scholarly journals Risk factors and interventions associated with mortality or survival in adult COVID-19 patients admitted to critical care: a systematic review and meta-analysis

2020 ◽  
pp. 116-127 ◽  
Author(s):  
EH Taylor ◽  
R Hofmeyr ◽  
A Torborg ◽  
C van Tonder ◽  
R Boden ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Critical Care ◽  
Intensive Care ◽  
Meta Analysis ◽  
Smoking History ◽  
Intensive Care Admission ◽  
Risk Indices ◽  
History Of ◽  
Male Sex

Background: Patients with confirmed COVID-19 admitted to intensive care units have a high mortality rate, which appears to be associated with increasing age, male sex, smoking history, hypertension and diabetes mellitus. Methods: A systematic review to determine risk factors and interventions associated with mortality/survival in adult patients admitted to an intensive care unit (ICU) with confirmed COVID-19/SARS-CoV-2 infection. The protocol was registered with PROSPERO (CRD42020181185). Results: The search identified 483 abstracts between 1 January and 7 April 2020, of which nine studies were included in the final review. Only one study was of low bias. Advanced age (odds ratio [OR] 11.99, 95% confidence interval [CI] 5.35–18.62) and a history of hypertension were associated with mortality (OR 4.17, 95% CI 2.90–5.99). Sex was not associated with mortality. There was insufficient data to assess the association between other comorbidities, laboratory results or critical care risk indices and mortality. The critical care interventions of mechanical ventilation (OR 6.25, 95% CI 0.75–51.93), prone positioning during ventilation (OR 2.06, 95% CI 0.20–21.72), and extracorporeal membrane oxygenation (ECMO) (OR 8.00, 95% CI 0.69, 92.33) were not associated with mortality. The sample size was insufficient to conclusively determine the association between these interventions and ICU mortality. The need for inotropes or vasopressors was associated with mortality (OR 6.36, 95% CI 1.89–21.36). Conclusion: The studies provided little granular data to inform risk stratification or prognostication of patients requiring intensive care admission. Larger collaborative research is needed to address this limitation.

The burden of cardiovascular disease risk factors in the Middle East: A systematic review and meta-analysis focusing on primary prevention

2020 ◽  
Vol 18 ◽  
Author(s):  
Akshaya Srikanth Bhagavathula ◽  
Abdullah Shehab ◽  
Anhar Ullah ◽  
Jamal Rahmani
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Cardiovascular Disease ◽  
Family History ◽  
Primary Prevention ◽  
Middle East ◽  
Disease Risk ◽  
Meta Analysis ◽  
Middle Eastern ◽  
History Of

Background: The increasing incidence of cardiovascular disease (CVD) threatens the Middle Eastern population. Several epidemiological studies have assessed CVD and its risk factors in terms of the primary prevention of CVD in the Middle East. Therefore, summarizing the information from these studies is essential. Aim: We conducted a systematic review to assess the prevalence of CVD and its major risk factors among Middle Eastern adults based on the literature published between January 1, 2012 and December 31, 2018 and carried out a meta-analysis. Methods: We searched electronic databases such as PubMed/Medline, ScienceDirect, Embase and Google Scholar to identify literature published from January 1, 2012 to December 31, 2018. All the original articles that investigated the prevalence of CVD and reported at least one of the following factors were included: hypertension, diabetes, dyslipidaemia, smoking and family history of CVD. To summarize CVD prevalence, we performed a random-effects meta-analysis. Results: A total of 41 potentially relevant articles were included, and 32 were included in the meta-analysis (n=191,979). The overall prevalence of CVD was 10.1% (95% confidence interval (CI): 7.1-14.3%, p<0.001) in the Middle East. A high prevalence of CVD risk factors, such as dyslipidaemia (43.3%; 95% CI: 21.5-68%), hypertension (26.2%; 95% CI: 19.6-34%) and diabetes (16%; 95% CI: 9.9-24.8%), was observed. The prevalence rates of other risk factors, such as smoking (12.4%; 95% CI: 7.7-19.4%) and family history of CVD (18.7%; 95% CI: 15.4-22.5%), were also high. Conclusion: The prevalence of CVD is high (10.1%) in the Middle East. The burden of dyslipidaemia (43.3%) in this region is twice as high as that of hypertension (26.2%) and diabetes mellitus (16%). Multifaceted interventions are urgently needed for the primary prevention of CVD in this region.

Risk Factors for Nonunion Following Ankle Arthrodesis: A Systematic Review and Meta-analysis

2021 ◽  
pp. 193864002199849
Author(s):  
Sumit Patel ◽  
Lauren Baker ◽  
Jose Perez ◽  
Ettore Vulcano ◽  
Jonathan Kaplan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Avascular Necrosis ◽  
Strong Evidence ◽  
Meta Analysis ◽  
Ankle Arthrodesis ◽  
Male Gender ◽  
Site Infection ◽  
Open Injury ◽  
History Of

Background Nonunion is a postoperative complication after ankle arthrodesis (AA), which leads to increased morbidity and revision rates. Previous studies have identified risk factors for nonunion following AA, but no meta-analysis has been performed to stratify risk factors based on strength of evidence. Methods Abstracts and full-text articles were screened by 2 independent reviewers. Relevant data were extracted from the included studies. Random effects meta-analyses were summarized as forest plots of individual study and pooled random effect results. Results Database search yielded 13 studies involving 987 patients were included, and 37 potential risk factors for nonunion. Meta-analysis found 5 significant risk factors for nonunion post-AA. Strong evidence supports male gender (OR: 1.96; 95% CI: 1.13-3.41), smoking (OR: 2.89; 95% CI: 1.23-6.76), and history of operative site infection prior to arthrodesis (OR: 2.40; 95% CI: 1.13-5.09) as predictors for nonunion following AA. There was moderate evidence supporting history of open injury (OR: 5.95; 95% CI: 2.31-15.38) and limited evidence for preoperative avascular necrosis (OR: 13.16; 95% CI: 2.17-79.61) as possible risk factors for nonunion. Conclusion The results of our meta-analysis suggest that male gender, smoking, and history of operative site infection have strong evidence and that history of open injury and avascular necrosis also have evidence as risk factors for nonunion. Surgeons should be cognizant of these risks when performing AA and closely follow up with patients with the aforementioned risk factors to ensure postoperative success. Levels of Evidence: Level V: Systematic review of cohort and case-control studies

scholarly journals Recalibrating the risk of hamstring strain injury (HSI): A 2020 systematic review and meta-analysis of risk factors for index and recurrent hamstring strain injury in sport

2020 ◽  
Vol 54 (18) ◽  
pp. 1081-1088 ◽  
Author(s):  
Brady Green ◽  
Matthew N Bourne ◽  
Nicol van Dyk ◽  
Tania Pizzari
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Evidence Synthesis ◽  
Meta Analysis ◽  
Significant Risk ◽  
Older Age ◽  
Future Research ◽  
Hamstring Strain ◽  
Best Evidence Synthesis ◽  
History Of

ObjectiveTo systematically review risk factors for hamstring strain injury (HSI).DesignSystematic review update.Data sourcesDatabase searches: (1) inception to 2011 (original), and (2) 2011 to December 2018 (update). Citation tracking, manual reference and ahead of press searches.Eligibility criteria for selecting studiesStudies presenting prospective data evaluating factors associated with the risk of index and/or recurrent HSI.MethodSearch result screening and risk of bias assessment. A best evidence synthesis for each factor and meta-analysis, where possible, to determine the association with risk of HSI.ResultsThe 78 studies captured 8,319 total HSIs, including 967 recurrences, in 71,324 athletes. Older age (standardised mean difference=1.6, p=0.002), any history of HSI (risk ratio (RR)=2.7, p<0.001), a recent HSI (RR=4.8, p<0.001), previous anterior cruciate ligament (ACL) injury (RR=1.7, p=0.002) and previous calf strain injury (RR=1.5, p<0.001) were significant risk factors for HSI. From the best evidence synthesis, factors relating to sports performance and match play, running and hamstring strength were most consistently associated with HSI risk. The risk of recurrent HSI is best evaluated using clinical data and not the MRI characteristics of the index injury.Summary/conclusionOlder age and a history of HSI are the strongest risk factors for HSI. Future research may be directed towards exploring the interaction of risk factors and how these relationships fluctuate over time given the occurrence of index and recurrent HSI in sport is multifactorial.

scholarly journals Development and Evaluation of Models to Predict Readmission or Death After Discharge from Intensive Care 

2021 ◽  
Author(s):  
Jamie M Boyd ◽  
Matthew T James ◽  
Danny J Zuege ◽  
Henry Thomas Stelfox
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Intensive Care ◽  
Risk Prediction ◽  
Prediction Models ◽  
Meta Analysis ◽  
Local Data ◽  
Predictive Values ◽  
Risk Prediction Models ◽  
Icu Discharge

Abstract Background Patients being discharged from the intensive care unit (ICU) have variable risks of subsequent readmission or death; however, there is limited understanding of how to predict individual patient risk. We sought to derive risk prediction models for ICU readmission or death after ICU discharge to guide clinician decision-making. Methods Systematic review and meta-analysis to identify risk factors. Development and validation of risk prediction models using two retrospective cohorts of patients discharged alive from medical-surgical ICUs (n = 3 ICUs, n = 11,291 patients; n = 14 ICUs, n = 11,400 patients). Models were developed using literature and data-derived weighted coefficients. Results Sixteen variables identified from the systematic review were used to develop four risk prediction models. In the validation cohort there were 795 (7%) patients who were re-admitted to ICU and 703 (7%) patients who died after ICU discharge. The area under the curve (AUROC) for ICU readmission for the literature (0.615 [95%CI: 0.593, 0.637]) and data (0.652 [95%CI: 0.631, 0.674]) weighted models showed poor discrimination. The AUROC for death after ICU discharge for the literature (0.708 [95%CI: 0.687, 0.728]) and local data weighted (0.752 [95%CI: 0.733, 0.770]) models showed good discrimination. The negative predictive values for ICU readmission and death after ICU discharge ranged from 94%-98%. Conclusions Identifying risk factors and weighting coefficients using systematic review and meta-analysis to develop prediction models is feasible and can identify patients at low risk of ICU readmission or death after ICU discharge.

scholarly journals The relationship of COVID-19 severity with cardiovascular disease and its traditional risk factors: A systematic review and meta-analysis

2020 ◽  
Author(s):  
Kunihiro Matsushita ◽  
Ning Ding ◽  
Minghao Kou ◽  
Xiao Hu ◽  
Mengkun Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Cardiovascular Disease ◽  
Meta Analysis ◽  
Multivariable Analysis ◽  
Renin Angiotensin System ◽  
Regression Analyses ◽  
Male Sex ◽  
Meta Regression ◽  
Traditional Risk Factors

AbstractBackgroundWhether cardiovascular disease (CVD) and its traditional risk factors predict severe coronavirus disease 2019 (COVID-19) is uncertain, in part, because of potential confounding by age and sex.MethodsWe performed a systematic review of studies that explored pre-existing CVD and its traditional risk factors as risk factors of severe COVID-19 (defined as death, acute respiratory distress syndrome, mechanical ventilation, or intensive care unit admission). We searched PubMed and Embase for papers in English with original data (≥10 cases of severe COVID-19). Using random-effects models, we pooled relative risk (RR) estimates and conducted meta-regression analyses.ResultsOf the 661 publications identified in our search, 25 papers met our inclusion criteria, with 76,638 COVID-19 patients including 11,766 severe cases. Older age was consistently associated with severe COVID-19 in all eight eligible studies, with RR >∼5 in >60-65 vs. <50 years. Three studies showed no change in the RR of age after adjusting for covariate(s). In univariate analyses, factors robustly associated with severe COVID-19 were male sex (10 studies; pooled RR=1.73, [95%CI 1.50-2.01]), hypertension (8 studies; 2.87 [2.09-3.93]), diabetes (9 studies; 3.20 [2.26-4.53]), and CVD (10 studies; 4.97 [3.76-6.58]). RR for male sex was likely to be independent of age. For the other three factors, meta-regression analyses suggested confounding by age. Only four studies reported multivariable analysis, but most of them showed adjusted RR ∼2 for hypertension, diabetes, and CVD. No study explored renin-angiotensin system inhibitors as a risk factor for severe COVID-19.ConclusionsDespite the potential for confounding, these results suggest that hypertension, diabetes, and CVD are independently associated with severe COVID-19 and, together with age and male sex, can be used to inform objective decisions on COVID-19 testing, clinical management, and workforce planning.

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