Coronavirus Disease 2019 as Cause of Viral Sepsis: A Systematic Review and Meta-Analysis*
Bibliographic record
Abstract
ABSTRACT Importance COVID-19 is a heterogenous disease most frequently causing respiratory tract infection but in its severe forms, respiratory failure and multiple organ dysfunction syndrome may occur, resembling sepsis. The prevalence of viral sepsis among COVID-19 patients is still unclear. Objective We aimed to describe this in a systematic review. Data sources MEDLINE(PubMed), Cochrane and Google Scholar databases were searched for studies reporting on patients hospitalized with confirmed COVID-19, diagnosed with sepsis or infection-related organ dysfunctions or receiving organ replacement therapy. Study selection Eligible were full-text English articles of randomized and non-randomized clinical trials and observational studies reporting on patients with confirmed COVID-19, who are diagnosed with sepsis or have infection-related organ dysfunctions. Systematic reviews, editorials, conference abstracts, animal studies, case reports, articles neither in English nor full-text, and studies with fewer than 30 participants were excluded. Data extraction and synthesis All eligible studies were included in a narrative synthesis of results and after reviewing all included studies a meta-analysis was conducted. Separate sensitivity analyses were conducted per adult vs pediatric populations and per Intensive Care Unit (ICU) vs non-ICU populations. Main outcomes and measures Primary endpoint was the prevalence of sepsis using Sepsis-3 criteria among patients with COVID-19 and among secondary, new onset of infection-related organ dysfunction. Outcomes were expressed as proportions with respective 95% confidence interval (CI). Results Of 1,903 articles, 104 were analyzed. The prevalence of sepsis in COVID-19 was 39.9% (95% CI, 35.9-44.1; I 2 , 99%). In sensitivity analysis, sepsis was present in 25.1% (95% CI, 21.8-28.9; I 2 99%) of adult patients hospitalized in non-Intensive-Care-Unit (ICU) wards (40 studies) and in 83.8 (95% CI, 78.1-88.2; I 2 ,91%) of adult patients hospitalized in the ICU (31 studies). Sepsis in children hospitalized with COVID-19 was as high as 7.8% (95% CI, 0.4-64.9; I 2 , 97%). Acute Respiratory Distress Syndrome was the most common organ dysfunction in adult patients in non-ICU (27.6; 95% CI, 21.6-34.5; I 2 , 99%) and ICU (88.3%; 95% CI, 79.7-93.5; I 2 , 97%) Conclusions and relevance Despite the high heterogeneity in reported results, sepsis frequently complicates COVID-19 among hospitalized patients and is significantly higher among those in the ICU. PROSPERO registration number: CRD42020202018. No funding. KEY POINTS Question What is the prevalence of viral sepsis by Sepsis-3 definition among hospitalized patients with COVID-19? Findings In this systematic review and meta-analysis, we systematically reviewed published literature for evidence of organ failure in COVID-19, to estimate the prevalence of viral sepsis in this setting, by means of SOFA score calculation. The prevalence of sepsis in COVID-19 was 39.9% (95% CI, 35.9-44.1; I 2 , 99%). Meaning This is the first study to address the burden of viral sepsis in hospitalized patients with COVID-19, a highly heterogenous infection ranging from asymptomatic cases to severe disease leading to death, as reflected in the high heterogeneity of this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| grok | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| opus | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | medium |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".