Cardiovascular diseases are the leading cause of mortality in patients. In this context, proprotein convertase subtilisin/kexin type 9 (PCSK9) appears to be the new biomarker identified as interfering in lipid homeostasis. This study aimed to investigate the association between PCSK9, dyslipidemia, and future risk of cardiovascular events in a population of black Africans.A cross-sectional study was conducted between August 2016 and July 2020 in six hemodialysis centers in the city of Kinshasa, Democratic Republic of the Congo. Serum PCSK9 was measured by ELISA; lipid levels of 251 chronic kidney disease grade 5 (CKD G5) hemodialysis patients and the Framingham predictive instrument were used for predicting cardiac events.P<0.001) and highest tertiles  presented a greater risk of cardiac event.Total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), and triglycerides (TG) were significantly increased in the tertile with the highest PCSK9. By contrast, high-density lipoprotein cholesterol (HDL-c) was significantly decreased in the same tertile. A strong positive and significant correlation was found between PCSK9 and TC, TG, and LDL-c. Negative and significant correlation was observed between PCSK9 and HDL-c. The levels of PCSK9, smoking, overweight, and atherogenic dyslipidemia were associated with future risks for cardiovascular events in univariate analysis. After adjustment, all these variables persisted as independent determinants of future risk for cardiovascular events. The probability of having a cardiovascular event in this population was independently associated with PCSK9 levels. Compared to the patients in the lowest PCSK9 tertile, patients with PCSK9 levels in the middle (aOR 5.9, 95% CI 2.06–17.3, Increased PCSK9 serum levels are associated with higher levels of TC, LDL-c, and TG and lower levels of HDL-c in black African hemodialysis patients. Serum PCSK9 levels in these patients predict increased risk of cardiovascular events, independent of traditional potential confounders. In chronic kidney disease (CKD), patients die more likely from cardiovascular complications than from progression to kidney failure with replacement therapy. Indeed, clinical evidence shows that cardiovascular disease begins as soon as kidney function declines, and its severity increases with the progression of CKD.3Among the modifiable cardiovascular risk factors identified, dyslipidemia remains one of the major risk factors in chronic kidney disease grade 5 (CKD G5) hemodialysis patients or CKD without kidney failure with replacement therapy.10Dyslipidemia (particularly atherogenic dyslipidemia) does not respond well to statins, which partly explains the residual cardiovascular risk observed in patients on statins.In a cross-sectional study, consecutive CKD G5 hemodialysis patients aged >16 years were examined between August 2016 and July 2020 in the following six hemodialysis centers in the city of Kinshasa, the Democratic Republic of Congo: University Hospital of Kinshasa; General Provincial Referral Hospital of Kinshasa; General Referral Hospital of the Congolese National Police; Ngaliema Medical Center Clinic; HJ Hospitals; and AFIA Medical Center.Variables of interests included: age, sex, CKD etiology, diabetes mellitus (DM), high blood pressure (HBP), smoking, alcoholism, physical inactivity, duration on hemodialysis, and current pharmacological treatment. The physical examination was performed before the hemodialysis session and focused on the following parameters: weight (kg), height (cm), systolic blood pressure (SBP) (mmHg), diastolic blood pressure (DBP) (mmHg), mean arterial pressure (MAP) (mmHg), waist circumference (cm), and pulse and heart rate (beat/min). Laboratory parameters of interest in this study encompassed: serum hemoglobin, hematocrit, urea, creatinine, glycemia, uric acid, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), triglycerides (TG), non-HDL-c, calcium, phosphorus, parathyroid hormone (PTHi), vitamin D, and PCSK9. The non-biological parameters included: ankle–brachial pressure index (ABI)  and the body composition of the study population .Agence nationale d’accréditation et d’évaluation en santé (ANAES) in 2004, which made it possible to predict the 10-year risk of a major cardiovascular event . This model takes into account the following parameters: sex, age, systolic blood pressure, TC, HDL-c, smoking, antihypertensive treatment, diabetes mellitus, and family history of hypertension. Framingham scores of <20%, 20%–30%, and >30% were considered as low risk, high risk, and very high risk, respectively.The PCSK9 concentration was measured by competitive immunoenzymatic inhibition in accordance with the sandwich enzyme-linked immunosorbent assay (ELISA) human proprotein convertase subtilisin/kexin type 9, MBS920252 Kit . Protein concentrations in the range 0.45 ng/mL to 30 ng/mL were detected. In this study, PCSK9 levels were divided into tertiles: tertile 1: PCSK9 <9.56 ng/L; tertile 2: PCSK9 9.56–23.1 ng/L; and tertile 3: PCSK9 >23.1 ng/L. The lipid fractions were assayed according to the enzymatic colorimetric method on the Cobas C 311, Roche-Paris/France revised version 2010 automated system. Isolated dyslipidemia was defined by a TC ≥200 mg/dL; HDL-c <50 mg/dL in women and <40 mg/dL in men; LDL-c ≥100 mg/dL; or TG ≥150 mg/dL.Written informed consent was obtained from all participants before enrollment. This study protocol was submitted to the ethics committee of the School of Public Health of Kinshasa/DRC for analysis and received approval registered at number: ESP/CE/053/2016.n) proportions for categorical data. Student’s t test was performed to compare two means. The ANOVA test was used for multiple comparisons. ANOVA tests which were significant at the P<0.05 level were supplemented by a post hoc Scheffé test. For the comparison of the medians of two groups, we used the Mann–Whitney U test, and for more than two medians the Kruskal–Wallis H test. The linear regression test was applied to check the correlation between the different lipid fractions and PCSK9. Pearson’s correlation coefficients (r) were calculated to assess this association. The search for the determinants of high future risks of cardiovascular event was carried out using the multivariate binary logistic regression model. The adjusted ORs and their 95% CIs were calculated to determine the degree of association between elevated future cardiovascular risks and the independent variables. The significance level retained was P value <0.05.All data were analyzed using SPSS for Windows version 24 software. The descriptive statistics were: the mean and standard deviation for quantitative variables with Gaussian distribution; the median and interquartile range (IQR) for variables not normally distributed; and the relative (%) and absolute  men and 69 (27.5%) women. Their average age was 55.8±13.6 years . The maiIn a univariate analysis, smoking, overweight, atherogenic dyslipidemia, and PCSK9 levels were associated with future risks of cardiovascular events . FollowiIndeed, the probability of having a cardiovascular event in this population is strongly associated with the PCSK9 level. Hence, compared to patients in tertile 1, patients with PCSK9 levels in tertile 2 and tertile 3 had a 6- and 9-fold higher OR, respectively.This study identified, for the first time, to the best of our knowledge, a positive and significant correlation between PCSK9 and TC, LDL-c, and TG in sub-Saharan African hemodialysis patients. In addition, plasma PCSK9 levels are independently associated with future risks of cardiovascular events. The strong positive and significant correlation found in this study between PCSK9 and TC, TG, and LDL-c is similar to that reported elsewhere.33Several limitations exist in this study, including its cross-sectional design, the relatively small sample size, and the method used to predict risk of future cardiovascular events. Thus, these findings require confirmation in a larger cohort of prospective African samples.This study suggests that a higher plasma level of PCSK9 is associated with a higher Framingham score. Therefore, PCSK9 could be used as a biomarker for the prediction of cardiovascular events in black African hemodialysis patients. This preliminary study suggests the importance of future studies on the effect of PCSK9 in cardiovascular events as well the worse survival encountered in African hemodialysis patients.


P < 0.001). Binary logistic model in modulate of the GLM model revealed that the lower level of blood zinc was associated with piHTN . Multivariate analysis confirmed both above results. Our study indicated that lower blood zinc was independently associated with piHTN in patients undergoing MHD, but prospective studies with larger population are still needed.Intradialytic hypertension (iHTN) has been related with an increased risk of mortality, with imbalances in trace elements being frequent in maintenance hemodialysis (MHD) patients. The aim of this study was to analyze the relationships between the levels of blood trace elements and iHTN in MHD patients. A total of 144 MHD patients were enrolled in September, 2019 , with a mean age of 64.33 ± 13.39 years and median vintage of 33.50 (16.25–57.50) months. Patients exhibited an average peridialytic systolic blood pressure (SBP) change of − 4.18 ± 20.22 mm Hg in the next 3 months. Thirty-four (23.6%) patients had persistent iHTN (piHTN). These patients were characterized by older age, higher rate of hypozincemia, and modified Charlson comorbidity score, whereas lower blood zinc and hemoglobin, at the time of their recruitment. No significant difference in the levels of other blood trace elements was observed between groups. A general linear mixed (GLM) model showed that with every mg/L point lower mean blood zinc at baseline, the peridialytic SBP change was increased by 4.524 mm Hg ( Although hemodialysis (HD) is known to promote a reduction in the levels of blood pressure (BP) in most hypertensive patients, because of the removal of fluids and salt , a minorImbalances in trace elements have been associated with the development of cardiovascular disease (CVD), including hypertension . Both hyPatients undergoing maintenance hemodialysis (MHD) were enrolled in this study in September 2019 at the HD center of the Guangzhou Red Cross Hospital, Jinan University. Inclusion criteria were as follows: (1) HD therapy for more than 3 months, (2) age ≥ 18 years, (3) treated with bicarbonate dialysate and polysulfone membranes, and (4) signed informed consent form. Exclusion criteria were as follows: (1) patients with an expected survival time of less than 3 months or expected to have kidney transplantation within 3 months; (2) patients who had a history of trauma, surgery, or serious infection within the last 3 months; (3) patients who had a confirmed diagnosis of malignancies; (4) patients who refused participating in the study; and (5) patients who were taking trace element supplements or drugs affecting the metabolism of trace elements. Clinical, biochemical, and blood trace elements data were collected following enrollment in the study. Drug usage and dosage were also recorded in the next 3 months. Patients were censored in the event of dialysis modality change, kidney transplantation, transfer to other centers, or recovery of kidney function.2, a blood flow of 180–300 mL/min, a dialysate flow rate of 500 mL/min, and a dialysis time of 4 h, with. Ultra-pure water dialysate was used, and the iron concentrations of dialysate were as follows, respectively: Na+ 137.8 mmol/L, K+ 2.0 mmol/L, Ca2+ 1.5 mmol/L, Mg2+ 0.5 mmol/L, Cl– 108.7 mmol/L, CH3COO– 4.0 mmol/L, and HCO3– 31.1 mmol/L.Patients enrolled in the study were subjected to hemodialysis and hemodiafiltration treatments 3 times a week. The machines used were Braun Dialog +. A REXEED-15L high-flux polysulfone membrane dialyzer  with a membrane area of 1.5 mThe Omron HEM-7133 electronic sphygmomanometer  was used for the measurement of BP in the non-fistula side of the upper arm, and in the right side of the upper arm in patients with catheters. Predialytic BP (preHD BP) was measured after resting for 30 min, whereas postdialytic BP (postHD BP) was measured shortly after the end of dialysis. Accordingly, the peridialytic change in BP was calculated as follows: Peridialytic BP change = postHD BP − preHD BP. All patients were followed for 3 months, and their postHD BPs, postHD BPs, and peridialytic SBP changes were recorded in every HD treatment. Only patients with an average peridialytic SBP increase ≥ 10 mm Hg throughout the entire 3-month observation period were defined as patients with persistent iHTN (piHTN). Sphygmomanometers in our center were regularly calibrated by the manufacturer.Demographic, clinical, and laboratorial variables were collected following the enrollment of patients in the study.Demographic variables were as follows: age; gender; predialytic body weight and height; primary kidney disease; smoking; interdialytic weight gain (IDWG); ultrafiltration volume. Drug usage in the next 3 months was also recorded: dosage of recombinant human erythropoietin (rHuEPO); usage of low calcium concentration dialysate (1.5 mmol/L); usage of angiotensin converting enzyme inhibitor (ACEI), angiotensin II receptor blocker (ARB), calcium channel blocker (CCB), β-receptor blocker, α-receptor blocker, and diuretics.+), serum sodium ion (Na+), serum magnesium ion (Mg2+), serum calcium ion (Ca2+), serum phosphorus (P), parathyroid hormone (PTH), and albumin (ALB). The weekly total Kt/V was measured using the methods described by Gotch et al. [Venous blood samples were collected shortly before the HD session, and then were taken to the clinical laboratory department of our hospital for routine blood and biochemical tests to evaluate the following parameters: red blood cell (RBC), hemoglobin (Hb), hematocrit (Hct),serum creatinine (SCr), serum urea nitrogen (BUN), serum potassium ion  for further use.Venous blood samples before dialysis treatment were collected at the time of the enrollment of patients in the study. After thorough mixing of the blood sample, 100 μL of it was taken to make a 1:19 dilution with diluents containing 0.1 % nitric acid  and 0.1% triton  were measured using an inductively coupled plasma mass spectrometer . Instrument parameters were as follows: forward power 1550 W; carry gas (Argon) 1.0 L/min; aux gas (Argon) 1.0 L/min; plasma gas (Argon) 15.0 L/min; S/C temperature 2 °C; uptake speed 0.2 r/s; sample depth 6–8 mm; uptake time 30 s; acquisition time 0.1 s; repetition 2; cell entrance − 40 V; cell exit − 60 V; deflect 0 V; plate bias − 60 V; octP RF 180 V; octP bias − 18 V; QP bias − 15 V: gas flow (He) 4.0–5.0 mL/min. All selected trace elements were measured under optimum analytical conditions, as shown in Table Modified Charlson comorbidity (CCI), which has been widely used in hemodialysis patients, was employed to assess the comorbidities of patients  at the tt test or Mann–Whitney test or χ2 test, as appropriate. Both general linear mixed (GLM) and binary logistic regression models in the GLM module of SPSS were performed with univariate and multivariate analysis to determine the variables significantly affecting peridialytic SBP change and piHTN respectively. Repeated-measured data of blood pressure–related variables were applied into the GLM model. Confounding factors were selected based on their documented or hypothesized association with exposure and outcome. The SPSS version 24.0 for Windows  was used for statistical analysis. A P value < 0.05 was considered to be statistically significant.Descriptive statistics comprised mean ± standard deviation for continuous variables with normal distribution, median (25–75% interquartile range) for data with a skewed distribution, and percentages for categorical variables, respectively. Patients were stratified based on average peridialytic SBP changes recorded during the following 3-month observation period in the piHTN group  and the non-piHTN group . Differences between the 2 groups were evaluated using the Student’s n = 63, 43.8%), followed by hypertension , and chronic glomerulonephritis . Detailed characteristics of study population are provided in Table A total of 144 MHD patients were included in the study in September, 2019. Patients had a mean age of 64.33 ± 13.39 years, median vintage of 33.50 (16.25–57.50) months, with 66 being females (45.8%). The primary cause of end-stage renal disease was diabetic nephropathy  μg/L, 103.15 (91.71–112.92) μg/L, and 13.55 (9.93–17.48) μg/L respectively; all with abnormal distributions. Following the recently published prospective study with a large population of MHD patients , all cutP < 0.05). There was no significant difference observed in the levels of other blood trace elements , or other clinical or laboratory markers between the 2 groups at the time of enrollment in the study, or throughout the use of antihypertension drugs, or low calcium concentration dialysate, or dosage of rHuEPO, in the next 3 months.Thirty-four 23.6 %) patients were identified with having piHTN. A comparison between the 2 groups at the time of their enrollment in the study is displayed in Tables 3.6 % pathypozincemia (defined by a level of blood zinc < 4.220 mg/L) were independently associated with piHTN, respectively /ET-1 pathway, resulting in increased secretion of ET-1 and migration of endothelial cells . ResearcOur study also reported that the piHTN group was characterized by older age, and higher CCI, whereas lower predialytic Hb, which were also corroborated in other studies with large and diverse populations , 10, 33.Excess of potentially toxic trace elements and deficiency of essential trace elements are known to be common conditions in HD patients, and available data have suggested that levels of copper were higher, whereas levels of selenium, zinc, and manganese were lower in hemodialysis patients compared with controls . ResearcTo a certain extent, the results of our study are strengthened because of the 3-month follow-up in assessing and defining piHTN. But admittedly, there have been a few limitations in our study. First, as this was a cross-sectional and observational study, and although we could note a possible protective effect of sufficient zinc in iHTN, no conclusions towards causation could be drawn. Second, multivariable models were performed after adjusting for many factors, but this study included a relatively small sample size. Therefore, our results should be cautiously interpreted due to a certain degree of unknown bias. Third, we conducted repeated measurements on blood pressure, but we only once tested the levels of blood zinc at the time of the enrollment of patients in the study. Fourth, we did not collect information on the source water used for HD or on the urine content of trace elements, residual kidney function, dietary intake, or extent of albuminuria, all of which could be associated with the level of blood zinc. Lastly, data related to endothelial dysfunction, such as plasma ET-1 and NO, were not recorded, and we acknowledge that these data might have been helpful in analyzing the relationship between the level of blood zinc and endothelial function.Not much attention has been paid on the relationship between trace elements and iHTN, and hence, this is the first study demonstrating an association between lower levels of blood zinc and iHTN, after adjustment for confounding factors. We speculated that the underlying cause might be the negative effects of zinc deficiency on the vascular and endothelial function of MHD patients. Therefore, more attention should be paid to the levels of blood zinc for the management of iHTN in MHD patients, as iHTN has been associated with increased risk for hospitalizations and mortality. Prospective studies with larger sample size and with zinc supplementation are needed in the future in order to clarify the exact role of zinc in iHTN.


Telemedicine visit use vastly expanded during the COVID-19 pandemic, and this has had an uncertain impact on cardiovascular care quality.Controlling High Blood Pressure (BP) quality measure from the Centers for Medicare & Medicaid Services.We sought to examine the association between telemedicine visits and the failure to meet the Controlling High Blood Pressure quality measure, which was defined as having no BP recorded or having a last recorded BP of ≥140/90 mm Hg . Multivariable logistic regression was used to assess the association between telemedicine visit use during the study period  and poor BP control; we adjusted for demographic and clinical characteristics.This was a retrospective cohort study of 32,727 adult patients with hypertension who were seen in primary care and cardiology clinics at an urban, academic medical center from February to December 2020. The primary outcome was a failure to meet the P<.001; ≥2 telemedicine visits: OR 2.49, 95% CI 2.31-2.68; P<.001; reference: in-person visits only). This effect disappeared when the analysis was restricted to patients with at least 1 recorded BP .During the study period, no BP was recorded for 2.3%  of patients with in-person visits only, 27.1% (1863/6878) of patients with 1 telemedicine visit, and 25% (1277/5104) of patients with ≥2 telemedicine visits. After adjustment, telemedicine use was associated with poor BP control (1 telemedicine visit: odds ratio [OR] 2.06, 95% CI 1.94-2.18; Controlling High Blood Pressure quality measure. However, telemedicine visit use may not negatively impact BP control when BP is recorded.Increased telemedicine visit use is associated with poorer performance on the  The COVID-19 pandemic resulted in the rapid expansion of telemedicine as an integral part of outpatient care . A telemControlling High Blood Pressure quality measure from the Centers for Medicare & Medicaid Services (CMS) that defines poor BP control as having no recorded BP measurements or having a last recorded BP of ≥140/90 mm Hg [BP measurement is a fundamental component of hypertension management ,13, and 90 mm Hg ,16, we sThe study was approved by the Columbia University Irving Medical Center Institutional Review Board (AAAT0375), in accordance with the ethical standards of the responsible committee on human experimentation  and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was waived due to the study being of minimal risk.After approval by our institutional review board, we queried our EHR  to identify all completed outpatient visits to primary care and cardiology clinics at Columbia University Irving Medical Center from February 1, 2020, to December 31, 2020. The Medical Center transitioned to Epic EHR on February 1, 2020, that is, 1 month prior to the start of the COVID-19 pandemic in New York City. For each visit, we extracted information, including patients’ date of birth, sex, race, and ethnicity; the primary payer; and the International Classification of Diseases, 10th Revision (ICD-10) codes associated with the visits. BP data associated with the visits were extracted from Epic flow sheets, and BP measurements were recorded in accordance with standard clinical protocols .HTN-2: Controlling High Blood Pressure [Controlling High Blood Pressure quality measure if (1) BP was not recorded during any visit included in the study period or (2) the last BP recorded during the study period was ≥140/90 mm Hg.For our analysis, we defined the study population by using specifications published by the CMS for the 2020 version of the quality measure Pressure . SpecifiFor the primary exposure variable—telemedicine visit use—we defined telemedicine visits based on appointment type  . BecauseWe used patients’ self-reported race and ethnicity to classify patients into the following race and ethnicity categories: non-Hispanic White; non-Hispanic Black; Hispanic; Asian, Hawaiian, and Pacific Islander; and other, declined to answer, or unknown. Patient insurance was categorized as “commercial,” “Medicare,” or “Medicaid” by using the primary payer field associated with the last visit during the study period. Using a similar approach as the one described above for hypertension, we identified patients with a diagnosis of atherosclerotic cardiovascular disease (ASCVD) and diabetes mellitus through visit-associated ICD-10 codes.Descriptive statistics were calculated for the proportion of visits in which BP was recorded . Descriptive statistics were also calculated for demographic and clinical characteristics according to the categories of telemedicine use. A chi-square test, a 1-way ANOVA, and the Kruskal-Wallis test were used for categorical variables, normally distributed continuous variables, and nonnormally distributed continuous variables, respectively. A multivariable logistic regression model was used to determine if telemedicine use was associated with higher odds of poor BP control; we adjusted for age, race and ethnicity, payer, and the presence of comorbidities. Because telemedicine visits frequently do not have recorded BP data, we applied the same model for the subgroup of patients with at least 1 recorded BP. As disparities in telemedicine visit use have been previously described for older patients and by race, ethnicity, and insurance status ,4,5, we For the study population, we identified 32,727 patients aged between 18 and 85 years who had at least 1 completed outpatient visit to primary care or cardiology clinics at Columbia University Irving Medical Center between February 1, 2020, to December 31, 2020, and who had a diagnosis of hypertension . Of these patients, 20,745 (63.3%) had an in-person visit only, 6878 (21%) had 1 telemedicine visit, and 5104 (15.6%) had ≥2 telemedicine visits. Detailed baseline characteristics are described in Of the total 87,309 visits across the study period, 59,409 were conducted in person, 14,982 were video visits, and 12,918 were telephone visits. BP was recorded for 93%  of in-person visits, 20%  of video visits, and 9%  of telephone visits .Controlling High Blood Pressure quality measure . In this model, female sex, Hispanic patients of color, Black patients, Medicaid insurance, and diabetes mellitus were associated with higher odds of not meeting the measure, while ASCVD and 2 or ≥3 total visits during the study period continued to be associated with lower odds of not meeting the measure  with a least 1 recorded BP, telemedicine use was associated with lower odds of not meeting the  measure .Subgroups analyses for patients who were aged ≥65 years, Hispanic patients, non-Hispanic Black patients, and those with Medicaid insurance are shown in Controlling High Blood Pressure quality measure. These findings are largely driven by BP being recorded in less than 20%  of telemedicine visits, as BP was recorded in 93%  of in-person visits. When the analysis was restricted to patients with at least 1 recorded BP, patients with higher telemedicine visit use had a better or similar likelihood of poor performance on the Controlling High Blood Pressure quality measure. These findings were also robust for the subgroups of patients who were previously described to have more difficulty with using telemedicine services, including patients aged ≥65 years, Black or Hispanic patients, and those with Medicaid insurance [In our analysis of patients with hypertension who were seen in primary care and cardiology clinics at an urban, academic medical center during the COVID-19 pandemic in 2020, we found that increased telemedicine visit use was associated with poorer performance on the nsurance ,18.P values when compared to in-person visits is consistent with prior literature. A recent report from a large US database containing 125.8 million primary care visits from 2018 to 2020 demonstrated that BP is recorded in less than 10% of telemedicine visits, whereas BP is recorded in approximately 70% of in-person visits [Controlling High Blood Pressure quality measure. These findings highlight potential unintended consequence of the rapid adoption of telemedicine visits and have direct implications for various quality payment programs, such as those of Medicare accountable care organizations, that use BP control as a key quality benchmark [Our finding that primary care and cardiology telemedicine visits are less likely to have recorded Benchmark . More brenchmark , especiaControlling High Blood Pressure quality measure when the analysis was restricted to patients with at least 1 recorded BP. This suggests that while BP is less likely to be recorded during telemedicine visits, in general the quality of BP management in primary care and cardiology settings may be similar regardless of telemedicine visit use. It is also reassuring that we observed similar results even in populations that are known to have decreased telemedicine use and poorer BP control, such as older patients, Black or Hispanic patients, or patients with Medicaid [Nonetheless, it is reassuring that telemedicine visit use did not negatively impact the Medicaid ,4,5,19. Medicaid ,7,20. FuMedicaid ,22. ExamMedicaid  as well Medicaid ,25.Controlling High Blood Pressure quality measure may also not accurately reflect a patient’s true BP control status at a given point in time. Finally, because there were dramatic care disruptions during the COVID-19 pandemic, our findings may not be generalizable to in-person visits and telemedicine visits when the COVID-19 pandemic ends, and longitudinal research is needed to assess the continued impact of telemedicine visits on cardiovascular care delivery.There are several additional limitations to our study. As a retrospective cohort study that uses EHR data, our study is necessarily hypothesis-generating research, and additional confounding factors, including those outside of EHR data capture, cannot be excluded. Because we did not assess the quality of BP medications and potential clinical inertia, we have limited insight on how telemedicine use can affect clinical management practices for hypertension. Furthermore, the BP recordings used for this analysis reflect actual clinical practice, and we could not assess the quality of BP measurements that were taken at patents’ homes and then recorded during telemedicine visits, although home BP measurements have been shown to be potentially more reliable than BPs measured during office visits ,26. The Controlling High Blood Pressure quality measure, this was mainly driven by BP being much less likely to be recorded during telemedicine visits. When BP was recorded, telemedicine use was found to be associated with similar or slightly improved BP control. These results provide timely insights into the impact of telemedicine on cardiovascular care quality with important implications for research, implementation, and policy making in the telemedicine era.Despite these limitations, our study is among the first to describe the real-world impact of telemedicine visits on BP control for a diverse population of patients who access ambulatory care. We found that while the higher use of telemedicine visits was associated with poorer performance on the


Genetic contributions to blood pressure were modeled via polygenic scores (PGS) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) that were derived from a prior trans-ethnic blood pressure genome-wide association study (GWAS). Results of trans-ethnic meta-analyses revealed significant main effects of the PGS on blood pressure levels . Significant main effects of PTSD symptoms were also detected for SBP and DBP in trans-ethnic meta-analyses, though there was significant heterogeneity in these results. When including data from the largest contributing study – United Kingdom Biobank – PTSD symptoms were negatively associated with SBP levels  and positively associated with DBP levels . However, when excluding the United Kingdom Biobank cohort in trans-ethnic meta-analyses, there was a nominally significant positive association between PTSD symptoms and SBP levels ; no significant association was observed for DBP . Blood pressure PGS did not significantly moderate the associations between PTSD symptoms and blood pressure levels in meta-analyses. Additional research is needed to better understand the extent to which PTSD is associated with high blood pressure and how genetic as well as contextual factors may play a role in influencing cardiovascular risk.Growing research suggests that posttraumatic stress disorder (PTSD) may be a risk factor for poor cardiovascular health, and yet our understanding of who might be at greatest risk of adverse cardiovascular outcomes after trauma is limited. In this study, we conducted the first examination of the individual and synergistic contributions of PTSD symptoms and blood pressure genetics to continuous blood pressure levels. We harnessed the power of the Psychiatric Genomics Consortium-PTSD Physical Health Working Group and investigated these associations across 11 studies of 72,224 trauma-exposed individuals of European ( Cardiovascular disease (CVD) is the leading cause of death and disability worldwide , and lonAlthough growing evidence suggests that PTSD may be linked to elevated blood pressure – a major risk factor for CVD – there is a lack of understanding of who may be at greatest risk. Harnessing information about genetic liability may help to shed light on who is most vulnerable to developing adverse physical health outcomes after trauma. For example, in a predominantly male sample of younger veterans, Recent work has documented the genetic underpinnings of blood pressure in both European ancestry and trans-ethnic samples . These lThis study investigated whether blood pressure PGS moderated the associations of PTSD with SBP and DBP. Through a collaborative effort of the Psychiatric Genomics Consortium-PTSD (PGC-PTSD) Physical Health Working Group, we examined main effects of PTSD and blood pressure PGS on continuous blood pressure levels, as well as their interaction, in 72,224 trauma-exposed individuals of European and African ancestry. To estimate associations across studies and examine the role of ancestry, we conducted trans-ethnic, as well as single ancestry, meta-analyses. We hypothesized that both PTSD and blood pressure PGS would be associated with higher SBP and DBP levels and that the association between PTSD and SBP/DBP would be greatest for those with higher blood pressure PGS.N = 78), D-cycloserine study , Grady Trauma Project , Gallipoli Medical Research Foundation-Queensland University of Technology , Hostility, PTSD, and Physical Health Risk Factors , Marine Resiliency Study , Optimizing Treatment for PTSD , Shared Roots Study , Translational Research Center for TBI and Stress Disorders , United Kingdom Biobank , and Vietnam Era Twin Study of Aging . Inclusion criteria were as follows: (1) study administered a measure of PTSD symptoms; (2) blood pressure was measured directly; and (3) genetic data were available. Blood pressure measurement was conducted at the same time or after PTSD assessment. If a study included more than one blood pressure measurement , investigators selected the earliest blood pressure measure administered to participants in the study that occurred at or after the assessment of PTSD symptoms. In cohorts that received treatment , PTSD and blood pressure measurements used were obtained prior to randomization. Cohort details, including information about measures of PTSD symptoms and blood pressure, are provided in the Eleven studies participating in the PGC-PTSD consortium and PGC-PTSD Physical Health Working Group contributed data to the current investigation. These studies included the CHOICE study  < 1%, SNPs with effects estimated in less than 90% of the total sample size, or strand ambiguous SNPs. Imputed genotypes for PGC-PTSD datasets were converted from probabilities to hard calls, where the genotype called was the one with the highest imputation probability. If the highest imputation probability was < 0.8, the genotype call was instead set to missing. Only markers with < 5% missing rate and MAF > 1%  were retained. For computation of PGS, variants were linkage disequilibrium (LD) clumped  based on a 250 kb window where only variants with r2 < 0.1 were retained. PGS were calculated at multiple p-value thresholds (pT), varying by increments of 0.01 and ranging from 5E-8 to 1.Blood pressure PGS were calculated using PRSice v2.3.3  based onp > 1E-3, or ambiguous strand, or were located in the major histocompatibility complex region  or chromosome 8 inversion .Each study provided information on participant age (in years) and biological sex. In addition, ancestry PCs were calculated. Specifically, within each dataset, related participants were identified using identity by state estimation in PLINK 1.9 . For evepT for the largest sample: UKBB. In this sample, the various PGS were tested for associations with their corresponding blood pressure measure in linear models adjusting for the first five ancestry PCs, age, age-squared, and sex. The best-fitting thresholds in UKBB were then used for all analyses of blood pressure PGS in the remaining datasets. To make effect estimates comparable, PGS were centered to the UKBB cohort sample means and SDs.To enhance comparability of the blood pressure PGS used across cohorts, we identified the best fitting PGS 2.Analyses were performed stratified by cohort. As in prior research in the PGC-PTSD , CHOICE,Q and the I2 statistic were calculated  by conducting sex-stratified analyses and by fitting Sex × PTSD Symptoms and Sex × Blood Pressure PGS interaction terms in models with PTSD symptoms and blood pressure PGS main effects in the full cohort. Again, per z = 4.10, p < 1E-4). For the majority of studies, mean SBP and DBP were in the normotensive range. Average blood pressure levels were similar for participants of European and African ancestry. For those studies reporting antihypertensive medication use, prevalence in cohorts ranged from 0% in MRS to 57% in VETSA.Demographic information, PTSD symptom severity, and blood pressure levels for each study, stratified by ancestry, are presented in pTs were selected based on results from the largest study: UKBB. The optimal pT for predicting SBP in UKBB was p ≤ 0.02, where PGS explained 2.56% of the variation in SBP (p < 1E-100). Every 1 SD increase of PGS relative to the sample mean was associated with a 3.03-point increase in SBP . The optimal pT for predicting DBP in UKBB was p ≤ 0.01; PGS explained 1.66% of the variation in DBP (p < 1E-100). For every 1 SD increase of PGS relative to the sample mean, there was a 1.37-point increase in DBP .Polygenic scores for SBP and DBP were calculated using the Million Veteran Program blood pressure GWAS results  and werep < 1E-20; DBP: β = 1.32, SE = 0.04, p < 1E-20; z = −8.17, p < 3.8E-16; DBP: z = −4.27, p < 2.0E-5). Trans-ethnic meta-analyses of studies excluding UKBB indicated a 1.46-point increase in SBP for every 1 SD increase in PGS  and a 0.83-point increase in DBP for every 1 SD increase in PGS . Further, when excluding UKBB in trans-ethnic meta-analyses, heterogeneity was minimal and not statistically significant. A significant positive main effect of PTSD symptoms on SBP was also detected in the European ancestry meta-analysis without UKBB . No significant main effect of PTSD symptoms was detected for SBP for the African ancestry meta-analysis .Significant main effects of PTSD symptoms on SBP were detected in three individual cohorts, although the effect directions differed . Whereasp = 8.1E-3; p = 0.58; z = 0.37, p = 0.71). A larger positive, albeit non-significant, main effect of PTSD symptoms was observed in the European ancestry meta-analysis without UKBB , whereas a negative, non-significant main effect of PTSD symptoms was observed in the African ancestry meta-analysis .For DBP, there were significant main effects of PTSD symptoms in the UKBB and GTP cohorts, but effects were in the opposite direction. In UKBB, PTSD symptoms were positively associated with DBP levels, but PTSD symptoms were negatively associated with DBP levels in GTP. The trans-ethnic meta-analysis was statistically significant and suggested a small positive association between PTSD symptoms and DBP .Despite nominally significant interaction terms of PTSD symptoms and blood pressure PGS for TRACTS for SBP and for SHRS for DBP, no significant interaction effects emerged in trans-ethnic meta-analyses . Furtherp = 2.0E-3). A similar finding was observed for DBP, although the Sex × PGS interaction was only nominally significant . The negative association between PTSD symptoms and SBP levels was somewhat larger for men than for women, although there was no significant Sex × PTSD Symptoms interaction . Furthermore, even though PTSD symptoms were significantly positively associated with DBP levels in women only, the Sex × PTSD Symptoms interaction was not significant . Similar to the overall trans-ethnic meta-analyses, no significant PTSD Symptom × PGS interactions emerged in sex-stratified analyses in UKBB.In the largest study examined – UKBB – we were able to conduct sex-stratified analyses in order to explore potential sex-specific effects . Women hp = 3.7E-6) and a significant positive effect of PTSD on SBP in the military cohorts . For DBP, the positive main effect of PTSD was nominally significant for community-based cohorts  but not for military cohorts . No significant PTSD Symptoms × PGS interactions emerged in analyses stratified by military or community-based cohort type.The patterns of results from meta-analyses stratified by military or community-based cohort type paralleled those of the trans-ethnic meta-analyses when excluding versus including UKBB, respectively . Both seWhen restricting analyses to studies that assessed for antihypertensive medication use and were therefore able to adjust blood pressure values for medication use, results of trans-ethnic and single ancestry meta-analyses indicated significant positive main effects of PGS on SBP and DBP . AdditioA substantial body of research suggests that PTSD may be a risk factor for poor cardiovascular health , and yetp-value thresholds in UKBB accounted for slightly less variance in SBP and slightly more variance in DBP in this cohort compared to that observed for the sentinel SNPs in the A notable feature of our study is that we conducted trans-ethnic meta-analyses and used the results from a trans-ethnic blood pressure GWAS from the Million Veteran Program  to derivAlthough PTSD symptoms were significantly associated with continuous blood pressure levels across studies in trans-ethnic meta-analyses, the results were heterogeneous across studies and for SBP versus DBP. Indeed, directions of the PTSD main effect varied across cohorts, although significant, yet small, main effects were observed in the overall trans-ethnic meta-analyses and were driven by the largest cohort included: UKBB. Interestingly, greater PTSD symptoms were associated with lower SBP and higher DBP levels in trans-ethnic meta-analyses of all cohorts. In particular, the SBP finding was contrary to our hypotheses given the literature documenting associations between PTSD and elevated blood pressure levels and hypertension . HoweverThe disparate results for associations of PTSD symptoms with blood pressure that were obtained when including versus excluding UKBB may be due, in part, to particular aspects of that cohort’s study design. In UKBB, only six symptoms of PTSD were assessed using self-report, which would be expected to limit the variance in PTSD symptoms in this cohort. In addition, no information on antihypertensive medication was available, which would be expected to result in artificially lowered blood pressure readings for those taking such medications. These study characteristics may explain some differences in findings compared to other studies that comprehensively measured symptoms of PTSD and included information on antihypertensive medication use, allowing for adjustment of estimated blood pressure . NeverthUnlike prior research suggesting that PTSD symptom severity may be most strongly related to cardiometabolic risk among those individuals with greater genetic risk for obesity , we did Our findings need to be considered in light of several limitations. First, although we conducted trans-ethnic meta-analyses across 11 different studies, there was variability in the nature of samples  and in the measures of PTSD  and blood pressure . Including a variety of studies increases the external validity but also contributed to the heterogeneity that we observed. Furthermore, this heterogeneity precluded our ability to engage in deep phenotyping and made it difficult to determine if results were due to differences in sample characteristics or methodological factors. Although we considered secondary stratified analyses in military and community-based cohorts to examine whether this study characteristic might explain some of the heterogeneity we observed in overall analyses, it is worth noting that cohort type overlapped with other study factors . Additionally, it is possible that community-based cohorts included participants who served in the military but did not collect this information and/or that military cohorts included participants who experienced non-military trauma. Second, despite the large sample size, it is possible that we were statistically underpowered to detect PTSD × Blood Pressure PGS interactions. Future research with larger sample sizes is needed. Third, although we focused in particular on individuals of European and African ancestry in the current investigation given the composition of our cohorts, additional work that incorporates individuals from a variety of additional ancestry groups is needed. Fourth, even though we accounted for antihypertensive medication as recommended by Posttraumatic stress disorder has been linked to adverse cardiovascular health, and research suggests that shared genetic factors may explain, in part, this association . In the https://www.med.unc.edu/pgc/shared-methods/data-access-portal/. The UKBB data can be obtained by applying here: https://www.ukbiobank.ac.uk/enable-your-research. Other data that contributed to the findings of this study may be available from study Principal Investigators upon request.Access to individual-level data for available datasets may be requested through the PGC Data Access Portal at The studies involving human participants were reviewed and approved by the Institutional Review Boards of Boston University, Duke University Medical Center, Durham, NC VA, Emory University, Grady Memorial Hospital, Greenslopes Private Hospital, Puget Sound VA Healthcare System, Queensland University of Technology, Stellenbosch University, the Department of Veterans Affairs, University Hospitals, University of California, San Diego, VA Boston Healthcare System, and VA San Diego. The patients/participants provided their written informed consent to participate in this study.JAS, EW, CN, AM, and MWL conceptualized the study and design. LA, OA, AA-K, DB, JB, BB, GB, JC, AD, MD, NF, CF, MG, CG, GG, MH, SH, TJ, NK, WK, BL, AL, MWL, MJL, JM-K, AM, MRM, ReM, DM, RM, VM, WM, MWM, CM, CN, MP, KR, VR, AR, BR, PR-B, SS, AS, JSS, LV, JV, RY, and LZ assisted with obtaining funding for the included studies, and data collection and preparation. AM conducted the analyses, with assistance from MWL and MG. JAS prepared the first draft of the manuscript. AM, VM, AR, and EW provided edits as members of a writing group. All authors reviewed the manuscript, provided feedback, and approved the manuscript for submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


To investigate the relationship of ocular blood flow  and contrast sensitivity (CS) in healthy as well as normal tension glaucoma (NTG) subjects.Mono-center comparative prospective trialTwenty-five NTG patients without medication and 25 healthy test participants were recruited. AVP as a measure of retinal blood flow was recorded via fluorescein angiography after CS measurement using digital image analysis. Association of AVP and CS at 4 spatial frequencies  was explored with correlation analysis.p< 0.03; 6 cpd: r =  − 0.629, p< 0.0005; 12 cpd: r =  − 0.535, p< 0.005; and 18 cpd: r =  − 0.58, p< 0.001), whereas no significant correlations were found in the control group. Visual acuity was significantly correlated to CS at 6, 12, and 18 cpd in NTG patients , however not in healthy control patients. Age, visual field defect MD, and PSD were not significantly correlated to CS in in the NTG group. MD and PSD were significantly correlated to CS at 3 cpd in healthy eyes .Significant differences regarding AVP, visual field defect, intraocular pressure, and CS measurement were recorded in-between the control group and NTG patients. In NTG patients, AVP was significantly correlated to CS at all investigated cpd (3 cpd: r =  − 0.432, Retinal blood flow alterations show a relationship with contrast sensitivity loss in NTG patients. This might reflect a disease-related link between retinal blood flow and visual function. This association was not recorded in healthy volunteers. Glaucoma is one of the leading causes of irreversible blindness in the world .Whereas first described in 1857, glaucoma in absence of elevated intraocular pressure, consequently named normal tension glaucoma, remains not sufficiently understood today –4. WhileThere are two major issues in the discussion about ocular hemodynamics. On one hand, we are still insufficiently able to measure ocular blood flow directly and rely on different surrogates which are related to ocular blood flow depending on the technique used. Furthermore, we don’t know if recorded ocular blood flow alterations in glaucomatous eyes are primary or secondary in nature .Contrast sensitivity (CS) is important in human vision and substantially affects the level of disability experienced by the patient –14.It was previously reported that retinal ganglion cells significantly contribute to contrast sensitivity and contrast adaptation –17. As gFurthermore, impairments in CS can be detected particularly early in glaucomatous eyes, even prior to visible retinal nerve fiber layer damage, manifested visual field defects, or a decrease in visual acuity , 19, 20.Disturbances in ocular blood flow seem to play a critical role in glaucoma, particularly in normal tension glaucoma (NTG). To date, little is known concerning the association between altered blood flow and visual function in glaucoma. The aim of this study was to investigate if alterations in ocular blood flow are correlated to CS test performance in NTG patients. To verify that this potential relationship  only exists in glaucoma patients, a control group of healthy test subjects was recruited.Twenty-five patients suffering from NTG  and twenty-five healthy control subjects  were included in this study.All examinations in this study were performed in accordance with the Declaration of Helsinki for research involving human subjects. Informed consent was acquired from each patient and the study was approved by the local ethics committee (EK 123/03) All participants underwent a detailed ophthalmological examination prior to the inclusion in this study. Patients with best-corrected visual acuity > 0.22 LogMAR  were excluded from the study. Further exclusion criteria were other significant ocular comorbidities that could either influence ocular blood flow or contrast sensitivity testing .p < 0.05 probability of being normal (one of which should have p < 0.01), not contiguous with the blind spot, or (c) corrected pattern standard deviation (CPSD) was abnormal with p < 0.05. All parameters were confirmed on two consecutive visual fields performed with Humphrey Field Analyzer. All patients with glaucomatous visual field loss underwent diurnal curves of IOP measurements (Goldmann applanation tonometry) at 8.00 h, 12.00 h, 16.00 h, 20.00 h, and 24.00 h without any topical or systemic IOP-lowering medication. In patients with NTG, diagnosis was confirmed by readings of IOP never above 21 mmHg. All patients had no other serious eye diseases .Patients with NTG had glaucomatous excavation of the optic disc  and a glaucomatous visual field defect as defined by the European Glaucoma Society. The diagnostic criteria for glaucomatous visual field loss are as follows. Field loss was considered significant when (a) glaucoma hemifield test was abnormal, (b) 3 points are confirmed with Topical antiglaucomatous eye drops were discontinued and washed out in the NTG group for 3 weeks prior to the inclusion into this study. No topical medication was taken by the healthy control patients.The CSV-1000  was used for CS measurement. The device measures contrast sensitivity at 3, 6, 12, and 18 cycles/degree frequency. The device projects 4 double rows  displaying circles of decreasing contrast sensitivity at 3, 6, 12, and 18 cycles/degree, respectively. Each row consists of 17 circles, with the first circle of each row displaying the highest contrast. The remaining 16 circles are presented in 2 rows consisting of 8 pairs of circles. The patient is instructed to choose the one circle out of each pair showing the grid pattern. The last correct response for each level of contrast is defined as the contrast threshold for that spatial frequency [Systemic and diastolic blood pressure and heart rate were recorded after a resting time of 5 min in the supine position before fluorescein angiography.Fluorescein angiography with a scanning laser ophthalmoscope  was performed to evaluate the AVP and for digital image analysis. We previously described the technique in greater detail . A 40-dep values were set at 0.05 to be considered statistically significant. Matlab (Version R2018b for Windows) as well as GraphPad Prism (Version 7.0 for Windows) was used for statistical analysis.Fisher’s transformation was used to find statistically significant correlations between the individual parameters. Unpaired t-test was used for the analysis of the descriptive parameters in both groups. Baseline parameters of the two groups are presented in Table p < 0.03), at 6 cpd , at 12 cpd , and at 18 cpd  using Fisher’s transformation. Please refer to Fig. For the NTG patients, statistically significant correlations were computed between AVP and contrast sensitivity at 3 cpd .No significant correlations were computed between AVP and contrast sensitivity in healthy control subjects .In neither NTG patients nor healthy control subjects was age significantly correlated to CPD   in NTG patients. Whereas in the healthy control group, visual acuity was only correlated to age .Visual acuity was significantly correlated to CS at 6, 12, and 18 cpd .MD and PSD were not significantly correlated to CS at any cpd in NTG patients. However, significant correlations were found in healthy patients between MD and PSD and CS at 3 cpd .Furthermore, AVP was not significantly correlated to MD, PSD, and age in both groups  was significantly correlated to worse performance in CS. No significant correlations were computed for AVP and either MD or PSD in our patients.Our findings highlight a potential direct link between impaired ocular blood flow and visual function in patients with NTG. Reduced ocular blood flow remains an important issue not only in the pathogenesis of NTG, but also with a direct impact on visual disturbances in these patients.The findings, significant correlations between blood flow and CS but not VF-performance in glaucomatous eyes, highlight that CS and VF present different functional aspects of the human visual system that are often correlated , 23 but The potential importance and benefits of CS testing have recently been highlighted in various studies. Fatehi et al.  were ablCS testing provides additional important functional information in glaucomatous eyes that can either be used in the early diagnosis of glaucoma or in advanced stages to monitor further disease progression, whereas the currently available conventional diagnostic tools often fail to provide reliable measurements . In our Investigations into the associations of altered blood flow and visual function such as CS parameters are sparse to date.Harris  reportedSimilar findings regarding the effect of dorzolamide were previously reported by our group for brinzolamide, a different antiglaucomatous drug, as well . Thirty In the study, reduced IOP resulted in improved CS; accordingly, Owidza et al.  reportedThe importance of ocular blood flow in glaucomatous eyes has been shown in other studies as well. In previous studies, ocular blood flow disturbances showed a significant correlation to the extent of visual field defects in glaucomatous eyes , 31. SomHowever, the complexity of the issue is exemplified by the findings of Hosking et al. . The autTo further complicate the issue of blood flow and glaucoma, Harris et al.  reportedThis and other studies highlight how poorly our understanding of glaucoma is to date.We and other authors are strong believers that glaucoma is a systemic disease that primarily manifests with ocular damage. We were able to differentiate NTG patients from healthy test subjects just by continuous heart rate and blood pressure measurement with high specificity and sensitivity . These sTherefore, in the future, it appears necessary that we ophthalmologists start looking in new directions and even beyond the eye in search of a better understanding of glaucoma.Some limitations in our work have to be mentioned. The patients in both groups were not matched for systemic disease as well as systemic medication. The exact influences of systemic medication on ocular blood flow have not been described in greater detail today. However, various studies reported partially contradicting results on the influence of topical medication on ocular blood flow , and thiIn summary, this study was able to verify that blood flow alterations in untreated NTG patients are significantly correlated to CS function in glaucomatous eyes, whereas no association exists in healthy test subjects. Further studies are necessary to verify that including CS testing as well as blood flow measurement is beneficial in the assessment and care of glaucoma patients.


Blood pressure variability (BPV) is significantly associated with cardiovascular diseases (CVD) and mortality in hemodialysis patients. However, the relationship between blood pressure and CVD in hemodialysis patients is complex and affected by many factors. The present study aimed to assess the association of long‐term predialysis BPV with all‐cause mortality and major adverse cardiovascular events (MACE). One thousand seven hundred twenty‐seven patients receiving maintenance hemodialysis were recruited in nine hemodialysis centers. Predialysis BPV was assessed over 1‐year intervals. Outcomes included all‐cause mortality and MACE during follow‐up periods. The mean age of the final cohort was 59 years, of which 57% were males. Greater predialysis systolic BPV was associated with an increased risk of all‐cause mortality  and MACE . Results were similar when systolic BPV was stratified by baseline systolic blood pressure. In conclusion, greater predialysis BPV among hemodialysis patients was associated with all‐cause mortality and MACE. Strategies to reduce blood pressure variability might be beneficial for hemodialysis patients. Those fluctuations entail changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP) that occurs before , during , or after  the treatments.In hemodialysis patients, the relationships between short‐term BPV and prognosis have been extensively studied.22.12.1.1Adult patients (aged ≥18 years), who had received maintenance hemodialysis for more than 3 months prior to August 1, 2018, were recruited from the Fourth Affiliated Hospital, Zhejiang University School of Medicine and eight public hospitals in Jinhua city, Zhejiang Province of China .Patients with any one of the following criteria were excluded: (1) died, or underwent kidney transplantation, or switched to peritoneal dialysis, or transferred to a different renal unit between August 1, 2018 and July 31, 2019; (2) had a history of arrhythmia, including atrial fibrillation, atrial flutter, atrial tachycardia, ventricular tachycardia, ventricular fibrillation, and II‐ or III‐degree atrioventricular block; (3) incomplete dialysis records (no data for > 3 months).2.1.2After the initial screening, we followed patients from August 1, 2019, to July 31, 2020. Patients were censored from the analyses if they underwent kidney transplantation, switched to peritoneal dialysis, transferred to a different renal unit, or were lost to follow‐up.This study was approved by the Research Ethics Committee of the Fourth Affiliated Hospital, Zhejiang University School of Medicine (K20190047) and was recorded in the Chinese Clinical Trial Register (ChiCTR2000028945). All methods were performed in accordance with the approved guidelines and relevant regulations.2.2The hemodynamic data was collected prospectively from all of the hemodialysis sessions of the participants between August 1, 2018, and July 31, 2019. At each session, patients were assessed for pre‐ and post‐ dialysis weight, and predialysis and intradialytic SBP, DBP and heart rate. The BP and heart rate were measured with patient seated in a chair with feet on the floor and back supported. Measurement was made by trained research assistants with a validated automated oscillometric brachial BP monitor . Predialysis BP and heart rate were measured after a 10‐minute rest period in a chair before dialysis. BP was measured three times consecutively before each dialysis, with a 1‐minute interval and the results averaged. Intradialytic BP and heart rate were measured automatically at 30, 60, 120, 180, and 240 minutes by the dialysis apparatus.Patients were dialyzed on either Monday‐Wednesday‐Friday or Tuesday‐Thursday‐Saturday schedules. Prescriptions for patient's dry weight and antihypertensive drug were made by the nephrologist during their weekly visits. Dry weight was assessed by cardiopulmonary radiology and clinical symptoms including peripheral edema, pulmonary congestion, intra‐ and extra‐dialytic BP and muscle spasm. Excess predialysis weight was defined as the difference between predialysis and dry weight.2.2.1SBP and SDDBP) with the coefficient of variation  and the variability independent of the mean . The CV was SD factored by mean BP values (MSBP and MDBP), and the VIM by the SD factored by the mean to the power x, which was obtained by fitting a curve to the plot of SD against the mean BP level.We defined patients’ baseline BP as the mean of all predialysis BPs between August 1, 2018, and July 31, 2019. For each BPV measurements, the SD was calculated , body mass index (BMI), use of antihypertensive medications, and dialysis vintage. Antihypertensive medications were classified as one of five mutually exclusive classes: β‐blocker–containing regimen (without an RAS agent), RAS‐containing regimen without a β‐blocker (RAS), regimen containing both a β‐blocker and an RAS agent (BB + RAS), and any other antihypertensive regimen without β‐blocker or RAS agent (other). The following laboratory parameters were also collected: Kt/V, blood hemoglobin, serum albumin, calcium, phosphate, and parathyroid hormone (PTH). All laboratory values were measured using standardized automated methods. Laboratory values were measured monthly except PTH that was measured quarterly. The averaged or median values during the exposure period served as the baseline data.2.3The primary outcome was all‐cause mortality. The second outcome was MACE, a composite of fatal cardiovascular event, nonfatal myocardial infarction, nonfatal stroke, ventricular arrhythmias and limb amputation because of peripheral vascular disease.2.4p < .05 using two‐tailed tests. Statistical analyses were undertaken by using SPSS Statics, version 22.0 . Kaplan‐Meier curves analysis was performed using R programming language, version 4.1.0.The baseline characteristics of all the patients were compared tertiles of BPV to assess factors that were associated independently with BPV at baseline using linear mixed effects models with a random intercept for the clinic to account for clustering of outcomes by providers. The follow factors were also incorporated as explanatory variables: demographic characteristics , clinical factors , heart rate measured simultaneously with blood pressure, dialysis‐related factors , laboratory measurements , and use of antihypertensive medications. The association of BPV with outcomes was assessed by discrete time proportional hazards models using binary regression. Hazard ratios were calculated for each outcome per 1 SD increase in BPV after adjustment for the same a pre–defined potential confounders. BPV was categorized into tertiles, and the association with all‐cause mortality was measured using Kaplan‐Meier curves. A sensitivity analyses for BPV was undertaken by tertiles to quantify the association of BPV with outcomes after stratification by categories of SBP at baseline (tertiles of SBP). Statistical significance was taken as 33.1SBP that was used for the BPV metric was 15.52±4.19, and mean VIMDBP was 8.61±2.15 .In total, 224 deaths occurred in 1727 patients during the follow‐up periods. The risk of all‐cause mortality was associated with higher VIM3.4SBP in both the unadjusted and fully adjusted models .In total, 299 MACEs occurred in 1727 patients during the follow‐up periods. The risk of MACE was associated with higher VIMls Table . In the 3.5SBP and outcomes remained similar to the primary analysis in each of the categories, suggesting that the association between VIMSBP and outcomes was not dependent on baseline BP  and with 9.1% higher risk of MACE  (Table Higher predialysis VIM4SBP was selected to assess the association between predialysis BPV and prognosis in hemodialysis patients. SD, CV and VIM were recognized as the most common BPV metrics.Predialysis SBP is most commonly selected to diagnose and manage BP in hemodialysis patients.In non‐hemodialysis CKD patients, higher long‐term BPV was found to be associated with cardiovascular events and was considered as a risk factor for all‐cause and cardiovascular mortality.The BPV is one compelling putative risk factor to explain the strikingly high rate of CVD in hemodialysis patients.In the present study, we found that dry weight, or the ratio of excess weight at hemodialysis start to dry weight, was not significantly associated with predialysis BPV. Meanwhile, the adjustment for the dry weight and the ratio of excess weight at hemodialysis start to dry weight in the final outcomes model did not change the association between BPV and outcomes. In a previous retrospective study on the association between predialysis BPV and outcomes, they observed that achievement of prescribed dry weight was associated with lower predialysis BPV, but the adjustment for achievement of prescribed dry weight in the finally outcomes model did not change the association between BPV and outcomes.This study aimed to minimize the confounding effect on the measured variables. It is well known that BP fluctuates with season changes.There are several limitations to our study. First, we only explored the association between predialysis systolic and diastolic BPV, but not other components of BP, such as mean arterial pressure, intradialytic or postdialysis BP. Fluctuation in these BP components may be risk factors for poor outcomes and needs additional research. Second, the final cohort recruited most prevalent hemodialysis patients, not incident hemodialysis patients, whose dialysis history might influence the adverse outcome. However, after adjusted for dialysis vintage, the association still remains. Third, this is a prospective observational study. The results can only explain the association and provide clues for treatment of reducing BPV. Further study will be deserved to explore optimal BP management strategy and relevant mechanisms in hemodialysis patients.In summary, greater predialysis BPV was associated with all‐cause mortality and MACE in hemodialysis patients. Reducing BPV might be beneficial in improving adverse outcomes for hemodialysis patients.The authors report no relationships that could be construed as a conflict of interestJJ Yang and J Huang performed data interpretation, statistical analysis, and manuscript writing. BY Yu, Q Zhang, SS Zhang, LL Wu, L Luo, LZ Li, and L Li performed data collection. F Han and EY Lai involved in manuscript revision, and supervised the study. Y Yang performed study design and manuscript writing. All authors approved the final version of the manuscript.


As the importance of diastolic impairment in the occurrence of TE events is increasingly recognized, it is crucial to evaluate the predictive power of CHA2DS2-VASc scores with C criterion integrating diastolic parameters. We analyzed 4200 Korean nonvalvular AF patients  to compare multiple echocardiographic definitions of CHF. Various guideline-suggested echocardiographic parameters for systolic or diastolic impairment, including left ventricular ejection fraction (LVEF) ≤ 40%, the ratio of early diastolic mitral inflow velocity to early diastolic velocity of the mitral annulus (E/E’) ≥ 11, left atrial volume index > 34 mL/m2, and many others were tested for C criteria. Multivariate-adjusted Cox regression analysis showed that CHA2DS2-VASc score was an independent predictor for composite thromboembolic events only when CHF was defined as E/E’ ≥ 11  but not with other criteria including the original definition . Our findings suggest that C criterion defined as diastolic impairment, such as E/E’ ≥ 11, may improve the predictive value of CHA2DS2-VASc scores.The association between congestive heart failure (CHF) of the CHA The pF) ≤ 40% . However2DS2-VASc scheme. A Meta-analysis demonstrated that out of 12 studies that define CHF as clinical heart failure, only 3 showed an association between CHF and the occurrence of stroke in patients with AF [The clinical diagnostic component of the definition, evidence of HF, may be unreliable due to difficulty differentiating HF from lung or pulmonary vascular diseases. As clinical diagnoses are open to interpretation, some studies define CHF based on International Classification of Diseases (ICD) codes  while ot with AF .2DS2-VASc scores in patients with nonvalvular AF (NVAF) [Whether the echocardiographic component of CHF criteria, LVEF ≤ 40%, reflects the risk of stroke is also of significant importance. LVEF has been criticized for not appropriately reflecting cardiac contractility and being preload- or afterload-dependent . The assF (NVAF) . Accordi2DS2-VASc schemes are evaluated by comparison of the traditional CHF definition (ICD code or LVEF ≤ 40%) with various guideline-suggested echocardiographic parameters of HFpEF or AF.The ambiguity of the original criteria and the emergence of diastolic impairment that is likely to be associated with stroke collectively prompt an investigation of novel echocardiographic criteria into the current C criterion. In this study, the performance of TE risk prediction of CHA2DS2-VASc scores were obtained from the ICD codes of the medical records of each individual at the time of transthoracic echocardiography (TTE) exam, as described previously [This study was approved by the institutional review board (IRB) of Gil Medical Center (GDIRB2018-305) and complied with the Declaration of Helsinki. Written informed consents were waived by the IRB due to the retrospective nature of study. We retrospectively analyzed the medical charts and our echocardiographic database of Korean AF patients at Gachon University Medical Center between 2011 and 2017. Inclusion criteria were: (1) Korean patients with AF during the transthoracic echocardiographic exam, during which AF was confirmed by A wave loss; (2) AF was confirmed by review of electrocardiogram between one-month prior to or after the echocardiography; and (3) age ≥ 18 years. Exclusion criteria were: (1) patients with more than moderate severity of either mitral or aortic valvular disease except for functional mitral regurgitation of any degree; and (2) history of surgery to the mitral or aortic valves. Comorbidities for evaluating CHAeviously .We analyzed the two-dimensional transthoracic echocardiography data at initial presentation of AF. The LVEF, left ventricular end diastolic volume and left ventricular end systolic volume was calculated using the modified Simpson’s method. Left ventricular end-diastolic dimension (LVEDD) and left ventricular end-systolic dimension was measured in the two-dimensional mode of the parasternal long axis view. Maximal left atrial (LA) volume was calculated using the prolate ellipsoid model3. LA volume index (LAVI) was defined as LA volume indexed to the body surface area. In the apical window view, pulsed Doppler sample volume sized 1–2 mm was located at the tip of mitral valve, where mitral inflow velocities were measured. The peak early diastolic filling velocity (E) was divided by the early diastolic mitral annulus velocity (E’) measured by Doppler tissue imaging at the medial mitral annulus for E/E’ calculation. Detailed information regarding echocardiography were described previously .2DS2-VASc score scheme, which was clinical HF or systolic dysfunction [2). There are various guideline-suggested indicators for DD in patients with AF [2, TR max PG ≥ 2.8 m/s, septal E’ velocity < 7 cm/s, and average E/E’ ≥ 15 in subjects with normal sinus rhythm [The main comparator of this study was the original definition of CHF in the CHAfunction . We defifunction . Tested function , mitral function , LVEF ≤ function , or indi with AF . Sohn et with AF ,22. The  with AF ,23. In ts rhythm . We modiConcurrent medications taken during the follow-up period were assessed by chart review. The follow-up duration was cut to two years because there was a concern of data quality after two years since over 70% (2941 out of 4200) of patients were lost after two years. The duration of anticoagulant use was also evaluated. Anticoagulation was defined as the administration of a vitamin K antagonist or a novel oral anticoagulant. The primary endpoint was composite adverse thromboembolic events (CATE), which was defined as a composite of ischemic stroke, transient ischemic attack (TIA), and non-cerebral thromboembolism (NCT). Patients with more than one constituent endpoints were regarded as having one CATE; although, the final follow-up date was assigned to the endpoint that occurred earlier.t-test and Mann–Whitney U-test, respectively. One-way analysis of variance was applied to compare intergroup differences in normally distributed variables. Categorical variables were analyzed by Pearson’s χ2 test. To evaluate the independent effect of CHA2DS2-VASc scores with different definitions for CHF on outcomes, we performed a stepwise multivariate Cox proportional hazards regression model. We included parameters either clinically relevant or statistically significant in the univariate analysis for subsequent multivariate analysis. CHA2DS2-VASc scores using other CHF criteria were divided into three categories based on scores  and were defined as ordinal variables in the Cox model. The adjusted hazards ratio (HR) and 95% confidence interval (CI) of each CHA2DS2-VASc scores category were adjusted for left ventricular hypertrophy, cardioversion, or radiofrequency catheter ablation (RFCA), anticoagulation, anticoagulation duration, and the use of antiplatelet, angiotensin-converting enzyme/angiotensin receptor blocker antagonist (ACEi/ARB), beta-blockers (BB), calcium channel blockers, antiarrhythmics, and diuretics. Longitudinal data for outcomes were plotted using the Kaplan–Meier estimates with the log-rank test. We also performed multivariate linear regression to exclude variables with multicollinearity among adjusting variables for multivariate-Cox regression. C-statistics were also evaluation for each CHA2DS2-VASc score categories using different CHF definitions for predicting CATE.The data analysis was performed using SPSS Statistics for Windows version 23.0 . Continuous normally distributed data are expressed as mean ± standard deviation, whereas continuous non-normally distributed data are given as a median and interquartile range (IQR). The continuous normally and non-normally distributed data between groups were compared by the two-sample 2DS2-VASc score of the total population was 3.2 ± 1.9. Different criteria including the original definition, LVEF ≤ 40%, HFpEF, E/E’ ≥ 11, LAVI > 34 mL/m2, TR max PG ≥ 2.8 m/s, DD, LVEF ≤ 40% and mDT ≤ 160 ms, and ICD codes were used to define CHF ) group were significantly less likely to take anticoagulants, antiplatelets, antiarrhythmics, BB, ACEi/ARB, and diuretics than the CATE(−) group  were men . The meafine CHF . Of the −) group . DemograClinical outcomes of the total population are shown in 2, 13.4, 2.5 m/s, and 119 ms, respectively. The CATE(+) group had significantly higher LV end diastolic diameter/body surface area and TR max PG than the CATE(−) group  and CATE(−) populations are shown in −) group . Echocar2DS2-VASc score categories were assessed using different criteria for CHF  as CHF are shown in finition A,B.2DS2-VASc score categories are shown in 2DS2-VASc scores when CHF was as E/E′ ≥ 11 was the highest among other definitions.The C-statistics of each CHA2DS2-VASc score was an independent predictor for CATE when CHF was E/E’ ≥ 11 but not when defined as originally (ICD code or LVEF ≤ 40%) in the Korean NVAF population. When other guideline-suggested parameters for HFpEF/HFrEF or AF were tested for the C criterion, such as LVEF ≤ 40%, HFpEF, DD, LAVI > 34 mL/m2, TR max PG ≥ 2.8 m/s, LVEF ≤ 40% and mDT ≥ 160 ms, or ICD codes, CHA2DS2-VASc scores were not predictors for CATE.In this study, we found that CHAThe concept of LVEF was originally proposed by a seminal study in the 1960s to reliably measure contractility . LVEF is2DS2-VASc schema, leaves clinical HF (ICD codes) open to being construed arbitrarily. These problems are highlighted by only 29.8% (433 patients) and 36.7% (533 patients) of patients with a clinical diagnosis (ICD code) of CHF (1454 patients) having HFrEF or HFpEF, respectively, in our study. These findings propose the unreliable nature of clinical diagnoses or LVEF to predict TE events in AF patients and question the adequacy of including such criteria in the definition of CHA2DS2-VASc scores.Although risk scoring systems were originally devised to conveniently use clinical information, there is a growing need for clearly defined echocardiography criteria for CHF. The original definition of CHF in the CHA2DS2-VASc scores. Impaired diastolic function is associated with elevated LV filling pressure, stroke, and high CHA2DS2-VASc scores [2DS2-VASc scores of NVAF patients [Diastolic echocardiographic parameters such as E/E’ ≥ 11 may be considered a definition of CHF for the CHAc scores . Among tc scores . E/E’ hac scores ,26. It wpatients . E/E’ ispatients ,27,28. ASeveral aspects may have contributed to the comparable LA dimensions between the CATE(+) and CATE(−) group. First, the presence of AF in all patients may have confounding effects. Four factors that are generally accepted as determinants of LAVI are the presence of AF, mitral regurgitation, DD, and LV remodeling . Since p2DS2-VASc scores among different populations has not been validated, bringing into question the generalizability of our findings to all populations. For example, in a study predominantly enrolled with Caucasians, LVEF or E/E’ was not predictive of TE events; although, E/E’ > 13 was significantly predictive of death [The current study has several limitations. The difference in predictive value of the CHAof death . Since t2DS2-VASc scores had the most promising performance for predicting CATE when E/E’ ≥ 11 was the definition for CHF in Korean NVAF patients. When other definitions, including the original definition, were used for CHF, the CHA2DS2-VASc scores were not predictive of CATE. These results lead to a demand for integrating a diastolic parameter into the current C criterion of the CHA2DS2-VASc scores.In this study: we found that CHA


Background: After mandibular distraction osteogenesis (MDO), most infants with Pierre Robin sequence (PRS) require mechanical ventilation to assist their breathing. However, the optimal duration of intubation during early mandibular distraction osteogenesis activation is poorly understood. This retrospective study was carried out to identify perioperative risk factors of prolonged mechanical ventilation in infants undergoing MDO.Methods: A total of 95 infants with PRS underwent MDO at Guangzhou Women and Children's Medical Center between 2016 and 2018, and the clinical records of 74 infants who met the selection criteria were analyzed. Of the 74 infants, 26 (35.1%) underwent prolonged mechanical ventilation, 48 (64.9%) did not. t-test, Wilcoxon Sum Rank test or chi-squared test were performed to compare variables that might associate with prolonged mechanical ventilation between the two groups, and then, significant variables identified were included in the multivariate logistic regression model to identify independent variables.Results: Univariate logistic regression analysis revealed that age, preoperative gonial angle, and postoperative pulmonary infection were associated with prolonged mechanical ventilation . Multivariate logistic regression analysis confirmed that the preoperative gonial angle and postoperative pulmonary infection were independent risk factors of prolonged mechanical ventilation (both P < 0.05).Conclusions: Infants with PRS and smaller preoperative gonial angle or postoperative pulmonary infection may be more likely to undergo prolonged mechanical ventilation after MDO. For others, extubation may be attempted within 6 days after MDO. Pierre Robin sequence (PRS) is a congenital disease characterized by micrognathia, glossoptosis, and upper airway obstruction. It is often accompanied with cleft palate . The incCurrently, risk factors and complications of prolonged mechanical ventilation are not well-studied and the optimal duration of intubation during early mandibular distraction osteogenesis activation is poorly understood. Therefore, this study was conducted to identify risk factors of PMV in infants undergoing MDO.Patients younger than 1 year with PRS who underwent MDO at Guangzhou Women and Children's Medical Center, Guangzhou, China, between November 2016 and November 2018 were included in this study. Demographic and clinical data, such as microlaryngoscopy and bronchoscopy report, computed tomography (CT) of the maxillofacial skeleton, distraction protocol, timing of extubation trial, and respiratory outcomes data were extracted from the electronic medical records of subjects meeting inclusion criteria. Patients were excluded if he/she was older than 1 year and/or had incomplete medical records. The study protocols were complied with the 1975 Declaration of Helsinki and were approved by the Research Ethics Committee of Guangzhou Women and Children's Medical Center, Guangzhou, China and written consent was obtained from the guardian of every child participant.The trial was registered in China Clinical Trial Registry and the registration number is ChiCTR1800020384.A multidisciplinary team with members from departments of dentistry, neonatology, pulmonology, anesthesiology and nursing participated in patient assessment and surgical decision-making. The treatment of PRS began with non-invasive techniques at our center. All Children were treated conservatively first by closely checking their breath in the prone position. If the child's respiratory status remained compromised after positioning alone, a placement of a nasopharyngeal airway (NPA) was performed. If NPA failed to relieve airway obstruction, continuous positive airway pressure (CPAP) was applied. Surgical options were mainly reserved for infants with severe airway obstruction who did not respond to non-invasive interventions aimed at mitigating the need for tracheostomy. It was considered to be severe airway obstruction if there were at least three clusters of desaturations with at least 3 dips below 80% within 24 h , sex, age, low birth weight , weight, body mass index (BMI) percentile , prematurity (defined as <37 weeks' gestation), preexisting cardiac malformation (defined according to echocardiography), laryngomalacia/tracheomalacia (defined according to results of fiberoptic bronchoscopy), difficult laryngoscopic exposure (defined as glottis exposure of grade III/IV based on laryngoscopy), method of tracheal intubation, preoperative and postoperative pulmonary infection , preoperative arterial partial pressure of oxygen and carbon dioxide, duration of the operation and postoperative outcome . Cone-beam CT scans were performed using standard institutional protocols before operation and at the end of distraction. CT scan was performed when the patient was sleeping. If the patients couldn't fall asleep naturally, oral chloral hydrate (0.5 ml/kg) was administered. All images were acquired in the left-lateral position at slice thickness between 0.625 and 1.25 mm. Axial images were reformatted parallel to the Frankfort horizontal plane and sagittal images were subsequently generated. All CT reconstruction and analyses were carried out using MIMICS 17.0 image processing software . Airway volumes were calculated based on the axial images using region of interest (ROI) analysis set at a threshold for air density using the volume calculator. Volumes occupied by the radio-opaque border of an artificial airway were excluded from the palatine pharyngeal volume and glossopharyngeal volume. Craniocaudal lengths were calculated based on the reconstructed sagittal images. Preoperative and postoperative non-contrast CT of the maxillofacial skeleton was performed to assess mandibular morphology and airway conditions based on the height of the mandible, the length of the mandibular ramus, the gonial angle, the inferior pogonial angle, the airway section area at the tip of epiglottis, and the palatine pharyngeal  and glossopharyngeal  airway volumes. All of these measurements based on CT are shown in 2 <40%, PaO2 > 60 mmHg, PaCO2 <50 mmHg, SpO2 > 95%, positive end-expiratory pressure <5cm H2O.Sedation and mechanical ventilation weaning followed the standardized protocols: while the patients were mechanically ventilated at ICU, primary sedative agents were fentanyl (2 mcg/kg/h) and midazolam (0.1 mg/kg/h) to maintain the Ramsay Sedation Score at 3~4. Midazolam and fentanyl infusions were discontinued at least 3 h prior to planned extubation. Steroids were used before extubation. Criteria to initiate weaning from the ventilator included pharyngeal reflex and spontaneous breath recovery, hemodynamic stability, postoperative distraction of at least 5 mm and 3 days, and respiratory parameters of FiOt-test; and those with abnormal distribution were analyzed using the non-parametric Wilcoxon rank sum test. Categorical variables were expressed as frequencies (percentages) and were analyzed using Pearson's chi-square test. The ordinal variable BMI percentile was analyzed using the Wilcoxon rank-sum test. Significant variables identified through the univariate analysis were included in the multivariate logistic regression model to identify independent variables. P < 0.05 was considered statistically significant.Statistical analysis was performed using SPSS Statistics version 22.0  to identify variables which are associated with prolonged mechanical ventilation. Continuous variables were expressed as the median and range, and were analyzed using the Shapiro-Wilk normality test. Variables with normal distribution were analyzed using the P < 0.05). These variables were then included in a multivariate logistic regression model, and the multivariate analysis revealed that preoperative gonial angle , P = 0.021,) and postoperative pulmonary infection  were independent risk factors of prolonged mechanical ventilation . It seems that the duration of mechanical ventilation after MDO and postoperative pulmonary infection compose a reciprocal causation. Postoperative pulmonary infection, a common cause of prolonged mechanical ventilation after surgery, may delay extubation, thus prolonging hospitalization and increasing medical costs , although age is not an independent risk factor of prolonged mechanical ventilation as demonstrated in the multivariate regression analysis (P = 0.100). In addition, weight and gestational age, which are usually correlated with age, showed no significant difference between patients in the two groups in univariate analysis. Younger patients are more difficult in airway maintenance and clearance with less airway distensibility, fewer collateral airways, higher chest wall compliance, poor airway stability, and lower functional residual capacity (Another interesting finding of the present study is that the patients with prolonged mechanical ventilation are significantly younger (33.0 vs. 56.0 days, capacity . These pThe present study has several limitations. First, the number of patients with delayed extubation was limited. Further studies with larger sample sizes are needed to validate the conclusions. Second, it was a single-center design that would confine the generalization of our findings. For example, the ventilation weaning protocols and extubation readiness tests can vary among intensive care units. Multicenter studies with standardized protocols are needed to verify our conclusions.Infants with PRS who have smaller preoperative gonial angle and postoperative pulmonary infection may be more likely to undergo prolonged mechanical ventilation after MDO. Extubation may be attempted within 3–6 days after MDO to reduce possible complications, such as pulmonary infection.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This study was approved by the Research Ethics Committee of Guangzhou Women and Children's Medical Center. Since the study was retrospective, the Research Ethics Committee of Guangzhou Women and Children's Medical Center agreed to waive patient parental consent to review their medical records. Images relating to participants in the manuscript were obtained with written informed consent from the guardian. The study protocol was complied with the 1975 Declaration of Helsinki. Written informed consentto participate in this study was provided by the participants' legal guardian/next of kin.NZ and YT designed study. ZM and YC assisted data analysis and manuscript drafting. NZ and YX analyzed data and drafted manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.