors.2 based on the four-variable modification of diet in renal disease study equation  a decrease in eGFR of ≤60 mL/min/1.73 mequation , and thoequation . PatientThis study was conducted according to the guidelines of the Declaration of Helsinki and was approved by the Institutional Review Board of the Shin-Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan (IRB no. 20200901R). Informed consent was waived because our study was based on a medical chart review. Patient information was anonymized and de-identified before analysis.This study aimed to predict eGFR changes and the corresponding relationship between risk factors in the fourth examination of each patient; thus, the results of the first three examinations of each patient were utilized as independent variables. As the results of the first three examinations were collected from each patient, the independent variables used in this study could be regarded as longitudinal predictor variables.Vi,t represents the tth time examination result of ith variable . A total of 17 variables were utilized in this study. Moreover, as all patients had previous records of their first three examinations, the variables used in this study could be further defined as Equation (1).The definitions of the longitudinal variables used in this study are presented in i ≤ 17; 1 ≤ t ≤ 3.where 1 ≤ Vi,3) in this study. The predictor variable generated using the “closest” approach (iCV) was defined as Equation (2). For example, V1C is the SBP result of the third examination  and can be written as SBP(C).Then, this study utilized three approaches for generating more predictor variables that can be used to construct the ML predictive models. These three approaches, namely, “closest,” “mean,” and “standard deviation,” could provide various data from the independent variables. The “closest” approach generated the predictor variable using the result of the latest examination, which is the third examination result . The predictor variable generated using the “mean” approach (iMV) was defined as Equation (3). For demonstration, V1M was constructed by calculating the mean of the results of the first , second , and third  SBP examinations. V1M can also be written as SBP(M).The “mean” approach generated the predictor variable by calculating the mean of the results of the first three examinations (iSV) by calculating the standard deviation of the results of the first three examinations , as shown in Equation (4). For example, V1S is the standard deviation of the results of the first three SBP examinations  and can be written as SBP(S).Similar to the concept of the “mean” approach, the “standard deviation” approach generated the predictor variable  are presented in This study proposed an integrated multistage predictive scheme known as ML&IVS based on five ML methods, including SGB, MARS, RF, XGBoost, and LightGBM, for predicting eGFR changes and subsequently identifying important risk factors. The five ML algorithms have been successfully used in various medical/healthcare applications , 34–37. In this process, first, 4-year health examination data of patients with CKD were collected; the dataset is described in Section “2.1. Dataset.” Second, 47 longitudinal risk variables were defined, and the patients were categorized into five subgroups: Group 1 (patients with CKD stage 3 and DM), Group 2 (patients with CKD stage 3 without DM), Group 3 (patients with CKD stages 4–5 and DM), Group 4 (patients with CKD stages 4 and 5 without DM), and Group 5 . The definitions of variables are presented in Section “2.2. Definition of longitudinal variables.”Third, RF, SGB, MARS, XGBoost, and LightGBM were used to construct predictive models for all five groups. As multiple linear regression (MLR) is a commonly used statistical method in medical/healthcare applications, it was used in this study as a bench method. RF is an ensemble learning decision tree algorithm that combines bootstrap resampling and bagging . The RF XGBoost is a gradient boosting technology based on an SGB-optimized extension . It traiFourth, after constructing effective ML models for all five groups, the relative importance values of each risk factor can be obtained via ML algorithms. In this study, the most important risk factor had an importance value of 100, whereas the least important risk factor had an importance value of 0. Values can be repeated, i.e., two or more variables can have similar variable importance. Because different ML algorithms have different calculus architectures and selection features, the five ML algorithms in this study may generate different variable importance values for a single risk factor. Within the same group, a single, robust, and complete variable importance value can be generated for each risk factor to facilitate subsequent comparison of variable rankings and identification of important risk factors. A single pooled value of variable importance was generated based on the average value of variable importance derived from the five ML models.Fifth, the important variables among groups were compared, and their differences were discussed. Sixth, the conclusions of this study were presented based on the abovementioned findings.For constructing each model, nested cross-validation (Nest-CV) was utilized. Nest-CV is a variation of the CV family. Under the structure of Nest-CV, two loops are required (inner and outer loops). The inner loop is used for hyperparameter tuning , whereas the outer loop is used for model evaluation, with the optimal hyperparameter set in the inner loop. Nest-CV is commonly utilized, and several studies have demonstrated that Nest-CV can overcome the problem of overfitting effectively –47.During model construction under Nest-CV structure, the outer loop first randomly splits the dataset into several folds (10 folds in this study). Then, for each iteration, one fold of the data from the outer loop is used for testing, whereas the remaining folds are used for training. Next, the training data from the inner loop are used for hyperparameter tuning with 10-fold CV. In the 10-fold CV approach, the training dataset was further randomly divided into 10 folds, wherein 9 folds were used to construct the model with a different set of hyperparameters, and 1 fold was used for validation. All 10 folds were used for validation at least once, and all possible combinations of the hyperparameters were investigated using a grid search. The hyperparameter set during validation with the lowest root mean square error (RMSE) was regarded as the most optimized set. After determining the set and training the model using the set, the test data from the outer loop were used for evaluation, which involves the completion of one iteration. Entire Nest-CV was completed when each fold of the data from the outer loop was used for testing at least once. After constructing the ML models, the variable importance values can be extracted from these models. As 10-fold Nest-CV is utilized, the extracted variable importance ranking from each ML model will have 10 scores for each variable. Therefore, to obtain the final corresponding variable importance values, the approach of averaging the importance scores for each variable was employed.As the target variable of this study (changes in eGFR) for model construction is a numerical variable, the metrics used for model performance comparison included symmetric mean absolute percentage error (SMAPE), mean absolute percentage error (MAPE), relative absolute error (RAE), root relative squared error (RRSE), and RMSE . In addiThe dataset was divided into five subgroups, i.e., Group 1 (patients with CKD stage 3 and DM), Group 2 (patients with CKD stage 3 without DM), Group 3 (patients with CKD stages 4–5 and DM), Group 4 (patients with CKD stages 4 and 5 without DM), and Group 5 . All groups followed the same modeling process for predicting eGFR in the fourth examination. The performance of the methods used in all five groups is presented in n in the first column indicate the corresponding proportion of the group. In Group 1, ML methods showed better performance than the MLR method. Among these ML methods, SGB showed the best performance with the following values: SMAPE, 0.097; MAPE, 0.098; RAE, 0.672; and RMSE, 4.922. RF had similar RRSE as SGB but lower SD than SGB.As shown in Similarly, in Group 2, ML methods outperformed the MLR method. Furthermore, SGB showed the best performance in this subgroup with the following values: SMAPE, 0.102; MAPE, 0.104; RAE, 0.682; RRSE, 0.713; and RMSE, 5.259. In Group 3, RF showed the best performance with the following values: SMAPE, 0.135; MAPE, 0.147; RAE, 0.383; RRSE, 0.432; and RMSE, 3.009.In Group 4, RF showed the best performance with the following values: SMAPE, 0.159; MAPE, 0.178; RAE, 0.406; RRSE, 0.464; and RMSE, 3.333. Finally, in Group 5, the CKD stage 3–5 dataset was considered the full dataset without subgrouping. ML methods showed better performance than the MLR method. Among them, MARS showed the best performance with the following values: MAPE, 0.147; RAE, 0.350; RRSE, 0.397; and RMSE, 5.281.Overall, the performance of the five ML methods used in each subgroup had low SD, indicating that the ML usage in this study was reasonable and robust. Furthermore, different ML methods have different mechanisms for generating data regarding various risk factors, and each method visualizes data with a distinct perspective. In other words, ML methods can generate valuable information for supporting decision making with various perspectives; thus, the information generated from all ML methods can be considered. To accurately rank the risk factors using ML methods in different subgroups, this study revealed the top 10 risk factors in each subgroup .V17C, rank 2 was V17M, and rank 3 was V17S. Similarly, in Groups 2–5, the top 10 important risk factors were calculated. Further, to easily compare the important risk factors between subgroups, the results from As shown in This study utilized longitudinal electronic health records to identify the risk factors associated with the prediction of eGFR changes in different CKD groups. This analysis considered the current values, mean values, and variation of biochemical data. Our proposed ML&IVS scheme yielded valuable results that can aid clinicians in effectively managing CKD progression and providing preventive measures in the CKD multidisciplinary care program. In addition to identifying important factors in CKD progression, our ML scheme, with some necessary modifications, can be seamlessly integrated into an electronic system, enabling the early identification of CKD progression. To the best of our knowledge, this study represents the first attempt to utilize ML methods to predict short-term eGFR changes in patients with CKD. The innovative application of ML in this context holds great potential for advancing the field and improving patient care.ML has demonstrated promising performance in the nephrological field, including kidney function prediction via ultrasonography , acute kIn this study, we employed the widely used Pearson correlation method to identify the top 10 factors with the highest correlation coefficients within each group . HoweverNumerous studies have attempted to identify the risk factors associated with clinical CKD progression , and mos2). Such kidney damage is associated with the accumulation of uremic toxins, inflammatory factors, and oxidative stress . FGF23 participates in serum phosphate hemostasis by decreasing phosphorus absorption from the alimentary tract . Approximately 29% of phosphorus resides in the bones and <1% circulates in the serum . In CKD,ry tract . Therefory tract , 87, resThis study has some limitations. The dataset used in this study was from a single medical center, which may limit the generalizability of our findings. Therefore, federated learning, which refers to collaborative ML without centralized training data, is necessary to include more data from multiple centers in future studies . In addiWhen longitudinal data are used to predict eGFR changes in patients with CKD with or without DM, the proposed ML&IVS scheme can effectively integrate the most significant risk factors from each model, resulting in more robust and comprehensive identification of important risk factors for predicting eGFR changes. It is crucial to increase awareness regarding eGFR changes, particularly in government health-promotion initiatives within the multidisciplinary CKD care program. This study provides valuable insights for initiating further discussions and follow-up research in this field. These findings contribute to our understanding of the factors influencing eGFR changes and can guide future investigations on the early identification and management of CKD progression.chaomsmyth.tw@gmail.com.The data analyzed in this study is subject to the following licenses/restrictions: data are available on request to the first author due to privacy/ethical restrictions. Requests to access these datasets should be directed to M-HT, M-HT: conceptualization, data curation, formal analysis, writing—review and editing, funding acquisition, and supervision. M-JJ and T-CL: formal analysis, methodology, software, and writing original draft. Y-WF: data curation and writing original draft. C-JL: conceptualization, formal analysis, methodology, writing—review and editing, funding acquisition, and supervision. All authors have contributed to the article and approved the submitted version.