Work

Predictors of Shoulder Dystocia: A Retrospective Case–Control Study

Year: 2026

Type: article

Abstract: ABSTRACT Introduction Shoulder dystocia (SD) is rare, but it has serious consequences. Antepartum risk stratification for SD has demonstrated variability across populations, reflecting differences in assessment methodologies. Methods We conducted a retrospective analysis using a prospectively audited electronic database from a single center. All singleton vertex deliveries between January 2012 and December 2017 were reviewed. SD cases were identified by the recorded use of ancillary maneuvers during shoulder delivery. Case–control matching was informed by previously published odds ratios for key variables and evaluated using conditional logistic regression. Results A total of 80,349 eligible delivery records were reviewed, of which 23,392 (29.11%) were Cesarean deliveries. Among the remaining 56,957 vaginal births, 58 cases of SD were identified, representing an incidence of 0.10%. An additional 880 gestational age‐matched controls were selected, based on a conservative control‐to‐case ratio of 15:1. Maternal and neonatal birth injuries were documented in 5 SD cases (8.6%) and 6 control cases (0.7%), respectively ( p < 0.001). Adjusted odds ratios (95% confidence intervals) for associated risk factors were as follows: fetal macrosomia (birthweight >/= 4000 g), 22.99 (8.49–62.25); maternal overweight (body mass index >/= 25 kg/m 2 ), 3.44 (1.41–8.44); diabetes mellitus, 2.32 (1.12–4.78); and nulliparity, 1.62 (0.89–2.94), with statistical significance observed for all ( p < 0.05) except nulliparity. Conditional logistic regression modeling revealed distortion in matching between parity and maternal age >/= 35 years, as well as fetal macrosomia, which attenuated statistical significance ( p = 0.113). Conclusions Fetal macrosomia was the most robust independent predictor of SD. Maternal overweight and diabetes mellitus were contributory and modifiable risk factors. Parity did not independently predict SD events, likely due to a Type I statistical error.

Source: Birth

DOI: 10.1111/birt.70107

Authors: Nisarat Phithakwatchara, Katika Nawapun, Suparat Jaingam, Julaporn Pooliam, Tuangsit Wataganara

Institutions: Siriraj Hospital, Mahidol University

Language: English

Topic: Maternal and Perinatal Health Interventions

Subfield: Obstetrics and Gynecology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,850