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Record W2981112842 · doi:10.1097/md.0000000000017513

The association between weight fluctuation and all-cause mortality

2019· review· en· W2981112842 on OpenAlexaboutno aff
Yan Zhang, Fangfang Hou, Jiexue Li, Haiying Yu, Li Lu, Shilian Hu, Guodong Shen, Hiroshi Yatsuya

Bibliographic record

VenueMedicine · 2019
Typereview
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
FundersAnhui Medical University
KeywordsMedicineMeta-analysisConfidence intervalPublication biasHazard ratioObservational studyDemographyRandom effects modelRelative riskInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Many observational studies have reported an association between weight fluctuation and all-cause mortality. However, the conclusions obtained from these studies have been unclear. OBJECTIVE: The current meta-analysis aimed to clarify the association between weight fluctuation and all-cause mortality. DATA SOURCE: We electronically searched PubMed, Embase, and Web of Science for articles reporting an association between weight fluctuation and all-cause mortality that were published before April 30, 2018. STUDY APPRAISAL AND SYNTHESIS METHODS: The methodological quality of each study was appraised using the modified Newcastle Ottawa Quality Assessment Scale. The hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were extracted from the included studies and pooled using random-effect models. Meta-regression approaches were also performed to explore sources of between-study heterogeneity. RESULTS: A total of 15 studies were eligible for the current meta-analysis. The pooled overall HR for all-cause mortality in the group with the greatest weight fluctuations compared with the most stable weight category was 1.45 (95% CI: 1.29-1.63). Considerable between-study heterogeneity was observed, some of which was partially explained by the different follow-up durations used by the included studies. Moreover, publication bias that inflated the risk of all-cause mortality was detected using Egger's test (P = .001). CONCLUSION: Weight fluctuation might be associated with an increased risk of all-cause mortality.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.202
GPT teacher head0.478
Teacher spread0.277 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations21
Published2019
Admission routes1
Has abstractyes

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