ArticleThe American journal of emergency medicine2021
Identifying and quantifying robust risk factors for mortality in critically ill patients with COVID-19 using quantile regression.
Article in The American journal of emergency medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04659876 (Clinical Characteristics and Laboratory Values Affecting Mortality in Critical Coronavirus Disease 2019 Patients Followed in the Intensive Care Unit), which is not on this map. Cited by 5 papers.
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The trial behind it
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Clinical Characteristics and Laboratory Values Affecting Mortality in Critical Coronavirus Disease 2019 Patients Followed in the Intensive Care Unit
Who cites it
5 citing papers in PubMed.
- The Mutual Relationship among Cardiovascular Diseases and COVID-19: Focus on Micronutrients Imbalance.Nutrients · 2022Review
- Performance evaluation of a point of care cartridge of the new GEM Premier ChemSTAT analyzer.Practical laboratory medicine · 2022Article
- Hypocalcemia in COVID-19: Prevalence, clinical significance and therapeutic implications.Reviews in endocrine & metabolic disorders · 2022Review
- Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse.Intensive care medicine experimental · 2021Article
- A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19.Frontiers in public health · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveMany laboratory indicators form a skewed distribution with outliers in critically ill patients with COVID-19, for which robust methods are needed to precisely determine and quantify fatality risk factors.
methodA total of 192 critically ill patients (142 were discharged and 50 died in the hospital) with COVID-19 were included in the sample. Quantile regression was used to determine discrepant laboratory indexes between survivors and non-survivors and quantile shift (QS) was used to quantify the difference. Logistic regression was then used to calculate the odds ratio (OR) and the predictive power of death for each risk indicator.
resultsAfter adjusting for multiple comparisons and controlling numerous confounders, quantile regression revealed that the laboratory indexes of non-survivors were significantly higher in C-reactive protein (CRP; QS = 0.835, p < .001), white blood cell counts (WBC; QS = 0.743, p < .001), glutamic oxaloacetic transaminase (AST; QS = 0.735, p < .001), blood glucose (BG; QS = 0.608, p = .059), fibrin degradation product (FDP; QS = 0.730, p = .080), and partial pressure of carbon dioxide (PCO
conclusionLaboratory indexes provided reliable information on mortality in critically ill patients with COVID-19, which might help improve clinical prediction and treatment at an early stage.
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