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Record W4402889600 · doi:10.1097/jpn.0000000000000805

Risk Factors for Neonatal Clavicular Fractures

2024· article· en· W4402889600 on OpenAlexaff
Assaf Kadar, Noga Yaniv, Tal Frenkel Rutenberg, ‪Adi Turjeman‬‏, Shai Shemesh, Eliezer Sidon, Matan J. Cohen

Bibliographic record

VenueThe Journal of Perinatal & Neonatal Nursing · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineObstetricsBirth weightBody mass indexPopulationPregnancyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Neonatal clavicular fractures represent the most common fracture during delivery. We aimed to define risk factors associated with these fractures in a large population-based database. METHODS: Data were extracted from Clalit Health Services' electronic health records from 2000 to 2020. Newborns with clavicular fractures were compared with a healthy control group. The following parameters were compared-for the newborns: sex, birth weight, birth height, and head circumference; for the delivery process: assisted delivery, cesarean section, use of epidural, birth week, and number of fetuses; and for the mother: age at delivery, socioeconomic status, height, weight, and body mass index (BMI). RESULTS: We found a rate of 0.28% for neonatal clavicular fractures (5015 clavicular fractures/1 755 660 deliveries). Male gender and heavier birth weight were found to be significantly associated with clavicular fractures ( P < .001). Increased risk was also associated with lower socioeconomic status, baseline weight, and maternal BMI ( P < .001 for all). Assisted delivery increased the risk of clavicular fracture (OR = 2.274; 95% CI, 1.661-3.115; P < .0001), while cesarean section and use of epidural were found to be protective (OR = 0.149; 95% CI, 0.086-0.26; P < .0001; and OR = 0.687; 95% CI, 0.0531-0.89; P < .004, respectively). CONCLUSIONS: This study provides insight into the risk factors associated with neonatal clavicular fractures on the largest group of patients reported to date.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.368
Teacher spread0.348 · 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 designOther design
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes1
Has abstractyes

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