METHODOLOGY: A cross-sectional study with a universal sampling of children and adolescents with special needs aged 2-18 years old, diagnosed with cerebral palsy, down syndrome, autism and attention-deficit/hyperactivity disorder was conducted at Community-Based Rehabilitation in Central Zone Malaysia. Socio-demographic data were obtained from files, and medical reports and anthropometric measurements (body weight, height, humeral length, and mid-upper arm circumference) were collected using standard procedures. Data were analysed using IBM SPSS version 26. The accuracy of the formula was determined by intraclass correlation, prediction at 20% of actual body weight, residual error (RE) and root mean square error (RMSE).
RESULT: A total of 502 children with a median age of 7 (6) years were enrolled in this study. The results showed that the Mercy formula demonstrated a smaller degree of bias than the Cattermole formula (PE = 1.97 ± 15.99% and 21.13 ± 27.76%, respectively). The Mercy formula showed the highest intraclass correlation coefficient (0.936 vs. 0.858) and predicted weight within 20% of the actual value in the largest proportion of participants (84% vs. 48%). The Mercy formula also demonstrated lower RE (0.3 vs. 3.6) and RMSE (3.84 vs. 6.56) compared to the Cattermole formula. Mercy offered the best option for weight estimation in children with special needs in our study population.
METHODS: We used relevant key words to search electronic databases to identify studies published up to 2019 that used receiver operating characteristic (ROC) curves for assessing the cut-off points of anthropometric indices. We used a random-effects model to pool study results and assessed between-study heterogeneity by using the I2 statistic and Cochran's Q test.
RESULTS: This meta-analysis included 38 cross-sectional and 2 cohort studies with 105 to 137,256 participants aged 18 or older. The pooled area under the ROC curve (AUC) value for BMI was 0.66 (95% CI, 0.63-0.69) in both men and women. The pooled AUC values for WC were 0.69 (95% CI, 0.67-0.70) in men and 0.69 (95% CI, 0.64-0.74) in women, and the pooled AUC values for WHR were 0.69 (95% CI, 0.66-0.73) in men and 0.71 (95% CI, 0.68-0.73) in women.
CONCLUSION: Our findings indicated a slight difference between AUC values of these anthropometric indices. However, indices of abdominal obesity, especially WHR, can better predict CVD occurrence.
METHODS: This cross-sectional study was carried out on 293 patients without a prior history of diabetes at a primary care clinic in Malaysia. Questions on body mass index and waist circumference were modified based on the Asian standard in ModAsian FINDRISC. Haemoglobin A1c of ≥6.5% (48 mmol/mol) was used to diagnose diabetes. Areas under the receiver operating curve (ROC-AUC) for FINDRISC and ModAsian FINDRISC were analyzed.
RESULTS: The prevalence of undiagnosed diabetes was 7.5% and prediabetes was 32.8%. The ROC-AUC of FINDRISC was 0.76 (undiagnosed diabetes) and 0.79 (dysglycaemia). There was no statistical difference between FINDRISC and ModAsian FINDRISC. The recommended optimal FINDRISC cut-off point for undiagnosed diabetes was ≥11 (Sensitivity 86.4%, Specificity 48.7%). FINDRISC ≥11 point has higher sensitivity compared to USPSTF criteria (72.7%) and higher specificity compared to the ADA (9.6%).
CONCLUSIONS: FINDRISC is a useful diabetes screening tool to identify those at risk of diabetes in primary care in Malaysia.
MATERIALS AND METHODS: Nineteen linear facial measurements were derived from 16 standardized surface landmarks obtained from 37 cleft patients (20 males, 17 females; mean age 23.84 years, standard deviation ± 6.02). They were taken manually with calipers and were compared with the digitally calculated distance on the 3D images captured using the VECTRA-M5 360° Imaging System with pre-marked landmarks. Another pair of 19 linear measurements were computed on the 3D images 2 weeks apart for intra- and inter-observer agreements. Statistical analyses used were paired t test, the Bland-Altman analysis, and the intra-class correlation coefficient (ICC) index.
RESULTS: Most of the linear measurements showed no statistically significant differences between the proposed method and direct anthropometry linear measurements. Nevertheless, bias of the 3D imaging system is present in the linear measurements of the nose width and the upper vermillion height. The measurements' mean biases were within 2 mm, but the 95% limit of agreement was more than 2 mm. Intra- and inter-observer measurements generally showed good reproducibility. Four inter-observer measurements, the upper and lower face heights, nose width, and pronasale to left alar base were clinically significant.
CONCLUSIONS: Measurements obtained from this 3D imaging system are valid and reproducible for evaluating CLP patients.
CLINICAL RELEVANCE: The system is suitable to be used in a clinical setting for cleft patients. However, training of the operator is strictly advisable.
Materials and Methods: A retrospective study analysed 120 adult patients operated between 2014-2017 using modified short PFN for intertrochanteric fractures, having a minimum follow-up of 12 months. Clinical and radiological parameters including tip-apex distance (TAD), position of tip of lag screw in femoral head, lateral slide of lag screw as well as length of anti-rotation screw were measured. Final functional outcome was assessed using Barthel's index and Kyle's criteria.
Results: Good reduction was achieved in 90.83% cases and 79.16% had ideal placement of lag screw in femoral head. Intra-operative difficulties were encountered in 13.33% (n=16). Mean TAD AP (anteroposterior) was 11.8mm, TAD LAT (lateral) was 11.0mm and mean TAD TOT was 22.8mm. Overall mean lateral slide was 3.20mm and it was more in unstable fracture. We had five mechanical failures, one patient with screw breakage without loss of reduction and two peri-implant fractures after union. 81.66% returned to pre-injury levels of activity with 88.33% good to excellent outcome as per Kyle's criteria.
Conclusion: Although, not devoid of complications, modified short PFN results in good functional recovery of patients with intertrochanteric fractures of femur.
DESIGN & PARTICIPANTS: 332 mothers (197 NGTF, 56 SGTF-U, 79 SGTF-T) aged 41.2±5.3 years (mean±SD) and 326 paired children assessed 9.3±1.0 years after birth for (i) body mass index (BMI); (ii) lean, fat, and bone mass by dual-energy X-ray absorptiometry; (iii) blood pressure, augmentation index, and aortic pulse-wave-velocity; and (iv) thyroid function, lipids, insulin, and adiponectin. The difference between group means was compared using linear regression.
RESULTS: Offspring's measurements were similar between groups. Although maternal BMI was similar between groups at CATS-I, after 9 years (at CATS-II) SGTF-U mothers showed higher BMI (median [interquartile ratio] 28.3 [24.6-32.6] kg/m2) compared with NGTF (25.8 [22.9-30.0] kg/m2; P = 0.029), driven by fat mass increase. At CATS-II SGTF-U mothers also had higher thyroid-stimulating hormone (TSH) values (2.45 [1.43-3.50] mU/L) than NGTF (1.54 [1.12-2.07] mU/L; P = 0.015), since 64% had never received levothyroxine. At CATS-II, SGTF-T mothers had BMI (25.8 [23.1-29.8] kg/m2, P = 0.672) and TSH (1.68 [0.89-2.96] mU/L; P = 0.474) values similar to NGTF mothers.
CONCLUSIONS: Levothyroxine supplementation of women with SGTF did not affect long-term offspring anthropometric, bone, and cardiometabolic measurements. However, absence of treatment was associated with sustained long-term increase in BMI and fat mass in women with SGTF.
METHODS: A total of 109 (64 males and 45 females) aged 0-12 in Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) took part in this study. They underwent ultrasonography of both kidneys, and their demographic and anthropometric data were collected. The mean and standard deviations of the renal length and renal volume according to their age groups was calculated, and the final data was compared to the ones reported by Rosenbaum et al. (1984).
RESULT: Body weight and Body Surface Area (BSA) of the children reported the strongest correlation with renal size. Significant differences were found between local and the data from Rosenbaum et al (1984). A nomogram on paediatric renal size based on children in PPUKM was then created.
DISCUSSION: Ultrasonography is regarded as the standard method for determining renal size. Body weight and BSA were both strongly correlated with renal size. It was shown that the widely used nomograms derived from data obtained from Caucasian was not suitable to represent the population of Malaysian children.
METHODS: A cross-sectional study was performed in 150 children aged 12-36 months.
EXCLUSION CRITERIA: recurrent infections, moderate to severe asthma, recent systemic steroid, other diseases affecting growth/nutrition. Growth parameters, SCORing Atopic Dermatitis (SCORAD), hemoglobin, hematocrit, sodium, potassium, albumin, protein, calcium, phosphate, B12, iron, and folate values were determined. Parents completed a 3-day food diary.
RESULTS: The prevalence of food restriction was 60.7%. Commonly restricted foods were shellfish 62.7%, nuts 53.3%, egg 50%, dairy 29.3%, and cow's milk 28.7%. Food-restricted children have significantly lower calorie, protein, fat, riboflavin, vitamin B12, calcium, phosphorus and iron intakes and lower serum iron, protein and albumin values. Z scores of weight-for-age (-1.38 ± 1.02 vs -0.59 ± 0.96, P = .00), height-for-age (-1.34 ± 1.36 vs -0.51 ± 1.22, P = .00), head circumference-for-age (-1.37 ± 0.90 vs -0.90 ± 0.81, P = .00), mid-upper arm circumference (MUAC)-for-age (-0.71 ± 0.90 vs -0.22 ± 0.88, P = .00), and BMI-for-age (-0.79 ± 1.15 vs -0.42 ± 0.99, P = .04) were significantly lower in food-restricted compared to non-food-restricted children. More food-restricted children were stunted, underweight with lower head circumference and MUAC. Severe disease was an independent risk factor for food restriction with OR 5.352; 95% CI, 2.26-12.68.
CONCLUSION: Food restriction is common in children with AD. It is associated with lower Z scores for weight, height, head circumference, MUAC, and BMI. Severe disease is an independent risk factor for food restriction.
Methods: A total of 413 individuals (163 men and 250 women) aged 30-60 years were selected by stratified random sampling. The participants had safe alcohol consumption habits (<2 drinks/day) and no symptoms of hepatitis B and C. NAFLD was diagnosed through ultrasound. Blood pressure, anthropometric, and body composition measurements were made and liver function tests were conducted. Biochemical assessments, including the measurement of fasting blood sugar (FBS) and ferritin levels, as well as lipid profile tests were also performed. Metabolic syndrome was evaluated according to the International Diabetes Federation (IDF) criteria.
Results: The overall prevalence of ultrasound-diagnosed NAFLD was 39.3%. The results indicated a significantly higher prevalence of NAFLD in men than in women (42.3% vs 30.4%; P < 0.05). Binary logistic regression analysis was performed to determine the significant variables as NAFLD predictors. Overall, male gender, high body mass index (BMI), high alanine aminotransferase (ALT), high FBS, and high ferritin were identified as the predictors of NAFLD. The only significant predictors of NAFLD among men were high BMI and high FBS. These predictors were high BMI, high FBS, and high ferritin in women (P < 0.05 for all variables).
Conclusions: The metabolic profile can be used for predicting NAFLD among men and women. BMI, FBS, ALT, and ferritin are the efficient predictors of NAFLD and can be used for NAFLD screening before liver biopsy.