Population-based Study Comparing Predictors of Ischemic Stroke Recurrence After Index Ischemic Stroke in Non-elderly Adults with or without Diabetes

Elhefnawy, Marwa Elsaeed; Ghadzi, Siti Maisharah Sheikh; Tangiisuran, Balamurugan; Zainal, Hadzliana; Looi, Irene; Ibrahim, Khairul Azmi; Sidek, Norsima Nazifah; Loo, Keat Wei; Lee, Keng Yee; Aziz, Zariah Abdul; Harun, Sabariah Noor

doi:10.2147/ijgm.s303641

Cited by 6 publications

(4 citation statements)

References 33 publications

(15 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, IHD, HPLD, and HTN were identi ed as independent predictors for recurrent IS. These ndings are consistent with data reported previously (20)(21)(22)(23). Additionally, this model quanti ed the hazard of having recurrent IS between the patients who have a history of HPLD, IHD, and HTN.…”

Section: Discussionsupporting

confidence: 91%

See 1 more Smart Citation

Predictor Naïve Temporal Baseline Hazard of Recurrent Ischemic Stroke

Elhefnawy

Ghadzi

Albitar

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

There are established correlation between risk factors and the recurrence of ischemic stroke (IS), however does the hazard of recurrent IS change although without the influence of established risk factors? This study aimed to quantify the hazard of recurrent IS at different time points after the index IS. This was a population cohort study extracted data of 7697 patients with a history of first IS attack registered with National Neurology Registry of Malaysia. A repeated time to recurrent IS model was developed using NONMEM version 7.5. Three baseline hazard models were fitted into the data. The best model was selected using maximum likelihood estimation, clinical plausibility and visual predictive checks. Three hundred and thirty-three (4.32%) patients developed at least one recurrent IS within the maximum 7.37 years follow-up. In the absence of significant risk factors, the hazard of recurrent IS was predicted to be 0.71 within the first month after the index IS and reduced to 0.022 between the first to third months after the index attack. The hazard of IS recurrence accelerated with the presence of typical risk factors such as hyperlipidaemia (HR, 2.64 [2.10-3.33]), hypertension (HR, 1.97 [1.43-2.72], and ischemic heart disease (HR, 2.21 [1.69-2.87]). In conclusion, the absence of significant risk factors, predicted hazard of recurrent IS was prominent in the first month after the index IS and was non-zero even three months after the index IS or later. Optimal secondary preventive treatment should incorporate the ‘nature risk’ IS recurrence.

show abstract

Section: Discussionsupporting

confidence: 91%

“…Data of all Malaysian patients with a history of index IS from August 2009 to December 2016 were extracted from the NNEUR of Malaysia. The details on the National Stroke Registry of Malaysia were published previously (21)(22)(23). The stroke was diagnosed according to the World Health Organization's criteria (24).…”

Section: Patients and Data Acquisitionmentioning

confidence: 99%

Predictor Naïve Temporal Baseline Hazard of Recurrent Ischemic Stroke

Elhefnawy

Ghadzi

Albitar

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…This study is considered a secondary analysis of the data from the Malaysian NNEUR. The information on the Malaysian National Stroke Registry was included in previously published papers [ 9 , 10 , 17 ]. DM was identified in the registry database either by physician diagnosis, antidiabetic medication history, patients’ electronic records, or the antidiabetic medications prescribed during discharge.…”

Section: Methodsmentioning

confidence: 99%

A Parametric Time-to-Event Modelling of Recurrent Ischemic Stroke After Index Stroke Among Patients With and Without Diabetes Mellitus: Implementation of Temporal Validation of the Model

Elhefnawy,

Noor Harun,

Leykhim

et al. 2023

Cureus

Self Cite

View full text Add to dashboard Cite

Objectives Compared with the first stroke, neurological impairment caused by stroke recurrence is more serious, more difficult to treat, and has a higher mortality rate, especially among ischemic stroke (IS) patients with diabetes mellitus (DM). Although there are established correlations between factors and IS recurrence, there were some issues regarding the naive hazard of IS recurrence with no risk factor influence, and how does the baseline hazard differ among patients with DM and non-DM? To answer all these questions, two time-to-event (TTE) models of recurrent IS after the index IS were developed among IS patients with DM and non-DM. Method A total of 7697 patients with an index IS attack were extracted from the Malaysian Registry of Neurology and stratified according to DM status. Several parametric survival models were evaluated using nonlinear mixed-effect modeling software (NONMEM 7.5). The final model was determined according to the lowest objective function value, graphical evaluation, numerical diagnostics, and clinical plausibility. Additionally, the final model was validated internally and temporally using Kaplan-Meier visual predictive checks (KM-VPCs). Results One hundred ninety-five (5.82%) of 3493 DM patients and 138 (3.28%) of 4204 non-DM patients developed a recurrent IS with a maximum follow-up of 7.37 years. Gompertz’s model best fitted the data. With no influence on risk factors, the index IS attack was predicted to contribute to the hazard of recurrent IS by 0.356 and 0.253 within the first six months after the index IS among patients with and without DM, respectively. Even after six months of index IS, the recurrent IS baseline hazard was not equal to zero among both groups (0.0023, 0.0018). Moreover, after incorporating the time and risk factors, the recurrent hazards increased exponentially during the first three years after the index IS followed by an exponential reduction afterward. The recurrent IS predictors among DM patients were ischemic heart disease (IHD) and hyperlipidemia (HPLD). IHD and HPLD increased the hazard of recurrent IS by 2.40 and 1.88 times, respectively, compared to those without IHD and HPLD before index IS (HR, 2.40 (1.79-3.20)), and (HR, 1.88 (1.44-2.45)) respectively. Conclusion The baseline hazard was the highest during the first six months after the index IS. Moreover, receiving medications for secondary prevention failed to demonstrate a significant association with reducing IS recurrence among IS patients with DM, suggesting a need for more intensive patient screening and new strategies for secondary prevention among IS patients with DM.

show abstract

“…Stroke is considered as one of the cerebrovascular accidents and is the third-leading cause of disability and accounted for over 6 million deaths worldwide in 2015 [51]. Diabetes is associated with an increased risk of subsequent strokes [52,53], greater functional disability, longer hospital stays, and increased mortality [54][55][56]. A higher risk of developing stroke-related dementia has also been reported in the diabetic population [57].…”

Section: Ischemic Strokementioning

confidence: 99%

Predictors Associated with Type 2 Diabetes Mellitus Complications over Time: A Literature Review

Elhefnawy

Ghadzi

Harun

2022

JVD

Self Cite

View full text Add to dashboard Cite

Early detection of type 2 diabetes mellitus (T2DM) complications is essential to prevent disability and death. Risk prediction models are tools to estimate the probability that an individual with specific risk factors will develop a future condition within a certain time period. A predictive model that incorporates time to quantify the risk of T2DM complications such as cardiovascular diseases (CVD) event is still lacking. Well-established and validated predictive models of T2D complications are vital to stratify patients based on their risks; thus, individualization therapy could be optimized. New approaches (e.g., the parametric approach) are needed in developing predictive models of T2DM complications by incorporating new and time-varying predictors that may improve the existing models’ predictive ability. This review aimed (1) to summarize the reported predictors for the five main complications of T2DM, which include cardiovascular diseases, ischemic stroke, diabetic nephropathy, diabetic neuropathy, and diabetic retinopathy, and (2) to highlight the persistent need for future risk score models as screening tools for the early prevention of T2D complications.

show abstract

Population-based Study Comparing Predictors of Ischemic Stroke Recurrence After Index Ischemic Stroke in Non-elderly Adults with or without Diabetes

Cited by 6 publications

References 33 publications

Predictor Naïve Temporal Baseline Hazard of Recurrent Ischemic Stroke

Predictor Naïve Temporal Baseline Hazard of Recurrent Ischemic Stroke

A Parametric Time-to-Event Modelling of Recurrent Ischemic Stroke After Index Stroke Among Patients With and Without Diabetes Mellitus: Implementation of Temporal Validation of the Model

Predictors Associated with Type 2 Diabetes Mellitus Complications over Time: A Literature Review

Contact Info

Product

Resources

About