Creation and validation of the Singapore birth nomograms for birth weight, length and head circumference based on a 12-year birth cohort

<p><b>INTRODUCTION</b>Both gestation and birth weight have significant impact on mortality and morbidity in newborn infants. Nomograms at birth allow classification of infants into small for gestational age (SGA) and large for gestational age (LGA) categories, for risk stratification and more intensive monitoring. To date, the growth charts for preterm newborn infants in Singapore are based on the Fenton growth charts, which are constructed based on combining data from various Western growth cohorts. Hence, we aim to create Singapore nomograms for birth weight, length and head circumference at birth, which would reflect the norms and challenges faced by local infants.</p><p><b>MATERIALS AND METHODS</b>Growth parameters of all babies born or admitted to our unit from 2001 to 2012 were retrieved. Following exclusion of outliers, nomograms for 3 percentiles of 10th, 50th, and 90th were generated for the gestational age (GA) ranges of 25 to 42 weeks using quantile regression (QR) combined with the use of restricted cubic splines. Various polynomial models (second to third degrees) were investigated for suitability of fit. The optimum QR model was found to be a third degree polynomial with a single knotted cubic spline in the mid-point of the GA range, at 33.5 weeks. Check for goodness of fit was done by visual inspection first. Next, check was performed to ensure the correct proportion: 10% of all cases fall above the upper 90th percentile and 10% fall below the lower 10th percentile. Furthermore, an alternative formula-based method of nomogram construction, using mean, standard deviation (SD) and assumption of normality at each gestational age, was used for counterchecking.</p><p><b>RESULTS</b>A total of 13,403 newborns were included in the analysis. The new infant-foetal growth charts with respect to birth weight, heel-crown length and occipitofrontal circumference from 25 to 42 weeks gestations with the 10th, 50th and 90th were presented.</p><p><b>CONCLUSION</b>Nomograms for birth weight, length and head circumference at birth had significant impact on neonatal practice and validation of the Singapore birth nomograms against Fenton growth charts showed better sensitivity and comparable specificity, positive and negative predictive values.</p>

Obstructive sleep apnoea in Singapore: polysomnography data from a tertiary sleep disorders unit

<p><b>INTRODUCTION</b>Comprehensive sleep architecture and respiratory event data in local patients with suspected obstructive sleep apnoea (OSA) from overnight polysomnography (PSG), the gold standard for the evaluation of sleep-related breathing disorders, are not widely available. We present 1 year retrospective PSG data with the objective of describing PSG characteristics of patients evaluated for OSA in Singapore.</p><p><b>MATERIALS AND METHODS</b>PSG data of patients evaluated for OSA in 1 year (January through December 2005) in the Sleep Laboratory of a public tertiary hospital were retrospectively reviewed.</p><p><b>RESULTS</b>Five hundred and eighty-four diagnostic PSG studies were performed in patients with symptoms suggestive of sleep-disordered breathing, including snoring, excessive daytime sleepiness, unrefreshing sleep, or recurrent unexplained awakenings. There were 449 male patients (76.9%) and 135 female patients (23.1%), with a mean age of 47.5 years (SD 12.7). Men were on average younger than women, 46.1 years versus 52.0 years (P <0.0005). The mean body mass index (BMI) was 27.9 (SD 6.7), with no significant difference between genders. An association was shown between apnoea-hypopnoea index (AHI) and BMI (Pearson correlation index r = 0.362). Men had overall significantly higher AHI (16.5 vs 9), shorter mean sleep onset latency (11 vs 16.5 minutes), more light sleep (65.5% vs 58.9%), less deep sleep (17.7% vs 23%), and more respiratory event related arousals per hour of sleep (11.6 vs 5.1) (P <0.0005). Severity was classified: AHI <5 ("Normal Overall AHI") (28.3%), AHI 5-15 ("Mild") (22.3%), AHI >15-30 ("Moderate") (18.3%), AHI >30 ("Severe") (31.2%). There was no significant age difference among the 4 groups. More severe OSA patients were significantly heavier, and had more light sleep, less deep sleep, less REM sleep, more respiratory event related arousals and lower levels of oxygen desaturation.</p><p><b>CONCLUSION</b>OSA is predominant in middle-aged, overweight Singapore males and much less common in females who tend to be older. A majority of patients have moderate to severe OSA, which significantly disturbs normal sleep architecture. The relatively lower BMI compared to Caucasian OSA populations may be related to local craniofacial characteristics and/or higher percentage of body fat for BMI which has been described in Singaporeans.</p>