Non-thyroidal illness syndrome and the prognosis of heart failure: a systematic review and meta-analysis
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.
Bibliographic record
Abstract
Background: Heart failure (HF) is a complex and multifactorial syndrome caused by impaired heart function. The high morbidity and mortality of HF cause a heavy burden of illness worldwide. Non-thyroidal illness syndrome (NTIS) refers to aberrant serum thyroid parameters in patients without past thyroid disease. Observational studies have indicated that NTIS is associated with a higher risk of all-cause mortality in HF. This meta-analysis aimed to investigate the association between NTIS and HF prognosis. Methods: Medline, Embase, Web of Science, and the Cochrane database were searched for any studies reporting an association between NTIS and HF prognosis from inception to 1 July 2022. A meta-analysis was then performed. The quality of studies was assessed using the Newcastle-Ottawa Scale. The heterogeneity of the results was assessed with I2 and Cochran's Q statistics. Sensitivity analysis and publication bias analysis were also conducted. Results: A total of 626 studies were retrieved, and 18 studies were finally included in the meta-analysis. The results showed that NTIS in HF patients was significantly associated with an increased risk of all-cause mortality and major cardiovascular events (MACE), but not with in-hospital mortality. The stability of the data was validated by the sensitivity analysis. There was no indication of a publication bias in the pooled results for all-cause mortality and MACE. Conclusions: This meta-analysis showed that NTIS was associated with a worse outcome in HF patients. However, the association between NTIS and in-hospital mortality of HF patients requires further investigation.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it