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Record W3216343066 · doi:10.1111/ppe.12831

The association between late preterm birth and cardiometabolic conditions across the life course: A systematic review and meta‐analysis

2021· review· en· W3216343066 on OpenAlexafffundabout
Yulika Yoshida‐Montezuma, Erica Stone, Saman Iftikhar, Vanessa De Rubeis, Alessandra T. Andreacchi, Charles Keown‐Stoneman, Lawrence Mbuagbaw, Hilary K. Brown, Russell J. de Souza, Laura N. Anderson

Bibliographic record

VenuePaediatric and Perinatal Epidemiology · 2021
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationPopulation Health Research InstituteSt. Michael's HospitalHospital for Sick ChildrenThe Scarborough HospitalSt. Joseph’s Healthcare HamiltonPublic Health OntarioHamilton Health SciencesUniversity of TorontoImpactWomen's College HospitalMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMedicineHazard ratioConfidence intervalOdds ratioBody mass indexRelative riskMeta-analysisGestational diabetesIncidence (geometry)Gestational ageInternal medicineObstetricsPregnancyGestation

Abstract

fetched live from OpenAlex

Abstract Background The effect of being born late preterm (34–36 weeks gestation) on cardiometabolic outcomes across the life course is unclear. Objectives To systematically review the association between being born late preterm (spontaneous or indicated), compared to the term and cardiometabolic outcomes in children and adults. Data sources EMBASE(Ovid), MEDLINE(Ovid), CINAHL. Study selection and data extraction Observational studies up to July 2021 were included. Study characteristics, gestational age, cardiometabolic outcomes, risk ratios (RRs), odds ratios (ORs), hazard ratios (HRs), mean differences and 95% confidence intervals (CIs) were extracted. Synthesis We pooled converted RRs using random‐effects meta‐analyses for diabetes, hypertension, ischemic heart disease (IHD) and body mass index (BMI) with subgroups for children and adults. The risk of bias was assessed using the Newcastle‐Ottawa scale and certainty of the evidence was assessed using the grading of recommendations, assessment, development and evaluation (GRADE) approach. Results Forty‐one studies were included (41,203,468 total participants; median: 5.0% late preterm). Late preterm birth was associated with increased diabetes (RR 1.24, 95% CI 1.17, 1.32; nine studies; n = 6,056,511; incidence 0.9%; I2 51%; low certainty) and hypertension (RR 1.21, 95% CI 1.13, 1.30; 11 studies; n = 3,983,141; incidence 3.4%; I2 64%; low certainty) in children and adults combined. Late preterm birth was associated with decreased BMI z‐scores in children (standard mean difference −0.38; 95% CI −0.67, −0.09; five studies; n = 32,602; proportion late preterm 8.3%; I2 96%; very low certainty). There was insufficient evidence that late preterm birth was associated with increased IHD risk in adults (HR 1.20, 95% CI 0.89, 1.62; four studies; n = 2,706,806; incidence 0.3%; I2 87%; very low certainty). Conclusions Late preterm birth was associated with an increased risk of diabetes and hypertension. The certainty of the evidence was low or very low. Inconsistencies in late preterm and term definitions, confounding variables and outcome age limited the comparability of studies.

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 imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.040
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0190.027
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.083
GPT teacher head0.411
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations31
Published2021
Admission routes3
Has abstractyes

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