Peripartum Management of Obstructive Sleep Apnea.

The prevalence of obstructive sleep apnea is unknown during pregnancy, but the syndrome is likely underdiagnosed and rising in frequency along with the obesity epidemic. Obstructive sleep apnea is associated with adverse outcomes, including hypertensive disorders of pregnancy, gestational diabetes, preterm, and cesarean delivery. Obese pregnant women should be screened and referred to a sleep medicine specialist for evaluation. Continuous positive airway pressure is the treatment of choice with demonstrated safety and compliance in pregnancy. Early anesthesia consultation allows for preparation and implementation of a peripartum plan that includes early labor analgesia, avoidance of respiratory depressants, and closer monitoring of oxygenation.

Predicting acute pain after cesarean delivery using three simple questions.

BACKGROUND: Interindividual variability in postoperative pain presents a clinical challenge. Preoperative quantitative sensory testing is useful but time consuming in predicting postoperative pain intensity. The current study was conducted to develop and validate a predictive model of acute postcesarean pain using a simple three-item preoperative questionnaire. METHODS: A total of 200 women scheduled for elective cesarean delivery under subarachnoid anesthesia were enrolled (192 subjects analyzed). Patients were asked to rate the intensity of loudness of audio tones, their level of anxiety and anticipated pain, and analgesic need from surgery. Postoperatively, patients reported the intensity of evoked pain. Regression analysis was performed to generate a predictive model for pain from these measures. A validation cohort of 151 women was enrolled to test the reliability of the model (131 subjects analyzed). RESULTS: Responses from each of the three preoperative questions correlated moderately with 24-h evoked pain intensity (r = 0.24-0.33, P < 0.001). Audio tone rating added uniquely, but minimally, to the model and was not included in the predictive model. The multiple regression analysis yielded a statistically significant model (R = 0.20, P < 0.001), whereas the validation cohort showed reliably a very similar regression line (R = 0.18). In predicting the upper 20th percentile of evoked pain scores, the optimal cut point was 46.9 (z =0.24) such that sensitivity of 0.68 and specificity of 0.67 were as balanced as possible. CONCLUSIONS: This simple three-item questionnaire is useful to help predict postcesarean evoked pain intensity, and could be applied to further research and clinical application to tailor analgesic therapy to those who need it most.

An efficient method of identifying major depression and panic disorder in primary care.

The research literature is replete with evidence of and concerns about the prevalence and undertreatment of mental disorders in primary care. Although screening, on its own, may not directly affect clinical outcomes, it is still the most efficient and effective way to identify psychologically distressed patients for either research purposes or to provide patients with or refer patients to appropriate care. The current study sought to establish the utility of the MHI-5 for the detection of patients suffering from major depression or panic disorder, two of the most common psychiatric conditions seen in primary care settings. This study was conducted in a family medicine clinic and 246 adult outpatients participated. Patients completed the Mental Health Index-5 (MHI-5) as the screening measure and the PRIME-MD Patient Health Questionnaire (PHQ) as the diagnostic instrument. ROC analyses indicated that a cut-off score of 23 on the MHI-5 yielded a sensitivity of 91% and a specificity of 58% for predicting provisional diagnoses of major depression or panic disorder from the PHQ. Using a single item to screen for a PHQ diagnosis of major depression yielded a sensitivity of 88% and a specificity of 62% and a second question had a sensitivity of 100% and specificity of 63% for PHQ diagnosis of panic disorder. These results indicate that it is possible to use a small number of items to efficiently and effectively screen for mental disorders affecting a significant portion of primary care patients.