Publications by authors named "A C Ong"

The Kidney Disease: Improving Global Outcomes (KDIGO) 2025 Clinical Practice Guideline for the Evaluation, Management, and Treatment of Autosomal Dominant Polycystic Kidney Disease (ADPKD) represents the first KDIGO guideline on this subject. Its scope includes nomenclature, diagnosis, prognosis, and prevalence; kidney manifestations; chronic kidney disease (CKD) management and progression, kidney failure, and kidney replacement therapy; therapies to delay progression of kidney disease; polycystic liver disease; intracranial aneurysms and other extrarenal manifestations; lifestyle and psychosocial aspects; pregnancy and reproductive issues; pediatric issues; and approaches to the management of people with ADPKD. The guideline has been developed with patient partners, clinicians, and researchers around the world, with the goal to generate a useful resource for healthcare providers and patients by providing actionable recommendations.

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Introduction: It is unclear if intracranial pressure monitoring (ICPM) after open cranial procedures (craniotomy or craniectomy) (OC) for traumatic brain injury is associated with mortality. We hypothesized that ICPM placed early after OC was associated with lower mortality compared to no ICPM or delayed ICPM placement.

Methods: Using 2020-2021 data from the American College of Surgeons Trauma Quality Improvement Program, patients ≥16 y from level 1 and 2 trauma centers who underwent OC were divided into two groups: ICPM placed within 72 h of OC (early) and no ICPM or ICPM placed after 72 h (none/delayed).

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Background: TikTok is a global social media platform with over 1 billion active users. Presently, there are few data on how TikTok users navigate the platform for mental health purposes and the content they view.

Objective: This study aims to understand the patterns of mental health-related content on TikTok and assesses the accuracy and quality of the advice and information provided.

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Intensive longitudinal data, increasingly common in social and behavioral sciences, often consist of multivariate time series from multiple individuals. Dynamic factor analysis, combining factor analysis and time series analysis, has been used to uncover individual-specific processes from single-individual time series. However, integrating these processes across individuals is challenging due to estimation errors in individual-specific parameter estimates.

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