Effectiveness of intrapartum fetal surveillance to improve maternal and neonatal outcomes: a systematic review and network meta-analysis.

BACKGROUND: Cesarean delivery is the most common surgical procedure worldwide. Intrapartum fetal surveillance is routinely offered to improve neonatal outcomes, but the effects of different methods on the risk of emergency cesarean deliveries remains uncertain. We conducted a systematic review and network meta-analysis to evaluate the effectiveness of different types of fetal surveillance. METHODS: We searched MEDLINE, Embase and CENTRAL until June 1, 2020, for randomized trials evaluating any intrapartum fetal surveillance method. We performed a network meta-analysis within a frequentist framework. We assessed the quality and network inconsistency of trials. We reported primarily on intrapartum emergency cesarean deliveries and other secondary maternal and neonatal outcomes using risk ratios (RRs) and 95% confidence intervals (CIs). RESULTS: We included 33 trials (118 863 patients) evaluating intermittent auscultation with Pinard stethoscope/handheld Doppler (IA), cardiotocography (CTG), computerized cardiotocography (cCTG), CTG with fetal scalp lactate (CTG-lactate), CTG with fetal scalp pH analysis (CTG-FBS), CTG with fetal pulse oximetry (FPO-CTG), CTG with fetal heart electrocardiogram (CTG-STAN) and their combinations. Intermittent auscultation reduced the risk of emergency cesarean deliveries compared with other types of surveillance (IA v. CTG: RR 0.83, 95% CI 0.72-0.97; IA v. CTG-FBS: RR 0.71, 95% CI 0.63-0.80; IA v.CTG-lactate: RR 0.77, 95% CI 0.64-0.92; IA v. FPO-CTG: RR 0.75, 95% CI 0.65-0.87; IA v.FPO-CTG-FBS: RR 0.81, 95% CI 0.67-0.99; cCTG-FBS v. IA: RR 1.21, 95% CI 1.04-1.42), except STAN-CTG-FBS (RR 1.17, 95% CI 0.98-1.40). There was a similar reduction observed for emergency cesarean deliveries for fetal distress. None of the evaluated methods was associated with a reduced risk of neonatal acidemia, neonatal unit admissions, Apgar scores or perinatal death. INTERPRETATION: Compared with other types of fetal surveillance, intermittent auscultation seems to reduce emergency cesarean deliveries in labour without increasing adverse neonatal and maternal outcomes.

Predictors of perceived risk in first-degree relatives of patients with rheumatoid arthritis.

OBJECTIVES: To define variables associated with perceived risk of developing rheumatoid arthritis (RA) in first-degree relatives (FDRs) of patients with RA. METHODS: Patients with RA and their FDRs were invited to complete cross-sectional surveys. FDR and index patient responses were linked. FDRs' perceived absolute risk, comparative risk, experiential risk and worry about risk were assessed using 5-point Likert scales. FDR predictor variables included demographics, illness perceptions and psychosocial variables. Patient predictors of FDR perceived risk were assessed. Binary logistic regression examined the relationship between FDR characteristics and perceived risk of RA. Generalised estimating equations assessed whether patient variables predicted FDR's perceived risk. RESULTS: 396 FDRs returned a survey. 395 FDRs provided sufficient data and were included in analysis. Paired data from 213 patients were available for 291 of these FDRs. All measures of perceived risk were inter-correlated. 65.2% of FDRs perceived themselves to be 'likely' or 'very likely' to develop RA in their lifetime. Relationship with index patient, high health anxiety, female gender, long perceived RA duration, high perceived concern about RA, negative perceived emotional impact of RA and low perceptions of how well treatment would control RA were all associated with increased FDRs' perceived risk. Patient characteristics did not associate with FDRs' risk perceptions. CONCLUSIONS: FDRs' perceived risk of RA was high. Key predictors included being a child of a patient with RA, higher health anxiety and lower perceptions of RA treatment control. An understanding of these predictors will inform the development of tailored risk communication resources and preventive clinical strategies for RA.

Diminished ovarian reserve in recurrent pregnancy loss: a systematic review and meta-analysis.

OBJECTIVE: To evaluate the association between diminished ovarian reserve (DOR) in women at risk of recurrent pregnancy loss (RPL) using ovarian reserve tests. DESIGN: Systematic review and meta-analysis. SETTING: University medical schools. PATIENT(S): Women with a history of RPL. INTERVENTION(S): Systematic reviews of major electronic databases (MEDLINE, EMBASE, Web of Science, and Scopus) for studies that evaluated the incidence of DOR in women with RPL. MAIN OUTCOME MEASURE(S): Association between RPL and DOR. RESULT(S): In studies up to May 2019 we assessed quality using the Newcastle-Ottawa Scale and meta-analyzed data using a random-effect model. We included 15 studies (n = 3,082 women) reporting on six ovarian reserve tests: antimüllerian hormone [AMH], antral follicle count, follicle-stimulating hormone (FSH), luteinizing hormone (LH), estradiol, and FSH:LH ratio. More women with RPL seemed to have DOR compared with women who did not have RPL as measured by low AMH levels (odds ratio [OR] 2.77; 95% confidence interval [CI], 1.41-5.46) and AFC (OR 2.45; 95% CI, 1.16-5.19). Women with unexplained RPL also seemed to have a higher association with DOR compared with women whose RPL had a known etiology, as measured by low AMH levels (OR 3.23; 95% CI, 1.81-5.76). No statistically significant differences were found in the levels of any of the remaining ovarian reserve tests between those groups of women. CONCLUSION(S): There is an apparent association between DOR and RPL. Low AMH and AFC levels could predict higher odds for pregnancy loss, but more studies are needed to evaluate their prognostic value in the management of women with RPL. SYSTEMATIC REVIEW REGISTRATION NUMBER: Prospero CRD42018114673.

Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches.

OBJECTIVES: (1) To develop and internally-validate Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) thresholds for separating sedentary behaviours from common light-intensity physical activities using raw acceleration data collected from both hip- and wrist-worn tri-axial accelerometers; and (2) to compare and evaluate the performances between the ENMO and MAD metrics. METHODS: Thirty-three adults [mean age (standard deviation (SD)) = 27.4 (5.9) years; mean BMI (SD) = 23.9 (3.7) kg/m2; 20 females (60.6%)] wore four accelerometers; an ActiGraph GT3X+ and a GENEActiv on the right hip; and an ActiGraph GT3X+ and a GENEActiv on the non-dominant wrist. Under laboratory-conditions, participants performed 16 different activities (11 sedentary behaviours and 5 light-intensity physical activities) for 5 minutes each. ENMO and MAD were computed from the raw acceleration data, and logistic regression and receiver-operating-characteristic (ROC) analyses were implemented to derive thresholds for activity discrimination. Areas under ROC curves (AUROC) were calculated to summarise performances and thresholds were assessed via executing leave-one-out-cross-validations. RESULTS: For both hip and wrist monitor placements, in comparison to the ActiGraph GT3X+ monitors, the ENMO and MAD values derived from the GENEActiv devices were observed to be slightly higher, particularly for the lower-intensity activities. Monitor-specific hip and wrist ENMO and MAD thresholds showed excellent ability for separating sedentary behaviours from motion-based light-intensity physical activities (in general, AUROCs >0.95), with validation indicating robustness. However, poor classification was experienced when attempting to isolate standing still from sedentary behaviours (in general, AUROCs <0.65). The ENMO and MAD metrics tended to perform similarly across activities and accelerometer brands. CONCLUSIONS: Researchers can utilise these robust monitor-specific hip and wrist ENMO and MAD thresholds, in order to accurately separate sedentary behaviours from common motion-based light-intensity physical activities. However, caution should be taken if isolating sedentary behaviours from standing is of particular interest.

Accuracy of Posture Allocation Algorithms for Thigh- and Waist-Worn Accelerometers.

PURPOSE: The objective of this study is to compare the accuracy of the activPAL and ActiGraph GT3X+ (waist and thigh) proprietary postural allocation algorithms and an open-source postural allocation algorithm applied to GENEActiv (thigh) and ActiGraph GT3X+ (thigh) data. METHODS: Thirty-four adults (≥18 yr) wore the activPAL3, GENEActiv, and ActiGraph GT3X+ on the right thigh and an ActiGraph on the right hip while performing four lying, seven sitting, and five upright activities in the laboratory. Lying and sitting tasks incorporated a range of leg angles (e.g., lying with legs bent and sitting with legs crossed). Each activity was performed for 5 min while being directly observed. The percentage of the time the posture was correctly classified was calculated. RESULTS: Participants consisted of 14 males and 20 females (mean age, 27.2 ± 5.9 yr; mean body mass index, 23.8 ± 3.7 kg·m). All postural allocation algorithms applied to monitors worn on the thigh correctly classified ≥93% of the time lying, ≥91% of the time sitting, and ≥93% of the time upright. The ActiGraph waist proprietary algorithm correctly classified 72% of the time lying, 58% of the time sitting, and 74% of the time upright. Both the activPAL and ActiGraph thigh proprietary algorithms misclassified sitting on a chair with legs stretched out (58% and 5% classified incorrectly, respectively). The ActiGraph thigh proprietary and open-source algorithm applied to the thigh-worn ActiGraph misclassified participants lying on their back with their legs bent 27% and 9% of the time, respectively. CONCLUSION: All postural allocation algorithms when applied to devices worn on the thigh were highly accurate in identifying lying, sitting, and upright postures. Given the poor accuracy of the waist algorithm for detecting sitting, caution should be taken if inferring sitting time from a waist-worn device.