OBJECTIVETo explore relationships among sleep disturbances, glucose tolerance, and pregnancy outcomes.RESEARCH DESIGN AND METHODSFour validated sleep questionnaires were administered to 169 pregnant women at the time of 50-g oral glucose tolerance testing (OGTT) during the second trimester. Pregnancy outcomes were analyzed in 108 women with normal glucose tolerance (NGT).RESULTSOf the participants, 41% had excessive daytime sleepiness (Epworth Sleepiness Scale [ESS] >8); 64% had poor sleep quality; 25% snored frequently; 29% had increased risk of sleep-disordered breathing (SDB); 52% experienced short sleep (SS); 19% had both increased SDB risk and SS (SDB/SS); and 14% had daytime dysfunction. Reported sleep duration inversely correlated with glucose values from 50-g OGTT (r = −0.21, P < 0.01). Each hour of reduced sleep time was associated with a 4% increase in glucose levels. Increased likelihood of gestational diabetes mellitus (GDM) was found in subjects with increased SDB risk (odds ratio 3.0 [95% CI 1.2–7.4]), SS (2.4 [1.0–5.9]), SDB/SS (3.4 [1.3–8.7]), and frequent snoring (3.4 [1.3–8.8], after adjustment for BMI). Among NGT subjects, preterm delivery was more frequent in those with increased ESS (P = 0.02), poor sleep quality (P = 0.02), and SS (P = 0.03). Neonatal intensive care unit admissions were associated with increased ESS (P = 0.03), SDB/SS (P = 0.03), and daytime dysfunction (P < 0.01) in mothers.CONCLUSIONSPregnant women experience significant sleep disturbances that are associated with increased risk of GDM and unfavorable pregnancy outcomes. Pregnant women with increased SDB risk, frequent snoring, and sleep duration of <7 h/night have increased risk of developing GDM.

Pregnancy is associated with sleep disturbances. Sleep is more disturbed in GDM than in P-NGT women. There is a strong association between GDM and OSA.

Background: Accurate diagnosis of anemia by community workers using a point-of-care device is a challenge. The objective of the study was to establish the diagnostic accuracy of point-of-care devices for detecting anemia in community settings. Methods: It was diagnostic accuracy study with cross-sectional design on adult patients attending the outpatient department of rural/ urban health centres of Medical colleges from India. The index tests were HemoCue, TrueHb, Massimo's device and spectroscopic device, compared against autoanalyzer (gold standard). Accuracy was expressed by sensitivity, specificity, likelihood ratios, predictive values, area under the curve (AUC) and levels of agreement. For the diagnostic accuracy component, 1407 participants were recruited with a minimum of 600 for each device. An additional 200 participants were considered to elucidate the performance of devices in different weather conditions. Results: HemoCue and TrueHb performed better than Massimo and spectroscopic devices. Detection of anemia by technicians was similar between TrueHb and HemoCue (AUC 0.92 v/s 0.90, p > 0.05). Community workers performed better with Hemocue for detecting anemia compared to TrueHb (AUC 0.92 v/s 0.90, p < 0.05). For detection of severe anemia, accuracy of TrueHb was significantly better with technicians (AUC 0.91 v/s 0.70; p < 0.05) and community workers (AUC 0.91 v/s 0.73; p < 0.05). HemoCue showed a bias or mean difference (95%CI) of 0.47 g/dl (0.42, 0.52) for all values, and 0.92 g/dl (0.82, 1.03) for severe anemia. For TrueHb, it was − 0.28 g/dl (− 0.37, − 0.20) for all readings, and 0.06 g/dl (− 0.52, 0.63) for severe anemia. TrueHb appeared to be more consistent across different weather conditions, although it overestimated Hb in extreme cold weather conditions. Conclusion: For detection of anemia, True Hb and HemoCue were comparable. For severe anemia, True Hb seemed to be a better and feasible point-of-care device for detecting anemia in the community settings.

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