Stroke risk factors, subtypes and outcome in elderly Thai patients

Samuthpongtorn, Chatpol; Jereerat, Tul; Suwanwela, Nijasri C.

doi:10.1186/s12883-021-02353-y

Cited by 18 publications

(14 citation statements)

References 18 publications

(19 reference statements)

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“…Predicting long-term mortality can help guide decisions about ongoing medical management, such as the use of secondary prevention measures, and can also inform discussions about end-of-life care. Several features have been identified that are strongly associated with death in patients with ischemic stroke, namely, age (4)(5)(6), underlying dementia (7), underlying cancer (5,6), white blood cells (WBC) (6), anion gap (AG) (8), mechanical ventilation (MV) (9), and osmotic therapy (10).…”

Section: Introductionmentioning

confidence: 99%

Prediction of long-term mortality in patients with ischemic stroke based on clinical characteristics on the first day of ICU admission: An easy-to-use nomogram

Jin

Zeng

et al. 2023

Front. Neurol.

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BackgroundThis study aimed to establish and validate an easy-to-use nomogram for predicting long-term mortality among ischemic stroke patients.MethodsAll raw data were obtained from the Medical Information Mart for Intensive Care IV database. Clinical features associated with long-term mortality (1-year mortality) among ischemic stroke patients were identified using least absolute shrinkage and selection operator regression. Then, binary logistic regression was used to construct a nomogram, the discrimination of which was evaluated by the concordance index (C-index), integrated discrimination improvement (IDI), and net reclassification index (NRI). Finally, a calibration curve and decision curve analysis (DCA) were employed to study calibration and net clinical benefit, compared to the Glasgow Coma Scale (GCS) and the commonly used disease severity scoring system.ResultsPatients who were identified with ischemic stroke were randomly assigned into developing (n = 1,443) and verification (n = 646) cohorts. The following factors were associated with 1-year mortality among ischemic stroke patients, including age on ICU admission, marital status, underlying dementia, underlying malignant cancer, underlying metastatic solid tumor, heart rate, respiratory rate, oxygen saturation, white blood cells, anion gap, mannitol injection, invasive mechanical ventilation, and GCS. The construction of the nomogram was based on the abovementioned features. The C-index of the nomogram in the developing and verification cohorts was 0.820 and 0.816, respectively. Compared with GCS and the commonly used disease severity scoring system, the IDI and NRI of the constructed nomogram had a statistically positive improvement in predicting long-term mortality in both developing and verification cohorts (all with p < 0.001). The actual mortality was consistent with the predicted mortality in the developing (p = 0.862) and verification (p = 0.568) cohorts. Our nomogram exhibited greater net clinical benefit than GCS and the commonly used disease severity scoring system.ConclusionThis proposed nomogram has good performance in predicting long-term mortality among ischemic stroke patients.

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Section: Introductionmentioning

confidence: 99%

Prediction of long-term mortality in patients with ischemic stroke based on clinical characteristics on the first day of ICU admission: An easy-to-use nomogram

Jin

Zeng

et al. 2023

Front. Neurol.

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“…More than 85% of all strokes occur in populations over 65 years old, while 72% occur in those ≥75 years [4]. Patients <65 years are reported to present with less severe stroke and better outcomes when compared to ≥75 years of age group [5,6]. This finding suggests that specific age-related risk factors may differentially contribute to stroke severity in patients 65 and 74 years old when compared with those ≥75 years.…”

Section: Introductionmentioning

confidence: 98%

“…However, how HF and other risk factors contribute to stroke severity in older patients is not fully understood. This is because most studies regarding stroke in the elderly population did not differentiate between risk factors associated with 65-74 years old patients where the stroke is reported to be less severe compared with ≥75 where stroke severity is higher [5,6].…”

Section: Introductionmentioning

confidence: 99%

Age Stratification in Acute Ischemic Stroke Patients with Heart Failure

Edrissi

Rathfoot

Knisely

et al. 2022

JCM

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Background and Purpose. Heart failure (HF) is considered one of the major risk factors associated with the severity of acute ischemic stroke(AIS). The risk factors associated with stroke severity in AIS with a history of HF is not fully understood. Methods. A prospectively maintained database from comprehensive stroke centers in PRISMA Health Upstate Sc, was analyzed for patients with AIS and a history of HF from January 2010 to 30 June 2016. The primary outcome was risk factors associated with a National Institute of Health Stroke Scale score (NIHSS) < 7 indicating lower severity and a score ≥ 7 indicating high severity for 65–74 age category and ≥75 years age category for AIS-HF patients. Univariate analysis was used to determine risk factors based on age categories and stroke severities, while multivariable analysis was used to adjust for the effect of confounding variables. Results: A total 367 AIS-HF patients were identified in this study, 113 patients were between 65–74 years old, while 254 patients were in the ≥75 years old age category. In the adjusted analysis for 65–74 age category, history of smoking (OR = 0.105, 95% Confidence interval (CI): 0.018–0.614, p = 0.012), triglycerides (Odd ratio(OR) = 0.993, 95% (CI): 0.987–0.999, p = 0.019), and International Normalized Ratio (INR) (OR = 0.454, 95% CI: 0.196–1.050, p = 0.045), and direct admission treatment (OR = 0.355, 95% CI: 0.137–0.920, p = 0.033) were associated with a lower stroke severity, elevated heart rate (OR = 1.032, 95% CI: 1.009–1.057, p = 0.007) was associated with a higher stroke severity. For the ≥75 years old age category, previous stroke (OR = 2.297, 95% CI: 1.171–9.852, p = 0.024), peripheral vascular disease (OR = 6.784, 95% CI: 1.242–37.065, p = 0.027), heart rate (OR = 1.035, 95% CI: 1.008–1.063, p = 0.012), and systolic blood pressure (OR = 1.023, 95% CI: 1.005–1.041, p = 0.012) were associated with a higher severe stroke severity. Conclusions: After adjusting for the effect of potential confounders, more risk factors were associated with a high severity of stroke among ≥75 years old compared with 65–74 years old AIS-HF patients. Elevated heart rate was an independent risk factor associated with stroke severity in 65–74 and ≥75 years old AIS-HF patients. Elevated heart rate and other identified risk factors should be managed to reduce stroke severity among elderly AIS-HF patients.

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“…Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, accounting for around 14% of all strokes in the UK, and linked to a significantly high risk of developing ischaemic stroke (Workman et al ., 2008; Samuthpongtorn et al ., 2021). The prevalence of AF in the general population is 2%, although AF is age-dependent and this figure rises to 3.7-4.2% in ages 60-70 and 10-17% in the over 80s (Zoni-Berisso et al ., 2014).…”

Section: Introductionmentioning

confidence: 99%

Compartmentalisation proteomics revealed endolysosomal protein network changes in a goat model of atrial fibrillation

Ayagama

Charles

Bose

et al. 2023

Preprint

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Endolysosomes (EL) are known for their role in regulating both intracellular trafficking and proteostasis. EL help facilitate elimination of damaged membrane and cytosolic proteins, protein aggregates, membranous organelles and also play an important role in calcium signalling. Despite the importance of EL, their specific role in cardiovascular disease is not well understood. In particular, it's unclear how EL contribute to atrial pathology over longer time frames. To shed light on this question, we conducted a comprehensive analysis that involved proteomics, transcriptomics, integrated analysis, electron tomography, western blotting, and enzyme assays. To identify the role of EL in atrial fibrillation (AF), we applied a recently published organelle protein isolation method. We used this method to study biopsies from AF goat model and analyse the EL-specific proteins and pathways involved in this condition. Our results revealed the upregulation of the AMPK pathway and the expression of EL-specific proteins that were not found in whole tissue lysates (TL), including GAA, DYNLRB1, CLTB, SIRT3, CCT2, and muscle-specific HSPB2. We also observed structural anomalies, such as autophago-vacuole formation, irregularly shaped mitochondria, and glycogen deposition, which provide insights into the EL's contribution to AF and related pathways and molecular mechanisms. Overall, our findings suggest that EL play an important role in the development of AF over longer time frames, and provide a more detailed understanding of the underlying molecular processes involved.

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Stroke risk factors, subtypes and outcome in elderly Thai patients

Cited by 18 publications

References 18 publications

Prediction of long-term mortality in patients with ischemic stroke based on clinical characteristics on the first day of ICU admission: An easy-to-use nomogram

Prediction of long-term mortality in patients with ischemic stroke based on clinical characteristics on the first day of ICU admission: An easy-to-use nomogram

Age Stratification in Acute Ischemic Stroke Patients with Heart Failure

Compartmentalisation proteomics revealed endolysosomal protein network changes in a goat model of atrial fibrillation

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