Additional file 1 of Frailty and pre-frailty in cardiac surgery: a systematic review and meta-analysis of 66,448 patients
Bibliographic record
Abstract
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 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 | 0.003 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.715 | 0.031 |
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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".