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Record W3174033189 · doi:10.1371/journal.pone.0253894

Biomarkers of cytokine storm as red flags for severe and fatal COVID-19 cases: A living systematic review and meta-analysis

2021· review· en· W3174033189 on OpenAlexaboutno aff
Ana Karla Guedes de Melo, Keilla Machado Martins Milby, Ana Luíza Mendes Amorim Caparroz, Ana Carolina Pereira Nunes Pinto, Rodolfo Rodrigo Pereira Santos, Aline Pereira da Rocha, Gilda Aparecida Ferreira, Viviane Angelina de Souza, Lilian David Azevedo Valadares, Rejane Maria Rodrigues de Abreu Vieira, Gecilmara Salviato Pileggi, Virgínia Fernandes Moça Trevisani

Bibliographic record

VenuePLoS ONE · 2021
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProcalcitoninMeta-analysisInternal medicineCreatinineFerritinCochrane LibrarySepsis

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the laboratory parameters and biomarkers of the cytokine storm syndrome associated with severe and fatal COVID-19 cases. METHODS: A search with standardized descriptors and synonyms was performed on November 28th, 2020 of the MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, LILACS, and IBECS to identify studies of interest. Grey literature searches and snowballing techniques were additionally utilized to identify yet-unpublished works and related citations. Two review authors independently screened the retrieved titles and abstracts, selected eligible studies for inclusion, extracted data from the included studies, and then assessed the risk of bias using the Newcastle-Ottawa Scale. Eligible studies were those including laboratory parameters-including serum interleukin-6 levels-from mild, moderate, or severe COVID-19 cases. Laboratory parameters, such as interleukin-6, ferritin, hematology, C-Reactive Protein, procalcitonin, lactate dehydrogenase, aspartate aminotransferase, creatinine, and D-dimer, were extracted from the studies. Meta-analyses were conducted using the laboratory data to estimate mean differences with associated 95% confidence intervals. DATA SYNTHESIS: The database search yielded 9,620 records; 40 studies (containing a total of 9,542 patients) were included in the final analysis. Twenty-one studies (n = 4,313) assessed laboratory data related to severe COVID-19 cases, eighteen studies (n = 4,681) assessed predictors for fatal COVID-19 cases and one study (n = 548) assessed laboratory biomarkers related to severe and fatal COVID-19 cases. Lymphopenia, thrombocytopenia, and elevated levels of interleukin-6, ferritin, D-dimer, aspartate aminotransferase, C-Reactive-Protein, procalcitonin, creatinine, neutrophils and leucocytes were associated with severe and fatal COVID-19 cases. CONCLUSIONS: This review points to interleukin-6, ferritin, leukocytes, neutrophils, lymphocytes, platelets, C-Reactive Protein, procalcitonin, lactate dehydrogenase, aspartate aminotransferase, creatinine, and D-dimer as important biomarkers of cytokine storm syndrome. Elevated levels of interleukin-6 and hyperferritinemia should be considered as red flags of systemic inflammation and poor prognosis in COVID-19.

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

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.296
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.437
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.296
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0190.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.393
GPT teacher head0.480
Teacher spread0.087 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations157
Published2021
Admission routes1
Has abstractyes

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