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  1. Lau CF, Malek S, Gunalan R, Saw A, Milow P, Song C
    Health Informatics J, 2023;29(4):14604582231218530.
    PMID: 38019888 DOI: 10.1177/14604582231218530
    The paediatric orthopaedic expert system analyses and predicts the healing time of limb fractures in children using machine learning. As far we know, no published research on the paediatric orthopaedic expert system that predicts paediatric fracture healing time using machine learning has been published. The University Malaya Medical Centre (UMMC) offers paediatric orthopaedic data, comprises children under the age of 12 radiographs limb fractures with ages recorded from the date and time of initial trauma. SVR algorithms are used to predict and discover variables associated with fracture healing time. This study developed an expert system capable of predicting healing time, which can assist general practitioners and healthcare practitioners during treatment and follow-up. The system is available online at https://kidsfractureexpert.com/.
  2. Dhanoa A, Rajasekaram G, Hassan SS, Ramadas A, Azreen Adnan NA, Lau CF, et al.
    Platelets, 2017 Nov;28(7):724-727.
    PMID: 28287000 DOI: 10.1080/09537104.2017.1293802
    Severe thrombocytopenia is common in dengue virus (DENV) infections. However, studies focusing on the role of profound thrombocytopenia (PT) (nadir platelet counts ≤ 20 000/mm3) in DENV infections are scarce. This study aims to identify the associated features and outcome of DENV patients with PT. It involves 237 adult hospitalized patients who were DENV PCR positive. The presence of comorbidity (AOR = 4.625; 95% CI = 1.113-19.230), higher admission hematocrit (AOR = 1.213; 95% CI = 1.067-1.379), lower admission albumin (AOR = 0.870; 95% CI = 0.766-0.988) and lower admission platelets (AOR = 0.980; 95% CI = 0.969-0.991) was associated with platelets ≤ 20 000/mm3 in multivariate logistic regression. PT was not affected by DENV serotypes, coinfections and secondary DENV infections. Patients with PT had significantly higher risk of experiencing warning signs (AOR = 3.709, 95% CI = 1.089-12.634) and longer hospital stay (AOR = 1.943, 95% CI = 1.010-3.774). However, severe dengue disease, hemorrhagic manifestations and need for intensive care were not significantly associated with PT.
  3. Dhanoa A, Hassan SS, Ngim CF, Lau CF, Chan TS, Adnan NA, et al.
    BMC Infect Dis, 2016 08 11;16(1):406.
    PMID: 27514512 DOI: 10.1186/s12879-016-1731-8
    BACKGROUND: The co-circulation of 4 DENV serotypes in geographically expanding area, has resulted in increasing occurrence of DENV co-infections. However, studies assessing the clinical impact of DENV co-infections have been scarce and have involved small number of patients. This study explores the impact of DENV co-infection on clinical manifestations and laboratory parameters.

    METHODS: This retrospective study involved consecutive hospitalized patients with non-structural protein 1 (NS1) antigen positivity during an outbreak (Jan to April 2014). Multiplex RT-PCR was performed directly on NS1 positive serum samples to detect and determine the DENV serotypes. All PCR-positive serum samples were inoculated onto C6/36 cells. Multiplex PCR was repeated on the supernatant of the first blind passage of the serum-infected cells. Random samples of supernatant from the first passage of C6/36 infected cells were subjected to whole genome sequencing. Clinical and laboratory variables were compared between patients with and without DENV co-infections.

    RESULTS: Of the 290 NS1 positive serum samples, 280 were PCR positive for DENV. Medical notes of 262 patients were available for analysis. All 4 DENV serotypes were identified. Of the 262 patients, forty patients (15.3 %) had DENV co-infections: DENV-1/DENV-2(85 %), DENV-1/DENV-3 (12.5 %) and DENV-2/DENV-3 (2.5 %). Another 222 patients (84.7 %) were infected with single DENV serotype (mono-infection), with DENV- 1 (76.6 %) and DENV- 2 (19.8 %) predominating. Secondary dengue infections occurred in 31.3 % patients. Whole genome sequences of random samples representing DENV-1 and DENV-2 showed heterogeneity amongst the DENVs. Multivariate analysis revealed that pleural effusion and the presence of warning signs were significantly higher in the co-infected group, both in the overall and subgroup analysis. Diarrhoea was negatively associated with co-infection. Additionally, DENV-2 co-infected patients had higher frequency of patients with severe thrombocytopenia (platelet count < 50,000/mm(3)), whereas DENV-2 mono-infections presented more commonly with myalgia. Elevated creatinine levels were more frequent amongst the co-infected patients in univariate analysis. Haemoconcentration and haemorrhagic manifestations were not higher amongst the co-infected patients. Serotypes associated with severe dengue were: DENV-1 (n = 9), DENV-2 (n = 1), DENV-3 (n = 1) in mono-infected patients and DENV-1/DENV-2 (n = 5) and DENV-1/DENV-3 (n = 1) amongst the co-infected patients.

    CONCLUSION: DENV co-infections are not uncommon in a hyperendemic region and co-infected patients are skewed towards more severe clinical manifestations compared to mono-infected patients.

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