METHODS: A cross-sectional study was conducted at 11 paediatric endocrine units in Malaysia. Blood samples for antithyroglobulin antibodies, antithyroid peroxidase antibodies and thyroid function test were obtained. In patients with pre-existing thyroid disease, information on clinical and biochemical thyroid status was obtained from medical records.
RESULTS: Ninety-seven TS patients with a mean age of 13.4 ± 4.8 years were recruited. Thyroid autoimmunity was found in 43.8% of TS patients. Nineteen per cent of those with thyroid autoimmunity had autoimmune thyroid disease (Hashimoto thyroiditis in 7.3% and hyperthyroidism in 1% of total population). Patients with isochromosome X and patients with 45,X mosaicism or other X chromosomal abnormalities were more prone to have thyroid autoimmunity compared to those with 45,X karyotype (OR 5.09, 95% CI 1.54-16.88, P = 0.008 and OR 3.41, 95% CI 1.32-8.82, P = 0.01 respectively). The prevalence of thyroid autoimmunity increased with age (33.3% for age 0-9.9 years; 46.8% for age 10-19.9 years and 57.1% age for 20-29.9 years) with autoimmune thyroid disease detected in 14.3% during adulthood.
CONCLUSION: Thyroid autoimmunity was significantly associated with the non 45,X karyotype group, particularly isochromosome X. Annual screening of thyroid function should be carried out upon diagnosis of TS until adulthood with more frequent monitoring recommended in the presence of thyroid autoimmunity.
METHODS: Two hundred and twenty sets of radiographs of the spine and the left hand and wrist of patients with idiopathic scoliosis were assessed for skeletal maturity and reliability testing. Risser staging, Sanders staging (SS), distal radius and ulna (DRU) classification, the proximal humeral ossification system (PHOS), and the novel proximal femur maturity index (PFMI) were used. The PFMI was newly developed on the basis of the radiographic appearances of the femoral head, greater trochanter, and triradiate cartilage. It consists of 7 grades (0 to 6) associated with increasing skeletal maturity. The PFMI was evaluated through its relationship with pubertal growth (i.e., the rate of changes of standing and sitting body height [BH] and arm span [AS]) and with established skeletal maturity indices. Longitudinal growth data and 780 corresponding spine radiographs were assessed to detect peak growth using receiver operating characteristic (ROC) curve analysis.
RESULTS: The PFMI was found to be correlated with chronological age (τb = 0.522), growth rates based on standing BH (τb = -0.303), and AS (τb = -0.266) (p < 0.001 for all). The largest growth rate occurred at PFMI grade 3, with mean standing BH growth rates (and standard deviations) of 0.79 ± 0.44 cm/month for girls and 1.06 ± 0.67 cm/mo for boys. Growth rates of 0.12 ± 0.23 cm/mo (girls) and 0 ± 0 cm/mo (boys) occurred at PFMI grade 6, indicating growth cessation. Strong correlations were found between PFMI gradings and Risser staging (τb = 0.743 and 0.774 for girls and boys), Sanders staging (τb = 0.722 and 0.736, respectively), and radius (τb = 0.792 and 0.820) and ulnar gradings (τb = 0.777 and 0.821), and moderate correlations were found with PHOS stages (τb = 0.613 and 0.675) (p < 0.001 for all). PFMI gradings corresponded to as young as SS1, R4, U1, and PHOS stage 1. Fair to excellent interrater and intrarater reliabilities were observed. PFMI grade 3 was most prevalent and predictive for peak growth based on ROC results.
CONCLUSIONS: The PFMI demonstrated clear pubertal growth phases with satisfactory reliability. Grade 3 indicates peak growth and grade 6 indicates growth cessation.
CLINICAL RELEVANCE: The use of PFMI can benefit patients by avoiding additional radiation in skeletal maturity assessment and can impact current clinical protocol of patient visits. PFMI gradings had strong correlations with SS, DRU gradings, and Risser staging, and they cross-referenced to their established grades at peak growth and growth cessation. PFMI may aid in clinical decision making.
Methods: We conducted a retrospective study of culture-confirmed melioidosis among adults admitted to Bintulu Hospital in Sarawak, Malaysia, from January 2011 until December 2016.
Results: One hundred forty-eight adults with culture-confirmed melioidosis were identified. Of 129 (87%) tested, 84 (65%) had gentamicin-susceptible B pseudomallei. The average annual incidence of melioidosis was 12.3 per 100 000 population, with marked variation between districts ranging from 5.8 to 29.3 per 100 000 population. Rural districts had higher incidences of melioidosis and overwhelmingly larger proportions of gentamicin-susceptible B pseudomallei infection. Significantly more patients with gentamicin-susceptible infection had no identified risk factors, with diabetes less frequently present in this group. Ninety-eight percent had acute presentations. Pneumonia, reported in 71%, was the most common presentation. Splenic abscesses were found in 54% of those imaged. Bacteremia was present in 88%; septic shock occurred in 47%. Forty-five (35%) patients died. No differences in clinical, laboratory, or outcome characteristics were noted between gentamicin-susceptible and gentamicin-resistant infections.
Conclusions: Gentamicin-susceptible B pseudomallei infections are common in Sarawak and dominate in the high-incidence rural interior regions. Clinical manifestations and outcomes are the same as for gentamicin-resistant B pseudomallei infections. Further studies are required to determine if all gentamicin-susceptible B pseudomallei infections in Sarawak are clonal and to ascertain their environmental drivers and niches.
Case presentation: A 29-year-old man presented with pneumonia and melioidosis septicaemia. His condition was complicated with infective endocarditis and septic emboli to the brain. Despite difficulties in reaching a diagnosis, the patient was successfully treated using intravenous gentamicin and ceftazidime and was discharged well.
Discussion: The role of gentamicin in the treatment of the gentamicin-susceptible strain of B. pseudomallei remains unclear.
METHODS: A part prospective, part retrospective study of children aged <15 years with culture-confirmed melioidosis was conducted in the 3 major public hospitals in Central Sarawak between 2009 and 2014. We examined epidemiological, clinical and microbiological characteristics.
FINDINGS: Forty-two patients were recruited during the 6-year study period. The overall annual incidence was estimated to be 4.1 per 100,000 children <15 years, with marked variation between districts. No children had pre-existing medical conditions. Twenty-three (55%) had disseminated disease, 10 (43%) of whom died. The commonest site of infection was the lungs, which occurred in 21 (50%) children. Other important sites of infection included lymph nodes, spleen, joints and lacrimal glands. Seven (17%) children had bacteremia with no overt focus of infection. Delays in diagnosis and in melioidosis-appropriate antibiotic treatment were observed in nearly 90% of children. Of the clinical isolates tested, 35/36 (97%) were susceptible to gentamicin. Of these, all 11 isolates that were genotyped were of a single multi-locus sequence type, ST881, and possessed the putative B. pseudomallei virulence determinants bimABp, fhaB3, and the YLF gene cluster.
CONCLUSIONS: Central Sarawak has a very high incidence of pediatric melioidosis, caused predominantly by gentamicin-susceptible B. pseudomallei strains. Children frequently presented with disseminated disease and had an alarmingly high death rate, despite the absence of any apparent predisposing risk factor.
RESULTS: Our models learned several syntactic, lexical, and n-gram linguistic biomarkers to distinguish the probable AD group from the healthy group. In contrast to the healthy group, we found that the probable AD patients had significantly less usage of syntactic components and significantly higher usage of lexical components in their language. Also, we observed a significant difference in the use of n-grams as the healthy group were able to identify and make sense of more objects in their n-grams than the probable AD group. As such, our best diagnostic model significantly distinguished the probable AD group from the healthy elderly group with a better Area Under the Receiving Operating Characteristics Curve (AUC) using the Support Vector Machines (SVM).
CONCLUSIONS: Experimental and statistical evaluations suggest that using ML algorithms for learning linguistic biomarkers from the verbal utterances of elderly individuals could help the clinical diagnosis of probable AD. We emphasise that the best ML model for predicting the disease group combines significant syntactic, lexical and top n-gram features. However, there is a need to train the diagnostic models on larger datasets, which could lead to a better AUC and clinical diagnosis of probable AD.