MétaCan
Menu
Back to cohort
Record W4385827345 · doi:10.1111/ppe.13002

Small for gestational age preterm infants and later adiposity and height: A systematic review and meta‐analysis

2023· review· en· W4385827345 on OpenAlexaff
Seham Elmrayed, Jahaira Pinto, Suzanne Tough, Sheila McDonald, Natalie V. Scime, Krista Wollny, Yoonshin Lee, Michael S. Kramer, Maria B. Ospina, Diane Lorenzetti, Ada Madubueze, Alexander A. C. Leung, Manoj Kumar, Tanis R. Fenton

Bibliographic record

VenuePaediatric and Perinatal Epidemiology · 2023
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of AlbertaQueen's UniversityUniversity of CalgaryMcGill UniversityPositive Living Society of British ColumbiaLibin Cardiovascular Institute of AlbertaAlberta Children's Hospital
Fundersnot available
KeywordsMedicineOverweightSmall for gestational ageBody mass indexMeta-analysisGestational ageBirth weightObesityPediatricsObstetricsAnthropometryWaistCINAHLPregnancyInternal medicinePsychological intervention

Abstract

fetched live from OpenAlex

Abstract Background Overweight and obesity and their consequent morbidities are important worldwide health problems. Some research suggests excess adiposity origins may begin in fetal life, but unknown is whether this applies to infants born preterm. Objective The objective of the study was to assess the association between small for gestational age (SGA) birth and later adiposity and height among those born preterm. Data sources MEDLINE, EMBASE and CINAHL until October 2022. Study selection and data extraction Studies were included if they reported anthropometric (adiposity measures and height) outcomes for participants born preterm with SGA versus non‐SGA. Screening, data extraction and risks of bias assessments were conducted in duplicate by two reviewers. Synthesis We meta‐analysed across studies using random‐effects models and explored potential heterogeneity sources. Results Thirty‐nine studies met the inclusion criteria. In later life, preterm SGA infants had a lower body mass index (−0.66 kg/m2, 95% CI −0.79, −0.53; 32 studies, I2 = 16.7, n = 30,346), waist circumference (−1.20 cm, 95% CI −2.17, −0.23; 13 studies, I2 = 19.4, n = 2061), lean mass (−2.62 kg, 95% CI −3.45, 1.80; 7 studies, I2 = 0, n = 205) and height (−3.85 cm, 95% CI −4.73, −2.96; 26 studies, I2 = 52.6, n = 4174) compared with those preterm infants born non‐SGA. There were no differences between preterm SGA and preterm non‐SGA groups in waist/hip ratio, body fat, body fat per cent, truncal fat per cent, fat mass index or lean mass index, although power was limited for some analyses. Studies were rated at high risk of bias due to potential residual confounding and low risk of bias in other domains. Conclusions Compared to their preterm non‐SGA peers, preterm infants born SGA have lower BMI, waist circumference, lean body mass and height in later life. No differences in adiposity were observed between SGA preterm infants and non‐SGA preterm infants.

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)0.011
metaresearch head score (Gemma)0.032
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 score0.020
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.032
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.030
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.185
GPT teacher head0.400
Teacher spread0.215 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePaediatric and Perinatal EpidemiologySame topicBirth, Development, and HealthFrench-language works237,207