Survival in adult inpatients with COVID-19

Murillo-Zamora, Efrén; Hernandez-Suarez, Carlos

doi:10.1016/j.puhe.2020.10.029

Cited by 44 publications

(45 citation statements)

References 17 publications

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“…Furthermore, the OS rates for days 7, 14, and 21 were obtained as 87.5%, 78.3%, and 52.2%, respectively, in the re-infected COVID-19 inpatients. These rates have been reported differently for COVID-19 patients in other studies (12,15,37). For example, Murillo-Zamora and Hernandez-Suarez found that 7-, 15-, 21-and 30-day OS rates were respectively 72.2%, 47.6%, 35.0%, and 23.9% which were lower than the results obtained in the current study (37).…”

Section: Discussioncontrasting

confidence: 90%

“…These rates have been reported differently for COVID-19 patients in other studies (12,15,37). For example, Murillo-Zamora and Hernandez-Suarez found that 7-, 15-, 21-and 30-day OS rates were respectively 72.2%, 47.6%, 35.0%, and 23.9% which were lower than the results obtained in the current study (37). In another study by Sousa et al, the 24-day OS rate in 2070 patients with COVID-19 was calculated as 87.7% (15).…”

Section: Discussionmentioning

confidence: 72%

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Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm

Ebrahimi

Sharifi

Mousavi‐Roknabadi

et al. 2021

Preprint

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Background: Narrowing a large set of features to a smaller one can improve our understanding of the main risk factors for in-hospital mortality in patients with COVID-19. This study aimed to derive a parsimonious model for predicting overall survival (OS) among re-infected COVID-19 patients using machine-learning (ML) algorithms.Methods: The retrospective data of 283 re-infected COVID-19 patients admitted to twenty-six medical centers (affiliated with Shiraz University of Medical Sciences) from 10 June to 26 December 2020 were reviewed and analyzed. An elastic-net regularized Cox proportional hazards (PH) regression and model approximation via backward elimination were utilized to optimize a predictive model of time to in-hospital death. Then, the model was reduced to its core features to maximize simplicity and generalizability.Results: The empirical in-hospital mortality rate among the re-infected COVID-19 patients was obtained as 9.5%. In addition, the mortality rate among the intubated patients was 83.5%. Using the Kaplan-Meier approach, the OS (95% CI) rates for days 7, 14, and 21 were 87.5% (81.6-91.6%), 78.3% (65.0-87.0%), and 52.2% (20.3-76.7%), respectively. The elastic-net Cox PH regression retained 8 out of 35 candidate features of death. Transfer by Emergency Medical Services (EMS) (HR=3.90, 95% CI: 1.63-9.48), SpO2≤85% (HR=8.10, 95% CI: 2.97-22.00), increased serum creatinine (HR=1.85, 95% CI: 1.48-2.30), and increased white blood cells (WBC) count (HR=1.10, 95% CI: 1.03-1.15) were associated with higher in-hospital mortality rates in the re-infected COVID-19 patients.Conclusion: The results of the ML analysis demonstrated that transfer by EMS, profound hypoxemia (SpO2≤85%), increased serum creatinine (more than 1.6 mg/dL), and increased WBC count (more than 8.5 (×109 cells/L)) reduced the OS of the re-infected COVID-19 patients.

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Section: Discussioncontrasting

confidence: 90%

Section: Discussionmentioning

confidence: 72%

Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm

Ebrahimi

Sharifi

Mousavi‐Roknabadi

et al. 2021

Preprint

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“…The two sensitivity analyses showed similar results to the main analysis (OR = 1.23, 95% CI: 1.10-1.38 and OR = 1.23, 95% CI = 1.09-1.39). In addition to the 11 studies that reported diabetes of any type and were included in the meta-analysis, the study by Murillo-Zamora et al [ 28 ] reported a similar estimate for type-2 diabetes (OR = 1.47, 95% = 1.21-1.56).…”

Section: Resultsmentioning

confidence: 98%

Risk factors for poor outcomes in hospitalised COVID-19 patients: A systematic review and meta-analysis

Ashcroft

Chung

et al. 2021

J Glob Health

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Background Understanding the risk factors for poor outcomes among COVID-19 patients could help identify vulnerable populations who would need prioritisation in prevention and treatment for COVID-19. We aimed to critically appraise and synthesise published evidence on the risk factors for poor outcomes in hospitalised COVID-19 patients. Methods We searched PubMed, medRxiv and the WHO COVID-19 literature database for studies that reported characteristics of COVID-19 patients who required hospitalisation. We included studies published between January and May 2020 that reported adjusted effect size of any demographic and/or clinical factors for any of the three poor outcomes: mortality, intensive care unit (ICU) admission, and invasive mechanical ventilation. We appraised the quality of the included studies using Joanna Briggs Institute appraisal tools and quantitatively synthesised the evidence through a series of random-effect meta-analyses. To aid data interpretation, we further developed an interpretation framework that indicated strength of the evidence, informed by both quantity and quality of the evidence. Results We included a total of 40 studies in our review. Most of the included studies (29/40, 73%) were assessed as “good quality”, with assessment scores of 80 or more. We found that male sex (pooled odds ratio (OR) = 1.32 (95% confidence interval (CI) = 1.18-1.48; 20 studies), older age (OR = 1.05, 95% CI = 1.04-1.07, per one year of age increase; 10 studies), obesity (OR = 1.59, 95% CI = 1.02-2.48; 4 studies), diabetes (OR = 1.25, 95% CI = 1.11-1.40; 11 studies) and chronic kidney diseases (6 studies; OR = 1.57, 95% CI = 1.27-1.93) were associated with increased risks for mortality with the greatest strength of evidence based on our interpretation framework. We did not find increased risk of mortality for several factors including chronic obstructive pulmonary diseases (5 studies), cancer (4 studies), or current smoker (5 studies); however, this does not indicate absence of risk due to limited data on each of these factors. Conclusion Male sex, older age, obesity, diabetes and chronic kidney diseases are important risk factors of COVID-19 poor outcomes. Our review provides not only an appraisal and synthesis of evidence on the risk factors of COVID-19 poor outcomes, but also a data interpretation framework that could be adopted by relevant future research.

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“…A total of 1595 studies were screened; only thirty observational studies met the final inclusion criteria in the analysis ( Figure 1 ; Table A1 ) [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ]. Main study characteristics of COPD and asthma analysis cohorts are abridged in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

Assessment of the Association of COPD and Asthma with In-Hospital Mortality in Patients with COVID-19. A Systematic Review, Meta-Analysis, and Meta-Regression Analysis

Reyes

Hache-Marliere

Karamanis

et al. 2021

JCM

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Together, chronic obstructive pulmonary disease (COPD) and asthma account for the most common non-infectious respiratory pathologies. Conflicting preliminary studies have shown varied effect for COPD and asthma as prognostic factors for mortality in coronavirus disease 2019 (COVID-19). The aim of this study was to explore the association of COPD and asthma with in-hospital mortality in patients with COVID-19 by systematically reviewing and synthesizing with a meta-analysis the available observational studies. MEDLINE, Scopus, and medRxiv databases were reviewed. A random-effects model meta-analysis was used, and I-square was utilized to assess for heterogeneity. In-hospital mortality was defined as the primary endpoint. Sensitivity and meta-regression analyses were performed. Thirty studies with 21,309 patients were included in this meta-analysis (1465 with COPD and 633 with asthma). Hospitalized COVID-19 patients with COPD had higher risk of death compared to those without COPD (OR: 2.29; 95% CI: 1.79–2.93; I2 59.6%). No significant difference in in-hospital mortality was seen in patients with and without asthma (OR: 0.87; 95% CI: 0.68–1.10; I2 0.0%). The likelihood of death was significantly higher in patients with COPD that were hospitalized with COVID-19 compared to patients without COPD. Further studies are needed to assess whether this association is independent or not. No significant difference was demonstrated in COVID-19-related mortality between patients with and without asthma.

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Survival in adult inpatients with COVID-19

Cited by 44 publications

References 17 publications

Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm

Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm

Risk factors for poor outcomes in hospitalised COVID-19 patients: A systematic review and meta-analysis

Assessment of the Association of COPD and Asthma with In-Hospital Mortality in Patients with COVID-19. A Systematic Review, Meta-Analysis, and Meta-Regression Analysis

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