Complex obstetrical surgery: building a team and defining roles.

As the number of placenta accreta spectrum cases continues to rise, the gap in surgical skills in labor and delivery units becomes more apparent. Recent scholarly work has highlighted the diminishing advanced surgical skills among obstetrician-gynecologists, particularly among new graduates. Therefore, it has become a practice in many institutions to refer complex cesarean deliveries and obstetrical hysterectomies to subspecialists, specifically gynecologic oncologists. Hence, in this commentary, we propose a process through which key personnel within departments of obstetrics and gynecology are identified and their appropriate level of involvement in cases of complex obstetrical surgery is delineated. In doing so, we describe the surgical skills expected from each provider level so that the cesarean delivery complexity level can be matched with specific surgical expertise. Through this process, an obstetrician-led complex obstetrical surgery team is formed. Ultimately, the goal of this process is 2-fold; first, to return cases with higher levels of surgical complexity back to obstetricians and, second, to reduce the surgical back-up burden from gynecology subspecialists such as gynecologic oncologists.

Use of natural language processing to uncover racial bias in obstetrical documentation.

Natural Language Processing (NLP), a form of Artificial Intelligence, allows free-text based clinical documentation to be integrated in ways that facilitate data analysis, data interpretation and formation of individualized medical and obstetrical care. In this cross-sectional study, we identified all births during the study period carrying the radiology-confirmed diagnosis of fibroid uterus in pregnancy (defined as size of largest diameter of >5 cm) by using an NLP platform and compared it to non-NLP derived data using ICD10 codes of the same diagnosis. We then compared the two sets of data and stratified documentation gaps by race. Using fibroid uterus in pregnancy as a marker, we found that Black patients were more likely to have the diagnosis entered late into the patient's chart or had missing documentation of the diagnosis. With appropriate algorithm definitions, cross referencing and thorough validation steps, NLP can contribute to identifying areas of documentation gaps and improve quality of care.

One-step vs 2-step gestational diabetes mellitus screening and pregnancy outcomes: an updated systematic review and meta-analysis.

OBJECTIVE: This was a systematic review and meta-analysis comparing maternal and neonatal outcomes of patients screened with the 1-step or 2-step screening method for gestational diabetes mellitus. DATA SOURCES: PubMed, Scopus, Cochrane, ClinicalTrials.gov, and LILACS were searched from inception up to September 2022. STUDY ELIGIBILITY CRITERIA: Only randomized controlled trials were included. Studies that had overlapping populations were excluded (International Prospective Register of Systematic Review registration number: CRD42022358903). METHODS: Risk ratios were computed with 95% confidence intervals by 2 authors. Unpublished data were requested. Large for gestational age was the primary outcome. RESULTS: The search yielded 394 citations. Moreover, 7 randomized controlled trials met the inclusion criteria. A total of 54,650 participants were screened for gestational diabetes mellitus by either the 1-step screening method (n=27,163) or the 2-step screening method (n=27,487). For large for gestational age, there was no significant difference found between the groups (risk ratio, 0.99; 95% confidence interval, 0.93-1.05; I2=0%). Newborns of patients who underwent 1-step screening had higher rates of neonatal hypoglycemia (risk ratio, 1.24; 95% confidence interval, 1.14-1.34; I2=0%) and neonatal intensive care unit admissions (risk ratio, 1.13; 95% confidence interval, 1.04-1.21; I2=0%) than newborns of patients who underwent 2-step screening. Patients in the 1-step screening method group were more likely to be diagnosed with gestational diabetes mellitus (risk ratio, 1.73; 95% confidence interval, 1.44-2.09; I2=80%) than patients in the 2-step screening method group. In addition, among trials that tested all patients before randomization and excluded patients with pregestational diabetes mellitus, newborns were more likely to have macrosomia (risk ratio, 1.27; 95% confidence interval, 1.21-1.34; I2=0%). Overall risk of bias assessment was of low concern. CONCLUSION: Large for gestational age did not differ between patients screened using the 1-step screening method and those screened using the 2-step screening method. However, patients randomized to the 1-step screening method had higher rates of neonatal hypoglycemia and neonatal intensive care unit admission and maternal gestational diabetes mellitus diagnosis than the patients randomized to the 2-step screening method.