MétaCan
Menu
Back to cohort
Record W4386155147 · doi:10.1177/1721727x231197922

Efficacy of thymosin-α-1 in patients with COVID-19: A systematic review and meta-analysis

2023· review· en· W4386155147 on OpenAlex
Pu Wang, Changhong Wang, Da Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEuropean Journal of Inflammation · 2023
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCochrane LibraryMeta-analysisConfidence intervalInternal medicinePopulationRelative riskIncidence (geometry)Coronavirus disease 2019 (COVID-19)MEDLINEDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Objective To identify whether thymosin-α-1 (Tα1) is effective in patients with Coronavirus disease 2019 (COVID-19) and to determine a suitable population for Tα1 treatment. Methods We included studies with ≥10 cases and adults (aged ≥18 years) with laboratory-confirmed SARS-CoV-2 infection, data on mortality or length of hospitalization, disease severity, and study location, while excluded pregnant and breastfeeding women and minors. Publications were searched from November 1, 2019, to July 5, 2023, in six databases, including PubMed, Web of Science, Embase, Cochrane Library, China Knowledge Resource Integrated Database, and Wanfang Database. We separately utilized Newcastle-Ottawa Scale and Cochrane handbook methodology to evaluate risk of bias and used Review Manager (version 5.4, Cochrane Collaboration, Copenhagen, Denmark) to present and synthesize results. Relative risks (RR) and Standardized Mean Difference (SMD) with 95% confidence intervals (CI) were analyzed for dichotomous variables and continuous variables, respectively. Results Nine studies (participants = 5417) were included. No significant differences were found in mortality (nine studies; n = 5417; RR = 0.95; 95% CI: 0.56, −1.60; p = .84; I 2 = 90%) or length of hospitalization (four studies; n = 3688; SMD = 0.16; 95% CI: −0.38, −0.69; p = .57; I 2 = 96%) between patients with COVID-19 who did and did not receive Tα1. Participants were divided by the severity of the disease (serious and non-serious) and study location. Among the serious group, the incidence of death among patients who received Tα1 treatment was 0.67 times that of patients who did not receive Tα1 treatment (four studies; n = 1230; RR: 0.67; 95% CI: 0.58, −0.77; p < .00,001; I 2 = 0%). There was no significant difference in length of hospitalization between the groups (two studies; n = 410; SMD = 0.66; 95% CI: −0.06, −1.38; p = .07; I 2 = 87%). Among the non-serious group, compared to not having Tα1 treatment, receiving Tα1 treatment reduced hospitalization length (two studies; n = 3670; SMD = −0.28; 95% CI: −0.41, −0.14; p < .0001; I 2 = 51%), while no significant difference in mortality (three studies; n = 3775; RR = 1.06; 95% CI: 0.22, −5.03; p = .94; I 2 = 89%). Moreover, there was no significant difference between subgroups when divided by study locations (Studies within China: seven studies; n = 5263; RR = 1.14; 95% CI: 0.64, −2.04; p = .65; I 2 =92%; Studies outside of China: two studies; n = 154; RR = 0.41; 95% CI: 0.14, −1.24; p = .11; I 2 = 51%). Discussion For patients with serious types of COVID-19, Tα1 significantly decreased mortality, which supports the utilization of Tα1 in patients with severe and critical types of COVID-19. Moreover, regarding hospitalization length, patients with non-serious COVID-19 who used Tα1 reduced their hospitalization length compared to those that did not use Tα1. However, these results have high heterogeneity and limited generalizability.

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.

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)0.009
metaresearch head score (Gemma)0.081
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.753
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.081
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.174
GPT teacher head0.455
Teacher spread0.281 · 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