POPULATION: Women with singleton, term pregnancies in active labour and immediate postnatal period, at low risk of complications.
SETTING: Healthcare facilities in low- and middle-income countries.
SEARCH STRATEGY: A systematic search and review were conducted on the current guidelines from WHO, NICE, ACOG and RCOG. Additional search was done on PubMed and The Cochrane Database of Systematic Reviews up to May 2020.
CASE SCENARIOS: Four common intrapartum urinary abnormalities were selected: proteinuria, ketonuria, glycosuria and oliguria. Using reagent strip testing, glycosuria was defined as ≥2+ on one occasion or of ≥1+ on two or more occasions. Proteinuria was defined as ≥2+ and presence of ketone indicated ketonuria. Oliguria was defined as hourly urine output ≤30 ml. Thorough initial assessment using history, physical examination and basic investigations helped differentiate most of the underlying causes, which include diabetes mellitus, dehydration, sepsis, pre-eclampsia, shock, anaemia, obstructed labour, underlying cardiac or renal problems. A clinical algorithm was developed for each urinary abnormality to facilitate intrapartum management and referral of complicated cases for specialised care.
CONCLUSIONS: Four simple, user-friendly and evidence-based clinical algorithms were developed to enhance intrapartum care of commonly encountered maternal urine abnormalities. These algorithms may be used to support healthcare professionals in clinical decision-making when handling normal and potentially complicated labour, especially in low resource countries.
TWEETABLE ABSTRACT: Evidence-based clinical algorithms developed to guide intrapartum management of commonly encountered urinary abnormalities.
DESIGN: Prospective, observational cohort study.
SETTING: Tertiary maternity hospital in Australia.
POPULATION: There were 320 singleton pregnancies: 141 (44.1%) AGA, 83 (25.9%) early FGR (<32+0 weeks) and 109 (30.0%) late FGR (≥32+0 weeks).
METHODS: Maternal serum PlGF and sFlt-1/PlGF ratio were measured at 4-weekly intervals from recruitment to delivery. Low maternal PlGF levels and elevated sFlt-1/PlGF ratio were defined as <100 ng/L and >5.78 if <28 weeks and >38 if ≥28 weeks respectively. Cox proportional hazards models were used. The analysis period was defined as the time from the first measurement of PlGF and sFlt-1/PlGF ratio to the time of birth or censoring.
MAIN OUTCOME MEASURES: The primary study outcome was overall PTB. The relative risks (RR) of birth within 1, 2 and 3 weeks and for medically indicated and spontaneous PTB were also ascertained.
RESULTS: The early FGR cohort had lower median PlGF levels (54 versus 229 ng/L, p
DESIGN: Retrospective observational study.
SETTING: A tertiary urogynaecological unit in Australia.
POPULATION: A total of 780 archived data sets of women seen for symptoms of lower urinary tract and pelvic floor dysfunction.
METHODS: Standardised in-house interview and assessment using the International Continence Society (ICS) pelvic organ prolapse quantification (POP-Q), and four-dimensional translabial ultrasound. Offline analysis for hiatal dimensions was undertaken blinded to history and clinical examination.
MAIN OUTCOME MEASURES: Hiatal area on maximum Valsalva.
RESULTS: Of 780 women, 64 were excluded because of missing ultrasound volumes, leaving 716 for analysis: 96% (n = 686) were parous, with a median parity of three (interquartile range, IQR 2-3), and 91.2% (n = 653) were vaginally parous. Levator avulsion was found in 21% (n = 148). The mean hiatal area on Valsalva was 29 cm(2) (SD 9.4 cm(2) ). On one-way anova, vaginal parity was significantly associated with hiatal area (P < 0.001). Most of the effect seems to occur with the first delivery. Subsequent deliveries do not seem to have any significant effect on hiatal dimensions. This remained true after controlling for potential confounding factors using multivariate regression analysis (P = 0.0123).
CONCLUSIONS: Vaginal parity was strongly associated with hiatal area on Valsalva. Most of this effect seems to be associated with the first vaginal delivery.
DESIGN: Population-based multi-country analyses.
SETTING: Births collected through routine data systems in 13 countries.
SAMPLE: 125 419 255 total births from 22+0 to 44+6 weeks' gestation identified from 2000 to 2020.
METHODS: We included 635 107 stillbirths from 22+0 weeks' gestation from 13 countries. We classified all births, including stillbirths, into six 'newborn types' based on gestational age information (preterm, PT, <37+0 weeks versus term, T, ≥37+0 weeks) and size-for-gestational age defined as small (SGA, <10th centile), appropriate (AGA, 10th-90th centiles) or large (LGA, >90th centile) for gestational age, according to the international newborn size for gestational age and sex INTERGROWTH-21st standards.
MAIN OUTCOME MEASURES: Distribution of stillbirths, stillbirth rates and rate ratios according to six newborn types.
RESULTS: 635 107 (0.5%) of the 125 419 255 total births resulted in stillbirth after 22+0 weeks. Most stillbirths (74.3%) were preterm. Around 21.2% were SGA types (PT + SGA [16.2%], PT + AGA [48.3%], T + SGA [5.0%]) and 14.1% were LGA types (PT + LGA [9.9%], T + LGA [4.2%]). The median rate ratio (RR) for stillbirth was highest in PT + SGA babies (RR 81.1, interquartile range [IQR], 68.8-118.8) followed by PT + AGA (RR 25.0, IQR, 20.0-34.3), PT + LGA (RR 25.9, IQR, 13.8-28.7) and T + SGA (RR 5.6, IQR, 5.1-6.0) compared with T + AGA. Stillbirth rate ratios were similar for T + LGA versus T + AGA (RR 0.7, IQR, 0.7-1.1). At the population level, 25% of stillbirths were attributable to small-for-gestational-age.
CONCLUSIONS: In these high-quality data from high/middle income countries, almost three-quarters of stillbirths were born preterm and a fifth small-for-gestational age, with the highest stillbirth rates associated with the coexistence of preterm and SGA. Further analyses are needed to better understand patterns of gestation-specific risk in these populations, as well as patterns in lower-income contexts, especially those with higher rates of intrapartum stillbirth and SGA.
DESIGN: Prospective observational cohort study.
SETTING: Single tertiary multidisciplinary antenatal clinic in Malaysia.
POPULATION: A total of 507 mothers: 145 with gestational diabetes mellitus (GDM); 94 who were obese with normal glucose tolerance (NGT) (pre-gravid body mass index, BMI ≥ 27.5 kg/m2 ), and 268 who were not obese with NGT.
METHODS: Maternal demographic, anthropometric, and clinical data were collected during an interview/examination using a structured questionnaire. Blood was drawn for insulin, C-peptide, triglyceride (Tg), and non-esterified fatty acid (NEFA) during the 75-g 2-hour oral glucose tolerance test (OGTT) screening, and again at 36 weeks of gestation. At birth, neonatal anthropometrics were assessed and data such as gestational weight gain (GWG) were extracted from the records.
MAIN OUTCOME MEASURES: Macrosomia, large-for-gestational-age (LGA) status, cohort-specific birthweight (BW), neonatal fat mass (NFM), and sum of skinfold thickness (SSFT) > 90th centile.
RESULTS: Fasting Tg > 95th centile (3.6 mmol/L) at screening for OGTT was independently associated with LGA (adjusted odds ratio, aOR 10.82, 95% CI 1.26-93.37) after adjustment for maternal glucose, pre-gravid BMI, and insulin sensitivity. Fasting glucose was independently associated with a birthweight ratio (BWR) of >90th centile (aOR 2.06, 95% CI 1.17-3.64), but not with LGA status, in this well-treated GDM cohort with pre-delivery HbA1c of 5.27%. In all, 45% of mothers had a pre-gravid BMI of <23 kg/m2 and 61% had a pre-gravid BMI of ≤ 25 kg/m2 , yet a GWG of >10 kg was associated with a 4.25-fold risk (95% CI 1.71-10.53) of BWR > 90th centile.
CONCLUSION: Maternal lipaemia and GWG at a low threshold (>10 kg) adversely impact neonatal adiposity in Asian offspring, independent of glucose, insulin resistance and pre-gravid BMI. These may therefore be important modifiable metabolic targets in pregnancy.
TWEETABLE ABSTRACT: Maternal lipids are associated with adiposity in Asian babies independently of pre-gravid BMI, GDM status, and insulin resistance.