Implementation of and Barriers to Optimizing Postpartum Care by Resident and Attending Physicians.

Background: The American College of Obstetricians and Gynecologists released Committee Opinion No. 736: Optimizing Postpartum Care (CO No. 736) to address severe maternal morbidity and mortality in the United States by outlining recommendations for care in the critical time following birth. This study aimed to evaluate implementation of and barriers to the recommendations of CO No. 736 among obstetricians in south Louisiana. Methods: A survey to general obstetric providers assessed opinions on the CO No. 736 recommendations, implementation of these recommendations, and barriers to implementation. Fisher exact test was used to compare distributions between resident and attending groups. Qualitative, free-text responses about barriers to implementation were organized by common themes and categorized into systemic and patient factors. Results: Of 124 survey responses, 59.7% of respondents reported that they had read CO No. 736. Of the respondents who had read the document, 86.5% believed it was important to implement these recommendations, but only 50.0% had established the recommendations in their practices. Overall, fewer than half (46.8%) of respondents reported actively implementing the recommendation to make contact with postpartum patients at 3 weeks or sooner, but 86.3% reported having comprehensive clinic visits within 12 weeks of delivery. Commonly identified systemic barriers to implementation included the 3-week contact not being common practice, overbooked schedules, and unclear provider expectations. Commonly identified patient factor barriers to implementation included childcare or transportation and no-shows at postpartum appointments. Conclusion: Both resident and attending obstetricians in South Louisiana believe that the CO No. 736 recommendations are important but reported lacking the ability to implement them into clinical practice.

Hemoglobin A1c as a Substitute for Oral Glucose Testing in Early Pregnancy Screening.

OBJECTIVE: Current recommendations for individuals with risk factors for gestational diabetes mellitus (GDM) call for screening in early pregnancy. However, there is currently no clear consensus on a specific screening modality. This study evaluates whether a hemoglobin A1c (HbA1c) screening in individuals with risk factors for gestational diabetes (GDM) could be used instead of an early 1-hour glucose challenge test (GCT). We hypothesized that the HbA1c could replace 1-hour GCT in early pregnancy evaluation STUDY DESIGN: This is a prospective observational trial at a single tertiary referral center of women with at least one risk factor for GDM who were screened at <16 weeks of gestation with both 1-hour GCT or HbA1c. Exclusion criteria include: previous diagnosis of diabetes mellitus, multiple gestation, miscarriage, or missing delivery information. The diagnosis of GDM was made by a 3-hour 100-g glucose tolerance test, using the Carpenter-Coustan criteria (at least two results >94, 179, 154, and 139 mg/dL for fasting, 1-, 2-, and 3-hour values, respectively), 1-hour GCT > 200 mg/dL, or HbA1c > 6.5%. RESULTS: A total of 758 patients met inclusion criteria. A total of 566 completed a 1-hour GCT and 729 had an HbA1c collected. The median gestational age at testing was 91/7 weeks (range: 40/7-156/7 weeks]. Twenty-one participants were diagnosed with GDM at <16 weeks' GA. The receiver operating characteristic (ROC) curves identified the optimal valves for a positive screen for an HbA1c > 5.6%. The HbA1c had a sensitivity of 84.2%, a specificity of 83.3%, and a false positive rate of 16.7% (p < 0.001). The area under the ROC curve for the HbA1c was 0.898. Gestational age of delivery was slightly earlier with individuals with an elevated HbA1c but no other changes in delivery or neonatal outcomes. Contingent screening improved specificity (97.7%) and decreased false positive rate to 4.4%. CONCLUSION: HbA1c may be a good assessment in early pregnancy for gestational diabetes. KEY POINTS: · HbA1c is a rational assessment in early pregnancy.. · An HbA1c > 5.6% is associated with gestational diabetes.. · Contingent screening limits the need for additional testing..

Chronic Hypoxia Inhibits Respiratory Complex IV Activity and Disrupts Mitochondrial Dynamics in the Fetal Guinea Pig Forebrain.

Mitochondrial dysfunction is an underlying cause of childhood neurological disease secondary to the crucial role of mitochondria in proper neurodevelopment. We hypothesized that chronic intrauterine hypoxia (HPX) induces mitochondrial deficits by altering mitochondrial biogenesis and dynamics in the fetal brain. Pregnant guinea pigs were exposed to either normoxia (NMX, 21%O2) or HPX (10.5%O2) starting at 28-day (early onset, EO-HPX) or 50-day (late onset, LO-HPX) gestation until term (65 days). Near-term male and female fetuses were extracted from anesthetized sows, and mitochondria were isolated from excised fetal forebrains (n = 6/group). Expression of mitochondrial complex subunits I-V (CI-CV), fission (Drp-1), and fusion (Mfn-2) proteins was measured by Western blot. CI and CIV enzyme activities were measured by colorimetric assays. Chronic HPX reduced fetal body wts and increased (P < 0.05) brain/body wt ratios of both sexes. CV subunit levels were increased in EO-HPX males only and CII levels increased in LO-HPX females only compared to NMX. Both EO- and LO-HPX decreased CIV activity in both sexes but had no effect on CI activity. EO-HPX increased Drp1 and decreased Mfn2 levels in males, while LO-HPX had no effect on either protein levels. In females, both EO-HPX and LO-HPX increased Drp1 but had no effect on Mfn2 levels. Chronic HPX alters abundance and activity of select complex subunits and shifts mitochondrial dynamics toward fission in a sex-dependent manner in the fetal guinea pig brain. This may be an underlying mechanism of reduced respiratory efficiency leading to disrupted metabolism and increased vulnerability to a second neurological injury at the time of birth in HPX fetal brains.

Combined process automation for large-scale EEG analysis.

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis.