Risk Factors Associated With Mortality in Hypersensitivity Pneumonitis: A Meta-analysis

Abstract Purpose: Hypersensitivity pneumonitis (HP), an immune-mediated form of diffuse parenchymal lung disease (DPLD), is triggered by inhalation of a wide variety of allergens in susceptible individuals. Several studies suggest that the death rate associated with this disease has increased significantly in recent years. This meta-analysis investigates the significant clinico-radiological characteristics which may be appraised as potential risk factors associated with disease mortality.Methods: Extensive literature search was conducted for original articles published between January 2009 and April 2021 through PubMed, Google Scholar, EMBASE, and Cochrane Library using the keywords: “hypersensitivity pneumonitis”, “hazard ratio” and “mortality”. Results: A total of 21 independent studies related to mortality of HP subjects could be identified. The combined results of univariate and multivariate analysis suggest that older age [univariate odds ratio (OR) 1.038 (1.028-1.048); multivariate OR 1.036, (1.025-1.046)], male subjects [univariate OR 1.508, (1.240- 1.834); multivariate OR 1.396, (1.004-1.943)], honeycombing [univariate OR 1.086 (1.065- 1.108); multivariate OR 1.121 (1.070- 1.175)] and traction bronchiectasis [univariate OR 1.141 (1.092- 1.192); multivariate OR 1.107 (1.048-1.169)] are significantly associated with mortality risk of HP subjects. Further, forced vital capacity (FVC), diffusing capacity for carbon monoxide (DLco), ground glass opacity (GGO) and mosaic attenuation were associated with lower risk of all-cause mortality. Although smoking status correlated with mortality risk in these patients, the findings appeared to be insignificant. Conclusion: Individual male subjects with older age and presence of extensive fibrosis, i.e., honeycombing and traction bronchiectasis experience an increased mortality risk.

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Prevalence and risk factors associated with birth asphyxia among neonates delivered in Ethiopia: A systematic review and meta-analysis

PLoS ONE ◽

10.1371/journal.pone.0255488 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0255488

Author(s):

Ritbano Ahmed ◽

Hassen Mosa ◽

Mohammed Sultan ◽

Shamill Eanga Helill ◽

Biruk Assefa ◽

...

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Meta Analysis ◽

Grey Literature ◽

Birth Asphyxia ◽

Public Health Problem ◽

Cochrane Library ◽

Chronic Hypertension ◽

Factors Associated ◽

Pooled Prevalence

Background A number of primary studies in Ethiopia address the prevalence of birth asphyxia and the factors associated with it. However, variations were seen among those studies. The main aim of this systematic review and meta-analysis was carried out to estimate the pooled prevalence and explore the factors that contribute to birth asphyxia in Ethiopia. Methods Different search engines were used to search online databases. The databases include PubMed, HINARI, Cochrane Library and Google Scholar. Relevant grey literature was obtained through online searches. The funnel plot and Egger’s regression test were used to see publication bias, and the I-squared was applied to check the heterogeneity of the studies. Cross-sectional, case-control and cohort studies that were conducted in Ethiopia were also be included. The Joanna Briggs Institute checklist was used to assess the quality of the studies and was included in this systematic review. Data entry and statistical analysis were carried out using RevMan 5.4 software and Stata 14. Result After reviewing 1,125 studies, 26 studies fulfilling the inclusion criteria were included in the meta-analysis. The pooled prevalence of birth asphyxia in Ethiopia was 19.3%. In the Ethiopian context, the following risk factors were identified: Antepartum hemorrhage(OR: 4.7; 95% CI: 3.5, 6.1), premature rupture of membrane(OR: 4.0; 95% CI: 12.4, 6.6), primiparas(OR: 2.8; 95% CI: 1.9, 4.1), prolonged labor(OR: 4.2; 95% CI: 2.8, 6.6), maternal anaemia(OR: 5.1; 95% CI: 2.59, 9.94), low birth weight(OR = 5.6; 95%CI: 4.7,6.7), meconium stained amniotic fluid(OR: 5.6; 95% CI: 4.1, 7.5), abnormal presentation(OR = 5.7; 95% CI: 3.8, 8.3), preterm birth(OR = 4.1; 95% CI: 2.9, 5.8), residing in a rural area (OR: 2.7; 95% CI: 2.0, 3.5), caesarean delivery(OR = 4.4; 95% CI:3.1, 6.2), operative vaginal delivery(OR: 4.9; 95% CI: 3.5, 6.7), preeclampsia(OR = 3.9; 95% CI: 2.1, 7.4), tight nuchal cord OR: 3.43; 95% CI: 2.1, 5.6), chronic hypertension(OR = 2.5; 95% CI: 1.7, 3.8), and unable to write and read (OR = 4.2;95%CI: 1.7, 10.6). Conclusion According to the findings of this study, birth asphyxia is an unresolved public health problem in the Ethiopia. Therefore, the concerned body needs to pay attention to the above risk factors in order to decrease the country’s birth asphyxia. Review registration PROSPERO International prospective register of systematic reviews (CRD42020165283).

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Predictors of Post-Thrombotic Syndrome (PTS) in Pediatric Thrombosis: A Systematic Review and Meta-Analysis of the Literature

Blood ◽

10.1182/blood-2018-99-114999 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 3806-3806 ◽

Cited By ~ 1

Author(s):

Elissa Engel ◽

Manuela Albisetti ◽

Leonardo R. Brandao ◽

Ernest Amankwah ◽

Anthony Nguyen ◽

...

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Prognostic Factors ◽

Prognostic Factor ◽

Cohort Studies ◽

Meta Analysis ◽

Cochrane Library ◽

Factors Associated ◽

Post Thrombotic Syndrome ◽

Statistical Heterogeneity

Abstract BACKGROUND: Post-thrombotic syndrome (PTS) is the most common long-term complication in pediatric deep venous thrombosis (DVT), affecting approximately 25% of children with an extremity DVT. PTS leads to a high physical, psychological and financial burden in affected patients. Although several risk factors have been associated with the development of pediatric PTS, few of them have been validated in the pediatric literature. A better understanding of the prognostic factors leading to PTS is a vital step for early identification of those children at greatest risk in order to develop risk-stratified interventions aimed at preventing this complication. AIM: To perform a systematic review and meta-analysis of available published evidence from the pediatric literature on prognostic factors for pediatric PTS. METHODS: A systematic search of MEDLINE, EMBASE, and the Cochrane Library from 1960 to December 2017 was performed. MeSH terms and search strategy employed were as follows: "postthrombotic syndrome" OR "postphlebitic syndrome" AND "all child 0-18 years" AND "young adult 19-24 years". A study was eligible for inclusion if it evaluated the development of PTS in pediatric patients (<21 years of age) with a confirmed extremity DVT and reported on at least one prognostic factor for the development of PTS. Single case reports, narrative reviews, and commentaries were excluded. Studies assessing the efficacy/safety of thrombolysis, and studies including patients >21 years of age with outcomes not reported by age group, were also excluded. Two reviewers independently screened all studies and extracted the data of interest. Data were analyzed using STATA v.15 statistical software. Meta-analyses were conducted for risk factors reported in at least three studies. Summary odds ratios (ORs) and 95% confidence intervals (CI) were calculated from the effect estimates from the individual studies using a random effects model. Statistical heterogeneity was quantified by I2 statistic. RESULTS: A total of 12 studies met the final inclusion criteria (Figure 1), nine cohort studies, two cross-sectional studies, and one case-control study. These studies reported a total of 1,160 patients with venous thromboembolism (VTE), of whom 938 (81%) were assessed for PTS (Table 1). Median age across studies ranged from 0.02 - 15.5 years. VTE was considered provoked in nearly 80% of patients. The most common reported risk factor for VTE was the presence of a central venous catheter (CVC, 54%) followed by congenital heart disease (26%). PTS was diagnosed in 46% (n=434) of patients with an extremity DVT. The median time from DVT diagnosis to PTS diagnosis ranged from 12 to 33 months across studies. Among studies reporting this information, mild PTS was most frequently diagnosed, followed by moderate and severe PTS (35%, 5% and 0.6% of patients respectively). Most common prognostic factors associated with PTS in individual studies included patient characteristics: age and gender; and DVT characteristics: recurrent DVT, symptomatic DVT, DVT degree of occlusion, and time between DVT diagnosis and PTS assessment. Three studies investigated the association of elevated factor VIII and d-dimer levels with PTS. Elevated levels of these biomarkers were found to be associated with development of adverse VTE outcomes in one study but this finding was not confirmed in the other studies. Meta-analysis of reported prognostic factors identified the presence of a CVC and occlusive DVT as significant risk factors for the development of pediatric PTS (OR= 1.8, 95%CI=1.08-2.98, and OR=1.89, 95%CI=1.04-3.46 respectively; Figure 2). CONCLUSION: Among 12 studies evaluating prognostic factors for PTS in children and meeting criteria for this meta-analysis, CVC-related DVT and complete occlusion were associated with pediatric PTS. Overall, high-quality evidence on pediatric PTS is lacking. Collaborative prospective cohort studies and trials that use validated pediatric PTS measures and standardized prognostic factor definitions are needed to better understand the risk factors associated with PTS. Disclosures No relevant conflicts of interest to declare.

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Meta-analysis of risk factors associated with oxaliplatin hypersensitivity reactions in cancer patients

International Journal of Clinical Oncology ◽

10.1007/s10147-021-02034-3 ◽

2021 ◽

Author(s):

Linhui Zhu ◽

Huan Li ◽

Qiong Du ◽

Xuan Ye ◽

Sijia Yu ◽

...

Keyword(s):

Risk Factors ◽

Cancer Patients ◽

Protective Factor ◽

Meta Analysis ◽

Cochrane Library ◽

Hypersensitivity Reactions ◽

Factors Associated ◽

Free Interval ◽

Effect Model ◽

Exposure History

AbstractThis study aimed to investigate risk factors associated with oxaliplatin hypersensitivity reactions in cancer patients through a meta-analysis. A comprehensive retrieve of Chinese databases China National Knowledge Infrastructure, Wanfang Data, VIP Database and English databases PubMed, ScienceDirect, Embase and Cochrane library was conducted. The studies that meet the requirements for meta-analysis according to inclusion and exclusion criteria were screened and assessed for eligibility. Odds ratio (OR) / Weighted mean difference (WMD) and 95% confidence intervals (95% CIs) or calculable dichotomous and continuous raw data were extracted to perform meta-analysis using random effect model or fixed effect model on the basis of heterogeneity between studies through Review Manager 5.4 software. A total of 14 cross-sectional studies and 3367 cancer patients were included. Meta-analysis results showed that platinum exposure history (OR value 3.13, 95% CI 2.19–4.48, heterogeneity P = 0.26), allergy history (OR value 1.76, 95% CI 1.09–2.85, heterogeneity P = 0.61), platinum free interval (OR value 3.75, 95% CI 2.00–7.06, heterogeneity P = 0.83), dexamethasone premedication dose (OR value 0.28, 95% CI 0.13–0.58, heterogeneity P = 0.21) were significantly correlated to oxaliplatin hypersensitivity reactions. Gender, age, metastasis, combination with bevacizumab, XELOX regimen and cancer types were detected to have no statistically significant effect on oxaliplatin hypersensitivity reactions. Platinum exposure history, allergy history and long platinum-free interval are risk factors of oxaliplatin hypersensitivity reactions. High dexamethasone premedication dose is a protective factor of oxaliplatin hypersensitivity reactions.

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Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain

Critical Care ◽

10.1186/s13054-021-03487-8 ◽

2021 ◽

Vol 25 (1) ◽

Author(s):

Alejandro Rodríguez ◽

◽

Manuel Ruiz-Botella ◽

Ignacio Martín-Loeches ◽

María Jimenez Herrera ◽

...

Keyword(s):

Risk Factors ◽

Critically Ill ◽

Mortality Risk ◽

Critically Ill Patients ◽

Clustering Analysis ◽

Unsupervised Clustering ◽

Older Age ◽

Icu Mortality ◽

Factors Associated ◽

Clinical Phenotypes

Abstract Background The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. Methods Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 ICUs in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient’s factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. Results The database included a total of 2022 patients (mean age 64 [IQR 5–71] years, 1423 (70.4%) male, median APACHE II score (13 [IQR 10–17]) and SOFA score (5 [IQR 3–7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A (mild) phenotype (537; 26.7%) included older age (< 65 years), fewer abnormal laboratory values and less development of complications, B (moderate) phenotype (623, 30.8%) had similar characteristics of A phenotype but were more likely to present shock. The C (severe) phenotype was the most common (857; 42.5%) and was characterized by the interplay of older age (> 65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications. Conclusion The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice.

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Diabetes in Pakistan: A systematic review and meta-analysis

Pakistan Journal of Medical Sciences ◽

10.12669/pjms.35.4.194 ◽

2019 ◽

Vol 35 (4) ◽

Cited By ~ 3

Author(s):

Sohail Akhtar ◽

Jamal Abdul Nasir ◽

Tahir Abbas ◽

Aqsa Sarwar

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Family History ◽

Random Effects ◽

Meta Analysis ◽

Cochrane Library ◽

Random Effects Model ◽

Continuous Increase ◽

Family History Of Diabetes ◽

Factors Associated

Objective: The purpose of this study was assess the time trend of the prevalence of prediabetes and diabetes and risk factors associated with diabetes in Pakistan by using a systematic review and meta–analysis. Methods: A systematic literature search of Embase, PubMed, and the Cochrane library was carried out between January 1, 1995 and August 30, 2018. Diabetes and prediabetes prevalence estimates were combined by the random–effects model. The existence of publication bias was tested by Egger regression. This systematic review was reported following the PRISMA guidelines. Results: The search conceded a total of 635 studies, only 14 studies were considered for meta-analysis. The prevalence of diabetes in Pakistan was revealed 14.62% (10.651%–19.094%; 14 studies) based on 49,418 people using the inverse–variance random–effects model. The prevalence of prediabetes was 11.43% (8.26%–15.03%; 10 studies) based on a total sample of 26,999 people. The risk factors associated with diabetes were mean age (β = 0.48%, 95% CI: 0.21–0.78, p<0.001), the proportion of participants with a family history of diabetes (β = 0. 45%, 95% CI: 0.08–0.82, p =0.018, p<0.001), hypertension (β = 0.40%, 95% CI: 0.06–0.75, p = 0.022), weight (BMI) (β = 0.21%, 95% CI: 0.02–0.4, p=0.030). Conclusions: There has been a continuous increase in the prevalence of prediabetes and diabetes in Pakistan. All parts of the country have been affected, with the highest in Sindh and lowest in Khyber Pakhtunkhwa. The main factors include growing age, family history, hypertension and obesity. A nationwide diabetes care survey on risk factors and prevention policy is highly recommended. doi: https://doi.org/10.12669/pjms.35.4.194 How to cite this:Akhtar S, Nasir JA, Abbas T, Sarwar A. Diabetes in Pakistan: A systematic review and meta-analysis. Pak J Med Sci. 2019;35(4):---------. doi: https://doi.org/10.12669/pjms.35.4.194 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Risk Factors for Colonization and Infection With Resistant Pseudomonas Aeruginosa in Intensive Care Unit: Protocol for a Systematic Review and Meta-analysis

10.21203/rs.3.rs-287779/v1 ◽

2021 ◽

Author(s):

Serge Eyebe ◽

Hugues Nana-Djeunga ◽

Magellan Guewo-Fokeng ◽

Guy Sadeu Wafeu ◽

Marius Wouking ◽

...

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Intensive Care Unit ◽

Pseudomonas Aeruginosa ◽

Intensive Care ◽

Environmental Factors ◽

Meta Analysis ◽

Cochrane Library ◽

Prevalence Odds Ratio ◽

Factors Associated

Abstract Background: Infection with resistant Pseudomonas aeruginosa (RPA) in Intensive Care Unit (ICU) is known to be either endogenous or exogenous or both, but the roles of each of these contamination routes is yet to be clarified. Data regarding prevalence, risk factors and environmental factors associated with RPA in ICU are very scanty and even when they exist, they seem to be contradictory. So, there is a strong interest in understanding both individual and environmental factors associated with RPA infection. This systematic review aims to investigate individual and environmental factors associated with the colonization and infection with RPA in ICU.Methodology: MEDLINE (Pubmed), EMBASE (OVID), the Cochrane Library (Wiley), Web of Science, CINAHL (EBSCOHost) and LILACS (BIREME) will be searched from inception onwards. Grey literature will be identified through Google Scholar and open Grey. Two reviewers will independently screen all citations, abstracts and full-text articles. Potential conflicts will be resolved through discussion. Methodological quality including bias will be appraised using appropriate approaches. A narrative synthesis will describe quality and content of the epidemiological evidence. Prevalence, Odds ratio, Relative Risk, Hazard radio with their respective 95% confidence intervals will be calculated. A meta-analysis of data extracted from eligible studies with similar population and RPA testing will be performed. The analysis will evaluate factors influencing the estimates. A random effect model will be used to summarize effect sizes.Discussion: Two contrasting hypotheses on risk factors of acquisition, colonisation, and infection of RPA are being debated, especially in a context where available data are scanty or exhibit high discrepancy. Indeed, most of the reviews have been focalized on hospitalised patients, and not in ICU, and few of them really address the environmental factors issue. To fill that gap, this review will combine both analysis of individual and environmental risk factors using prevalence study in ICU and evaluation of different methodologies. These two hypotheses will be tested and challenged, and could serve as a basis for a more in-depth studies to fill the methodological gaps that will be identified as part of this current review.Systematic review registration: This protocol has been submitted registered with Prospective Register of Systematic Reviews (PROSPERO) on 07 march 2021 under number CRD42021233832

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Mortality risk factors of COVID-19 infection in kidney transplantation recipients: a systematic review and meta-analysis of cohorts and clinical registries

Scientific Reports ◽

10.1038/s41598-021-99713-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Suwasin Udomkarnjananun ◽

Stephen J. Kerr ◽

Natavudh Townamchai ◽

Paweena Susantitaphong ◽

Wasee Tulvatana ◽

...

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Kidney Transplantation ◽

Mortality Risk ◽

Case Reports ◽

Meta Analysis ◽

Factors Associated ◽

Presenting Symptoms ◽

Risk Of Death ◽

Published Evidence

AbstractKidney transplantation recipients (KTR) with coronavirus disease 2019 (COVID-19) are at higher risk of death than general population. However, mortality risk factors in KTR are still not clearly identified. Our objective was to systematically analyze published evidence for risk factors associated with mortality in COVID-19 KTR. Electronic databases were searched for eligible studies on 1 August 2021. All prospective and retrospective studies of COVID-19 in KTR were considered eligible without language restriction. Since data in case reports and series could potentially be subsets of larger studies, only studies with ≥ 50 patients were included. Random-effects model meta-analysis was used to calculate weighted mean difference (WMD) and pooled odds ratio (OR) of factors associated with mortality. From a total 1,137 articles retrieved, 13 were included in the systematic review and meta-analysis comprising 4,440 KTR. Compared with survivors, non-survivors were significantly older (WMD 10.5 years, 95% CI 9.3–11.8). KTR of deceased donor were at higher risk of death (OR 1.73, 95% CI 1.10–2.74). Comorbidities including diabetes mellitus, cardiovascular disease, and active cancer significantly increased mortality risk. KTR with dyspnea (OR 5.68, 95% CI 2.11–15.33) and pneumonia (OR 10.64, 95% CI 3.37–33.55) at presentation were at higher mortality risk, while diarrhea decreased the risk (OR 0.61, 95% CI 0.47–0.78). Acute kidney injury was associated with mortality (OR 3.24, 95% CI 1.36–7.70). Inflammatory markers were significantly higher in the non-survivors, including C-reactive protein, procalcitonin, and interleukine-6. A number of COVID-19 mortality risk factors were identified from KTR patient characteristics, presenting symptoms, and laboratory investigations. KTR with these risk factors should receive more intensive monitoring and early therapeutic interventions to optimize health outcomes.

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Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2,022 critically ill patients with COVID-19 in Spain

10.21203/rs.3.rs-125422/v2 ◽

2021 ◽

Author(s):

Alejandro Rodríguez ◽

Manuel Ruiz Botella ◽

Ignacio Matín-Loeches ◽

María Jiménez Herrera ◽

Jordi Solé-Violan ◽

...

Keyword(s):

Risk Factors ◽

Intensive Care ◽

Critically Ill ◽

Mortality Risk ◽

Critically Ill Patients ◽

Clustering Analysis ◽

Older Age ◽

Icu Mortality ◽

Factors Associated ◽

Clinical Phenotypes

Abstract Background: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. Methods: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 Intensive Care Units(ICU) in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient’s factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. Results: The database included a total of 2,022 patients (mean age 64[IQR5-71] years, 1423(70.4%) male, median APACHE II score (13[IQR10-17]) and SOFA score (5[IQR3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A(mild) phenotype (537;26.7%) included older age (<65 years), fewer abnormal laboratory values and less development of complications, B (moderate) phenotype (623,30.8%) had similar characteristics of A phenotype but were more likely to present shock. The C(severe) phenotype was the most common (857;42.5%) and was characterized by the interplay of older age (>65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications.Conclusion: The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice.

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Risk factors for mortality in patients with Coronavirus disease 2019 (COVID-19) infection: a systematic review and meta-analysis of observational studies

10.1101/2020.04.09.20056291 ◽

2020 ◽

Cited By ~ 3

Author(s):

Mohammad Parohan ◽

Sajad Yaghoubi ◽

Asal Seraji ◽

Mohammad Hassan Javanbakht ◽

Payam Sarraf ◽

...

Keyword(s):

Risk Factors ◽

Early Stage ◽

Meta Analysis ◽

Older Age ◽

Cochrane Library ◽

Chronic Obstructive ◽

Pool Data ◽

Obstructive Pulmonary Disease ◽

Risk Of Death ◽

Retrospective Cohort Studies

AbstractPurposeCoronavirus disease 2019 (COVID-19) is an emerging disease that was first reported in Wuhan city, the capital of Hubei province in China, and has subsequently spread worldwide. Risk factors for mortality have not been well summarized. Current meta-analysis of retrospective cohort studies was done to summarize available findings on the association between age, gender, comorbidities and risk of death from COVID-19 infection.MethodsOnline databases including Web of Science, PubMed, Scopus, Cochrane Library and Google scholar were searched to detect relevant publications up to 1 May 2020, using relevant keywords. To pool data, random-effects model was used. Furthermore, sensitivity analysis and publication bias test were also done.ResultsIn total, 14 studies with 29,909 COVID-19 infected patients and 1,445 cases of death were included in the current meta-analysis. Significant associations were found between older age (≥65 vs <65 years old) (pooled ORs=4.59, 95% CIs=2.61-8.04, p<0.001), gender (male vs female) (pooled ORs=1.50, 95% CIs=1.06-2.12, p=0.021) and risk of death from COVID-19 infection. In addition, hypertension (pooled ORs=2.70, 95% CIs= 1.40-5.24, p=0.003), cardiovascular diseases (CVDs) (pooled ORs=3.72, 95% CIs=1.77-7.83, p=0.001), diabetes (pooled ORs=2.41, 95% CIs=1.05-5.51, p=0.037), chronic obstructive pulmonary disease (COPD) (pooled ORs=3.53, 95% CIs=1.79-6.96, p<0.001) and cancer (pooled ORs=3.04, 95% CIs=1.80-5.14, p<0.001), were associated with higher risk of mortality.ConclusionOlder age (≥65 years old), male gender, hypertension, CVDs, diabetes, COPD and malignancies were associated with greater risk of death from COVID-19 infection. These findings could help clinicians to identify patients with poor prognosis at an early stage.

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Meta-analysis of risk factors associated with suicidal ideation after stroke

Annals of General Psychiatry ◽

10.1186/s12991-021-00378-8 ◽

2022 ◽

Vol 21 (1) ◽

Author(s):

Shuangmei Zhang ◽

Anrong Wang ◽

Weifeng Zhu ◽

Zhaoyang Qiu ◽

Zhaoxu Zhang

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Suicidal Ideation ◽

Sleep Disorders ◽

Family Income ◽

Meta Analysis ◽

Cochrane Library ◽

Future Research ◽

Factors Associated ◽

Complications Of Stroke

Abstract Background Over the past decade, increasing attention has been paid on post stroke suicide (PSS), which is one of complications of stroke. The rates of stroke and suicide are relatively high, especially in Asian populations. Thus, a deeper understanding of the prevalence and epidemiological impact of suicide after stroke is urgently needed. Clinical diagnosis and prevention of PSS are at the incipient stage, but the risk factors responsible for the occurrence of PSS in different regions and stages of the disease remain largely unknown. The present meta-analysis aimed to determine the incidence of PSS at different stages and time courses, and to identify the underlying risk factors for PSS. Methods We systematically searched the Cochrane library, Embase, PubMed, CNKI and Web of Science databases from their inception until April 2019.The research articles reporting on the risk factor for PSS were screened and included in the meta-analysis. The data from the included studies were extracted according to the predefined criteria. Results A total of 12 studies (n = 2,693,036) were included for meta-analyses. Of these studies, 7 reporting suicide prevalence were meta-analyzed. The pooled estimate of suicidal ideation rates after stroke was 12%, which could be influenced by multiple risk factors, including sex, smoking, depression, sleep disorders, previous stroke and low household income. Studies conducted in Asia demonstrated higher suicide prevalence (approximately 15%) compared to other regions. Smoking, low family income, depression, heart disease and sleep disorders were important risk factors for PSS. When compared to PSS of more than 1 year, the incidence of suicide within 1 year after stroke was more likely to be statistically significant. It was found that 4 out of every 1000 stroke survivors tended to commit suicide. The results of this meta-analysis showed that depression (OR = 2.32; p < 0.01) was significantly associated with suicidal ideation, regardless of stroke duration. Conclusion PSS is one of the common complications of stroke. Despite some limitations, we successfully identified the risk factors associated with suicidal ideation after stroke. Notably, depression was significantly associated with suicidal ideation, regardless of stroke duration. Targeting this risk factor may be helpful to improve stroke patient care and prevent suicidal ideation after stroke. Future research will be carried out to assess whether suicidal ideation or thoughts and actual suicide attempts are strongly predictive of suicide deaths after stroke (Registration No. CRD42019128813).

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