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  1. Ahmad Shahabuddin F, Wah KY, Buji RI, Zulkafli NS, Lee SW, Soon HL, et al.
    BJPsych Int, 2020 May;17(2):43-44.
    PMID: 32558818 DOI: 10.1192/bji.2019.29
    We used medical record abstraction to conduct research in a psychiatric hospital with paper-based medical records. The challenges we encountered included: the difficulty in retrieving files; the extensive effort and time needed to extract clinical information; the lack of a standardised documentation system of medical records; and the need for advanced computer literacy. To promote future research using electronic medical records, potential solutions include creating a registry of all patients receiving treatment, as well as equipping busy clinicians with computer skills.
  2. Buji RI, Abdul Murad NA, Chan LF, Maniam T, Mohd Shahrir MS, Rozita M, et al.
    Lupus, 2018 Apr;27(5):744-752.
    PMID: 29161964 DOI: 10.1177/0961203317742711
    Background Systemic lupus erythematosus (SLE) patients are a high-risk population for suicide. Glutamatergic neurosystem genes have been implicated in the neurobiology of depression in SLE and suicidal behaviour in general. However, the role of glutamate receptor gene polymorphisms in suicidal behaviour among SLE patients remains unclear in the context of established clinical and psychosocial factors. We aimed to investigate the association of NR2A gene polymorphism with suicidal ideation in SLE while accounting for the interaction between clinical and psychosocial factors. Methods A total of 130 SLE patients were assessed for mood disorders (MINI International Neuropsychiatric Interview), severity of depression (Patient Health Questionnaire-9), suicidal behaviour (Columbia-Suicide Severity Rating Scale), socio-occupational functioning (Work and Social Adjustment Scale), recent life events (Social Readjustment Rating Scale) and lupus disease activity (SELENA-SLE Disease Activity Index). Eighty-six out of the 130 study participants consented for NR2A genotyping. Results Multivariable logistic regression showed nominal significance for the interaction effect between the NR2A rs2072450 AC genotype and higher severity of socio-occupational impairment with lifetime suicidal ideation in SLE patients ( p = 0.038, odds ratio = 1.364, 95% confidence interval = 1.018-1.827). However, only the association between lifetime mood disorder and lifetime suicidal ideation remained significant after Bonferroni correction ( p 
  3. Levis B, Bhandari PM, Neupane D, Fan S, Sun Y, He C, et al.
    JAMA Netw Open, 2024 Nov 04;7(11):e2429630.
    PMID: 39576645 DOI: 10.1001/jamanetworkopen.2024.29630
    IMPORTANCE: Test accuracy studies often use small datasets to simultaneously select an optimal cutoff score that maximizes test accuracy and generate accuracy estimates.

    OBJECTIVE: To evaluate the degree to which using data-driven methods to simultaneously select an optimal Patient Health Questionnaire-9 (PHQ-9) cutoff score and estimate accuracy yields (1) optimal cutoff scores that differ from the population-level optimal cutoff score and (2) biased accuracy estimates.

    DESIGN, SETTING, AND PARTICIPANTS: This study used cross-sectional data from an existing individual participant data meta-analysis (IPDMA) database on PHQ-9 screening accuracy to represent a hypothetical population. Studies in the IPDMA database compared participant PHQ-9 scores with a major depression classification. From the IPDMA population, 1000 studies of 100, 200, 500, and 1000 participants each were resampled.

    MAIN OUTCOMES AND MEASURES: For the full IPDMA population and each simulated study, an optimal cutoff score was selected by maximizing the Youden index. Accuracy estimates for optimal cutoff scores in simulated studies were compared with accuracy in the full population.

    RESULTS: The IPDMA database included 100 primary studies with 44 503 participants (4541 [10%] cases of major depression). The population-level optimal cutoff score was 8 or higher. Optimal cutoff scores in simulated studies ranged from 2 or higher to 21 or higher in samples of 100 participants and 5 or higher to 11 or higher in samples of 1000 participants. The percentage of simulated studies that identified the true optimal cutoff score of 8 or higher was 17% for samples of 100 participants and 33% for samples of 1000 participants. Compared with estimates for a cutoff score of 8 or higher in the population, sensitivity was overestimated by 6.4 (95% CI, 5.7-7.1) percentage points in samples of 100 participants, 4.9 (95% CI, 4.3-5.5) percentage points in samples of 200 participants, 2.2 (95% CI, 1.8-2.6) percentage points in samples of 500 participants, and 1.8 (95% CI, 1.5-2.1) percentage points in samples of 1000 participants. Specificity was within 1 percentage point across sample sizes.

    CONCLUSIONS AND RELEVANCE: This study of cross-sectional data found that optimal cutoff scores and accuracy estimates differed substantially from population values when data-driven methods were used to simultaneously identify an optimal cutoff score and estimate accuracy. Users of diagnostic accuracy evidence should evaluate studies of accuracy with caution and ensure that cutoff score recommendations are based on adequately powered research or well-conducted meta-analyses.

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