Publications by authors named "Kayvan Aflaki"
Article Synopsis
- - The study aimed to identify factors related to maternal deaths around pregnancy by analyzing coroner's data in Ontario, Canada, from 2004 to 2020.
- - Researchers found three distinct groups of maternal deaths: those occurring in hospitals during or shortly after birth (52.7%), those from accidents or complications (26.3%), and postpartum suicides (21.0%).
- - Key causes of death included physical injury (22.0%), hemorrhage (16.8%), and overdose (13.3%), suggesting these findings could help improve clinical practices and policies to reduce maternal mortality.
Maternal mortality is the death of a woman while pregnant or within 42 days of the end of pregnancy. Late maternal deaths are from 42 to 365 days thereafter. Maternal mortality is an important surrogate indicator of a woman's overall health, social and economic status, and the provision of antenatal and emergency obstetric care at regional and national levels.
View Article and Find Full Text PDFThis article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal).
View Article and Find Full Text PDFLatent class analysis (LCA) is an analytical approach for the identification of more homogeneous subgroups within an otherwise dissimilar patient population. In the current paper, Part II, we present a practical step-by-step guide for LCA of clinical data, including when LCA might be applied, selecting indicator variables, and choosing a final class solution. We also identify common pitfalls of LCA, and related solutions.
View Article and Find Full Text PDFLatent Class Analysis (LCA) is an analytical approach for the identification of more homogeneous subgroups within an otherwise dissimilar patient population. In the current paper, Part II, we present a practical step-by-step guide for LCA of clinical data, including when LCA might be applied, selecting indicator variables, and choosing a final class model. We also identify some common pitfalls of LCA, and some related solutions.
View Article and Find Full Text PDFLatent class analysis (LCA) offers a powerful analytical approach for categorizing groups (or "classes") within a heterogenous population. LCA identifies these hidden classes by a set of predefined features, known as "indicators". Unlike many other grouping analytical approaches, LCA derives classes using a probabilistic approach.
View Article and Find Full Text PDFBackground: Accurate identification of maternal deaths is paramount for audit and policy purposes. Our aim was to determine the accuracy and completeness of data on maternal deaths in hospital and those recorded on a death certificate, and the level of agreement between the 2 data sources.
Methods: We conducted a retrospective population-based study using data for Ontario, Canada, from Apr.