Clinical predictors of COVID-19 mortality

Yadaw, Arjun Singh; Li, Yan-chak; Bose, Sonali; Iyengar, Ravi; Bunyavanich, Supinda; Pandey, Gaurav

doi:10.1101/2020.05.19.20103036

Cited by 43 publications

(44 citation statements)

References 28 publications

(25 reference statements)

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“…Low oxygen saturation (SatO 2 <90%) at admission was also a risk factor for death. This has also been observed in other studies, with small variations in the cutoff point [ 34 , 35 ]. In New York, SatO2 less than 92% was associated with an increased risk of hospital lethality [ 36 ].…”

Section: Discussionsupporting

confidence: 88%

Phase 2 randomized study on chloroquine, hydroxychloroquine or ivermectin in hospitalized patients with severe manifestations of SARS-CoV-2 infection

Galan

Santos

Asato

et al. 2021

Pathogens and Global Health

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Objective : Given the urgent need for strategies to minimize the damage caused by this pandemic, this study performed a randomized, double-blind phase 2 study to assess the safety of the effectiveness of chloroquine (CQ), hydroxychloroquine (HCQ) or ivermectin in severe forms of COVID-19, in addition to identifying predictors of mortality in this group of patients. Methods : Phase 2, double-blind, randomized study to assess the safety and efficacy of enteral CQ, HCQ or ivermectin in patients hospitalized for SARS-CoV-2 infection, admitted to a Reference Hospital in Roraima (Brazil) in may 2020. Patients were randomized in a 1:1:1 ratio. The endpoints were need of supplemental O 2 , invasive ventilation, admission in ICU and death. The study was approved by an independent IRB. Results : 168 patients were randomized. The mean age was 53.4 years (±15.6), most participants were male ( n = 95; 58.2%). Therapy with corticosteroid, anticoagulant or antibiotics was a decision of the attending physicians, and there was no difference between the groups. The mortality was similar in three groups (22.2%; 21.3% and 23.0%) suggesting ineffectiveness of the drugs. No difference in the incidence of serious adverse events were observed. To be older than 60 years of age, obesity, diabetes, extensive pulmonary involvement and low SaO 2 at hospital admission due to independent risk factors for mortality. Conclusion : Although CQ, HCQ or ivermectin revealed a favorable safety profile, the tested drugs do not reduce the need for supplemental oxygen, ICU admission, invasive ventilation or death, in patients hospitalized with a severe form of COVID-19.

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Section: Discussionsupporting

confidence: 88%

Phase 2 randomized study on chloroquine, hydroxychloroquine or ivermectin in hospitalized patients with severe manifestations of SARS-CoV-2 infection

Galan

Santos

Asato

et al. 2021

Pathogens and Global Health

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“…The flow of studies through our meta-analysis is depicted in Figure 1 . A total of 76 studies with 31,067 patients were eventually included in our study ( 8 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 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 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , ...…”

Section: Resultsmentioning

confidence: 99%

Diabetes Mellitus is Associated with Severe Infection and Mortality in Patients with COVID-19: A Systematic Review and Meta-analysis

Shang

Shao

Guo

et al. 2020

Archives of Medical Research

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Background and Aim Currently, the number of patients with coronavirus disease 2019 (COVID-19) infection is increasing rapidly worldwide. In this study, we aimed to assess whether diabetes mellitus (DM) would increase the risk of severe infection and death in patients with COVID-19. Methods We systematically searched the PubMed, Web of Science, MedRxiv and COVID-19 academic research communication platform for studies reporting clinical severity and/or overall mortality data on DM in patients with COVID-19 published up to July 10, 2020. The primary outcome was to compare the severe infection rate and mortality rate in COVID-19 patients with and without DM, and to calculate the odds ratio ( OR ) and 95% confidence interval (CI). Results A total of 76 studies involving 31,067 patients with COVID-19 were included in our meta-analysis. COVID-19 patients with DM had higher severe infection and case-mortality rates compared with those without DM (21.4 vs. 10.6% and 28.5 vs. 13.3%, respectively, all p <0.01). COVID-19 patients with DM were at significantly elevated risk of severe infection ( OR = 2.38, 95% CI: 2.05–2.78, p <0.001) and mortality ( OR = 2.21, 95% CI: 1.83–2.66, p <0.001). Conclusion DM is associated with increased risk of severe infection and higher mortality in patients with COVID-19. Our study suggests that clinicians should pay more attention to the monitoring and treatment of COVID-19 patients with DM.

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“…Several studies have reported risk factors associated with death in patients with COVID-19, although very few propose reliable prediction models, which should be constructed using an adequate sample size and a standardized methodology to avoid significant bias [ 5 , 11 , 12 , 13 , 14 ].…”

Section: Discussionmentioning

confidence: 99%

The PANDEMYC Score. An Easily Applicable and Interpretable Model for Predicting Mortality Associated With COVID-19

Torres‐Macho

Ryan

Valencia

et al. 2020

JCM

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This study aimed to build an easily applicable prognostic model based on routine clinical, radiological, and laboratory data available at admission, to predict mortality in coronavirus 19 disease (COVID-19) hospitalized patients. Methods: We retrospectively collected clinical information from 1968 patients admitted to a hospital. We built a predictive score based on a logistic regression model in which explicative variables were discretized using classification trees that facilitated the identification of the optimal sections in order to predict inpatient mortality in patients admitted with COVID-19. These sections were translated into a score indicating the probability of a patient’s death, thus making the results easy to interpret. Results. Median age was 67 years, 1104 patients (56.4%) were male, and 325 (16.5%) died during hospitalization. Our final model identified nine key features: age, oxygen saturation, smoking, serum creatinine, lymphocytes, hemoglobin, platelets, C-reactive protein, and sodium at admission. The discrimination of the model was excellent in the training, validation, and test samples (AUC: 0.865, 0.808, and 0.883, respectively). We constructed a prognostic scale to determine the probability of death associated with each score. Conclusions: We designed an easily applicable predictive model for early identification of patients at high risk of death due to COVID-19 during hospitalization.

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Clinical predictors of COVID-19 mortality

Cited by 43 publications

References 28 publications

Phase 2 randomized study on chloroquine, hydroxychloroquine or ivermectin in hospitalized patients with severe manifestations of SARS-CoV-2 infection

Phase 2 randomized study on chloroquine, hydroxychloroquine or ivermectin in hospitalized patients with severe manifestations of SARS-CoV-2 infection

Diabetes Mellitus is Associated with Severe Infection and Mortality in Patients with COVID-19: A Systematic Review and Meta-analysis

The PANDEMYC Score. An Easily Applicable and Interpretable Model for Predicting Mortality Associated With COVID-19

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