Obesity and diabetes are risk factors for atrial fibrillation (AF) incidence and recurrence after catheter ablation. However, their impact on post‐ablation complications in real‐world practice is unknown.We examine annual trends in AF ablations and procedural outcomes in obese and diabetic patients in the US and whether obesity and diabetes are independently associated with adverse outcomes.Using the Nationwide Inpatient Sample (2005–2013), we identified obese and diabetic patients admitted for AF ablation. Common complications were identified using ICD‐9‐CM codes. The primary outcome included the composite of any in‐hospital complication or death. Annual trends of the primary outcome, length‐of‐stay (LOS) and total‐inflation adjusted hospital charges were examined. Multivariate analyses studied the association of obesity and diabetes with outcomes.p < .001).An estimated 106 462 AF ablations were performed in the US from 2005 to 2013. Annual trends revealed a gradual increase in ablations performed in obese and diabetic patients and in complication rates. The overall rate of the primary outcome in obese was 11.7% versus 8.2% in non‐obese and 10.7% in diabetic versus 8.2% in non‐diabetic patients , longer LOS , and higher charges . Diabetes was only associated with longer LOS . Obesity, but not diabetes, in patients undergoing AF ablation is an independent risk factor for immediate post‐ablation complications and higher costs. Future studies should investigate whether weight loss prior to ablation reduces complications and costs. Since the NIS is an administrative and de‐identified database, it does not require institutional review board approval or exempt determination and informed consent is waived. The NIS is a large publicly available all‐payer inpatient healthcare database designed by the Healthcare Cost and Utilization project to produce US regional and national estimates of inpatient utilization, access, charges, quality, and outcomes accounting for 20% of all US community hospitals. Each entry contains information on demographic details, including age, sex, race, insurance status, primary and secondary procedures, hospitalization outcome, total charges, and length of stay. The NIS contains clinical and resource use information, with safeguards to protect the privacy of patients, physicians, and hospitals.2.2We used ICD‐9‐CM  codes to identify admissions of patients from 2005 to 2013 with a primary diagnosis of AF (code 427.31) who underwent catheter ablation (code 37.34). We excluded patients aged <18, those with a secondary diagnosis of paroxysmal supraventricular tachycardia, paroxysmal ventricular tachycardia, atrial flutter, atrial or ventricular premature complexes, Wolff‐Parkinson‐White syndrome, Long‐Ganong‐Levine syndrome, and atrioventricular nodal tachycardia. We also excluded patients with a history of implantation of a pacemaker or implantable cardioverter‐defibrillator to omit cases of atrioventricular junction catheter ablation for permanent AF. Patients who had open surgical ablation during the hospitalization were also excluded. Similar methods have been used in previous studies analyzing AF ablation in the NIS and other databases.Obese and diabetic (combined uncomplicated diabetes and diabetes with chronic complications) patients were identified using the Agency for Healthcare Research and Quality comorbidity measure for ICD‐9 codes. ICD‐9‐CM codes for body mass index (BMI) were not available for the vast majority of admissions and thus were not used to identify or quantitate obesity given concern for sampling error.2.3We used the NIS data elements to identify patient age, sex, race, comorbidities, disposition, hospital volume status, hospital bed‐size, and total admission charges. We defined hospital procedural volume as follows: low volume as <50 AF ablations annually, medium volume as 50–100 AF ablations annually, high volume as >100 AF ablations annually. All hospital charges were inflation adjusted using the price index for the gross domestic product and are reported in 2020 US dollars.2.4Our primary outcome was the composite of any complication or in‐hospital death. We included vascular complications ; cardiac complications , respiratory complications ; neurological complications (stroke and transient ischemic attack [TIA]); postoperative infectious complications; and in‐hospital death. Patient safety indicators were used to identify certain respiratory and infectious complications Table . All of 2.52 test to compare categorical variables for demographics across the four subgroups of non‐obese non‐diabetic, obese non‐diabetic, diabetic non‐obese and obese diabetic, and for comparing the primary outcome between obese versus non‐obese and diabetic versus non‐diabetic patients. We used one‐way ANOVA for age. Generalized linear models were used to analyze annual trends. We also generated nested multivariable models to analyze independent predictors for our outcomes adjusting for different combinations of age, sex, race, hypertension, renal failure, chronic pulmonary disease, peripheral vascular disease, obesity, diabetes, hospital procedure volume, and bed‐size. We used logistic regression used for the primary outcome of any complication including death and secondary outcomes of in‐hospital mortality alone and LOS (0–1 vs. ≥2 days). Linear regression was used for inflation‐adjusted charges, which were initially log transformed. Significance level was set at 5%. All analyses were done using SPSS 26. Cases missing data elements were excluded from analyses.We used the NIS weights to generate national estimates of the number of admissions each year. We used the χ3After NIS weighing, we identified 106 462 AF ablations performed from 2005 to 2013 who met the inclusion criteria. Table N = 546) of all AF ablations in 2005 to 17.5% (N = 2155) in 2013 (p < .001). Similarly, the rates for diabetic patients increased from 10.7% (N = 960) of all AF ablations in 2005 to 18.8% (N = 2315) in 2013 (p < .001). There was a dip in the total number of captured ablations after 2011, likely due to the increased labeling of some of these procedures as outpatient . Meanwhile, Figure p < .001). Tables Figure p < .001). For diabetic patients, the median LOS also increased from 1 to 2 days (p < .05). Non‐obese and non‐diabetic patients displayed relatively constant median LOS at 1 day. The total inflation adjusted median hospital charges increased across all groups (p < .001). By 2013, obese patients had $9410 higher charges than non‐obese patients. Meanwhile, diabetics showed slightly lower charges than non‐diabetics across all years.There was no significant change in the annual trend in mortality for obese or diabetic patients. The overall mortality rates were 0.1% in non‐obese patients and 0.2% in obese, diabetic, and non‐diabetic groups each. The median LOS in obese patients increased from 1 to 2 days between 2008 and 2009 (p < .001)   Figure  and an i < .001) . Howeverp < .001). In a multivariate analysis, obesity was found to be an independent predictor of increased rates of the primary outcome (OR [95% CI]: 1.39 [1.20–1.62]), longer LOS (OR [95% CI]: 1.36 [1.23–1.49]) and higher inflation adjusted charges (OR [95% CI]: 1.16[1.12–1.19]) after adjusting for risk factors including diabetes and hospital bed‐size and volume. Whereas, diabetes was associated with longer LOS (OR [95% CI]: 1.27 [1.16–1.38]) but not increased primary outcome or inflation adjusted charges after adjusting for obesity  (2005–2013) in obese was 11.7% versus 8.2% in non‐obese patients and 10.7% in diabetic versus 8.2% in non‐diabetic patients (6 1.23–1.9) and hi), obesity was independently associated with increased rates of vascular/hemorrhagic (OR [95% CI]: 1.38 [1.15–1.66]) and respiratory (OR [95% CI]: 2.66 [2.06–3.42]) complications. Diabetes was associated with increased respiratory complications (OR [95% CI]: 1.59 [1.24–2.03]) only.In a similar multivariate model assessing individual complication rates Table , obesitp < .001).Lastly, 4In our study analyzing AF ablation admissions in the US from 2005 to 2013 using real‐world data from the NIS, there has been an increasing annual trend of ablations performed on obese (6.1% in 2005 to 17.5% in 2013) and diabetic (10.5% in 2005 to 18.8% in 2013) patients. The overall complication rate, median LOS and inflation adjusted charges have gradually increased, by approximately twofold or more, in both obese and diabetic patients. After adjusting for demographics, clinical variables and hospital size and volume, obesity was associated with 39% increase in complication rates driven mainly by an increase in vascular/hemorrhagic and respiratory complications. Obesity was also independently associated with longer LOS and higher inflation adjusted charges. Diabetes, however, was only associated with increased respiratory complications and longer LOS. Whether aggressive risk factor modification, particularly weight loss, prior to AF ablation reduces ablation costs and complications requires further extensive evaluation in future studies.p = .001).Catheter ablation is becoming standard‐of‐care for many AF patients due to its association with improved outcomes and quality‐of‐lifeIn our study, median LOS doubled for most years in patients with either obesity and/or diabetes but remained relatively steady at 1 day for patients without either comorbidity. The total inflation‐adjusted charges associated with inpatient AF ablation gradually increased by twofold across all groups. The largest difference ($ 11 844) in charges was between obese non‐diabetic patients and non‐obese non‐diabetic patients in 2013. This may be due to higher procedural and equipment charges, longer LOS, or higher charges to treat complications. The median total charges associated with inpatient AF ablations in our study are significantly higher than the costs reported in a study of Medicare supplemental databases and MarketScan® commercial claims from 2007 to 2011 (Median cost $25 100 with large facility variation in costs).We also demonstrate that in all captured AF ablations, obesity was independently associated with increased complication rates (driven primarily by vascular/hemorrhagic and respiratory complications), longer LOS and higher charges after adjusting for demographics, clinical variables, and hospital volume and size. Increased vascular/hemorrhagic complications in obese patients may be due to difficulty in attaining vascular or trans‐septal access even with ultrasound guidance and inadequate hemostasis after catheter removal. Moreover, obese patients undergoing general anesthesia or conscious sedation during this relatively lengthy procedure may experience higher rates of respiratory complications related to worse respiratory mechanics.The literature extensively describes that poorly controlled obesity and diabetes lead to increased AF recurrence rates after catheter ablation.Lastly, we want to address the increase of low‐volume hospitals accounting for 100% of AF ablations in the NIS by 2013. During 1988–2011, the NIS was constructed annually by including 100% of the discharges from 20% of US hospitals. However, it was redesigned in 2012 as a 20% national patient‐level sample, with non‐representative sampling across hospitals.5The NIS is a de‐identified administrative database making it difficult to validate individual ICD‐9‐CM codes. This significantly affects the sensitivity and specificity when applying the diagnostic codes. Studies based on data mining are susceptible to errors related to coding. Obesity and diabetes were defined using ICD‐9 codes, which may not be reliable particularly prior to electronic health records. In addition, outcomes related to the severity of obesity were not examined due to insufficient BMI coding in our sample (<10%) and the potential for selection bias. The data from the NIS lacks the level of detail and patient phenotyping available from clinical trials and registries. As previously described, our study is subject to selection bias towards AF ablations requiring admission due to the two‐midnight rule. However, censoring our analysis at 2013 was performed to minimize this bias. This limitation is also offset by the larger sample size from the NIS and the absence of reporting bias introduced by selective publication of results from specialized centers. This unfortunately also means we do not have more recent data from the last 7 years. AF ablation procedures have significantly evolved in the last 7 years leading to improved safety and efficacy, especially in high risk patients, and reduced procedure time as highlighted in contemporary clinical trials such as CABANA, STOP‐AF, CASTLE‐AF, and EAST‐AF4.We cannot exclude that confounding variables may have impacted our results. Data about procedural technique, anticoagulation used, medications, and type of AF  were unavailable in the NIS. Late complications like pulmonary vein stenosis and atrio‐esophageal were unavailable for analysis since they do not typically arise during an index hospitalization.6Our study involving real‐world data from the NIS demonstrates increased annual complication rates in patients with obesity or diabetes who underwent inpatient AF ablation from 2005 to 2013. Obesity, but not diabetes, is an independent predictor for higher complication rates, longer LOS and higher hospital charges after adjusting for demographics, clinical variables and hospital volume and size. Granted, our database contains only patients who underwent AF ablation as inpatients from the start or were converted to inpatient after developing complications. Weight loss before ablation may help reduce procedural complications and costs.The authors declare no potential conflict of interest.Data S1. Supporting Information.Click here for additional data file.


Myxomatous mitral valve disease (MMVD), a naturally occurring heart disease, affects 10% to 15% of the canine population. Canine MMVD shares many similarities with human MMVD. Untargeted metabolomics was performed to identify changes in metabolic pathways and biomarkers with potential clinical utilities.P<0.05), of which 40% belonged to amino acid super pathways, while 30% were lipids. More than 50% of significant metabolites were correlated with left atrial diameter but not left ventricular dimension. Acylcarnitines, tricarboxylic acid cycle intermediates, and creatine accumulated in proportion to MMVD severity. α‐Ketobutyrate and ketone bodies were increased as MMVD advanced. Nicotinamide, a key substrate of the main nicotinamide adenine dinucleotide (NAD+) salvage pathway, was decreased, while quinolinate of the de novo NAD+ biosynthesis was increased in CHF dogs versus healthy dogs. 3‐Methylhistidine, marker for myofibrillar protein degradation, was higher in CHF dogs than non‐CHF dogs. Trimethylamine N‐oxide (TMAO) and TMAO–producing precursors, including carnitine, phosphatidylcholine, betaine, and trimethyllysine, were increased in CHF dogs versus non‐CHF dogs. Elevated levels of uremic toxins, including guanidino compounds, TMAO, and urea, were observed in CHF dogs. Pathway analysis highlighted the importance of bioenergetics and amino acid metabolism in canine MMVD.Serum samples from 27 healthy, 22 stage B1, 18 stage B2 preclinical MMVD dogs, and 17 MMVD dogs with a history of congestive heart failure (CHF) were analyzed. Linear regression analysis identified 173 known metabolites whose concentrations were different among the 4 groups (adjusted Our study revealed altered energy metabolism, amino acid metabolic programming, and reduced renal function in the development of MMVD and CHF. Complex interplays along the heart‐kidney‐gut axis were implicated. One study compared serum samples between 18 healthy dogs and 11 age‐ and sex‐matched dogs with preclinical MMVD, while the other reported changes in serum metabolome in response to diet intervention in dogs with preclinical MMVD.The authors declare that all of the supporting data are available as Data S1 and S2.The study protocol was reviewed and approved by the University of Pennsylvania Institutional Animal Care and Use Committee, and informed owner consent was obtained. Clinically healthy dogs without a heart murmur and without concurrent systemic disease were prospectively enrolled as controls (group A). This group of dogs primarily consisted of systemically healthy dogs owned by students and staff of the hospital. A cohort of dogs with a left apical systolic murmur, echocardiographic diagnosis of thickened and prolapsing mitral valve leaflet(s), and mitral regurgitation, as well as clinical history and physical examination consistent with stage B1, B2, C, or D MMVD were considered for group B1, group B2, and group C/D, respectively.g for 5 minutes to yield serum samples, which were stored at −80°C until use.Venous blood samples of 2 to 3 mL were collected in plain red‐topped tubes. The blood was allowed to clot and centrifuged at 1600Echocardiographic studies  were performed without sedation. Left ventricular internal dimensions in end‐diastole and left ventricular internal dimensions in end‐systole, normalized left atrial diameter (nLAD), and normalized aortic root diameter were measured from right parasternal short‐axis 2‐dimensional images and normalized to body weight.Untargeted metabolomics assays were performed at a commercial laboratory . Sample preparation and extraction, liquid chromatography, and mass spectrometry followed Metabolon standard protocols as previously described .22, 3The raw data were generated based on the area‐under‐the‐curve formula using ion counts that provide relative quantification Data . MetabolP values were adjusted for multiple testing error.Principal component (PC) analysis (PCA) for high‐dimensional multivariate data was performed using the R function “prcomp” and PCs were calculated. The first 2 PCs, PC1 and PC2, which capture more data variations than other PCs, were examined for their ability to separate the 4 groups. A multiple linear regression using PC1 or PC2 as the dependent variable and group as the independent variable, adjusted for age, body condition score (BCS), and body weight was performed. Tukey's post hoc test was performed to compare the means between groups and P values were adjusted to control the false discovery rate (FDR) using the Benjamini‐Hochberg method. Significant metabolites were subjected to pairwise comparisons using the R function “pairwise.t.test” with pooled SD and Benjamini‐Hochberg adjustment for multiple testing. FDR ≤0.05 was considered significant.To identify differential metabolites, a multiple linear regression, adjusted for age, BCS, and body weight was performed. FC=2(log2g2‐log2g1).To compare the means of continuous variables, ANOVA and Tukey's post hoc tests were performed. To test the null hypothesis that the 2 categorical variables were independent, chi‐square test was performed if all expected numbers were >5. Otherwise, a Fisher's exact test was used instead. Fold‐change (FC) was defined as the ratio of the mean of group 2 (g2) over that of group 1 (g1): P values were adjusted for multiple testing errors using the Benjamini‐Hochberg method. Adjusted P≤0.05 was considered significant. Pairwise Pearson's correlation analysis among significant metabolites was also performed.Pearson's correlation coefficients between echocardiographic variables and significant metabolites were calculated. The 8 dogs without echocardiographic measurements from group A were excluded from the analysis. P value distributions were analyzed.To account for any potential confounding effect from age or body weight, 500 iterations of bootstrap resampling without replacement were performed where 10 samples from each group were randomly selected. Those bootstrapped subsamples with no difference in age or body weight were selected for further analysis. PCA and multiple linear regression were performed on each subsample set using PC1 or PC2 as the dependent variable and group as the explanatory variable, adjusted for age, BCS, and sex. t test were performed to test the null hypothesis that the means of PC1 or PC2 between group Y and group N were not different.Potential confounding effect from cardiac medications was also evaluated using data from groups B1 and B2 dogs. Dogs taking ≥1 of 4 commonly used cardiac medications, pimobendan, furosemide, angiotensin‐converting enzyme inhibitors, and spironolactone, for at least 2 weeks before the time of sampling were considered for group Y, while the rest of the dogs were considered for group N. PCA and Student homo sapiens was searched and pathway overrepresentation analysis was performed using hypergeometric test. The pathway impact was calculated as the sum of the importance measures of the matched metabolites normalized by the sum of the importance measures of all metabolites in each pathway. Quantitative metabolite set enrichment analysis (qMSEA) was performed to identify enriched metabolite sets between group C/D and group A using the PubChem IDs and the concentration data of all metabolites.www.smpdb.ca) was searched. Pathways with P≤0.05 were considered significant.Metabolomics pathway analysis (MetPA) was performed using the Human Metabolome Database IDs of the significant metabolites.Data processing and statistical analysis were performed in the statistical computing software R (version 3.5.0). Partial least square discriminant analysis, MetPA and qMSEA were performed in MetaboAnalyst 4.0.PANOVA<0.001). Dogs in group A were significantly younger than dogs in any other group, and had a greater mean body weight than those in groups B2 and C/D  except between groups A and B1 . Differences were found in all pairwise group comparisons  were known Table . Sixty‐nP>0.05 in both cases, Table P values for PC1 were 1.7×10−7, 2.5×10−4, and 0.02, respectively  and 8 of 22 (36.4%) of the acylcarnitines showed >1.5‐fold increases in group C/D versus group B1 or B2, respectively  cycle, were increased in groups B1, B2, and C/D versus group A, and in group C/D versus group B1  and acetoacetate were increased in both group B2 and group C/D compared with group A  salvage pathway, was decreased in group B1 and group C/D compared with group A  and 103 of 173 (59.5%) were significantly correlated with nLAD and ratio of the left atrial diameter to the aortic root diameter, respectively  and carnitine were correlated with nLAD (FDR<0.05, Table P<0.05, Figure Five KEGG pathways, including arginine biosynthesis, synthesis, and degradation of ketone bodies, nicotinate and nicotinamide metabolism, histidine metabolism, and branched chain amino acid biosynthesis, were overrepresented (Our analysis demonstrated robust changes in the metabolome of dogs with different stages of MMVD that affected several key metabolic pathways. Although the majority of these changes occurred at the stage of CHF, 41% of the significant metabolites had changes at the very early B1 stage, providing an opportunity to understand this early transition during the disease progression. In addition, a small number of metabolites had changes that occurred in the absence of overt congestion or any evidence of volume overload. Could they be early compensatory responses? Derangements in cardiac bioenergetics contribute to the pathogenesis of CHF in humans and animal models.Catabolism of threonine, serine, and methionine converges to α‐ketobutyrate, which enters mitochondrial matrix to produce succinyl‐coenzyme A via the propionate catabolic pathway. Accumulations of α‐ketobutyrate, TCA cycle intermediates, and inorganic phosphate signified perturbations in oxidative phosphorylation. In sarcolemma, creatine, which is produced in the liver and kidneys, is taken up by a membrane creatine transporter from the bloodstream.Carnitine level was also significantly increased in dogs with CHF. Carnitine plays a key role in the transport of long‐chain FAs into mitochondrial matrix for oxidation, and its deficiency was associated with dilated cardiomyopathy in dogs and humans.+ is an essential cofactor for mitochondrial bioenergetics and important for TCA cycle, glycolysis, and FA oxidation. It is synthesized by 3 pathways, the main salvage pathway that recycles nicotinamide or nicotinamide riboside, the de novo biosynthesis through the kynurenine pathway from L‐tryptophan, and the Preiss‐Handler pathway from nicotinic acid.+ biosynthesis is activated.In mammalian cells, NADThe “gut hypothesis” in cardiovascular disease and HF has gained considerable attention in recent years.Several uremic toxins were identified in this study. Deficiency in arginase, the enzyme that catalyzes the conversion from arginine to urea in the urea cycle, results in accumulations of guanidino compounds. The levels of 3 guanidino compounds, argininate, 2‐oxoarginine, and 4‐guanidinobutanoate, were elevated in groups B1, B2, and C/D versus group A. TMAP, a novel marker for kidney function, was also increased in CHF dogs versus non‐CHF dogs. The changes in blood uremic toxins, including TMAO, guanidino compounds, and urea and uric acid, as well as TMAP, provide yet another example of the complex interplay along the cardiorenal axis.A majority of the significant metabolites were correlated with both nLAD and ratio of the left atrial diameter to the aortic root diameter, but not left ventricular internal dimensions in end‐diastole. Left atrial enlargement was considered to be the most reliable independent indicator for increased risk of progression of MMVD in dogs.+ biosynthesis.The MetPA approach depends on a list of significant metabolites that meet the stringent threshold to discern telltale biological clues, while the qMSEA approach uses predefined pathways based on prior biological knowledge to determine whether and how many members of a metabolic pathway act in concert to exert cellular functions. Degradations of homocysteine, methionine, or threonine lead to the production of α‐ketobutyrate, and lysine catabolism generates acetyl‐coenzyme A in the mitochondria. In our study, >30% of metabolic pathways identified by qMSEA were associated with or led to energy productions. Perturbations in arginine and proline metabolism, ammonia recycling, and urea cycle were evidenced with changes in several uremic toxins in the blood. The 3‐MH is the methylation product of histidine residues on the main myofibrillar proteins actin and myosin. Muscle atrophy or cachexia is common in dogs with CHF.Our study underscored the challenge of matching age and body weight between healthy dogs and dogs with MMVD. MMVD is prevalent in small‐breed geriatric dogs, and dogs with CHF generally experience body weight loss attributable to cachexia.The study was funded by the Nestlé Purina PetCare Company.Li is a current employee of the Nestlé Purina PetCare Company. The remaining authors have no disclosures to report.Supplementary MethodsTables S1–S6Figures S1–S5Click here for additional data file.DataS1Click here for additional data file.DataS2Click here for additional data file.


A prothrombotic tendency could partially explain the poor prognosis of patients with coronary heart disease and depression. We hypothesized that cognitive depressive symptoms are positively associated with the coagulation activation marker D‐dimer throughout the first year after myocardial infarction (MI).n = 190), 3 months (n = 154) and 12 months (n = 106). Random linear mixed regression models were used to evaluate the relation between cognitive depressive symptoms, assessed with the Beck depression inventory (BDI), and changes in plasma D‐dimer levels. Demographics, cardiac disease severity, medical comorbidity, depression history, medication, health behaviors, and stress hormones were considered for analyses.Patients with acute MI  were investigated at hospital admission (p < .05) and categorical (p < .010) cognitive depressive symptoms were related to higher D‐dimer levels over time, independent of covariates. Indicating clinical relevance, D‐dimer was 73 ng/ml higher in patients with a BDI score ≥ 6 versus those with a score < 6. There was a cognitive depressive symptom‐by‐cortisol interaction (p < .05) with a positive association between cognitive depressive symptoms and D‐dimer when cortisol levels were high (p < .010), but not when cortisol levels were low (p > .05). Fluctuations (up and down) of cognitive depressive symptoms and D‐dimer from one investigation to the next showed also significant associations (p < .05).The prevalence of clinical depressive symptoms (13‐item BDI score ≥ 6) was 13.2% at admission and stable across time. Both continuous (Cognitive depressive symptoms were independently associated with hypercoagulability in patients up to 1 year after MI. Hypothalamic–pituitary–adrenal axis could potentially modify this effect. Using the Beck depression inventory (BDI), we examined the effect of cognitive depressive symptoms, because the prognostic impact of somatic symptoms of depression on cardiovascular outcomes is partially explained by cardiac disease severity.2ClinicalTrials.gov (NCT01781247). All participants provided written informed consent.This was a secondary analysis of data collected from 190 patients who participated in the MI‐Stress Prevention Intervention (MI‐SPRINT) randomized controlled trial (RCT).Inclusion criteria were a minimum age of 18 years, verified acute ST segment elevation MI (STEMI) or non‐STEMI, stable circulatory conditions and high distress during MI, defined by a minimum score of 5 (range 0–10) for pain intensity and fear of dying and/or helplessness. Exclusion criteria were emergency coronary artery bypass grafting, severe comorbid diseases, limited orientation, cognitive impairment, current severe depression , suicidal ideations in the prior 2 weeks, insufficient German skills, and participation in another randomized controlled trial.Of the originally enrolled 190 participants, 154 participated in the 3‐month follow‐up and 106 in the 12‐month follow‐up investigation. Therefore, for this longitudinal observation study, the 190 participants contributed a total of 450 assessments (mean of 1.6 assessments per participant) over the entire study period of 12 months. The recruitment procedure and reasons for loss to follow‐up have been detailed elsewhere.2.1Information on age and sex was taken from medical records.2.2These included a history of previous MI, the type of index MI (STEMI or non‐STEMI), left ventricular ejection fraction (LVEF), obtained from angiographic records, and C‐reactive protein (CRP), a marker of the acute inflammatory response during MI and low‐grade systemic chronic inflammation. CRP was measured with an immunoturbidimetric assay (C‐Reactive Protein Gen.3) using the COBAS 8000 c702 module from Roche Diagnostics at the Institute of Clinical Chemistry, Inselspital, Bern University Hospital, Switzerland. For clinical routine, the lab provides CRP values of 20 mg/L and higher as “CRP ≥ 20 mg/L", but no precise concentration. Based on this, and on the prognostic CVD risk with increasing CRP levels, CRP values were categorized as follows: <1 mg/L, 1 to ≤3 mg/L, 3 to ≤10 mg/L, 10 to <20 mg/L, and ≥ 20 mg/L.2.3We calculated the Charlson comorbidity index which was categorized by low (index = 1), medium (index =2) or high (index = 3+) 10‐year mortality risk.2.4Information on current use of aspirin, other platelet inhibitors , oral anticoagulants (OAC: vitamin K antagonists and direct OAC), statins, antidepressants, and glucocorticoids were collected from medical charts and interviewer‐assessed.2.5Body mass index (BMI) was calculated based on self‐disclosed weight and height at admission, and on measured weight and height at both follow‐ups. Patients were categorized in current or nonsmokers. Frequency of physical activity per week “that makes you sweat” was categorized as none, 1–2× or 3–7×. Alcohol consumption was categorized as none, moderate or heavy; the latter based on the number of standard drinks per week .2.6We assessed cognitive depressive symptoms with the 13‐item self‐rated cognitive depressive symptom subscale of the BDI.2.7Norepinephrine was quantified by high‐pressure liquid chromatography in ethylendiamintetraacetic acid (EDTA) plasma using electrochemical detection2.8r = 0.95) when determined with these two methods.Following a strict in‐house protocol to ensure adequate preanalytical conditions, D‐dimer was measured in citrate plasma at the accredited Hemostasis Laboratory, Inselspital, Bern University Hospital, Switzerland. Determination was with a quantitative sandwich enzyme immunoassay  or with a particle‐based immunoturbidimetric assay . Within‐run CV were 2%–12% and day‐to‐day CV were 2%–3% for both assays. The Vidas® assay is the most clinically validated D‐dimer measurement technique and thus considered the reference commercial quantitative immunoassay.p < .05. We conducted a linear mixed (random effects) regression analysis to examine the covariate‐adjusted longitudinal relation between cognitive depressive symptoms and plasma D‐dimer across three investigations . With linear mixed model regression an intercept and slope of each participant can be estimated based on the available data for that individual , augmented by the data from the entire sample. We prioritized the continuous BDI score as a predictor variable; however, to test for a relation between clinically significant depressive symptoms and D‐dimer levels, we also used a categorical BDI score of ≥6 versus <6.Data were analyzed with SPSS 26.0 for Windows  and two‐tailed significance at The covariates listed below were considered on an a priori basis as potential confounders of D‐dimer levels.As a next step, we calculated two multivariable models for cognitive depressive symptoms with covariates entered into models as fixed effects. In Model 1, these covariates were demographics ; indices of cardiac disease severity ; Charlson comorbidity index, depression history, medication use  and health behaviors . In Model 2, we additionally entered stress hormones . Like depressive symptoms, CRP, medication use, health behaviors, and stress hormones were all entered as time varying. Random intercepts were modeled for participants.SD vs. −1 SD from the mean) would moderate the relation between cognitive depressive symptoms and D‐dimer levels.Model 2 allowed us to test the extent to which stress hormones potentially mediate the link between cognitive depressive symptoms and D‐dimer. In statistical terms, this would be the case if a significant relation between cognitive depressive symptoms and D‐dimers was no longer significant after stress hormones were added to the equation. Potential effect modification by stress hormones was further tested by entering an interaction term between cognitive depressive symptoms and each stress hormone into Model 2. For significant interactions, we applied the Holmbeck methodWe computed both between‐ and within‐participants effects of cognitive depressive symptoms on D‐dimer. The between‐participants analysis tests whether patients who are generally  higher in cognitive depressive symptoms are also those showing higher D‐dimer levels over the entire study period. The within‐participants analysis tests whether, at individual investigations, a patient who reports a higher level of cognitive depressive symptoms also shows higher D‐dimer, suggesting an association between fluctuations (up or down) in cognitive depressive symptoms and D‐dimer. To obtain within‐participants effects, each patient's personal mean value across time was subtracted from each of his or her individual observation.3Table Univariable associations of between‐participants effects Table  showed aThe significance of a positive association of both continuous and categorical cognitive depressive symptoms with D‐dimer levels was maintained with adjustment for time, demographic factors, indices of cardiac disease severity, comorbidity, depression history, medication use, health behaviors, and stress hormones Table , Model 1Univariable analysis of within‐participants effects Table  showed tp < .05). Post hoc analysis revealed that cognitive depressive symptoms were associated with D‐dimer when cortisol levels were high (estimate [SE] = 0.022 (0.007), p < .010), but not significantly so when cortisol levels were low (estimate [SE] <0.001 (0.008)). No significant interactions emerged between categorical depressive symptoms and cortisol and between cognitive depressive symptom scores, both continuous and categorical, and norepinephrine levels.Next, we tested whether stress hormones would be effect moderators of between‐participants effects. There was a significant cognitive depressive symptom score‐by‐cortisol interaction for D‐dimer levels over time, adjusting for time, demographics, indices of cardiac disease severity, comorbidity, depression history, medication use, health behaviors, norepinephrine levels, and main effects of cortisol levels and cognitive depressive symptoms (estimate [SE] = 0.006 (0.003), In the within‐participants analysis, there was no significant interaction between continuous cognitive depressive symptoms and both norepinephrine and cortisol levels, adjusting for time, demographics, indices of cardiac disease severity, comorbidity, depression history, medication use, health behaviors, and main effects of both the other stress hormone and cognitive depressive symptoms.4We found a significant longitudinal relation between cognitive depressive symptoms and plasma D‐dimer levels in patients followed for up to 12 months after acute MI. Patients who endorsed more severe cognitive depressive symptoms had greater blood coagulability in the first year following MI than patients with less depressed mood. This relation was independent of a range of factors potentially confounding this relation. In fact, several covariates showed expected associations with D‐dimer levels in univariable and multivariable models. Significant independent associations with elevated D‐dimer emerged for older age, higher CRP and lower LVEF, whereas OAC use was associated with lower D‐dimer.These findings further substantiate the literature on a prothrombotic tendency as a potential mechanism underlying the increased risk of atherothrombotic CVD events in patients with depression. Previous research assessed hypercoagulability in terms of different hemostasis measures, including platelet hyperactivity, clotting factors, global hypercoagulability markers and impaired fibrinolysis.Our findings may help to understand why patients with treatment resistant depression,Our findings may have clinical implications. Higher D‐dimer during admission for MI, and when assessed following MI at similar time points as in our study, has been shown to predict recurrent cardiac events.We found some evidence for effect modification for cortisol levels. Specifically, there was a significant relation between cognitive depressive symptoms and D‐dimer when cortisol was high for the entire study period, but not when cortisol was low. This observation might reflect cumulative allostatic load referring to the biological and mental burden emerging from adaptation to chronic stress and life events.The longitudinal design with up to three repetitive investigations and rigorous control of time varying and of potentially confounding variables of D‐dimer values are notable strengths of our study, which also has several limitations worth mentioning. We included patients with high distress during MI who participated in an RCT aimed at preventing psychological sequelae of MI. Although additional adjustment for the intervention group did not change the results (not shown), our findings should not be generalized to the population of patients with acute MI at large. In addition, women were underrepresented in our sample and medical comorbidity was rather low. Venous thromboembolism was not an exclusion criterion, and we could not exclude the possibility that D‐dimer levels were influenced by intercurrent venous thromboembolism during follow‐up, which we did not systematically assess. The item to assess depression history did not ask for a health professional diagnosis of depression and cognitive depressive symptoms following MI were self‐rated. Moreover, for the RCT, we excluded patients with a current severe depressive illness based on clinical judgment. This likely resulted in underrepresentation of patients in the upper range of depressive symptom severity. Whereas the pooled prevalence of depression is 29% in patients with MI,Taken together, we showed a longitudinal and independent association between cognitive depressive symptoms and plasma D‐dimer levels in patients followed up to 1 year after acute MI. The main finding of our study is consistent with the notion of a prothrombotic tendency in patients with CHD, which can be partially explained by depressed mood. The extent to which hypercoagulability accounts for the increased risk of recurrent cardiac events and poor prognosis in patients with CHD and depression remains to be studied.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Roland von Känel: Conceptualization, data curation, formal analysis, funding acquisition, methodology, resources, supervision, writing–original draft, writing–review & editing.Aju P. Pazhenkottil: Conceptualization, methodology, supervision, validation, writing–review & editing.Rebecca E. Meister‐Langraf: Conceptualization, data curation, investigation, methodology, project administration, writing–review & editing.Hansjörg Znoj: Conceptualization, funding acquisition, methodology, supervision, validation, writing–review & editing.Jean‐Paul Schmid: Conceptualization, funding acquisition, methodology, supervision, validation, writing–review & editing.Claudia Zuccarella‐Hackl: Conceptualization, methodology, validation, writing–review & editing.Jürgen Barth: Conceptualization, formal analysis, funding acquisition, methodology, supervision, validation, writing–review & editing.Ulrich Schnyder: Conceptualization, funding acquisition, methodology, supervision, writing–review & editing.Mary Princip: Conceptualization, data curation, investigation, methodology, project administration, writing–review & editing.


This study aimed to verify the relationships between sleep problems and both commuting and workplace accidents in workers of both sexes.n = 2993; 50.2% female) from the Chilean Quality of Life Survey (ENCAVI) 2015–2016, while the rates of both workplace and commuting accidents were extracted from the statistics of the Superintendence of Social Security .The study was carried out with a sample of workers  = − 5.19; p < .001), while the Chilean people as a whole sleep less compared to those of other countries (7.24 h per day). Likewise, it was found that sleep problems are more strongly related to commuting than to workplace accidents. In this vein, sleep quantity can explain 24% of the variance in commuting accidents’ rates  = 5.49, p < .05; β = −.55, p < .05), by using aggregated data with all types of commuting roles .Chilean workers sleep less than the rest of the people in the country (Our findings show that sleep quantity has a more robust relationship with commuting than workplace accidents, a neglected issue so far. Future prevention programs should emphasize sleep hygiene and focus on commuting to and from work.The online version contains supplementary material available at 10.1186/s12889-021-10737-5. Two types of occupational accidents workers can be involved in: at the workplace and while commuting. A workplace accident is any physical injury suffered by an individual caused or as a result of working, while a commuting accident takes place on the way to and from the place of work . These tDespite their worse effects and persistence over time, commuting accidents have not received deep attention , 9, 10. Research usually considers two dimensions of sleep: quantity and quality. Sleep quantity is defined as the amount of time someone spends sleeping . MeanwhiConcerning sleep quality, Uehli et al. , in a syRegarding sleep quantity, sleeping less than 6 hours is a risk factor for traffic accidents in all drivers  and profIn sum, deficits in sleep quantity and quality—with their adverse effects on people’s normal functioning and health—are linked to either workplace and commuting accidents , 28. HowIn Chile, there is not a single database that simultaneously contains all the information we need. Then, as a proxy for exploration, we use two independent databases: ENCAVI 2015–2016 for both sleep quantities and sleep quality , and then = 2993; 50.2% women; average age = 43.3 years), which excluded pensioners, students, homemakers, among others. Sleep quantity and sleep quality were extracted from the topic ‘Sleep Hygiene’ of Module III, ‘Well-being and Health Perceptions,’ of ENCAVI 2015–2016. The question about the amount of sleep is this: ‘How many hours do you estimate you have slept, on average, each night during the last month?’ The six questions related to sleep quality are the following: i) Sleep quality in the last month ; ii) Use of medicines for sleeping in the last month ; iii) Incidents of sleepiness in the last month ; iv) Problems such as falling asleep during daytime, waking up frequently at night, or waking up too early in the morning during the last 30 days ; v) Difficulty in feeling rested and refreshed during the day ; and vi) Sleep quality in the last year  [ENCAVI 2015–2016 includes 7041 respondents nationwide, representing people over the age of 15 living in private homes located in urban and rural areas of the 15 regions of Chile. Interviewers applied this paper-and-pencil survey in a face-to-face procedure at the chosen household. Through a probabilistic, geographically stratified, and multi-stage design , houses were chosen. To homogenize the type of participants in both databases, only employees were considered from the ENCAVI 2015–2016 in this study , a passenger (public and private transport), or a pedestrian .Both ENCAVI 2015–2016 and SUSESO’s statistics contain national records corresponding to year 2015 in their respective topics.Both databases come from the same population, but individuals’ identification was not possible. So, we merged both databases taking the 15 regions of Chile as units of analysis, also differentiating by sex within each area. Correlations between average scores of sleep quantity and sleep quality with the rates of workplace and commuting accidents among Chilean workers, by region, were calculated using the SPSS 21. Regression analyses were performed on the workplace and commuting accident rates with sleep variables as predictors.r (15) = −.55; p < .05; and in the case of males, r (15) = −.52; p < .05  = .46; p = .08; and ‘sleepiness’ with commuting accidents, r (15) = .45; p = .09.Regarding sleep quality variables, marginally significant correlations were found in the case of males between ‘sleep quality (last month)’ with workplace accidents, To check whether the sleep quantity variable and the six indicators of sleep quality could explain the accident rates, linear regression models were performed on the workplace and commuting accident rates, with the seven sleep variables as predictors. Two regressions fit adequately into a model: ‘sleep hours’ as a predictor of commuting accident rates for the whole sample  = 4.79, p < .05; β = −.52, p < .05). Therefore, these results allow us to conclude that there were significant relationships between sleep hours and commuting accidents, but not with accidents at the workplace.Table R2Adjusted = .15, F (1.14) = 3.50, p = .08; β = .46, p = .08; and commuting accidents, R2Adjusted = .14, F (1.14) = 3.24, p = .09; β = .45, p = .09 .Additionally, for comparative purposes, regressions models using the enter method, show that sleep quality problems in males have similar strength to explain the variance of both workplace, The main finding is that hours of sleep are significantly related to commuting accident rates by region of the country, and it can explain 24% of their variance. That is, as workers in a region sleep lower, higher rates of commuting accidents in the region are found ”. Likewise, Salminen et al. [Nevertheless, unlike previous evidence –27, sleeRegarding sleep quality, although we have found marginally significant effects only in the case of males, they are in line with previous findings, which allows inferring they are not at random. Firstly, ‘sleep quality’ problems related to workplace accidents were verified by Uehli et al. . SecondlThus, our results for the whole sample combined with previous findings suggest that sleep problems, specifically sleep quantity have stronger relationships with commuting than workplace accidents, a neglected issue. More attention is needed on sleep problems, and workers’ health surveillance , 35, andWhich factors could then be related to the fact that detriment in sleep quantity affects workers’ accidents more strongly while they commute to work than at the workplace? Without a definitive answer, several factors should be considered.MW = 7.14 vs. MO = 7.33; t (6789) = − 5.19; p < .001 (ENCAVI 2015–2016). Likewise, the Chilean population, in general, seems to sleep less than those of other countries. In a multi-country comparison, Walch et al. [First, sleep inertia is a transitional stage of low activation that occurs after waking up and temporarily generates a decrease in performance. This phenomenon gets worse when there is a lack of sleep and can have effects up to 4 hours after awakening . Sleep ih et al.  found thh et al. .Second, some workplace conditions can interfere with sleep. Sleep disturbances can, in turn, endanger the safety of workers . For exaThird, a situational factor comprises those of the traffic context. These include the poor condition of streets and sidewalks, street dogs, crime and vandalism, reckless behaviors by other drivers, cyclists, and pedestrians, among others .All in all, we can conclude that workers with lack of sleep, while commuting to work, are subject to a series of adverse factors  that seem to interact with the impaired normal functioning that sleep detriment implies , 41, 43,Likewise Uehli et al.  pointed Among the limitations of the present work, the main one is using data from two different databases. Although the information comes from the same workers grouped by the country’s regions, any specific worker identification was impossible. In this vein, there might be individual differences in sleep patterns that are not considered and other not controlled factors, such as climatic conditions, traffic environments, etc. However, our findings are consistent with previous literature and shed light on more accurate and sophisticated future research procedures.Likewise, the reliability of the measurement of sleep hours by self-report could be questioned. However, evidence found through meta-analysis shows that a subjective or self-report measure strongly correlates with objective measures of the amount of sleep . LikewisAlso, we have used aggregated information with all workers’ commuting roles . There might be differences in the strength of relationships if those roles were studied separated. Nevertheless, commuting accidents have received few attention , 9, 10, To conclude, global data indicate that commuting accidents have more severe consequences and imply higher economic costs than workplace accidents . HoweverAdditional file 1: Annex 1. Workers’ Sleep Variables of ENCAVI 2015-2016 and Rates of Workplace and Commuting Accidents of SUSESO 2015, per sex and region of Chile


Increasing cassava production could mitigate one of the global food insecurity challenges by providing a sustainable food source. To improve the yield potential, physiological strategies  can be applied in breeding to screen for superior genotypes. However, the influences of source-to-sink carbon partitioning and carbon metabolism on the storage root development of cassava are relatively little understood. We hypothesized that carbon partitioning and utilization vary modulating the distinctive storage root yields of high and low-yielding cassava varieties, represented in this study by varieties Kasetsart 50 (KU50) and Hanatee (HN), respectively. Plant growth, photosynthesis measurements, soluble sugars, and starch contents of individual tissues were analyzed at different developmental stages. Also, the diurnal patterns of starch accumulation and degradation in leaves were investigated through iodine staining. Despite a comparable photosynthetic rate, KU50 grew better and yielded greater storage roots than HN. Interestingly, both varieties differed in their carbon partitioning strategies. KU50 had a high photosynthetic capacity and was better efficient in converting photoassimilates to carbon substrates and allocating them to sink organs for their growth. In contrast, HN utilized the photoassimilates at a high metabolic cost, in terms of respiration, and inefficiently allocated carbon to stems rather than storage roots. These results highlighted that carbon assimilation and allocation are genetic potential characteristics of individual varieties, which in effect determine plant growth and storage root yield of cassava. The knowledge gained from this study sheds light on potential strategies for developing new high-yielding genotypes in cassava breeding programs. Manihot esculenta Crantz), a perennial crop plant, is recognized as an effective starch producer  and final storage root yield, although a positive correlation has also been suggested , 29°C/24°C day/night, and 70% relative humidity on all days) during August 2016 to January 2017 at the Institute of Bio- and Geosciences Plant Sciences (IBG-2), Forschungszentrum, Jülich, Germany. KU50 is a widely grown commercial variety with high root yield and starch content, while HN is an edible low-yielding landrace. They were propagated by 10-cm long stem cuttings with at least two axillary buds. The individual stem cuttings were planted in commercial soil  in 25-cm diameter top, 19-cm diameter base, and 21-cm depth pots  for 12 weeks, and then transferred to the 53-cm diameter top, 40-cm diameter base, and 43-cm depth pots  to increase space for root growth. The plant positions were randomly rotated monthly during cultivation to ensure homogeneity of the microclimate to which each plant was exposed. Plants were watered twice a week with 1,000 ml of tap water per pot.Kasetsart 50 (KU50) and Hanatee (HN) cassava varieties were grown in a controlled greenhouse environment (14/10 h of light/dark with <500 μE mFifteen plants were harvested every 4 weeks until 12 weeks after planting (WAP), and 12 plants at 15 and 20 WAP. The plant samples were separated into leaves, petioles, stems, stem cuttings, and total roots for growth measurement. The adventitious roots of cassava were also separated into fibrous roots  and early storage roots  using the criteria modified from N), transpiration rate (Tr), stomatal conductance (Gs), intercellular CO2 concentration (Ci), and the ratio between intercellular and ambient CO2 concentrations (Ci/Ca) were measured using a portable gas exchange system, infrared gas analyzer , equipped with a CO2 mixer to control the CO2 level in the chamber. The measurements were conducted with the following settings: 500 μmol s−1 air flow rate, 400 μmol CO2 mol−1 air CO2 concentration, 27°C leaf temperature, and 1,000 μmol photons m−2 s−1 light intensity. For respiration rate (R), it was measured using a portable gas exchange system according to the method described above unless the light intensity was set to zero. Chlorophyll fluorescence parameters were measured at the same lobe using Mini PAM-II Photosynthesis Yield Analyzer  to measure steady-state fluorescence in the light-adapted state (F′) and the maximal fluorescence of the light-adapted state (Fm′). The effective quantum yield of photosystem II [ΦPSII = (Fm′ − F′)/Fm′] and electron transport rate [ETR = ΦPSII × 0.84 × 0.5 × photosynthetically active radiation (PAR)] were calculated by the software of Mini PAM-II . Net photosynthetic rate , leaf area, and plant dry weight. Plant height was measured from the point of stem emergence to shoot apex. The attached leaves were counted from the first fully expanded leaf to the last photosynthetic leaf showing more than 50% greenness over its entire area, while the remaining leaves were counted as senescent. Total leaf area per plant (leaf lamina only) was measured using a leaf area meter . Fresh and dry weights of all separated plant parts were determined. For dry weight measurement, all samples were oven-dried to a constant weight at 60°C. In addition to the destructive analysis, total root development in both cassava varieties was studied by MRI , a non-ivia the change of the reduced nicotinamide adenine dinucleotide phosphate (NADPH) during the enzymatic assay. The NADPH formation was measured through absorbance at 340 nm using a microplate spectrophotometer . The enzymatic assay started with mixing 20 μl of the extract with imidazole buffer, 36 mg ml−1 NADP+, 60 mg ml−1 ATP, and glucose-6-phosphate dehydrogenase. Subsequently, glucose, fructose, and sucrose concentrations were determined by absorbance measurement after adding hexokinase, phosphoglucoisomerase, and invertase, respectively. Each enzyme was added when the kinetic reaction reached saturation.Sugar and starch contents in leaf, stem, FRs, and parenchyma tissues of ESRs were examined in three biological replicates using an enzymatic assay . Fifty m−1 NADP+, 60 mg ml−1 ATP, glucose-6-phosphate dehydrogenase, and hexokinase. The total amount of glucose hydrolysate was determined by absorbance measurement at 340 nm with a microplate spectrophotometer .For starch measurement, the precipitate after the ethanolic extraction was mixed with 500 μl water before gelatinization in an autoclave at 135°C for 1 h. Next, the gelatinized starch was mixed with digestion buffer  and incubated at 37°C for 16 h. After incubation, an aliquot of 20 μl was mixed with tris buffer, 36 mg mlThe extracted sample from the analysis of soluble sugars was adjusted with 95% ethanol in prior to the determination of leaf chlorophyll contents  by using the UVIKON XL  spectrophotometer. The equations and specific absorption wavelength reported by 3 in volume)] outdoor at the Center for Agricultural Systems Biology (CASB), King Mongkut’s University of Technology Thonburi (KMUTT), Thailand during June 2018 to December 2018. Treatments used were similar to the conditions mentioned above. Leaf apices of the first fully expanded leaf of 2-month-old cassava plants were collected at different times of the day: 6:00 (dawn), 12:00 (midday), 18:00 (dusk/evening), and 24:00 (midnight), to illustrate the phenomena of diurnal carbon accumulation and assimilation in cassava leaves. All leaf apices were submerged in 80% ethanol with vigorous shaking and incubated at 37°C for 8–12 h until all chlorophyll spots were removed. The staining was performed using 12.5% (v/v) iodine solution prepared from Lugol’s dye to visualize differentially accumulated starch .All data were analyzed based on three biological replicates (mean ± SE), at least. Statistical testing was performed using a one-sided Student’s 2 acquisition, carbon assimilation, and carbon allocation for root development. The photosynthetic capability was studied by measuring the leaf gas exchange , chlorophyll fluorescence , and leaf greenness index  during canopy establishment (4–12 WAP) but leveled up thereafter. The PN values measured during the experiment (4–20 WAP) were 1.65–12.21 μmol CO2 m−2 s−1 for KU50 and 2.39–7.58 μmol CO2 m−2 s−1 for HN (N were similar to that of the intercellular CO2 concentration (Ci), the ratio between intercellular and ambient CO2 concentrations (Ci/Ca), effective quantum yield of photosystem II (ΦPSII), and ETR, which showed that HN had slightly higher capability at the early development stage  leaf greenness index (SPAD) than HN throughout the experiment  was 1.29 times higher than that of HN  to the highest at dusk (dark blue leaf), followed by a decline during nighttime . At the t-test, p ≤ 0.05; −1 averaging 1.50 ± 0.09 m2 leaf area plant−1, and 96.73 ± 5.67 gDW plant−1 for the total dry biomass ; HN measured 160.79 ± 17.34 cm in height with 26 ± 2 leaves plant−1 averaging 0.69 ± 0.09 m2 leaf area plant−1, and 36.23 ± 6.26 gDW plant−1 for the total dry biomass  higher dry weights of petioles and mature leaves than HN throughout the studied periods, indicating better-developed photosynthetic tissues (p ≤ 0.05) all through the developmental stages and outperforming HN by approximately 3.04 times at 20 WAP  the efficiency of crops to intercept radiation (photosynthetic capability), (ii) the efficiency of intercepted radiation conversion into biomass (carbon assimilation), and (iii) the efficiency of biomass partitioning into the harvested product  and sink  tissues during cassava plant development were analyzed to study the patterns of carbon allocation, also referred to as shoot-root carbon partitioning, in these distinct varieties . The invDifferences in pool sizes of the carbon substrates were observed between the varieties, which may reflect varying carbon assimilation and allocation capacity linked to their genetic backgrounds. Varietal differences in patterns of sucrose and starch accumulation in shoot and root tissues were found from 12th WAP. The patterns observed in KU50 plants at 12 WAP were similar to those in HN at 15 WAP when the storage roots were first observed. These patterns likely demonstrated the carbon allocation profile at the root bulking stage of cassava development. Taken together, the high-yielding KU50 showed decreasing leaf sucrose and increasing root sucrose during 4–20 WAP, with fairly even source-sink (leaf-root) sucrose distribution at 15 WAP. KU50 accumulated the least amount of starch in all tissues, except leaves, at 4 WAP and the most in stems during storage root bulking (12–15 WAP), which tended to be increasingly remobilized for storage root growth ; top. FoOverall, we report different patterns of sucrose and starch accumulation in source and sink tissues of a low-yielding landrace (HN) and a modern high-yielding variety (KU50) linking to their growth. Both varieties exhibited distinct strategies for carbon assimilation and allocation to shoots and roots , 8. KU50N, Ci, Ci/Ca, ΦPSII, ETR, Gs, and Tr) than KU50  and the low-yielding landrace (HN) showed different patterns of carbon assimilation and shoot-to-root carbon allocation. KU50 proved superior in allocating carbon from source to sink organs for their growth, while HN allocated photoassimilates more to stems than storage roots and showed a higher metabolic cost in terms of respiration. The knowledge gained from this study may be useful for whole plant constraint-based metabolic modeling and may be used as a criterion for screening and selecting high-yield genotypes in cassava breeding programs.The carbon assimilation in plant metabolism and source-to-sink carbon allocation are believed to be key modulators of plant growth and the final root yield of cassava. These characteristics have been highly linked to the genetic potential of the individual varieties. Our study reveals that the high root yield of cassava is related to the photosynthetic capacity, which is dependent on PThe original contributions presented in the study are included in the article/This study was conceived and designed by TS and TW. TS, SK, and TW supervised the project. PC cultivated plants, collected samples, and performed plant growth analysis and physiological measurement. JT, PB, and PC performed biochemical analysis. TS and PC analyzed all data and interpreted the results and drafted the manuscript. TS, PC, JT, SK, and TW discussed the results. All authors interpreted the results, wrote the article, and approved the final manuscript.This work was financially supported by National Science and Technology Development Agency (NSTDA), Thailand  and the National Science Research and Innovation Fund (NSRF) Thailand (grant no. 42951). Also, we would like to thank the Postdoctoral Fellowship from King Mongkut’s University of Technology Thonburi (KMUTT), Thailand for PC; and the Postdoctoral Fellowship from the Program Management Unit for Human Resources and Institutional Development, Research, and Innovation (grant no. B01F630003) for PB.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


There are limited data on the prevalence of anaemia and iron deficiency (ID) in Somalia. To address this data gap, Somalia's 2019 micronutrient survey assessed the prevalence of anaemia and ID in children (6–59 months) and non‐pregnant women of reproductive age (15–49 years). The survey also collected data on vitamin A deficiency, inflammation, malaria and other potential risk factors for anaemia and ID. Multivariable Poisson regressions models were used to identify the risk factors for anaemia and ID in children and women. Among children, the prevalence of anaemia and ID were 43.4% and 47.2%, respectively. Approximately 36% and 6% of anaemia were attributable to iron and vitamin A deficiencies, respectively, whereas household possession of soap was associated with approximately 11% fewer cases of anaemia. ID in children was associated with vitamin A deficiency and stunting, whereas inflammation was associated with iron sufficiency. Among women, 40.3% were anaemic, and 49.7% were iron deficient. In women, ID and number of births were significantly associated with anaemia in multivariate models, and approximately 42% of anaemia in women was attributable to ID. Increased parity was associated with ID, and incubation and early convalescent inflammation was associated with ID, whereas late convalescent inflammation was associated with iron sufficiency. ID is the main risk factor of anaemia in both women and children and contributed to a substantial portion of the anaemia cases. To tackle both anaemia and ID in Somalia, food assistance and micronutrient‐specific programmes (e.g. micronutrient powders and iron supplements) should be enhanced. The prevalence of anaemia is classified as a severe public health problem in Somali children and women, and the iron deficiency prevalence is considered high and moderate for children and women, respectively.Iron deficiency is the main risk factor of anaemia in both children and women; however, the risk factors of iron deficiency are not the same for each group.Programme planners can likely reduce the prevalence of anaemia and iron deficiency by increasing the coverage of nutrition interventions that increase the intake of iron and vitamin A, such as the distribution of MNPs, micronutrient supplements and vitamin A supplements.1Anaemia is characterized by a shortage of functional haemoglobin  as well as external household‐level factors  have been associated with anaemia in children and women WHO, . The cauers WHO, . Globallers WHO, ; howeverers WHO, . In sub‐ers WHO, . In addiers WHO,  and reduers WHO, .Awareness of anaemia and ID and interventions to address both conditions have increased over the past decades  collected information about anaemia prevalence, ID and other micronutrient deficiencies and data about risk factors for anaemia and ID in order to measure the relative importance of several potential risk factors for anaemia and ID.22.1geographic strata. For the IDP stratum, IDP settlements identified by the United Nations High Commissioner for Refugees  and women of reproductive age. Data were collected between December 2018 and September 2019. The survey sampled households separately in the following geographic strata: (1) Somaliland, (2) Puntland, (3) Hirshabelle and Galmudug states, (4) Jubaland and South West states and (5) Banaadir region. In addition, a sixth stratum consisted of internally displaced person (IDP) settlements in all of Somalia. Two‐stage sampling was conducted. In the first stage, enumeration areas listed as part of the 2014 Population Estimation Survey of Somalia , the first blood drop was discarded, the second blood drop was used to measure malaria parasitemia with a rapid test kit , and the third drop was used to measure haemoglobin concentration using HemoCue™ . Quality control blood of low and medium haemoglobin concentration  was used on a daily basis to assure accurate haemoglobin measurements with the HemoCue™ devices. Following the on‐site measurements, 300–400 μl of blood was collected from children and non‐pregnant women into a silica‐coated blood collection tube .Whole blood samples were stored in cold boxes at 4–8°C until further processing later the same day. Whole blood samples were centrifuged at 3000 rpm for 7 min to separate the serum using mobile centrifuges . Serum was then aliquoted into appropriately labelled cryovials and stored in portable freezers at −20°C  or stationary freezers (where possible) for the duration of the field data collection. After completion of fieldwork, all blood samples were transferred to a central freezer at Hargeisa, Somaliland, before shipment with frozen saltwater cold packs to international laboratories for analyses. All samples arrived frozen at their respective destinations.12 were analysed in a subsample of women by the Swiss Vitamin Institute  using microbiological assays with Lactobacillus casei (ATCC 7469) and Lactobacillus leichmannii (ATCC 7830) as test organisms, respectively, following the turbidimetric reference method performed in microtitre plates , ferritin, C‐reactive protein (CRP) and α1‐acid glycoprotein (AGP) at the VitMin Lab  using an ELISA method , sickle cell trait (HbAS), homozygous and heterozygous α‐thalassaemia and the homozygous/hemizygous and heterozygous G6PD c.202 form of glucose‐6‐phosphate dehydrogenase (G6PD) deficiency. Genetic analyses were conducted at the KEMRI‐Wellcome Trust Research Programme in Kilifi, Kenya , early convalescence (elevated CRP and AGP) and late convalescence (elevated AGP only) according to Thurnham et al. . To clasChild stunting, wasting, underweight, overweight and obesity were assessed using the WHO Growth Standards . Cut‐offs for BMI were as follows: <16.0 severe chronic energy deficiency; 16.0–16.9 moderate chronic energy deficiency; 17.0–18.4 at‐risk for energy deficiency; 18.5–24.9 normal; 25.0–29.9 overweight; ≥30.0 obese  software on tablet computers. To ensure data validity and integrity, multiple steps were taken. Firstly, as the SMS 2019 administered three separate questionnaires , the ODK questionnaires were programmed to facilitate the merging of household‐level data with individual‐level data. To illustrate, one ODK questionnaire form was composed of many individual questionnaires, such that the data for all children or women residing in a household were collected as part of the same form. Secondly, during the data collection, summary statistics of key variables were calculated for each team to identify any possible data collection errors. When potential issues were identified, teams were contacted to clarify the issue. Thirdly, any possible discrepancies found during the data analysis were cross‐checked against the paper biological forms that were collected for each child and woman. Data analysis was done using Stata/IC Version 14.2 . To account for unequal probability of selection in the six strata, statistical weights were applied in all analyses, which combined two or more strata.The statistical precision of prevalence estimations was assessed using 95% confidence intervals (95% CI), which were calculated accounting for the complex sampling. Only variables that were assessed in all subjects and not only in a subsample were considered for inclusion into multivariable models.epctile command . Using the adjusted risk ratios produced by the Poisson regression and the prevalence of exposure to the risk factor among anaemic children or women, we calculated the population attributable fraction (PAF) for each risk factor retained in the final regression models , and colinear variables were identified and removed accordingly. The remaining variables were included into a Poisson regression model with robust error variance; non‐significant variables were manually removed using backward elimination until all variables were statistically significant  are presented elsewhere  of non‐pregnant women tested positive.As shown in Table P‐value < 0.1, including ID, vitamin A deficiency, stunting, inflammation, α‐thalassaemia, G6PD deficiency, child weighed at birth, child received vitamin A supplements in the past 6 months and child registered in a feeding programme. Household‐level variables associated with anaemia in children included household wealth quintile, household food insecurity category and any soap in the house. In women, fewer variables were associated with anaemia status; individual‐level variables included ID, vitamin A deficiency and marital status, and household‐level variables included water at household's handwashing site and household wealth quintile.Tables P‐value < 0.1) with ID included sex, vitamin A deficiency, inflammation, stunting, wasting and consumed fortified cereal in the past 24 h. State of residence was the only non‐individual‐level variable associated with ID in children. In women, individual‐level variables associated with ID status included pregnancy in the past 2 years, inflammation and consumed organ meat in past 24 h. Household wealth quintile was the only household‐level variable associated with ID in women.Tables P < 0.001) and ID . Age category in months was also significantly associated with anaemia status  can be explained by the hepcidin‐induced blockage of iron absorption in the state of inflammation .4.2The high prevalence of iron and vitamin A deficiencies in children and women—and their association with anaemia (vitamin A deficiency in children only)—highlights the need to increase the intake of bioavailable iron and vitamin A in Somalia. Although relatively few children and women consume a diet with minimum diversity, promotional campaigns to increase the quantity and variety of foods consumed may not currently be a viable programme option in Somalia. Recent research from the World Food Programme (WFP) . This study is published with permission from the Director of the Kenya Medical Research Institute (KEMRI).Conceptualization: FS, FR, NP, JPW and BAW. Formal analysis: JPW. Funding acquisition: FS and MG. Methodology: FR, JPW, NP, BAW and FS. Project administration: FS, HOY, JPW, JM, YK, FR, NP, BAW, WESD and MG. Laboratory analysis: TNW, RV and SR. Supervision: SA, YK, JM and HOY. Writing–original draft: NP and JPW.Table S1. Bivariate anaemia analyses children 6–59 months of ageTable S2. Bivariate anaemia analyses women 15–49 yearsTable S3. Bivariate iron deficiency analyses children 6–59 months of ageTable S4. Bivariate iron deficiency analyses women 15–49 yearsClick here for additional data file.


Although there are reports on the effectiveness of microendoscopic laminotomy using a spinal endoscope as decompression surgery for lumbar spinal stenosis, predicting the improvement of low back pain (LBP) still poses a challenge, and no clear index has been established. This study aimed to investigate whether microendoscopic laminotomy for lumbar spinal stenosis improves low back pain and determine the preoperative predictors of residual LBP.In this single-center retrospective study, we examined 202 consecutive patients who underwent microendoscopic laminotomy for lumbar spinal stenosis with a preoperative visual analog scale (VAS) score for LBP of ≥40 mm. The lumbar spine Japanese Orthopaedic Association (JOA), and VAS scores for LBP, leg pain (LP), and leg numbness (LN) were examined before and at 1 year after surgery. Patients with a 1-year postoperative LBP-VAS of ≥25 mm composed the residual LBP group. The preoperative predictive factors associated with postoperative residual LBP were analyzed.p < 0.001), LBP-VAS improved from 66.7 to 29.7 mm (p < 0.001), LP-VAS improved from 63.8 to 31.2 mm (p < 0.001), and LN-VAS improved from 63.3 to 34.2 mm (p < 0.001). Ninety-eight patients (48.5%) had a postoperative LBP-VAS of ≥25 mm. Multiple logistic regression analysis revealed that Modic type 1 change , preoperative VAS for LBP ≥ 70 mm , and female sex  were preoperative predictors of residual LBP.JOA scores improved from 14.1 preoperatively to 20.2 postoperatively (Microendoscopic decompression surgery had an ameliorating effect on LBP in lumbar spinal stenosis. Modic type 1 change, preoperative VAS for LBP, and female sex were predictors of postoperative residual LBP, which may be a useful index for surgical procedure selection. Lumbar spinal stenosis (LSS) is a disease in which the dural tract and nerve roots are compressed because of degeneration of the intervertebral disk and facet joints, causing symptoms such as sciatica, intermittent claudication, and low back pain (LBP) , 2. The Microendoscopic laminotomy (MEL) is a minimally invasive surgical procedure that incorporates the use of a spinal endoscope. This procedure, which is derived from the microendoscopic discectomy technique, was developed to treat patients with LSS , 7. The In the procedure performed to improve lower limb symptoms, patients often report an improvement in LBP. It has been reported that open decompression surgery has an ameliorating effect on LBP . HoweverThis retrospective cohort study was approved by institutional review board of Wakayama Medical University (No. 2945). Written informed consent for involvement in this study was obtained from all patients included. In total, 220 consecutive patients who underwent MEL for LSS between July 2014 and December 2018 were enrolled. Patients who underwent microendoscopic discectomy for lumbar disc herniation were excluded from this study. The LSS diagnoses were made based on the presence of specific clinical symptoms, such as LBP, leg pain, numbness, and intermittent claudication, as well as on the existence of radiological spinal stenosis on magnetic resonance imaging (MRI) that confirmed the neurological symptoms. The inclusion criteria were as follows: (1) patients who underwent MEL for LSS due to failure of conservative treatment, (2) patients who had a preoperative baseline LBP of at least 40 mm on the 100-mm visual analog scale (VAS). Patients were excluded if they had a history of lumbar fusion surgery.The surgeries were performed using a METRx endoscopic system  by 11 spine surgeons who were certified as endoscopic spine surgeons by the Japanese Orthopedic Association. To perform the spinal decompression, a small paramedian skin incision of approximately 16 mm in length was made to target the interlaminar space in each decompressed level. The central canal and bilateral lateral recess were decompressed for all the patients through a unilateral tubular approach  score and VAS scores for LBP, leg pain, and leg numbness were examined before and at 1 year after surgery. The minimal clinically important difference (MCID) of the VAS value improvement was determined as ≥20 mm , and theSubsequently, for the purpose of examining preoperative predictors of postoperative residual LBP, patients with a 1-year postoperative LBP-VAS of ≥25 mm or those requiring additional surgery for residual LBP within 1 year after MEL surgery were considered to have postoperative residual LBP. The factors that may be associated with postoperative residual LBP, including age, sex, body mass index (BMI), disease duration, number of decompressed levels, and preoperative clinical scores (VAS scores) were investigated. Preoperative radiological findings, such as spondylolisthesis (Meyerding classification), degenerative scoliosis (Cobb angle ≥20°), spinal instability , disk sp value of < 0.2 in the univariate analysis and factors that have been reported as poor factors for decompression surgery  and SPSS Statistics Ver. 28 . n = 109; females, n = 93: follow-up rate, 91.8%) who had been observed for > 1 year after surgery were enrolled. Table Altogether, 202 patients , VAS score for LBP improved from 66.7 mm to 29.7 mm (p < 0.001), VAS score for leg pain improved from 63.8 mm to 31.2 mm (p < 0.001), and VAS score for leg numbness improved from 63.3 mm to 34.2 mm (p < 0.001) , BMI (p = 0.141), scoliosis (p = 0.003), Modic type 1 change (p ≤ 0.001), pelvic tilt ≥30° (p = 0.113), and preoperative VAS for LBP ≥ 70 mm (p = 0.001)  had a VAS for LBP ≥ 25 mm. Factors that showed a x p = 0.04, BMI (pp = 0.005), preoperative VAS for LBP ≥ 70 mm , and female sex  were predictors of postoperative residual LBP (Table Multiple logistic regression analyses showed that Modic type 1 change (odds ratio [OR], 5.61; 95% confidence interval [CI], 1.68–18.68; In the selection of a surgical procedure for LSS, it has been reported that decompression alone yields inferior results compared with fusion surgery in patients with LBP , 5 or raAs per the preoperative predictive factors, patients were divided according to a postoperative LBP VAS score of 25 mm. We adopted the VAS score of 25 mm, since the pain level less than that value is reported as acceptable pain for degenerative disorders . In the Modic type 1 endplate disorder is a change in T1 low intensity and T2 high intensity, which reflects inflammatory findings , and itsThere are some limitations in this study. First, this is a retrospective cohort study with a small number of patients. Future prospective studies with a larger patient population are needed. Second, the follow-up period in this study was short. However, since it is intended for LBP, which can be affected by multiple factors, we believe that the evaluation of short-term postoperative results is appropriate for the purpose of clearly evaluating the improving effect of surgery. Third, there is a risk of selection bias, and there is no comparison with fusion surgery. However, this study includes a considerable number of patients with spondylolisthesis or spinal instability, and there have been multiple cases of LBP improvement with decompression surgery alone. These results may provide valuable information for patients undergoing surgery.Microendoscopic decompression surgery for LSS has an ameliorating effect on LBP. Modic type 1 change of endplate, preoperative VAS for LBP, and female sex are predictors of postoperative residual LBP, which may be a useful index for surgical procedure selection. There is no need to select fusion surgery for these cases due to imaging abnormalities, such as spondylolisthesis, spinal instability, and sagittal malalignment.


Coronavirus disease‐2019 (COVID‐19) has been associated with an increased risk of acute cardiac events. However, the effect of COVID‐19 on repolarization heterogeneity is not yet established. In this study, we evaluated electrocardiogram (ECG) markers of repolarization heterogeneity in patients hospitalized with COVID‐19. In addition, we performed a systematic review and meta‐analysis of the published studies.QT dispersion (QTd), the interval between T wave peak to T wave end (TpTe), TpTe/QT (with and without correction), QRS width, and the index of cardio‐electrophysiological balance (iCEB) were calculated in 101 hospitalized COVID‐19 patients and it was compared with 101 non‐COVID‐19 matched controls. A systematic review was performed in four databases and meta‐analysis was conducted using Stata software.p‐value = .005; TpTe/QT = 0.217 vs. 0.203 ms, p‐value = .026). After a meta‐analysis of 679 COVID‐19 cases and 526 controls from 9 studies, TpTe interval, TpTe/QT, and TpTe/QTc ratios were significantly increased in COVID‐19 patients. Meta‐regression analysis moderated by age, gender, diabetes mellitus, hypertension, and smoking reduced the heterogeneity. QTd showed no significant correlation with COVID‐19.Tp‐Te, TpTe/QT, QRS width, and iCEB were significantly increased in COVID‐19 patients compared with controls (TpTe = 82.89 vs. 75.33 ms (ms), COVID‐19 adversely influences the ECG markers of transmural heterogeneity of repolarization. Studies evaluating the predictive value of these ECG markers are warranted to determine their clinical utility. COVID‐19 diagnosis was made either by a positive polymerase chain reaction (PCR) of the nasopharyngeal swab or evident COVID‐19 pneumonia on chest CT scan with no other etiology explaining the imaging findings. The control group was selected from gender‐ and age‐matched patients admitted for elective surgery during the same period of time. The control group had no clinical evidence of COVID‐19 and had negative PCR tests. The patients' demographics, lab results, and admission ECGs were available for all cases and controls. Patients with uninterpretable ECG, complete bundle branch block, nonsinus rhythms , symptoms of acute coronary syndromes, symptomatic heart failure with ejection fraction (EF) ≤ 40%, outpatient use of QT‐prolonging agents  and electrolyte imbalances on admission were excluded. The demographic data and medical history were extracted from the patients' charts. The medications prescribed in the outpatient setting were also collected. The laboratory data including white blood cell count, neutrophil to lymphocyte ratio (NLR), hemoglobin concentration, platelet count, plasma level of C‐reactive protein (CRP), and quantitative levels of troponin T and creatinine were recorded for COVID‐19 cases. This study posed no additive charge or harm to the study population. It was approved by the ethics committee of Tehran University of medical sciences. All patients' identifiers were removed to comply with Health Insurance Portability and Accountability Act regulations. Informed consent was obtained from all patients before the study.2.2Surface ECGs were scanned to a personal computer and transferred to Adobe Photoshop CC 2019 software . The measurement scales were set and the intervals were calculated at 200% magnification.The QT interval was considered as the distance between the first deflection of the QRS complex and the end of the T wave defined as the intersection of the tangent to the steepest downslope of the T wave and the isoelectric line. The longest QT and QRS intervals were used  to prevent underestimation of isoelectric T waves. In case of a discrete U wave in a precordial lead, that value was omitted.The TpTe interval was defined as the interval between the T wave peak to the T wave end in lead V5.To assess the contribution of repolarization heterogeneity duration to the total duration of the action potential, TpTe was divided by QT and QTc and the index of cardio‐electrophysiological balance (iCEB) was defined as the QT to QRS ratio.2.3SD and categorical variables are reported as frequency and percentage. Student t test and χ2 test were used to compare continuous variables and categorical variables, respectively. Pearson correlation analysis was applied to assess the correlation of ECG markers with laboratory and clinical data. A 2‐sided p value of < .05 was considered statistically significant. Statistical analyses were performed using the SPSS software version 25 (IBM Corp.).Continuous variables are presented as mean ± 2.4The current review followed the Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) guideline. The review protocol has been published on The International Prospective Register of Systematic Reviews, known as PROSPERO (ID: CRD42021244450). A systematic search was conducted until May 28, 2021 by two independent investigators (E. M. and M. K.) in four databases, including Scopus, Web of Science, PubMed, and Cochrane Library. To address the search question, the search queries included a combination of three keywords without any language restriction or time limitations:  AND [COVID‐19 and its equivalents]. The complete search queries for each database are described in the Supporting Information Material. A subsidiary manual search was also performed in ResearchGate and Google Scholar.The studies that presented the mean and standard deviation for any of the four ECG variables including “QTd,” “TpTe,” “TpTe to QT ratio,” and “TpTe to QTc ratio” in COVID‐19 patients were included. All types of observational studies were included. The search results were screened using their titles, abstracts, and full‐texts in more relevant studies. Duplications were removed and the full texts of all the included studies were obtained. The quality of the studies was assessed using Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklists at the study level . The number of cases and controls, the mean and standard deviation of QTd, TpTe, TpTe/QT, and TpTe/QTc in the study groups, and the characteristics of the study population including age, gender, hypertension, diabetes mellitus, smoking, study location, and COVID‐19 hospitalization status were extracted from each study by two independent investigators. In case of a discrepancy, a consensus was achieved by discussion.2.5I2 test based on Cochrane's Q. Higher Q values with p values less than .1 were considered as significant heterogeneity. An I2 value of <25%, 25%–50%, 50%–75%, and >50% indicated absent, low, moderate, and high heterogeneity, respectively.p values < .1 indicating publication bias. Sensitivity analysis was performed by excluding individual studies from the meta‐analysis.The values were summarized as mean differences (MDs) with a 95% confidence interval. MDs were standardized using Cohen's method and random‐effects meta‐analysis was performed on each target ECG marker by the Stata software . Statistical heterogeneity was evaluated using the Higgins' 3The study population included 101 patients hospitalized due to COVID‐19 and 101 gender‐ and age‐matched controls. Seventy percent of the cases and controls were male with a mean age of 60.11 ± 16.16 years for cases and 61.1 ± 17.22 years for controls. The patients' characteristics are summarized in Table p‐value = .005), corrected TpTe , TpTe/QT , and QRS width . iCEB and TpTe dispersion were significantly lower in cases . There were no significant differences in QT dispersion and TpTe/QTc between the two study groups.ECG parameters in the study groups are presented in Table r2 = .28, p‐value = .049 for TpTe and r2 = .30, p‐value = .035 for TpTe/QTc, Figure r2 = −.28, p‐value = .021 for TpTe/QT and r2 = −.27, p‐value = .025 for TpTe/QTc, Figure r2 = .28, p‐value = .025 for TpTe, Figure ECG parameters were also corrected using the Bazett's equation for use in the meta‐analysis. These values are reported separately in Table 3.1Eight studies were considered eligible for inclusion in the current meta‐analysis and the original data of the present study were added to these eight studies.After excluding a study by Rubin et al.p value of .1 , which makes the TpTe interval a useful marker to assess temporary electrophysiologic changes in the myocardium. COVID‐19 patients can particularly be complicated with numerous conditions that may affect cardiac electrophysiological properties.Myocardial injury in the setting of ischemia and viral myocarditis have been previously shown to increase repolarization heterogeneity and prolong the TpTe and TpTe/QT intervals.r2 = .185, p‐value = .128). In addition, TpTe/QT and TpTe/QTc ratios were negatively correlated with the platelet count, which can be secondary to bone marrow suppression and the resultant thrombocytopenia in the setting of septicemia and systemic inflammation.Sympathetic activation due to respiratory distress, hypoxia, and fever can increase the markers of repolarization heterogeneity.The multifaceted effects of COVID‐19 on myocardial repolarization heterogeneity markers are illustrated in Figure In terms of gender‐specific differences in myocardial electrophysiologic properties, androgen deprivation and anti‐androgen treatment have been associated with a prolonged TpTe interval and administration of testosterone can shorten this interval.Among the common comorbidities, diabetes mellitus has been associated with a tendency to increase the TpTe dispersion and TpTe/QT ratio.Eventually, the drug‐induced changes in repolarization heterogeneity markers and their role in the development of VA are well studied5According to this study, novel indicators of repolarization heterogeneity including TpTe, TpTe/QT, and TpTe/QTc are considerably increased in the course of COVID‐19. These adverse electrophysiological changes can be secondary to numerous conditions that impair myocardial supply‐demand, stimulate myocardial sympathetic nerves, and directly injure the myocytes in the course of COVID‐19. Owing to the imposed burden of cardiac arrhythmias in COVID‐19 morbidity and mortality, measurement of the electrocardiographic markers of repolarization heterogeneity may be considered an available, cost‐effective, and robust method of risk stratification, particularly in more severe cases.5.1ECG measurements are relatively heterogeneous and operator‐dependent. Besides this, there is no expert consensus on the definition of most of the novel markers we addressed in this study. Same heterogeneities exist about different methods of COVID‐19 diagnosis and the criteria for hospitalization. Another challenge was to prepare a sufficient sample of healthy controls from the low‐risk population with an available ECG, negative COVID‐19 PCR, and matched age and sex, which was not feasible, timely, and cost‐efficacious. So that we chose a sample of elective patients admitted to the surgery ward whose COVID‐19 was rolled out to prevent complications and they all had ECG by routine. In addition, investigating the prognostic value of ECG markers in predicting the in‐hospital or long‐term adverse cardiovascular events including arrhythmias and mortality could have been of great value but a larger sample of patients was needed to perform a statistically reliable analysis of these relatively rare outcomes.6According to previous studies, cardiovascular complications have imposed considerable burden to patients with COVID‐19.Repolarization heterogeneity is increased in patients with COVID‐19, before initiation of QT‐prolonging agents.Myocarditis, inflammation, Thrombophilia, Coronary ischemia, Hypoxia, adrenergic stimulation and therapeutic agents are possible mediators influencing repolarization duration and heterogeneity in patients with COVID‐19.TpTe, TpTe/QT, QRS width and iCEB should be considered as risk markers of arrhythmia in patients with COVID‐19.The authors declare that there are no conflict of interests.Pejman Mansouri, Shayan Mirshafiee, Behnam Hedayat, and Mojtaba Salarifar provided the original data summarized in Tables Supporting information.Click here for additional data file.