The association between duration of night shifts and eGFR (continuous) was partially modified by diastolic blood pressure , –0.077, 95% CI –0.134 to −0.030, p < 0.001). No significant associations were observed among the different brightness of bedroom ambient light levels: middle level , lightest level , and decreased eGFR compared with the darkest level. Long-term night-shift work, rather than the brightness of bedroom ambient LAN, is associated with early stage of renal dysfunction in steelworkers, and blood pressure may mediate the relationship between night shift work and decreased eGFR.The misalignment between the circadian clock and behavioral cycles has been implicated in pathogenesis of many diseases. The main purpose of this study is to examine the association between rotating night shift work, exposure to light at night, and glomerular filtration rate among steelworkers in north China. A total of 6869 steelworkers, aged 22 to 60 years, were included in this study. Multivariable logistic regression was used to examine the association between night shift work, the brightness of bedroom ambient light at night (LAN), and estimated glomerular filtration rate (eGFR), with adjustment for potential confounders. Mediation analysis was performed to examine the mediation effect of potential mediators on the association of duration of night shifts and eGFR. Long duration of night shift work (≥29 years) had elevated odds of decreased eGFR (≤89 mL/min/1.73 m To maximize economic and societal benefit, modern society is dependent on a 24 h schedule. In this circumstance, rotating night shift work and exposure to artificial light at night (ALAN) have become commonplace, even though its negative impact on health has been shown in a considerable body of evidence from epidemiological and experimental studies . ApproxiThe overall prevalence of CKD in China was 11.6% . Identifp = 0.032) and were older . This research was approved by the Ethics Committee of North China University of Science and Technology (No.16040). All participants gave informed consent before taking part in this study.This cross-sectional study reported results from the baseline survey conducted among steelworkers who were prospectively recruited at eleven steel production departments in north China . All wor2) = 141 × min  α × max  −1.209 × 0.993 Age ×  × (1.159 if black). Scr indicates serum creatinine (μmol/L), κ = 0.7 for females and 0.9 for males, α = −0.329 for females and −0.411 for males, min and max indicate the minimum of Scr/κ or 1, the maximum of Scr/κ or 1, respectively. According to the Kidney Disease Improving Global Outcomes 2012 recommendations, the range of GFR (mL/min/1.73 m2) was classed into five categories: normal or high , mildly decreased , mildly to moderately decreased , moderately to severely decreased , severely decreased , and kidney failure  [2 (G3a–G5), so we combined these categories into G2 in the subsequent analysis and defined them as “decreased eGFR”.Blood was drawn from the participants’ forearm venous between 08:00 and 09:30 after they have fasted for 12 h. For night shift workers, blood was drawn in the morning after a day off work. The sarcosine oxidase method was used to test serum creatinine . Within-laboratory intra- and inter-assay variable coefficients for serum creatinine were <6% and <8%, respectively. Assessment of eGFR was based on the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation . The CKD 15, G5) . Based oThe main work schedule of the present study population has been introduced in detail in our previous research . In brieExposure to LAN was assessed through participants’ reports about the brightness of the bedroom ambient at night. Participants were asked to class the brightness of their bedroom LAN into the following four categories: “you wear a mask or too dark to see your fingers”, “light enough to see your fingers but not to identify the indoor environment clearly”, “light enough to identify the indoor environment clearly but not enough to read”, and “light enough to read”. The two lightest categories were combined because of small numbers in the lightest category (2.01%). Finally, brightness of the bedroom ambient at night was divided into three categories: “darkest”, “middle”, “lightest”. The participants were also asked to report the usual number of times per night the subject’s sleep was interrupted due to light and living duration of current residence ,22.Covariates mainly included age, sex, body mass index (BMI), ethnicity, smoking status, drinking status, educational level, physical activity, sleep duration, insomnia, diabetes, hyperuricemia, and hypertension see .r) or Spearman’s rank correlation (sr) for continuous variables according to its distribution characteristics. Categorical variables are presented as numbers and percentages, and the chi-square test was used to compare differences among groups.Continuous variables are presented as means and standard deviations, and between-group comparisons were performed using Student’s t-test if the data were normally distributed. Otherwise, the median (upper quartile–lower quartile) and Wilcoxon Scores (Rank Sums) test were used to describe and compare these continuous variables between groups. Initial bivariate associations between eGFR and potential confounders were also assessed with Pearson’s correlation  ,10,19, tRestricted cubic spline models were utilized to visually examine the association between duration of night shifts (continuous), cumulative number of night shifts (continuous), and eGFR , with adjustment for potential confounders.2), bedroom ambient light level (darkest level/middle or lightest level), diabetes (no/yes), hypertension (no/yes), hyperuricemia (no/yes), insomnia (no/yes), and short sleep duration (no/yes) to assess potential effects modification. Log likelihood ratio test was used to compare models with and without cross-product interaction terms. Potential mediators of the association between duration of night shifts  and eGFR (continuous variable), including systolic blood pressure (continuous variable), diastolic blood pressure (continuous variable), fasting blood glucose (continuous variable), serum uric acid (continuous variable), sleep duration (continuous variable), and Athens Insomnia Scale (AIS) score (continuous variable), were introduced to estimate the average causal mediation effects (ACME) using a R package “mediation” (version 4.5.0) [p < 0.05 was regarded as significant for 2-sided tests.Subsequently, in subgroup analysis, we introduced multiplicative interaction terms using the duration of night shifts in quartiles and the stratifying factors including sex, BMI  . p < 0.02, and a mean eGFR of 101.7 mL/min/1.73 m2. Approximately 85% of participants currently or previously engaged in night shift work. 11.8% of participants reported a lightest brightness of bedroom ambient LAN exposure. 25.6% of participants reported hypertension and 10.5% diabetes. The prevalence of decreased eGFR in day workers (0 years), 1–12 years (Q1), 13–20 years (Q2), 21–28 years (Q3), and 29–43 years (Q4) of night shifts in night shift workers were 13.2%, 15.3%, 16.6%, 21.0%, and 34.0%, respectively. Current smoking and current drinking were more likely to be reported among night shift-workers , sleep duration , fasting blood glucose , systolic blood pressure , diastolic blood pressure , and duration of night shift work .The baseline characteristics according to the eGFR status are shown in -workers . Compare-workers . eGFR wap trend < 0.001, Model 1). After adjustment for age and sex (Model 2), this association remained robust . After additionally adjusting for BMI, smoking status, drinking status, education level, short sleep duration, living duration of current residence, number of times light on, insomnia, diabetes, hypertension, and hyperuricemia, the odds of decreased eGFR in the last quartile (Q4) of the duration of night shifts was attenuated but remained significantly elevated with the OR (95% CI) of 1.37 (1.09 to 1.73) (Model 3). In addition, positive associations were observed between duration of night shifts , cumulative number of night shifts , and odds of decreased eGFR , while negative associations were observed between duration of night shifts , cumulative number of night shifts , and eGFR  in the restricted cubic splines (RCS) models (The independent effect of night shift work and bedroom ambient LAN level on odds of decreased eGFR are shown in ) models . However) models . In addi) models .p for interaction > 0.05).We analyzed the relationship between duration of night shifts and decreased eGFR through stratification analysis based on potential effect modifiers . Comparep < 0.001))  on the association of duration of night shifts (ordered variable) and eGFR (continuous variable) was −0.077 ) . The ass 0.001)) .Considering that dust, heat stress, noise, and carbon monoxide are the major occupational hazards to the current steelworkers, we further adjusted these exposures on the basis of Model 3 in Our findings support that night shift work is significantly associated with early stage of renal dysfunction in steelworkers, and provide additional evidence concerning dose-response relationships between duration of night shifts, cumulative number of night shifts, and eGFR among night shift workers, which have never been reported in previous studies. However, no significant association is observed between the brightness of bedroom ambient LAN and decreased eGFR.Our findings are consistent with a small sample cross-sectional study conducted in 354 police officers, which concluded that night shift work was associated with decreased kidney function . They alWhat we already know is that the central oscillator for circadian rhythms in mammals resides in the suprachiasmatic nucleus (SCN) of the hypothalamus, and light serves as the primary “zeitgeber”. Asynchrony between circadian clocks and external world light/dark cycle due to LAN has been associated with increased urine production of the kidney . HoweverInterestingly, a partial mediation effect of diastolic blood pressure on the relationship between duration of night shifts and eGFR was observed in this study. It is well-known that hypertension could be a direct consequence of exposure to rotating shift work . In addiOne key assumption that explains these associations is that night shift work induces misalignment between the external behavioral and the endogenous molecular circadian clocks. Kidneys are organs with peripheral circadian clocks, which enable GFR to show a self-sustained rhythmicity. Studies in animals and humans have shown that feeding time plays a dominant role in resetting peripheral circadian oscillators, even in the absence of the synchronization of the central circadian clock in the suprachiasmatic nucleus (SCN) ,32. SincAnother potential mechanism by which night shift work might cause the decline of eGFR is the presence of psychological and psychosocial stressors . Shift-wThe major strengths of our study include the detailed shift work information, lifestyle information, health status related to CKD, and large sample size. However, our research also has certain limitations. First, we are unable to infer temporality of shift work and GFR in a cross-sectional study. Second, the assessment of LAN is based on the self-reported information rather than the objective measurement of intensity. Third, we did not collect chronotype information, which may have led to a confounding bias. Fourth, those who are competent for long-duration night shift work are more likely to have better physical fitness  or have acclimated to night shift work, which may result in an underestimation of the association between the exposure and outcome. Fifth, our survey population consisted of steelworkers, the vast majority of whom are male workers in north China, which limits our ability to generalize these results to the general population.Long-term night shift work, but not the brightness of bedroom ambient LAN, is associated with early stage of renal dysfunction in steelworkers. Since hypertension is one of the main markers and/or risk factors of CKD progression, and blood pressure may mediate the relationship between night shift work and decreased eGFR, control of blood pressure among shift-workers is particularly important for the prevention of CKD. Meanwhile, well-designed prospective research should be conducted with objective assessment of LAN exposure to explore the effect of LAN on renal function.


We trained ML models  and determined 5-year ASCVD risk prediction, including with and without incorporation of additional EHR variables, and in Asian and Hispanic subgroups. A total of 4309 patients had ASCVD events, with 2077 in PCE-ineligible patients. GBM performance in the full cohort, including PCE-ineligible patients (area under receiver-operating characteristic curve (AUC) 0.835, 95% confidence interval (CI): 0.825–0.846), was significantly better than that of the PCE in the PCE-eligible cohort . Among patients aged 40–79, GBM performed similarly before  and after  incorporating additional EHR data. Overall, ML models achieved comparable or improved performance compared to the PCE while allowing risk discrimination in a larger group of patients including PCE-ineligible patients. EHR-trained ML models may help bridge important gaps in ASCVD risk prediction.The pooled cohort equations (PCE) predict atherosclerotic cardiovascular disease (ASCVD) risk in patients with characteristics within prespecified ranges and has uncertain performance among Asians or Hispanics. It is unknown if machine learning (ML) models can improve ASCVD risk prediction across broader diverse, real-world populations. We developed ML models for ASCVD risk prediction for multi-ethnic patients using an electronic health record (EHR) database from Northern California. Our cohort included patients aged 18 years or older with no prior CVD and not on statins at baseline ( Developed using Cox proportional hazards modeling, the PCE represent a widely used guideline-endorsed calculator to assess 10-year ASCVD event risk for individuals without a prior history of ASCVD, and are a central part of ASCVD risk reduction approaches in clinical settings2. For calculating an individualized 10-year risk of ASCVD, the PCE are applicable to patients with characteristics within prespecified ranges—including age, race, cholesterol levels, and systolic blood pressure. PCE use is consequently limited for patients with values outside the prespecified PCE ranges as well as patients without all variables available, preventing accurate guideline-based risk estimation to guide ASCVD risk reduction strategies. The PCEs were derived primarily from non-Hispanic Whites (NHWs) and African-American (AA) populations, and it is not clear whether they adequately identify risk in diverse populations based on recent analyses demonstrating inconsistent results3. Indeed, the ACC/AHA Work Group that developed the PCE noted that the risk estimator may not accurately predict risk in other racial/ethnic groups4.Risk assessment algorithms have a well-established role in guiding atherosclerotic cardiovascular disease (ASCVD) management. The 2018 update to the 2013 ACC/AHA prevention guidelines highlighted the use of the revised pooled cohort equations (PCE) to determine ASCVD risk, which is used to guide crucial management decisions, particularly the initiation of moderate to high-intensity statin therapy for long-term risk reduction5. Predictive ML algorithms have been applied broadly in various disciplines6, with burgeoning evidence of their potential utility in medicine10.Machine learning (ML) algorithms present an opportunity to develop improved and more generalizable risk prediction models. By leveraging large-scale data—from electronic health records (EHRs), for instance—such algorithms can determine combinations of variables that reliably predict an outcome. ML may incorporate variables that may not be otherwise considered in traditional predictive algorithms and thus demonstrate favorable performance compared to traditional methods2 penalty (LRL2), and with an L1 lasso penalty (LRLasso). We hypothesized that ML methods would allow the development of ASCVD risk prediction algorithms that perform favorably compared to PCE and allow risk estimation for patients to whom the PCE do not apply.The applicability of the PCE to patients with missing or out-of-range PCE variables or in racial/ethnic subgroups other than NHW or AAs is limited. The aim of this study was to develop EHR-trained ML-based ASCVD risk prediction algorithms that demonstrate broad real-world applicability, including random forests (RF), gradient boosted machines (GBM), extreme gradient boosted models (XGBoost), and logistic regression with the standard LOf 797,505 patients, 518,114 patients using statins or with prior CVD at baseline, or with <5 years of ASCVD event-free follow-up after their index visit, were excluded. The final study population (the “full cohort”) included 262,923 patients with 4309 ASCVD-related events during 5-year follow-up. Within the full cohort, 105,692 patients were not aged 40–79 years on their baseline date and 25,510 patients’ cholesterol, blood pressure, or smoking status were unknown or out of range. This left 131,721 PCE-eligible patients, and 2232 with an ASCVD event during follow-up  algorithm may be less applicable in the United States given their derivation cohorts13. This study did not address patients with missing variables or racial/ethnic groups other than NHW and AA patients. A study that recalibrated PCE using modern cohort data with improved risk prediction did not address effects on diverse racial ethnic/racial subgroups2. To our knowledge, our study is the first to explore ML-derived models for ASCVD risk prediction in patients with missing PCE variables and diverse racial/ethnic subgroups.Several groups have reported PCE recalibration to optimize risk prediction. A study from the Women’s Health Initiative demonstrated that a statistical model incorporating events from the Centers for Medicare and Medicaid Services allowed improved risk discrimination14. Our algorithm was more broadly applicable compared to PCE, including for individuals with missing variables or values outside prespecified ranges—which may be important in practice. In our study, 48% of ASCVD events occurred in patients ineligible for PCE application. In a study of Northern California patients, out of 941,546 patients with available lipid levels, ~25%  had missing or out-of-range PCE values and were excluded from traditional PCE application11. ML-based models may help bridge ASCVD risk prediction gaps with such patients to allow guideline-directed management based on risk assessment. In addition, we found that GBM performance in the full cohort had favorable sensitivity compared to that of the PCE in PCE-eligible patients when assuming intermediate prevalence of high-risk patients of 5, 10, or 25%, which further supports the clinical utility of using ML models. For an initial screening test for ASCVD risk, sensitivity  is a crucial performance metric in order to minimize misclassifying high-risk patients as low risk, and maximize opportunities to initiate potentially life-saving management.Our results have implications for ASCVD risk prediction. As a tree-based ML method, GBM is able to incorporate complex variable interactions, which may explain its favorable performance compared to non-tree-based models, such as the PCE, as has been demonstrated in other contemporary ML studies addressing cardiovascular disease15. This analysis did not assess variables beyond lipid levels. Our results raise the hypothesis that efforts at improving ASCVD risk prediction by capturing additional EHR variables may be limited. A previously reported ML-based risk calculator derived from the Multi-Ethnic Study of Atherosclerosis used the same variables as PCE16. These findings suggest that the development of improved risk prediction may require richer data or incorporation of novel variables, such as genetic information across larger patient groups, although incorporation of genetic information may be susceptible to additional bias if not carefully performed18.Consistent with other studies, we found that incorporating structured EHR data beyond traditional PCE variables in ML models did not substantially improve risk prediction. While we did not check inter-correlation of EHR variables, it is likely that we used correlated variables, which we believe may be helpful for ML methods when variables are missing for a patient. The top 20 predictive variables employed by ML models included traditional variables, such as lipids along with socioeconomic factors, including education level. A study from the UK Biobank found that the addition of apolipoproteins, direct, or calculated low-density lipoprotein (LDL) cholesterol did not improve ASCVD risk prediction3. We found that ML-based risk prediction was comparable to PCE in Asians and Hispanics, and that incorporation of additional EHR variables did not substantially improve risk discrimination. Novel ASCVD risk estimation models aimed at improved performance in racial/ethnic subgroups may require consideration of variables that are not adequately captured in current structured EHRs.PCE performance and prevalence of ASCVD risk factors vary across racial/ethnic subgroups11. We report the effect of oversampling on ML model performance , who determined that the research does not involve human subjects and granted a waiver of consent based on the nature of the project, including the use of previously collected, de-identified data. The study sample was selected from EHR data of adults >18 years of age in a community-based outpatient healthcare system in Northern California between January 1, 2009 and December 31, 2018 with at least two outpatient visits that were at least 1 year apart. The index date was defined as the first outpatient visit, which was 1 year after the patient’s first clinic visit. If there were no cholesterol lab results before a patient’s index date, the index date was shifted to the date of the first cholesterol lab result. Patients with pre-existing ASCVD, atrial fibrillation, heart failure, or other cardiovascular disease identified by the International Classification of Diseases, 9th and 10th revision (ICD-9-CM/ICD-10-CM) coding scheme were excluded  cholesterol, systolic blood pressure, blood pressure treatment status, smoking status, and diabetes status; we refer to these as the PCE variables. For each patient, for total cholesterol, HDL cholesterol, systolic blood pressure, and smoking status, the most recent value on or before the index date was used. On the date of the patient’s blood pressure measurement, the use of antihypertensive medications  was assessed. Diabetes status was identified by either a diagnosis of diabetes  or a diabetes medication (GPI2: 27) prescribed on or prior to index date. Patients were included in the PCE-eligible cohort if all PCE variables were present and within specified ranges: age 40–79 years, total cholesterol 130–320 mg/dL, HDL-C 20–100 mg/dL, and systolic blood pressure 90–200 mmHg. Race/ethnicity was self-reported. Some patients’ races were inferred based on the Social Security Record database as previously describedWe assessed the value of including additional EHR variables beyond those from the PCE. These variables were selected a priori based on EHR availability, relevance to ASCVD risk, and predictive potential. Variables were grouped into socioeconomic, clinical, and healthcare utilization categories and extracted 1 year prior to the index date.Socioeconomic variables were based on addresses and included census block group level indicators of educational attainment and median household income.21. Self-reported family (parents or sibling) medical histories were extracted. The existence of each CCS and family history was coded as a binary variable. The most recent height, weight, and diastolic blood pressure measurements before each patient’s index date were included.Patient medical problems were extracted from the EHR problem list, which were coded in ICD-9-CM/ICD-10-CM, and grouped into 283 categories using the Clinical Classification Software (CCS)Medication prescription information was incorporated by considering the first four digits of prescriptions’ GPI codes (GPI4). An indicator was created for each GPI4 denoting whether any medication from that GPI4 was prescribed. The total number of medication prescriptions in the prior year was included as a variable.Two indicator variables were included for each lab test: whether the test was ordered and returned a “normal” result, and whether it was ordered and returned an “abnormal” result. The total number of laboratory tests ordered and the total number which returned “abnormal” results were also included. LDL cholesterol was included if available.Indicators of healthcare utilization included the number of primary care, urgent care, specialty, and other  services care visits in the previous year.4. Acute myocardial infarction was defined by ICD-9-CM codes 410.* and ICD-10-CM codes I21.*, I22.*, I23.3, I24.0, I24.9, I25.9, or I51.313. Stroke events were defined based on ICD-9-CM codes 430.*, 431.*, 432.*, 433.*1, 434.*1, or 436.0 and ICD-10-CM codes G46.*, I63.*, I67.85, I69.30, I77.89, P91.0, or Z86.7314. Fatal coronary artery disease was defined by the presence of an ICD-9-CM code 411.*, 413.*, or 414.* or an ICD-10-CM code I20.*, I23.7, I24.*, I25.*, or T82.85 code followed by death within a year. Death information was retrieved from EHRs and Social Security records.In accordance with ACC/AHA Work Group guidelines, an ASCVD event was defined as the first acute myocardial infarction, stroke, or fatal coronary artery disease22. Parameters developed for NHWs were used to estimate values for Asian, Hispanic, and other non-AA populations.The 5-year ASCVD predicted risk was calculated for the PCE-eligible cohort using published parameter estimates from the PCE23.In order to determine ML risk prediction performance, the PCE-eligible patient cohort was split into an 80% training set and a 20% test set stratified by outcome. Several ML algorithms were trained on the training set, including RF, GBM, XGBoost, and LRL2 and with an LRLasso. These were the only algorithms used. They were chosen for their ability to effectively incorporate many variables into the models returned by the algorithm. The tree-based models  can model complex, high-order interactions between the input variables. Analysis was performed in Python 3.7 using the scikit-learn and xgboost packages, versions 0.21.2 and 0.90, respectivelyC-statistic, across the 5-folds. AUC CIs were calculated24. Once hyperparameters were selected and the best-performing cross-validated model was retrained on the entire training set, the final metrics of the best-performing ML models as well as the metrics of the PCE, including AUC, sensitivity, specificity, precision, and F1-score were reported and evaluated on the 20% held-out test set.First, the ML algorithms were given the PCE variables as inputs and tasked with predicting whether a patient would have an ASCVD event in the next 5 years. For each ML algorithm, 5-fold cross-validation was used on the training set to tune hyperparameters, such as tree depth, learning rate, and number of trees. Hyperparameters used and values for those hyperparameters are shown in Supplementary Table Next, ML algorithms were given access to additional variables extracted from the EHR alongside the PCE variables. As before, hyperparameters were tuned on the training set using 5-fold cross-validation. Since some EHR variables were not expected to have robust predictive power, a composite score incorporating the feature importance metrics returned by the tree-based methods as well as nonzero coefficients of LRLasso was used to prune variables  were compared26. These techniques were chosen to represent the two ends of the spectrum of imputation techniques, with mean-value imputation being the least algorithmically and computationally intensive technique, and iterative imputation being one of the most algorithmically and computationally intensive techniques. Using the full patient cohort, first with PCE variables as inputs and then with PCE+ variables as inputs, imputation and hyperparameter search was carried out using 5-fold cross-validation, and ML model performance was assessed. Supplementary Figure Third, ML algorithm performance for ASCVD risk prediction was assessed in the full patient cohort, which included patients for which the PCE were not designed . First, the hyperparameter grid search was run and ML models were trained on Asian and Hispanic subgroups, and ML performance, using only the PCE variables and using the PCE+ variables, was compared to that of the PCE. Because the number of patients in these subgroups was lower, the LRLasso model was compared to the PCE on the test set, as it is robust to overfitting when working with smaller datasetsFurther information on experimental design is available in the Supplementary InformationReporting Summary Checklist


Asthma is one of the chronic diseases which affects the airway, and inhalers are the preferred medications to treat this problem. Improper inhalational technique leads to decreased efficacy of the medication by reducing its deposition in the lungs. The aim of this study was to assess the barriers to and competency with the use of Metered Dose Inhaler (MDI) and its impact on disease control among adult asthmatic patients.A prospective cross-sectional study was conducted in University of Gondar comprehensive specialized hospital outpatient department (OPD) chronic follow up from 12-March-2018 to 15-May- 2018. Patients were interviewed face to face with questions which determined their competency, asthma control level and barriers for inhaler use.Overall, 307 asthmatic patients were included in the study. More than half of participants were females, 170 (55.4%) and lived in urban area 185 (60.3%). The mean age of the respondents was 51.77 years with a standard deviation of ±15.40. The cost of medication, 282 (91.9%) and the perception that medication should be used in response to symptoms but not on a regular basis 277 (90.2%) were the most identified barriers. Only 56 (18.2%) were competent for Metered Dose Inhaler use (MDIU) and 17 (5.5%) patients had well controlled asthma. Being not competent AOR 0.168[0.41–0.687] was one of the factors decreasing asthma control.Generally from this study, cost of the medication and the perception that medication should be used only for symptoms were the major identified barriers that affect the MDI use among asthmatic patients. Patients show very poor competence to their MDI which in turn led to poor asthma control. So, patients need to be taught the correct inhaler technique in the hospital and pharmacy while they came for follow up every time. Asthma is disease of the airway, which is one of the major chronic disorders affecting more than 300 million people worldwide and nearly 25 million people in the United States , 2. It iDespite the availability of effective therapy, asthma control didn’t meet the specified goal in many countries. A cross sectional study done in 29 countries in North America, Europe, Japan, and the Asia-Pacific region shows asthma control is suboptimal . Asthma A meta-analysis which systematically reviews the errors in inhaler use from 1975 to 2014, concludes incorrect inhaler use in patients with asthma and COPD is unacceptably high . This maInhaler mishandling remains a serious issue and patients need education on the inhaler use by health caregivers . PatientIn Ethiopia, there are different types of inhalational asthmatic medications including, salbutamol, beclomethasone, budesonide, fluticasone, salmeterol and formoterol. MDIs are the most available and used devices for asthma treatment in Ethiopia. Yet, the dry powder is in the drug formulary, but not available in pharmacies . HoweverThis study was conducted in University of Gondar comprehensive specialized hospital outpatient department (OPD) chronic follow up from 12-March-2018 to 15-May- 2018. UoGCSH is found in Gondar town North West Ethiopia, which is 727 km far from the capital Addis Ababa. The hospital gives services for 5 million people and has both inpatient and outpatient departments. The chronic OPD gives service for chronic patients and asthma is one of the services given in the chronic OPD.A cross sectional prospective study was conducted on asthmatic patients.All patients who were diagnosed for asthma and who came for follow up to UoGCSH during the study period were our source population.All adult asthmatic patients who were using at least one metered dose inhaler asthma medication and who came for outpatient visit were our study population.All adult asthmatic patients using inhaler who came for follow up during the study period were included and patient’s age below 18 and who had communication problem were excluded.According to recent data from the record of the OPD of UoGCSH an estimated number of 1525 of asthma patients were supposed to attend the hospital. So far, the proportion of asthma population who had controlled asthma and level of competency was not known in north Ethiopia. Therefore, the final sample size was obtained using single population proportion and reduction formula. According to single population proportion formula the estimated sample size was 384. But the total asthmatic population attending the hospital was 1525 which was below 10,000, hence we applied a reduction formula to obtain a final sample size of 307 patients. We described the steps we followed to calculate the final sample size as follows.Since the total asthma population in the study setting is less than 10,000, a minimum sample size required. Hence, we used the following reduction formula to reach a final sample size.Level of asthma control, competency to MDI and barriers to the use of MDI were the dependent variables of this study.The predictive value of the study were socio demographic characteristics of the patients including age, gender, residence, educational status, comorbidity and number of type of medication, disease length and follow up.Data collectors were having knowledge on contents of questionnaire, data collection methods and ethical concerns before starting the data collection. The questionnaire was pre-tested on (5%) asthmatic patients attending their follow up at UoGCSH that was used prior to the actual data collection to modify the questionnaire. The content of the questionnaire was translated in to Amharic in order to maintain unbiased response. The filled questionnaire was checked daily for completeness by the principal investigators. The internal validity of the questionnaire was examined and demonstrated a Cronbach alpha value of more than 0.78. A specific number was given for each patient once they are done with the interview in order to avoid repetition for the next time.Data was collected by two undergraduate clinical pharmacy students. A structured questionnaire was prepared from previous literatures to assess barriers to MDI use. The questionnaire contains 25 barrier questions in five different domains , 21. SocP value of < 0.05 was considered significant. Binary logistic regression was employed to determine factors associated with asthma control and MDI use.All the statistical analysis was carried out using SPSS, version 20. Descriptive statistics was presented using means with standard deviation (±SDs) and percentages (%). Graphs and tables were utilized to represent the data. A 95% confidence interval with Not well controlled; according to the asthma control test if the overall score of the test is less than or 19 the asthma symptoms are very poorly controlled.Well controlled: if the score is above 20, the asthma symptoms are considered well controlled.Competent - According to the NAEPP evaluation tool, patients who scored 7 or above and demonstrate the essential steps correctly were classified as competent to the MDI.Poor competency - patients who didn’t perform all the essential steps and scored below 7 were considered as having poor competency or incompetent.Overall, 307 asthmatic patients were included in the study. The mean age of the respondents was 51.77 with a standard deviation of ±15.40. More than half of participants were females, 170 (55.4%) and lived in urban area 185 (60.3%). More than one-half of the patients 175 (57.0%) didn’t get formal education and one third of the patients, 103 (33.6%) had no occupation. The detailed socio demographics of the patients are presented in Table The mean duration of the disease in years was 11.22 with a standard deviation of ±9.92. All of the respondents were diagnosed with bronchial asthma. During exacerbation, nearly half of the patients showed symptoms continuously or all over the day, 149 (48.5%). Majority of the patients had regular follow up to the chronic OPD, 293 (95.4%) and more than half of them had comorbid disease, 164 (53.4%). The average period between visits was 1.31 ± 0.63 months. More than half of the patients 191 (62.2%) use beclomethasone with salbutamol for the treatment of Asthma (Table Different barriers were delineated in five major domains in the table below. Among the cognitive barriers (CBs), “the perception that medication should be used in response to symptoms only 277 (90.2%)”, “the belief of decreasing effectiveness of the medication over time 270 (87.9%)”, and “fears of addiction to their medication 266 (86.6%)” were the three most common barriers, respectively. Motivation and preferences related barriers (MPRBs) including “preference for other non-pharmacological approach 212 (69.1%)” and “preference for restriction of daily physical activity instead of taking medication 196 63.8%) were among the major barriers. Whereas, failing to brush teeth 236 (76.9%) and cost of the medications 282 (91.9%) were among the common practical implementation barriers (PIBs). About family and physician related barriers (FPRBs), “centering the asthma management on prescribed medication 274 (89.3%)” was a frequently stated barrier. Nearly ninety percent 274 (89.3%) of patients reported that contradictory messages provided by different health care professionals also affect their inhaler use among the health care related barriers (HCRBs)  and to replace the mouth piece cover, 300 (97.7%) respectively. The most missed or incorrectly performed step was to breath out slowly, 250 (81.4%). Nearly fifty percent of the respondents didn’t hold the inhaler in upright position, 153 (49.8%). The study shows that approximately three-fourth 230(74.9 %) of the patients did not hold their breath for 10-20 seconds after taking the drug, and they did not exhale and wait one minute before the second dose  of patients, Asthma was not well controlled while only 17 (5.5%) patients had well controlled asthma Fig. .Fig. 3Lp value of <0.05. However, other variables did not show any correlation with MDI competency on binary logistic regression  were able to perform more than seven steps out of eleven basic techniques of inhaler use. Among the essential steps according to NAEPP, the three most missed steps in our study were “breathe out slowly”, “hold breath for 10–20sec” and “begin breath in slowly and deeply through the mouth and actuate the canister once” respectively while removing the cap (88.7%) was the most correctly done procedure. This result is consistent with a study done to assess the inhalational technique among chronic respiratory patients which indicates about 60.3% patients failed to exhale before placing inhaler in the mouth, that makes it the most common obscuring error . This is.2% were Furthermore, this study revealed that asthma control was very poor among patients using inhalers. Only 5.5% of patients had well controlled asthma as per the asthma control test results. Using the asthma control test P. Demoly et al., and his colleagues also discovered that uncontrolled asthma was nearly 50 % . The difMoreover, this study indicated the associated factors affecting MDI competency using binomial logistic regression method. Accordingly, the duration of the disease significantly affected the competency of the patients for MDI. As the patients stayed with the disease for a long period of time than those with short duration of disease, their competence slightly increased. This was since, as the patients use the inhaler for longer period, they will have more experience plus in every follow up they have gotten enough instruction about the inhaler technique. Repeating the instruction in each follow up increases the ability to correctly perform the MDI , 45.The current study indicated that asthma control was significantly affected with the patient’s competency to the inhaler. Patients who were not competent to their inhalers had decreased asthma control level by 83% than the competent ones. Poor asthma control correlation with the inhaler use could be explained by inadequate amount of medication reached to the lung. This result has been similar with other studies, in which a cross sectional study in chest clinic also concluded that poor competence to MDI among asthmatic patients would lead to poor asthma control . AnotherIn addition, the present study indicated that patients living in urban area had adequate asthma control. In Ethiopia, most of the population living in the rural area did not get formal education. Due to that, they do have poor ability to read, understand medication instruction and to act on health information which will lead to poor competency to their MDI and asthma control. On the other hand, patients who can read and understand drug labels were found to be more likely to have good competence and asthma control , 48.Further, females show inadequate asthma control as compared to males in our study. This result is also supported by other findings, a study done in Cameroon finds that women were more likely to have inadequate asthma control . It is aOur study has also reported that, patients who were prescribed for both beclomethasone and salbutamol had better asthma control. In contrary, significant number of patients (33.87%) on salbutamol monotherapy failed to achieve good asthma control. Initiation of maintenance therapy with ICS combined with β 2 agonists had greater improvements in pulmonary function and symptom control . ICSs arIn general, this study provided detailed information on factors affecting MDIU, competency to MDI and asthma control. The prospective nature of the study enabled us to gather complete information since data was collected directly from the patients. In addition, there were no adequate literatures done in this research area. Hence, the present study will help to fill the unprecedented evidence gap in our set-up and to come up with solution for the problems in the future perspective. Also, while collecting the data, the patients were taught the correct inhaler technique, about major barriers and the main exacerbating factors of the disease.Despite the strength of our study, it is realized that our study had several limitations. For one, the study is done in a single population which is mono-centered, and it will make the study difficult to generalize the findings for large population. In addition, some factors for instance, the lifestyle of individual patients, that could affect asthma control were not exhaustively explored in the current study. Further, the method we applied to evaluate the MDI use is not standardized.To conclude, this study showed that different barriers affect for MDI use among asthma patients. Of these, cost of the medication and the perception that medication should be used only for symptoms are the major barriers. Our study indicated that patients showed very poor competency to their MDI. It was found that only 18% of patients were competent and almost 95% of the patients had poor asthma control. Many different independent variables have been identified as determinant for the level of asthma control in our study. Among the factors, being male, urban residence, duration of appointment, type of medication and level of competency significantly affected the asthma control. Based on our finding we recommend UoGCSH health care administrates to give different short trainings on MDI appropriate technique for the physicians, pharmacists and all other health care workers so that they can teach the patients to properly administer their medications.Additional file 1. Barrier and competency assessment questionnaire (BCA-Q).


We analyzed the time × group interaction effects of the eGFR and compared mean annual eGFR decline rates between the groups. We prospectively enrolled patients with MGAs, age- and sex-matched patients with IgAN, and MHCs (n = 15 each) and compared their urinary mtDNA copy numbers. Compared to the MHC group, the MGA and IgAN groups displayed differences in the time × group effects of eGFR, higher mean annual rates of eGFR decline, and higher urinary mtDNA copy numbers; however, these groups did not significantly differ from each other. The results indicate that MGAs are associated with deteriorating long-term kidney function, and mitochondrial injury, despite few additional pathological changes. We suggest that clinicians conduct close long-term follow-up of patients with MGAs. Minor glomerular abnormalities (MGAs) are unclassified glomerular lesions indicated by the presence of minor structural abnormalities that are insufficient for a specific pathological diagnosis. The long-term clinical outcomes and pathogenesis have not been examined. We hypothesized that MGAs would be associated with the deterioration of long-term kidney function and increased urinary mitochondrial DNA (mtDNA) copy numbers. We retrospectively enrolled patients with MGAs, age-/sex-/estimated glomerular filtration rate (eGFR)-matched patients with immunoglobulin A nephropathy (IgAN), and similarly matched healthy controls (MHCs;  Minor glomerular abnormalities (MGAs) are unclassified glomerular lesions indicated by the presence of minor structural abnormalities by light microscopy, immunofluorescence, or electron microscopy that are insufficient for specific pathological diagnosis. They are frequently detected in patients with persistent, asymptomatic, and isolated proteinuria or microhematuria. MGAs are common and are found in 5.5%  of adultAlthough many patients are diagnosed with MGAs after kidney biopsy, little is known about their impact on human health, and there are no clear definitions or guidelines regarding their management. To date, there are two case reports ,4 and onThe kidney is an organ with high energy demands and a consequent abundance of mitochondria. Mitochondrial injury plays an important role in the pathogenesis of various kidney diseases, including acute kidney injury , chronicTo investigate this hypothesis, we retrospectively analyzed changes in kidney function and prospectively examined urinary mtDNA copy numbers in biopsy-proven MGA patients compared to matched healthy controls (MHCs) and patients with IgAN, which is the most common cause of primary GN worldwide. Our results indicated that MGAs are associated with deterioration of kidney function and elevated urinary mtDNA copy numbers.This study was conducted according to the principles expressed in the Declaration of Helsinki. Clinical patient data were obtained from electronic medical records with the approval of the Institutional Review Board our hospital’s ethics committee (IRB no. 2016-01-002-007). n = 49 each). MHCs were included if they had no history of diabetes mellitus (DM), hypertension (HTN), congestive heart failure, coronary artery disease, liver cirrhosis, or stroke, and were excluded if they had hematuria or proteinuria as diagnosed by urine dipstick testing and microscopy.To evaluate long-term kidney function, we retrospectively screened patients who had undergone kidney biopsy at Soonchunhyang University Bucheon Hospital between February 2001 and January 2017. Of the 1,097 patients who underwent renal biopsy, 72 (6.6%) were diagnosed with MGAs. An additional pathologist who had not performed the initial diagnoses reviewed kidney tissues from these patients and confirmed the presence of MGAs. We included MGAs patients whose kidney tissue contained more than 10 glomeruli according to light microscopy and at least 1 well-preserved glomerulus according to immunofluorescence and electron microscopy. In these pathological exams, we reviewed the entire kidney structure, including the glomerulus, tubulointerstitium, and microvasculature. When any borderline lesions were discovered that were suspected to be specific pathological diagnoses, the patient was excluded. We specifically excluded patients with > 5% interstitial fibrosis, tubular atrophy, and interstitial inflammation. In terms of vascular damage, we ruled out moderate to severe atherosclerosis and arteriolar hyalinization. We then carefully reviewed disease possibilities with minimal change disease, IgAN, and thin basement membrane disease, which may show minimal pathological changes. After exclusion of 23 patients who were followed for <1 year, 49 patients with MGAs were enrolled . We alson = 15) from 279 biopsy-proven GN patients enrolled in the Cohort for Biomarker Inquiry of Renal Aggravation (COBRA) at Soonchunhyang University Seoul, Bucheon, and Cheonan Hospitals from May 2016 to January 2018. Age- and sex-matched patients with IgAN and MHC were also included (n = 15 each). All prospectively enrolled participants provided written informed consent.To evaluate mitochondrial injury, we prospectively enrolled patients with biopsy-proven MGAs  or hypertension (HTN). We collected body weight, height, body mass index, and systolic, diastolic, and mean arterial blood pressure  data at the time of kidney biopsy. We reviewed any administered antihypertensive drugs, such as calcium channel blockers, beta blockers, angiotensin converting enzyme (ACE) inhibitors, and angiotensin II receptor blockers (ARBs), and obtained information about administered immunosuppressant agents. Patients underwent regular check-ups at intervals of 3 to 6 months, and laboratory data was collected at every visit. We determined the eGFR using the Chronic Kidney Disease Epidemiology Collaboration equation . ProteinIn the retrospective study to evaluate long-term kidney function, we analyzed within-group differences in eGFR over time, and the mean annual rate of eGFR decline between the MHC, MGA, and IgAN groups. The date of kidney biopsy was defined as the start of the follow-up period (baseline). COX3) and mitochondrially encoded NADH dehydrogenase 1 (MT-ND1) in the three groups. In the prospective study to evaluate mitochondrial injury, we measured the urinary copy numbers of the mtDNA genes cytochrome c oxidase subunit III . DNA was isolated from urine samples (1.75 mL) using DNA isolation kits from Norgen Biotek . We analyzed DNA concentrations using a NanoDrop Spectrophotometer . RT-qPCR was performed using 20 ng of template DNA and MT-ND1  or COX3  primers obtained from Thermo Fisher Scientific. The PCR conditions were 95 °C for 10 min, then 40 cycles of 95 °C for 15 s and 60 °C for 60 s. The mtDNA copy numbers were normalized to the TaqMan® Copy Number Reference Assay RNase P , using human genomic DNA for the standard curve. The mtDNA copy numbers were calculated using Copy Caller software  and expressed as mtDNA/nDNA ratios [Urinary copy numbers of the mtDNA genes A ratios .t-test or Mann–Whitney test for continuous variables and either a χ2 test or Fisher’s exact test for categorical variables, as appropriate. All statistical tests were two-sided and the results are presented with 95% confidence intervals. We analyzed the statistical significance of time effects to determine whether changes in eGFR were meaningful, and evaluated within-group differences using a linear mixed model. The following variables were adjusted: age, sex, DM, HTN, eGFR, SBP, and DBP. All p values less than 0.05 were considered statistically significant. Statistical analyses were performed using SPSS version 25 for Windows .Descriptive characteristics of the study population are reported as the mean ± standard deviation for continuous variables and as the frequency count with percentage for categorical and binary variables. Comparisons of differences between groups were performed using either the Student’s SBP and MAP were higher in the MGA group than in the MHC group, while other demographic and clinical variables were not significantly different between the groups . The meaThe mean DBP was lower in the MGA group compared with the IgAN group, although not significantly. More patients in the IgAN group were treated with ACE inhibitors/ARBs than in the MGA group . The mea10MT-ND1/nDNA and log10COX3/nDNA ratios were significantly higher in the MGA group compared with the MHC group . Most of the patients were men (67.2%) and the mean age at diagnosis was 30.7 ± 14.4 years. The mean eGFR was 99.5 ± 17.3 mL/min/1.73 mhe study . To our knowledge, there has been no study evaluating long-term kidney function and the urinary mtDNA levels in MGA. In this study, we retrospectively evaluated long-term kidney function and prospectively analyzed urinary mtDNA copy numbers in patients with MGAs compared with MHCs and patients with IgAN. The prevalence of MGAs among patients undergoing kidney biopsy in our center over the last 17 years was 6.6%, consistent with their prevalence in the COBRA cohort (5.4% (19/356)), which involved three medical centers over 2 years [We analyzed differences in long-term kidney function by measuring the time × group effect of the eGFR and the mean rate of eGFR decline. The time × group effect differed between the MGA and MHC groups, but not between the MGA and IgAN groups. The mean rate of eGFR decline in patients with MGAs was higher compared with MHCs and was not different with patients with IgANs. These results indicate that long-term kidney function in patients with MGAs is worse than in healthy individuals and comparable to that in patients with IgAN. Since IgAN is the most common cause of primary GN worldwide, we used IgAN as a representative GN to assess the long-term kidney function of MGAs. Future studies are needed to compare MGAs with other types of GN, especially non-proliferative GN including hypertensive nephrosclerosis and secondary glomerulosclerosis. Overall, the findings indicate that MGAs, which are believed to be benign, may actually result in the deterioration of kidney function in the future. However, there were some limitations in these analyses. First, because these analyses were performed retrospectively, the follow-up duration differed between groups. In particular, a large number of patients with MGAs were excluded because of short follow-up duration. One-third of these patients entered the army after kidney biopsy, as they were initially referred to our center due to proteinuria and/or hematuria observed during their conscription examinations. These patients were relatively young and did not have underlying disease; therefore, there may be selection bias due to the exclusion of patients expected to maintain relatively good kidney function in the future. Another reason for the follow-up loss in the MGA group could be that many patients in this group maintained good kidney function at early phases of follow-up and did not return for subsequent appointments because they deemed it unnecessary. As a result, it is possible that long-term kidney function was worse in the MGA group as a whole because only patients with poor or deteriorating kidney function were followed-up for long periods. Second, there are limits in the methods used to evaluate long-term kidney function. In clinical trials, differences in long-term kidney function are typically measured by comparing the incidences of death and end-stage kidney disease, with serum creatinine doubling or 40% decline in eGFR used as the primary end point. Because the eGFRs of the MHCs and patients with IgAN were matched to those of patients with MGAs, their kidney functions were well preserved at baseline. This made it difficult to use the aforementioned primary end points, so the eGFR time × group effect and the mean rate of eGFR decline were used instead. As mentioned earlier, the former is limited by differences in follow-up duration and selection biases, and the latter remains a controversial method of assessing long-term kidney function .MT-ND1 and COX3 copy numbers correlated well with each other and were higher in the the MGA group than in MHC group, but did not differ between the MGA and IgAN groups. In the retrospective study, there were no difference in baseline eGFR and proteinuria levels between the MGA and IgAN groups. However, the IgAN group had lower baseline eGFR and higher proteinuria levels than the MGAs group in the prospective study. Previous studies have suggested that the presence of endocapillary proliferation and crescent formation among the MEST-C scores may represent particularly severe pathologic findings which correlate to poor prognosis in patients with IgAN [Our results demonstrated that urinary ith IgAN ,25,26,27ith IgAN . These rith IgAN , ischemiith IgAN , and renith IgAN ,31, can ith IgAN ,33, chroith IgAN ,18, and ith IgAN . Age-/seMGAs were diagnosed in 6.3% of patients undergoing biopsies during the planned study period, which is consistent with previous findings . MGAs weThe most important limitation of both the retrospective and prospective studies is the limited diagnostic accuracy of MGAs. To overcome this, a pathologist other than the one who performed the initial diagnoses reexamined the kidney tissues of enrolled patients with MGAs. Although we analyzed kidney tissue that had more than 12 glomeruli to diagnose MGAs, it is possible that the obtained kidney tissues may have been insufficient for diagnosis, as MGAs are a diagnosis of exclusion, or may have contained lesions too early in development to be specifically diagnosed as GN. For accurate diagnosis of MGAs, a repeat biopsy is needed after a sufficient time period has elapsed. Two patients enrolled in the retrospective study who displayed increasing proteinuria and deterioration of kidney function during the follow-up period had repeat biopsies and were again diagnosed with MGAs. However, most patients did not receive repeat biopsies, especially those with increased proteinuria or decreased renal function.In conclusion, this study demonstrates that MGAs are associated with deteriorating long-term kidney function. In patients with MGAs, mitochondria injury was evident, despite few additional pathological changes. The results suggest that clinicians should conduct close long-term follow-up of patients with MGAs.


The knowledge of new prognostic factors in out-of-hospital cardiac arrest (OHCA) that can be evaluated since the beginning of cardiopulmonary resuscitation (CPR) manoeuvres could be helpful in the decision-making process of prehospital care. We aim to identify metabolic variables at the start of advanced CPR at the scene that may be associated with two main outcomes of CPR (recovery of spontaneous circulation (ROSC) and neurological outcome).2, HCO3−, base excess (BE), Na+, K+, Ca2+ and lactate. ROSC upon arrival at the hospital and neurological status 30 days later  scale) were recorded.Prospective observational study of all non-traumatic OHCA in patients older than 17 years assisted by emergency medical services (EMS), with doctor and nurse on board, between January 2012 and December 2017. Venous blood gases were sampled upon initially obtaining venous access to determine the initial values of pH, pCOp = 0.020), high pCO2 levels  and high potassium levels . Poor neurological outcomes were associated with low pH levels , high pCO2 , low HCO3− , low BE  and high potassium levels .We included 1552 patients with OHCA with blood test data in a 6-year period. ROSC was achieved in 906 cases (58.4%), and good neurological recovery at 30 days (CPC I-II) occurred in 383 cases (24.68%). In multivariate analysis, we found a significant relationship between non-recovery of spontaneous circulation (no-ROSC) and low pH levels (adjusted odds ratio (OR) 0.03 (0.002–0.59), There is a significant relationship between severe alterations of venous blood-gas variables and potassium at the start of CPR of non-traumatic OHCA and low-ROSC rate and neurological prognosis. Medical attention to out-of-hospital cardiac arrest (OHCA) entails a variety of special challenges, besides the inherent ones when coping with this type of pathology, in any context. One of them would be the lack of exactness when estimating the time of the cardiac arrest (CA), which may be of utter relevance. No-flow time is probably one of the key factors in the neurological outcome –3. Some Along with the cardiac arrest onset and first monitored rhythm, it seems that the metabolic status during CPR would be another important factor with a relevant impact on the probability of survival and on the neurological outcome .Multiple responses have been sought in this regard, analysing factors that could be related to the neurological outcome and, therefore, that could lead to determine whether to maintain or to stop all resuscitation efforts. In most cases, such studies analyse the patient’s status after the recovery of spontaneous circulation (ROSC), either on arrival at the emergency department or at the critical-care unit in the hospital. Thus, the interaction between the forementioned neurological outcome and certain aspects of the CA has been evaluated, –9 such a2 or lactate, and the chance of survival with a good neurological outcome are remarkable. Several studies have demonstrated the statistical association between hypocapnia , Na+, K+, Ca2+ and lactate), prior to the administration of any drug, were analysed as independent variables in this study.As stated in the procedures of this EMS,  in everyCases in which CPR was not initiated, the patient was under aged or blood analysis could not be performed were excluded.SAMUR-PC is an EMS whose scope of action is developed in all public settings of the city of Madrid (Spain), with a population of 3.2 million inhabitants and 140,000 dispatches per year. A physician and a nurse are on board all mobile ALS units. In every suspected very severe patient, a mobile ALS unit is dispatched, as well as the chief doctor and the head nurse.Our service is enrolled in an international study on ECPR. The four cases included in that study have not been considered for the present one. When ROSC is not achieved after efforts according to recommendations—and the patient would otherwise be declared dead—he/she could be transferred to the hospital in asystole if meeting the inclusion criteria for uncontrolled non-heart beating donation. In the present study, these patients are included in the no-ROSC group.The dependent variables were ROSC upon arrival at the hospital and intact neurological survival (CPC I-II) at 30 days. CPC scale was performed by in-person interview by the responsible physician of the patient at the hospital.The description of quantitative variables was performed with central tendency and dispersion indices based on rankings (mean ± standard deviation). The description of categorical variables was performed with absolute and relative frequencies in percentages.t test.Proportions were compared with Pearson’s chi-squared tests to analyse the relationships between categorical variables. Quantitative variables were analysed with the Student’s In the first instance, a univariate analysis was carried out using simple binary logistic regression between each independent variable and the dependent variables.2, HCO3−, BE, Na+, K+, Ca2+ and lactate). Each model was evaluated separately for each independent variable of interest and was adjusted with the following covariables, selected based on their relationship with the dependent variables in the scientific literature [p < 0.05 were considered significant. The statistical treatment was performed with the SPSS, version 18  statistical package.To assess the relationship of the independent variables associated with the dependent variables, we used multivariate binary logistic regression models, one for each of the variables  were lost due to not being able to obtain the blood analytical data due to an ambient temperature that made the device unusable. Thus, the study was performed on 1552 records  and lower pH and higher levels of pCOum Table . Likewis2 and potassium levels was found in the multivariate analysis using intervals of increment or decrement. The internal validation of the models was positive for pH and pCO2 and negative for potassium  and low pH and high pCOum Table . In the 3− Table .Table 42, both for ROSC and for good neurological recovery.We continuously assessed the relationship between the values of the different analytes and the outcome variables Fig. , after nThe importance of these analyses lies in the fact that the study was carried out in a setting in which all patients were attended by emergency teams with physician, nurse and several emergency technicians (paramedics), usually helped by an additional chief physician and/or nurse, who performed all the ALS manoeuvres on the scene either until the recovery of the pulse or until certified death; with very few exceptions, patients were only taken to hospital if ROSC was achieved. These characteristics, in addition to others already mentioned, differentiate this study from others published previously , in whicIn our study, the analysis was performed on scene and makes it possible to have blood results even in cases of patients declared dead on scene, which was not possible in other studies analysing blood sample upon arrival at the hospital.Thus, according to these findings, the metabolic data collected at the arrival of the team, at the beginning of ALS on scene through a venous sample —underval+ and the prognosis of the patient [An interesting study with some similarities with ours revealed the association between blood variables such as pH and K patient . However2 (mmHg), 5% and 3%, respectively. In the same way, the risks of no-ROSC and no-neurological recovery decrease, on average, for each tenth of increase in pH, by 9.4% and 9.7%, respectively. Similar values can be deduced from Table The relationship between the analytical values and the clinical outcomes is remarkable, as can be seen from the magnitude of the effect of these variables: the risks of no-ROSC and no-neurological recovery increase, on average, for each unit of increase in pCOThese results are coincident, in terms of the influence on these two clinical outcomes , with those of some of the epidemiological factors assessed in this work, such as the first monitored rhythm, the presence of first responders, the age or sex, although in the last two we only managed to establish an association with neurological recovery Table .Lactate values were analysed in previous studies for its potential prognostic value in critical-care units, with positive results as a prognostic factor to predict the patient’s progress when measured after ROSC . However2 closer to normal. In our study, no survival was obtained with an optimal neurological recovery in patients with a pH lower than 6.60. Of particular interest was the bimodal graph that relates kalemia with CPC I-II survival, where both the levels of hypokalemia and hyperkalemia (mainly the latter) were related to survival with worse neurological outcome, as was stated by Lin et al. [Figure n et al. .Our study has some limitations. First, it was a study carried out in a single geographical area of action with specific assistance. Our good results could be explained by several factors: (1) Our EMS is based on physicians and nurses on board and in all severe cases the chief doctor and the head nurse are commissioned to collaborate with the team. (2) The scope of our service is the public area of a big city; only a scarce number of cases occur in homes, so it may probably influence the profile of patients. (3) Our response times are lower than those in other studies. (4) Training is of great importance in our institution, with frequent mandatory courses and sessions. (5) There is fluid feedback from hospitals to improve our quality standards. (6) SAMUR-PC has, as one of its main objectives, the citizenship education. The first responder programme is aimed mainly at members of security forces and firefighters.Second, 126 cases were lost because a partial or full blood analysis could not be performed due to high or low ambient temperatures that limited the use of the EPOC® device, given that the analyser needs to be in a certain interval to be operative and reliable. The possible relationship of those extreme temperatures with the cause of the CA and the probability of recovery is unknown. The percentage of these cases is under 10% and would probably have a minor effect on statistical analysis. Anyway, it could be speculated that colder ambient conditions could improve the neurological prognosis as well as the opposite. Third, blood samples were obtained when the first venous (or intraosseous) line was achieved, but the time from the start of CPR to that achievement was not recorded. It is known that the local metabolic condition (in the limb of the venous access) may not be exactly the same of that in the rest of the body, but it is the one we can analyse and it is the best available surrogate. Previous studies used the same method. Fourth, the cause of cardiac arrest and the no-flow/low-flow time are unknown. Some aetiologies could be related to a worse initial metabolic state if the patient was already deteriorating before cardiac arrest.Our approach is limited when trying to identify cases where CPR would be futile. This would require a different approach. It is really unlikely that we can find a threshold, except strikingly extreme values, above or below which continued resuscitation is surely futile. However, knowing which biomarkers predict outcome could be helpful when deciding to maintain a prolonged CPR effort. This could be challenging for future directions in investigation.Finally, we have assumed monotonic relationships between continuous variables and outcomes. This is probably true for most of them but potassium levels will probably have a more complex relationship with outcome and this may underestimate the association.Although this study was designed to find variables related with ROSC and CPC I-II survival, we feel that the importance of blood analysis on scene goes further, i.e. identifying the severity of this or other conditions so further research could follow these directions.In the context of the non-traumatic OHCA, our data show the association between gas test abnormalities at the start of CPR and worse clinical outcome in terms of lower ROSC rate and higher CPC scale grade. Given the difficulties obtaining reliable data in this area, these metabolic variables at the beginning of CPR are of great diagnostic and prognostic value. Further studies should address the usefulness of these measurements at the start of resuscitation for decision-making.


Cardiac resynchronization therapy (CRT) is a device‐based method of treatment which decreases morbidity and mortality in heart failure with reduced ejection fraction (HFrEF). This study was aimed to investigate the effects of CRT on hemodynamic and arterial stiffness parameters evaluated by noninvasive method, and determine whether there is a correlation between the changes after CRT in these parameters and the clinical response to CRT or not.The study included 46 patients with HFrEF who were planned to undergo CRT implantation. Before the CRT implantation, clinical and demographic data were recorded from all patients. Hemodynamic and arterial stiffness parameters were measured oscillometrically by an arteriograph before CRT implantation. The patients were re‐evaluated minimum three months after CRT; the above‐mentioned parameters were measured again and compared to the pre‐CRT period.P = .005), central SBP (cSBP) , cardiac output (CO) , stroke volume (65.6 ± 16.3 mL vs 72.0 ± 14.9 mL), and pulse wave velocity (PWV)  increased significantly in post‐CRT period. In addition, the same parameters were significantly increased post‐CRT period in patients with clinical response. However, there was not any similar increase in nonresponder patients.Compared to the period before CRT, mean systolic blood pressure (SBP) (116.8 ± 19.1 mm Hg vs 127.7 ± 20.9 mm Hg, This study demonstrated that SBP, CO, and PWV increased significantly after CRT. The modest increases in these parameters were observed to be associated with positive clinical outcomes. Hemodynamic effects of CRT evaluated by non‐invasive oscillometric method and association between the clinical response.This study demonstrated that SBP, CO and PWV increased significantly after CRT. The modest increases in these parameters were observed to be associated with positive clinical outcomes. Approximately 1%‐2% of the adult population in developed countries have HF, with the prevalence rising to ≥10% among persons 70 years of age or older.Arterial stiffness or reduced aortic distensibility has an important role in patients with HF, and is valuable in prognosis.When contraction synchronization was provided by CRT, improvement in hemodynamic parameters such as cardiac output and a modest increase in systolic blood pressure (SBP) and pulse pressure (PP) is expected.22.1This prospective study included 46 patients , 23.9% females (n = 11) who admitted to Ondokuz Mayis University, Faculty of Medicine, Cardiology Department between November 2015 and September 2017, have indication for CRT implantation according to the 2016 European Society of Cardiology guideline for the diagnosis and treatment of acute and chronic HF. CRT implantation was performed to all participants. The study excluded patients with acute heart failure, life expectancy less than one year due to a systemic disease, valvular heart disease requiring intervention, atrial fibrillation, change in medical therapy of heart failure during follow‐up, severe pulmonary hypertension (>60 mm Hg), acute renal and/or hepatic failure, hypo‐/hyperthyroidism, severe pulmonary diseases, and fistula, aneurysm or stenosis in brachial artery region.Age, sex, body weight, height, body mass index (BMI), cardiovascular risk factors, medications and treatment compliance, and other comorbidities were recorded for all patients. New York Heart Association (NYHA) functional class, 6‐minute walk test (6MWT), electrocardiographic findings, laboratory and echocardiographic data, arterial stiffness measurements and hemodynamic parameters were recorded. Study patients were evaluated again minimum 3 months after the CRT implantation. All included patients gave written informed consents. In addition, the ethics committee approval for the study was granted by Ondokuz Mayis University, Faculty of Medicine and Ethics Committee with the decision numbered OMU KAEK 2016/90.2.2Mobil‐O‐Graph 24 hours ABPM NG® arteriograph was used to measure arterial stiffness and cardiovascular hemodynamic parameters. All measurements were performed by a single experienced operator  who was blinded to other data. Each subject rested in a seated position for 10 minutes in a quiet room at 20°C‐23°C before the baseline hemodynamic measurements were recorded. Brachial blood pressure (BP) and heart rate (HR) were measured in the right arm before using arteriograph. Three sequential measurement sessions, separated by a 5‐min interval were obtained. A total of six measurements, one of which was a control, were taken automatically by the device for a session. The mean values of each session were recorded. If the mean PWV difference between sessions was less than 0.5 m/sec, the mean was used for the analysis. Otherwise, a third measurement session was to be conducted and the median of the three measurements was calculated. Thus, biases caused by single investigator measurements were eliminated. Also the measurements at follow‐up were performed at the same time of the day to minimize the variation as proposed by consensus.The measurement was performed after proper cuff size was selected (two sizes available: 24‐34 and 32‐42 cm). Briefly, underlying working principle of the oscillometric method is; to record oscillometric pressure curves based on plethysmography and register pulsatile pressure changes in an artery on the upper arm. After the conventional oscillometric BP measurement, the cuff instantly re‐inflates and the pulse waves are recorded at diastolic blood pressure (DBP) level for 10 seconds. By this method, the central aortic pressure is calculated from the brachial BP using a transfer function (TF) and the central aortic waveform is decomposed into forward and reflected waves using an uncalibrated triangular aortic flow waveform. The idea behind a TF is the modification of a certain frequency range within the acquired pulse signal to derive the aortic pressure wave . The waves formed by central pressure changes amplified and transferred to device‐specific tonometry and uploaded to HMS Client Server 5.1® software which was developed specifically for the device. Mobil‐O‐Graph 24 hours PWA Monitor uses these mechanisms for obtaining measurements which are validated.2.3Transthoracic echocardiography (TTE) was performed by an experienced echocardiography specialist who was blinded to other data. Vivid E9  TTE device and M5S (1.5‐4.5 MHz) ultrasound probe were used for the echocardiographic measurements. Left ventricle end‐diastolic (LVEDD) and end‐systolic diameters (LVESD), and left atrium (LA) anteroposterior diameter were measured from the long‐axis view of the heart using TTE. Ejection fraction (EF) was calculated by Modified Simpson method using apical 4‐chamber and 2‐chamber images. Valvular heart pathologies were detected and graded. Pulmonary arterial pressure was measured.2.4. After implantation AV delay of the patients was set to be 120 ms, and VV delay was 0 ms for optimal resynchronization.Following left pectoral region incision, subclavian venous puncture was performed, and right ventricle and right atrium leads were placed. After this, coronary sinus was found using a left amplatz catheter, and images were recorded using a contrast‐enhancing agent for the selection of the suitable branch. Left ventricular (LV) lead was placed on the lateral or posterolateral branch of coronary sinus if possible. All electrodes were connected to the generator, and the pouch was closed following stimulus and threshold values were controlled2.5The patients were invited for follow‐up minimum three months after CRT implantation. The mean follow‐up period of the patients was 20 weeks. They were questioned for their compliance to medical therapy and whether they were hospitalized for HF. The information whether they had a dose change in their medications during follow‐up period was noted. Their body weights and heights were measured again, and the BMI was re‐calculated. Their functional capacities were evaluated according to the NYHA classification, 6MWT was performed. Electrocardiography (ECG) was taken. Arterial stiffness and cardiovascular hemodynamic parameters were measured again. Pacemaker was controlled, and the ventricular pace rate being 95% and/or above was recorded.2.6Experts consider aortic pulse wave velocity as the gold standard in the assessment of arterial stiffness.Ischemic cardiomyopathy and nonischemic cardiomyopathy definitions were made based on the presence or absence of myocardial infarction events or 75% or more stenosis in the left coronary artery.Patients with 50‐meter and/or 20% increase in 6MWT after CRT, and who were not hospitalized due to decompensation of heart failure during the follow‐up were considered as “clinical responders.” Those who do not meet these criteria considered as "nonresponders."2.7). For the normally distributed variables Student's T Test was used for the statistical significances between two independent groups, and Paired Sample T Test for the statistical significances between two dependent groups. For not normally distributed data, as statistical methods Mann‐Whitney U Test were used between two independent groups and Wilcoxon signed‐rank test were used between two dependent groups. Statistical significance level was considered as P value < .05.Study data were computerized using “SPSS  for Windows 21.0 (SPSS Inc)” and assessed. Descriptive statistics were expressed as mean ± standard deviation, frequency distribution, and percentage. The distribution normality of the variables was examined using visual (histogram and probability graphs) and analytic methods (Shapiro‐Wilk Test3The mean age of 46 patients investigated in the study was 70.6 ± 7.9 (56‐85 year) years with 76.1% of them being males. While 45.7% of the patients had ischemic HF and 54.3% had nonischemic HF. The mean HF duration of the patients was 8.0 ± 4.00 (3‐20 year) years. As for the comorbidities, 56.5% of 46 patients had hypertension (HT), 26.1% had diabetes mellitus (DM), and 19.6% had hyperlipidaemia. 32.6% of the patients were smokers, and all patients were receiving optimal medical therapy . 54.3% of the patients under assessment were in NYHA class II, 32.6% were in NYHA class III, and 13.0% were in NYHA class III/IV. The mean LVEF of the patients was 28.1%  died during the follow‐up period. One patient died due to septic shock after pneumonia and the other patient died due to retroperitoneal bleeding caused by warfarin overdose.P < .05). When cardiovascular hemodynamic parameters were assessed, post‐CRT SBP, mean arterial pressure (MAP), PP, cSBP, stroke volume, and CO were significantly increased compared to pre‐CRT values (P < .05). Also, PWV was significantly increased compared to pre‐CRT values (P < .05), no statistically significant change was observed in AIx (P > .05) (Table Table 5) Table  and 3.P < .05). No statistically significant difference was detected in the same parameters for nonresponders (P > .05)  had clinical response and 43.2% (n = 19) did not. Table 4This study showed that CRT increased SBP, PP, and CO using a noninvasive oscillometric method. In addition, while we observed a significant increase in these parameters in patients that clinically responded to CRT, we did not observe a comparable increase in nonresponding patients.There is a close association between HF and arterial blood pressure. The lower BP in patients with reduced EF leads to worse outcomes, and higher BP leads to more positive outcomes.Although there is strong evidence that CRT increases EF and CO, the number of studies showing its effect on BP is limited. While a modest increase was detected in SBP after CRT in previous studies,As a result of these data, it is expected that CRT will increase the CO and stroke volume in patients with HFrEF, thereby increasing BP. Concordantly we detected a significant increase in SBP due to increase in CO and stroke volume after CRT in the whole study population. We detected the same increase in patients with positive clinical response to CRT, but not in those without clinical response. And also in post‐CRT period, there was a statistically significant difference in SBP and MAP between two groups. So we considered that a moderate increase in BP might affect the positive response to CRT. Furthermore, this increase in SBP after CRT would provide an opportunity to continue or increase the dosage of the standard, life‐extending HF medications, thereby, to contribute the better outcomes. However, it is obvious that larger studies are needed to prove whether arterial pressure increase improves clinical outcomes after CRT implantation.The prognostic importance of arterial stiffness was investigated in many cardiovascular diseases including HF.P = .009). Even though PWV increased following CRT, it is important to note that it was not above the values that were shown to be associated with poor prognosis in the literature.Arnold et al have found a decrease in arterial compliance in their study with. HFrEF patients regardless of the HF etiology. They thought that decreased arterial compliance would contribute to the pathophysiology of HF by increasing the LV wall stress.Up to 30%‐45% of patients treated with CRT do not clinically respond.There is no study in the literature evaluating the post‐CRT PWV change and its association with clinical response. We detected a statistically significant increase in PWV 3 months after CRT. Also we observed an increase in PWV in patients with clinical response, however, did not observe the same increase in patients without clinical response. Although increase in PWV is known to contribute to adverse clinical outcomes for cardiovascular diseases, it is not likely that CRT which was proved to increase CO, stroke volume, SBP and PP would cause a decrease in PWV. It is hard to say that the improvement of PWV independently predicts favourable CV outcome. This increase in PWV is thought to be a reflection of increased systolic blood pressure rather than an independent outcome. Further studies needed to confirm our findings. According to the data obtained in our study, modest increases in CO, SBP and PWV seen after CRT appear to be associated with positive clinical outcomes.5Several limitations have to be acknowledged. Firstly, short follow‐up duration, lower statistical power and results were major limitations. Also the patients included were not grouped by the etiology of heart failure. Even though patients were receiving optimal medical therapy and did not have dose modification during the follow‐up, not all patients were being treated with the same dose and medications. Lastly, this is a single center study and the measurements were made by a single researcher.6The systolic blood pressure, cardiac output, stroke volume, and PWV were increased after cardiac resynchronization therapy. The modest increases in these parameters appeared to be associated with positive clinical outcomes. The efficacy of CRT can be assessed easily by noninvasive measurement of these parameters.The authors declare no conflict of interest.