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Record W6957789459 · doi:10.6084/m9.figshare.14850898

Additional file 1 of Frailty and pre-frailty in cardiac surgery: a systematic review and meta-analysis of 66,448 patients

2021· other· en· W6957789459 on OpenAlexaff

Bibliographic record

VenueFigshare · 2021
Typeother
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsUniversity of ManitobaUniversity of Toronto
Fundersnot available
KeywordsForest plotStandard deviationMean differenceFunnel plotMEDLINEMeta-analysis

Abstract

fetched live from OpenAlex

Additional file 1: Supplementary Fig. 1: MEDLINE and EMBASE were searched for all records until July 2018. Abstracts were reviewed for 1297 citations. 78 studies were retrieved for full text review and 19 studies met inclusion criteria following full article review. Supplementary Fig. 2: Forest Plot for age in frail vs non-frail patients undergoing primarily CABG and valve surgery. The pooled mean difference (MD) with 95% CI was calculated using random-effects models. To include Marshall et al. [15], which provided means but not standard deviations for age, we imputed the largest standard deviation from the other studies. Alternatively, excluding [15] does not significantly change the pooled result: MD + 2.33, 95%CI:+ 1.25 to + 3.41 years for Frail vs Not Frail, MD + 2.66, 95%CI:+ 1.85 to + 3.48 years for Frail+Pre-Frail vs Not Frail, and MD + 2.00, 95%CI:+ 1.74 to + 2.25 years for Pre-Frail vs Not Frail subgroups. Supplementary Fig. 3: Forest Plot for baseline and operative characteristics in frail vs non-frail patients undergoing primarily CABG and valve surgery (binary outcomes). The pooled risk ratios (RRs) with 95% CI were calculated using random-effects models. Supplementary Fig. 4: Forest Plot for baseline and operative characteristics in frail vs non-frail patients undergoing primarily CABG and valve surgery (continuous outcomes). The pooled mean differences (MDs) with 95% CI were calculated using random-effects models. To include Marshall et al. [15], which provided means but not standard deviations for age, log EuroSCORE, and EuroSCORE II, we imputed the largest standard deviation from the other studies. Alternatively, excluding [15] does not significantly change the pooled results: 1) Age – MD + 2.33, 95%CI:+ 1.25 to + 3.41, p < 0.0001, 14 studies, 14,321 v 41,901 patients; 2) log EuroSCORE (%) – MD + 3.68, 95%CI:–0.27 to + 7.62, p = 0.07, 3 studies, 112 v 430 patients; and 3) EuroSCORE II (%) – MD + 0.96, 95%CI:+ 0.61 to + 1.31, p < 0.00001, 3 studies, 152 v 350 patients. Supplementary Fig. 5: Forest Plot for stroke. Individual study and pooled unadjusted risk ratios (RRs) of frail vs non-frail patients undergoing primarily CABG and valve surgery. The pooled RRs with 95% CI were calculated using random-effects models. Sensitivity analysis – Risk of stroke higher if the study with the largest weighting is excluded [14]: RR 1.97, 95% CI 1.17–3.30, p = 0.01, I2 = 0%. Supplementary Fig. 6: Forest Plot showing differences in 1 year mortality results for each of the 6 different frailty measures used in Afilalo et al. [21]: unadjusted 1 year mortality (Top), 1 year mortality adjusted for comorbidities (Middle) and 1 year mortality adjusted for Society of Thoracic Surgery Predicted Risk of Mortality (STS PROM) (Bottom).

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)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.967
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9670.000

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 head0.062
GPT teacher head0.254
Teacher spread0.192 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

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