Laparoscopic small bowel length measurement: nonassociative nature of total small bowel length with anthropometric and clinical characteristics in patients undergoing bariatric surgery.

BACKGROUND: Small bowel length (SBL) may have an impact on the outcomes of bariatric surgeries, but it can be difficult to make a direct association between SBL and the safety and outcome of bariatric surgeries. OBJECTIVES: To address this issue, we set out to devise a predictive model for SBL determination based on clinical and anthropometric variables. SETTING: An academic tertiary medical center. METHODS: Anthropometric and clinical data, including age, sex, height, weight, and past medical history, were collected upon enrollment. SBL was measured twice during the surgery using a marked grasper. In all cases, measurements were carried out by a single surgeon. To create a predictive model, a 2-step approach was employed. In the first step, linear regression was used to determine influential variables. In the second step, all variables with a P value < .2 were entered into a multivariate regression model. RESULTS: Overall, 961 bariatric candidates were enrolled. The mean age of the participants was 40.08 years, and 77.5% (n = 745) were female. The mean SBL was 748.90 centimeters. There was a weak but statistically significant positive correlation between SBL with both weight and height. Our univariate linear model determined only anthropometric parameters as a predictor of SBL. The multivariate model also yielded that none of the entered parameters were shown to be accurate predictors of SBL. Moreover, only 4.3% of variances were explainable by this model. CONCLUSION: Although we found a weak positive association between height and SBL, this association lacked clinical practicality.

Obesity as an independent risk factor for COVID-19 severity and mortality.

BACKGROUND: Since December 2019, the world has struggled with the COVID-19 pandemic. Even after the introduction of various vaccines, this disease still takes a considerable toll. In order to improve the optimal allocation of resources and communication of prognosis, healthcare providers and patients need an accurate understanding of factors (such as obesity) that are associated with a higher risk of adverse outcomes from the COVID-19 infection. OBJECTIVES: To evaluate obesity as an independent prognostic factor for COVID-19 severity and mortality among adult patients in whom infection with the COVID-19 virus is confirmed. SEARCH METHODS: MEDLINE, Embase, two COVID-19 reference collections, and four Chinese biomedical databases were searched up to April 2021. SELECTION CRITERIA: We included case-control, case-series, prospective and retrospective cohort studies, and secondary analyses of randomised controlled trials if they evaluated associations between obesity and COVID-19 adverse outcomes including mortality, mechanical ventilation, intensive care unit (ICU) admission, hospitalisation, severe COVID, and COVID pneumonia. Given our interest in ascertaining the independent association between obesity and these outcomes, we selected studies that adjusted for at least one factor other than obesity. Studies were evaluated for inclusion by two independent reviewers working in duplicate.  DATA COLLECTION AND ANALYSIS: Using standardised data extraction forms, we extracted relevant information from the included studies. When appropriate, we pooled the estimates of association across studies with the use of random-effects meta-analyses. The Quality in Prognostic Studies (QUIPS) tool provided the platform for assessing the risk of bias across each included study. In our main comparison, we conducted meta-analyses for each obesity class separately. We also meta-analysed unclassified obesity and obesity as a continuous variable (5 kg/m2 increase in BMI (body mass index)). We used the GRADE framework to rate our certainty in the importance of the association observed between obesity and each outcome. As obesity is closely associated with other comorbidities, we decided to prespecify the minimum adjustment set of variables including age, sex, diabetes, hypertension, and cardiovascular disease for subgroup analysis.  MAIN RESULTS: We identified 171 studies, 149 of which were included in meta-analyses.  As compared to 'normal' BMI (18.5 to 24.9 kg/m2) or patients without obesity, those with obesity classes I (BMI 30 to 35 kg/m2), and II (BMI 35 to 40 kg/m2) were not at increased odds for mortality (Class I: odds ratio [OR] 1.04, 95% confidence interval [CI] 0.94 to 1.16, high certainty (15 studies, 335,209 participants); Class II: OR 1.16, 95% CI 0.99 to 1.36, high certainty (11 studies, 317,925 participants)). However, those with class III obesity (BMI 40 kg/m2 and above) may be at increased odds for mortality (Class III: OR 1.67, 95% CI 1.39 to 2.00, low certainty, (19 studies, 354,967 participants)) compared to normal BMI or patients without obesity. For mechanical ventilation, we observed increasing odds with higher classes of obesity in comparison to normal BMI or patients without obesity (class I: OR 1.38, 95% CI 1.20 to 1.59, 10 studies, 187,895 participants, moderate certainty; class II: OR 1.67, 95% CI 1.42 to 1.96, 6 studies, 171,149 participants, high certainty; class III: OR 2.17, 95% CI 1.59 to 2.97, 12 studies, 174,520 participants, high certainty). However, we did not observe a dose-response relationship across increasing obesity classifications for ICU admission and hospitalisation. AUTHORS' CONCLUSIONS: Our findings suggest that obesity is an important independent prognostic factor in the setting of COVID-19. Consideration of obesity may inform the optimal management and allocation of limited resources in the care of COVID-19 patients.

The Rate of Successful Cardiopulmonary Resuscitation in COVID-19 Patients: A Retrospective Cohort Study.

Background: This study aims to provide information on the success rate of CPR in COVID-19 patients and some probable risk factors of mortality in these cases. Methods: In this historical cohort design, the CPR success rate probable risk factors of 737 critically ill patients during the COVID-19 pandemic in 17 hospitals in the catchment area of Iran University of Medical Sciences, Tehran, Iran, was evaluated between Feb and Apr 2020. Data were extracted from a database that is a part of a national integrated care electronic health record system and analyzed with logistic and Cox regression models. Results: COVID-19 cases were 341 (46.3%). The mean age in COVID-19 cases and non-COVID-19 patients were 70.0±14.6 and 63.0±19.3 years, respectively (P<0.001). The mortality was significantly higher in COVID-19 patients (99.1% vs. 74%, OR: 39.6, 95%CI: 12.4, 126.2). Cardiovascular diseases were the most frequent underlying disease (46.3% of COVID-19 cases and 35.1% of non-COVID-19 patients). Being a COVID-19 case (OR: 29.0, 95%CI: 8.9, 93.2), Intensive care unit admission (OR: 2.6, 95%CI: 1.5, 4.6) and age for each ten-year increase (OR: 1.2, 95%CI: 1.1, 1.4) were observed to be independent risk factors of mortality following CPR. The hazard ratio of being a COVID-19 patient was HR= 1.8 (95%CI: 1.5, 2.1). Conclusion: Critically ill COVID-19 patients who undergo CPR have a decreased chance of survival in comparison to non-COVID-19 patients.

Angiotensin enzyme inhibitors and angiotensin receptor blockers as protective factors in COVID-19 mortality: a retrospective cohort study.

Targeting the renin-angiotensin system is proposed to affect mortality due to coronavirus disease 2019 (COVID-19). We aimed to compare the mortality rates in COVID-19 patients who received angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEIs/ARBs) and those who did not. In this retrospective cohort study, mortality was considered as the main outcome measure. All underlying diseases were assessed by the chronic use of medications related to each condition. We defined two main groups based on the ACEIs/ARBs administration. A logistic regression model was designed to define independent predictors of mortality as well as a Cox regression analysis. In total, 2553 patients were included in this study. The mortality frequency was higher in patients with a history of underlying diseases (22.4% vs 12.7%, P value < 0.001). The mortality rate in patients who received ACEIs/ARBs were higher than non-receivers (29.3% vs. 19.5%, P value = 0.013, OR = 1.3, 95% CI 1.1, 1.7) in the univariate analysis. However, the use of ACEIs/ARBs was a protective factor against mortality in the model when adjusted for underlying conditions, length of stay, age, gender, and ICU admission (P value < 0.001, OR = 0.5, 95% CI 0.3, 0.7). The Kaplan-Meier curve showed an overall survival of approximately 85.7% after a 120-day follow-up. ACEIs/ARBs are protective factors against mortality in COVID-19 patients with HTN, and these agents can be considered potential therapeutic options in this disease. The survival probability is higher in ACEIs/ARBs receivers than non-receivers.