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Gestational Weight Gain (GWG) modulates pregnancy outcomes and long-term offspring metabolic health. The 2009 Institute of Medicine (IOM) GWG recommendations have largely been validated in Caucasian and mono-ethnic East Asian cohorts. Asians are at higher metabolic risk at a lower body mass index (BMI), and this has prompted the World Health Organization (WHO) to identify lower BMI cut-offs for risk evaluation amongst Asians. This prospective observational cohort study aimed to determine if 2009 IOM GWG thresholds are applicable in a contemporary multi-ethnic South-East Asian cohort. We recruited 875 mothers from an urban Malaysian tertiary clinic during screening for gestational diabetes mellitus (GDM) from 2014–2021. Data collected included measures of insulin-sensitivity, total GWG (maternal weight at delivery–self-reported pre-gravid weight), and neonatal anthropometrics (birthweight and skinfold-thickness measured with Harpenden calipers). BMI was stratified by Caucasian (overweight ≥25kg/m2, obese ≥30kg/m2) as well as Asian (overweight ≥23kg/m2, obese ≥27.5kg/ m2) cut-offs, and patients categorized by 2009 IOM GWG reference ranges. The cohort comprised 67% Malay-, 23% Chinese- and 10% Indian-descent mothers with a high prevalence of overweight/obesity (Asian cut-offs 56.9% vs Caucasian 44%). When Asian BMI cut-offs were deployed, excessive GWG incidence increased (34.1% → 40.6%) whilst inadequate GWG declined (30% → 24.8%) (p<0.05). Upon multivariate-analysis (adjusting for age, parity, race, GDM, insulin-sensitivity, baby-gender) excessive GWG categorized with Caucasian BMI cut-offs was significantly associated with increased risk of macrosomia (adjusted odds ratio (aOR) 8.65, 95% confidence interval (CI) 1.07–70.01), Neonatal-Fat-Mass (NFM) >90th centile (aOR 2.14, 95% CI 1.02–4.45) and Sum-of-Skinfold Thickness (SSFT) >90th centile (aOR 3.88, 95% CI 1.77–8.51). Excessive GWG by Asian cut-offs was also associated with increased risk of SSFT >90th centile (aOR 5.75, 95% CI 2.35–14.10). Inadequate GWG by both Caucasian and Asian BMI cut-offs was associated with Small-for-Gestational-Age (SGA) status (aOR 4.30, 95% CI 2.48–7.45 and aOR 3.66, 95% CI 2.13–6.30 respectively). In conclusion, the 2009 IOM GWG recommendations, using either Caucasian or regional Asian BMI cut-offs, are applicable in a contemporary Malay majority South-East Asian cohort in terms of predicting abnormal neonatal adiposity. Importantly, the association with neonatal adiposity is independent of increased maternal insulin resistance characteristic of Asians. [ABSTRACT FROM AUTHOR]

Background:Klebsiella pneumoniae is a major opportunistic pathogen frequently associated with nosocomial infections, and often poses a major threat to immunocompromised patients. In our previous study, two K. pneumoniae (K36 and B13), which displayed resistance to almost all major antibiotics, including colistin, were isolated. Both isolates were not associated with infection and isolated from the stools of two preterm neonates admitted to the neonatal intensive care unit (NICU) during their first week of life. Materials and Methods: In this study, whole genome sequencing was performed on these two clinical multidrug resistant K. pneumoniae. We aimed to determine the genetic factors that underline the antibiotic-resistance phenotypes of these isolates. Results: The strains harbored blaSHV-27, blaSHV-71, and oqxAB genes conferring resistance to cephalosporins, carbapenems, and fluoroquinolones, respectively, but not harboring any known plasmid-borne colistin resistance determinants such as mcr-1. However, genome analysis discovered interruption of mgrB gene by insertion sequences gaining insight into the development of colistin resistance. Conclusion: The observed finding that points to a scenario of potential gut-associated resistance genes to Gram negative (K. pneumoniae) host in the NICU environment warrants attention and further investigation. [ABSTRACT FROM AUTHOR]

Objective: The first objective is to develop a nuchal thickness reference chart. The second objective is to compare rule-based algorithms and machine learning models in predicting small-for-gestational-age infants., Method: This retrospective study involved singleton pregnancies at University Malaya Medical Centre, Malaysia, developed a nuchal thickness chart and evaluated its predictive value for small-for-gestational-age using Malaysian and Singapore cohorts. Predictive performance using conjunctive (AND)/disjunctive (OR) rule-based algorithms was assessed. Seven machine learning models were trained on Malaysia data and evaluated on both Malaysia and Singapore cohorts., Results: 5519 samples were collected from the University Malaya Medical Centre. Small-for-gestational-age infants exhibit significantly lower nuchal thickness (small-for-gestational-age: 4.57 [1.04] mm, appropriate-for-gestational-age: 4.86 [1.06] mm, p < 0.001). Implementing disjunctive rule (nuchal thickness < 10th centile or estimated fetal weight < 10th centile) significantly improved small-for-gestational-age prediction across all growth charts, with balanced accuracy gains of 5.83% in Malaysia (p < 0.05) and 7.75% in Singapore. The best model for predicting small-for-gestational-age was: logistic regression with five variables (abdominal circumference, femur length, nuchal thickness, maternal age, and ultrasound-confirmed gestational age), which achieved an area under the curve of 0.75 for Malaysia cohorts; support vector machine with all variables, achieved area under the curve of 0.81 for Singapore cohorts., Conclusions: Small-for-gestational-age infants demonstrate significantly reduced second-trimester nuchal thickness. Employing the disjunctive rule enhanced small-for-gestational-age prediction. Logistic regression and support vector machines show superior performance among all models, highlighting the advantages of machine learning. Larger prospective studies are needed to assess clinical utility., (© 2025 John Wiley & Sons Ltd.)