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Record W2098415311 · doi:10.1111/dmcn.12456

Contribution of socio‐economic status on the prevalence of cerebral palsy: a systematic search and review

2014· review· en· W2098415311 on OpenAlexaff
Myrill Solaski, Annette Majnemer, Maryam Oskoui

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2014
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsConfoundingCerebral palsySocioeconomic statusMedicineMeta-analysisDemographyGestational ageSystematic reviewMEDLINEPediatricsPregnancyEnvironmental healthPopulationPsychiatryBiology

Abstract

fetched live from OpenAlex

AIM: The association between socio-economic status (SES) and cerebral palsy (CP) remains controversial. Preterm birth, low birthweight, and postnatal injuries are accepted mediating risk factors for CP, but the question remains whether SES confers additional risk. The aim of this study was to analyse existing knowledge on the relationship between SES and the risk of CP. METHOD: We conducted a systematic search and review of potentially relevant research relating to SES and CP published from 1980 to 2012. Heterogeneity between studies did not allow for data aggregation or meta-analysis; therefore, a narrative review was used to summarize the findings. RESULTS: Twelve studies were included in the systematic review. Of these, eight found low SES to be a risk factor for increased CP prevalence. Three studies detected statistically significant associations even after controlling for birthweight and gestational age as variables. Two of these studies also accounted for additional confounding variables (multiple births and timing of CP acquisition) and continued to detect contributory effects of SES. Linear negative correlations between CP prevalence and SES were shown by three studies. INTERPRETATION: Evidence suggests that the effect of SES on CP prevalence goes beyond that of the mediating factors preterm birth, low birthweight, and postnatal trauma. These associations were seen in area-based and, to a lesser extent, individual measures of SES. A better understanding of mediating factors is imperative in developing targeted public health intervention programmes to reduce the prevalence of CP.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.312
Teacher spread0.282 · 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 designSystematic review
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

Citations72
Published2014
Admission routes1
Has abstractyes

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