Oxytocin: physiology, pharmacology, and clinical application for labor management.

Oxytocin is a peptide hormone that plays a key role in regulating the female reproductive system, including during labor and lactation. It is produced primarily in the hypothalamus and secreted by the posterior pituitary gland. Oxytocin can also be administered as a medication to initiate or augment uterine contractions. To study the effectiveness and safety of oxytocin, previous studies have randomized patients to low- and high-dose oxytocin infusion protocols either alone or as part of an active management of labor strategy along with other interventions. These randomized trials demonstrated that active management of labor and high-dose oxytocin regimens can shorten the length of labor and reduce the incidence of clinical chorioamnionitis. The safety of high-dose oxytocin regimens is also supported by no associated differences in fetal heart rate abnormalities, postpartum hemorrhage, low Apgar scores, neonatal intensive care unit admissions, and umbilical artery acidemia. Most studies reported no differences in the cesarean delivery rates with active management of labor or high-dose oxytocin regimens, thereby further validating its safety. Oxytocin does not have a predictable dose response, thus the pharmacologic effects and the amplitude and frequency of uterine contractions are used as physiological parameters for oxytocin infusion titration to achieve adequate contractions at appropriate intervals. Used in error, oxytocin can cause patient harm, highlighting the importance of precise administration using infusion pumps, institutional safety checklists, and trained nursing staff to closely monitor uterine activity and fetal heart rate changes. In this review, we summarize the physiology, pharmacology, infusion regimens, and associated risks of oxytocin.

Using ChatGPT-4 to Create Structured Medical Notes From Audio Recordings of Physician-Patient Encounters: Comparative Study.

BACKGROUND: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition software have been used to ease this burden, they have limitations in terms of accuracy and addressing provider-specific metrics. The integration of ambient artificial intelligence (AI)-powered solutions offers a promising way to improve documentation while fitting seamlessly into existing workflows. OBJECTIVE: This study aims to assess the accuracy and quality of Subjective, Objective, Assessment, and Plan (SOAP) notes generated by ChatGPT-4, an AI model, using established transcripts of History and Physical Examination as the gold standard. We seek to identify potential errors and evaluate the model's performance across different categories. METHODS: We conducted simulated patient-provider encounters representing various ambulatory specialties and transcribed the audio files. Key reportable elements were identified, and ChatGPT-4 was used to generate SOAP notes based on these transcripts. Three versions of each note were created and compared to the gold standard via chart review; errors generated from the comparison were categorized as omissions, incorrect information, or additions. We compared the accuracy of data elements across versions, transcript length, and data categories. Additionally, we assessed note quality using the Physician Documentation Quality Instrument (PDQI) scoring system. RESULTS: Although ChatGPT-4 consistently generated SOAP-style notes, there were, on average, 23.6 errors per clinical case, with errors of omission (86%) being the most common, followed by addition errors (10.5%) and inclusion of incorrect facts (3.2%). There was significant variance between replicates of the same case, with only 52.9% of data elements reported correctly across all 3 replicates. The accuracy of data elements varied across cases, with the highest accuracy observed in the "Objective" section. Consequently, the measure of note quality, assessed by PDQI, demonstrated intra- and intercase variance. Finally, the accuracy of ChatGPT-4 was inversely correlated to both the transcript length (P=.05) and the number of scorable data elements (P=.05). CONCLUSIONS: Our study reveals substantial variability in errors, accuracy, and note quality generated by ChatGPT-4. Errors were not limited to specific sections, and the inconsistency in error types across replicates complicated predictability. Transcript length and data complexity were inversely correlated with note accuracy, raising concerns about the model's effectiveness in handling complex medical cases. The quality and reliability of clinical notes produced by ChatGPT-4 do not meet the standards required for clinical use. Although AI holds promise in health care, caution should be exercised before widespread adoption. Further research is needed to address accuracy, variability, and potential errors. ChatGPT-4, while valuable in various applications, should not be considered a safe alternative to human-generated clinical documentation at this time.

Importance of PCR-based Tumor Testing in the Evaluation of Lynch Syndrome-associated Endometrial Cancer.

Lynch syndrome (LS) is a hereditary cancer syndrome caused by a germline mutation in a DNA mismatch repair gene, usually MLH1, MSH2, MSH6, or PMS2. The most common cancers associated with LS are colorectal adenocarcinoma and endometrial carcinoma. Identification of women with LS-associated endometrial cancer is important, as these women and their affected siblings and children are at-risk of developing these same cancers. Germline testing of all endometrial cancer patients is not cost effective, and screening using young age of cancer diagnosis and/or presence of family history of syndrome-associated is underutilized and ineffective. Therefore, most groups now advocate for tumor tissue testing to screen for LS, with germline testing targeted to women with abnormal tissue testing results. Immunohistochemistry for MLH1, MSH2, MSH6, and PMS2 is used in many clinical laboratories for this tumor screening step, as immunohistochemistry is relatively inexpensive and is technically more accessible for smaller clinical labs. PCR-based tissue testing, whereas technically more challenging, does play an important role in the identification of these patients. MLH1 methylation analysis identifies women with tumor MLH1 loss who likely have sporadic endometrial cancer and do not need heightened cancer prevention surveillance. High levels of microsatellite instability have been identified in tumors with retained positive expression of mismatch repair proteins. Somatic sequencing of mismatch repair genes from tumor DNA, whereas not currently available in most clinical laboratories, is helpful in resolution of cases in which germline sequencing fails to identify a mutation in a mismatch repair gene. The tumor tissue testing approach can help to identify most women at-risk for germline mutations in a LS gene, but not all patients will be captured using this approach. Clinical suspicion can still play a pivotal role in accurately identifying a subset of these patients.

Pregnancy as a risk factor for severe coronavirus disease 2019 using standardized clinical criteria.

BACKGROUND: As of November 18, 2020, more than 11 million people have been infected with coronavirus disease 2019 and almost 250,000 people have died from the disease in the United States, less than 1 year since its discovery. Although literature is beginning to emerge on pregnancy as a risk factor for severe coronavirus disease 2019, these studies are heterogeneous and use primary outcomes such as intensive care unit admission or hospitalization as surrogate markers that may subject analyses to misclassification bias in pregnant patients. OBJECTIVE: This study aimed to determine the risk of severe coronavirus disease 2019 among pregnant women with symptomatic coronavirus disease 2019 compared with nonpregnant women using nonadmission-based, standardized clinical criteria for severe disease. STUDY DESIGN: This is a retrospective cohort study of women aged 13 to 45 years and diagnosed as having symptomatic coronavirus disease 2019 between May 28, 2020, and July 22, 2020. The primary outcome was severe coronavirus disease 2019 as defined by 2 sets of nonadmission-based, clinical criteria: the World Health Organization Ordinal Scale for Clinical Improvement and the Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. Adjusted risk ratios were estimated using multivariable logistic regression analyses. RESULTS: Of 262 women aged 13 to 45 years with symptomatic coronavirus disease 2019, 22 (8.4%) were pregnant and 240 (91.6%) were nonpregnant. After adjusting for covariates potentially associated with the primary outcome, symptomatic pregnant women were at a significantly increased risk of severe coronavirus disease 2019 compared with nonpregnant women using both the World Health Organization Ordinal Scale for Clinical Improvement (adjusted relative risk, 3.59; 95% confidence interval, 1.49-7.01) and Novel Coronavirus Pneumonia Emergency Response Epidemiology Team (adjusted relative risk, 5.65; 95% confidence interval, 1.36-17.31) criteria. CONCLUSION: Pregnancy significantly increases the risk of severe coronavirus disease 2019 as defined by nonadmission-based, clinical criteria.

Universal Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) Testing Uptake in the Labor and Delivery Unit: Implications for Health Equity.

OBJECTIVE: To understand severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing uptake in the labor and delivery unit and rationales for declining testing, and to institute a process to increase equitable testing uptake. METHODS: We conducted a quality-improvement initiative from May 28-June 25, 2020, during the first 4 weeks of universal SARS-CoV-2 testing in the Barnes-Jewish Hospital labor and delivery unit. All consecutive patients presenting for delivery without coronavirus disease 2019 (COVID-19) symptoms were offered testing over four 1-week phases. Phase I documented the rate of testing uptake. Phase II recorded patients' reasons for declining testing. Phase III used phase II findings to create and implement shared decision-making tools. Phase IV offered each patient who declined nasopharyngeal testing an oropharyngeal alternative. The primary outcome was rate of SARS-CoV-2 testing uptake by phase. RESULTS: Of 270 patients, 223 (83%) accepted testing and 47 (17%) declined. Maternal age and mode of delivery were similar between groups, whereas testing uptake was higher among nulliparous, White, Hispanic, or privately insured patients. There was a significant increase in the primary outcome of SARS-CoV-2 testing across phases I-IV, from 68% to 76% to 94% to 95%, respectively (Somers' D 0.45; 95% CI of association 0.30-0.59). The most commonly cited reason for declining testing was concern regarding testing discomfort. In subgroup analyses by race and insurance type, there was a significant increase in testing uptake across phases I-IV for Black patients (56%, 54%, 91%, 92%; Somers' D 0.36; 95% CI of association 0.28-0.64), White patients (76%, 93%, 96%, 100%; Somers' D 0.59; 95% CI of association 0.38-0.8), those with Medicaid insurance (60%, 64%, 88%, 92%; 95%; Somers' D 0.39; CI of association 0.22 to 0.56), and those with private insurance (77%, 96%, 97%, 100%; Somers' D 0.63; 95% CI of association 0.40-0.86). CONCLUSION: Universal SARS-CoV-2 testing uptake significantly increased through a rapid-cycle improvement initiative. Aligning hospital policy with patient-centered approaches led to nearly universally acceptable testing.

False-negative testing for severe acute respiratory syndrome coronavirus 2: consideration in obstetrical care.

Because the obstetrical population seems to have a high proportion of asymptomatic patients who are carriers of severe acute respiratory syndrome coronavirus 2, universal testing has been proposed as a strategy to risk-stratify all obstetrical admissions and guide infection prevention protocols. Here, we describe a case of a critically ill obstetrical patient with all the clinical symptoms of coronavirus disease 2019 and 3 false-negative results of nasopharyngeal swabs for molecular testing. We review and discuss the uncertain clinical characteristics of current severe acute respiratory syndrome coronavirus 2 molecular testing and the implications of false-negative results in the obstetrical population.

Augmentation of Labor: A Review of Oxytocin Augmentation and Active Management of Labor.

Labor augmentation can be used to hasten labor, shorten the time to delivery, and perhaps reduce the risk of cesarean delivery. Particularly in women with longer labors or less frequent contractions, oxytocin augmentation seems to have positive impacts on these outcomes. Despite this, the evidence for augmentation alone on the risk of cesarean delivery is unclear, with varying evidence. More recently, oxytocin protocols have been recommended to standardize care and ensure patient safety.