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Record W4379598809 · doi:10.7570/jomes22061

Association between Body Mass Index and Mortality in Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis

2023· review· en· W4379598809 on OpenAlexaboutno aff
Han Na Jung, Sehee Kim, Chang Hee Jung, Yun Kyung Cho

Bibliographic record

VenueJournal of Obesity & Metabolic Syndrome · 2023
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
FundersUniversity of UlsanKorean Society for the Study of Obesity
KeywordsUnderweightMedicineOverweightBody mass indexHazard ratioInternal medicineMeta-analysisObesityConfidence intervalDiabetes mellitusCochrane LibraryEndocrinology

Abstract

fetched live from OpenAlex

Background: The association between body mass index (BMI) and mortality in patients with type 1 diabetes mellitus (T1DM) has been poorly examined and has never been systematically reviewed. This meta-analysis investigated the all-cause mortality risk for each BMI category among patients with T1DM. Methods: ). The Newcastle-Ottawa Scale was used to assess the risk of bias. Results: Three prospective studies involving 23,407 adults were included. The underweight group was shown to have a 3.4 times greater risk of mortality than the normal-weight group (95% confidence interval [CI], 1.67 to 6.85). Meanwhile, there was no significant difference in mortality risk between the normal-weight group and the overweight group (HR, 0.90; 95% CI, 0.66 to 1.22) or the obese group (HR, 1.36; 95% CI, 0.86 to 2.15), possibly due to the heterogeneous results of these BMI categories among the included studies. Conclusion: Underweight patients with T1DM had a significantly greater risk of all-cause mortality than their normal-weight counterparts. Overweight and obese patients showed heterogeneous risks across the studies. Further prospective studies on patients with T1DM are required to establish weight management guidelines.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.581
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0180.002
Bibliometrics0.0010.003
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 head0.091
GPT teacher head0.379
Teacher spread0.287 · 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 designMeta-analysis
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

Citations11
Published2023
Admission routes1
Has abstractyes

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