Outcomes of Ischemic Stroke and Associated Factors Among Elderly Patients With Large-Artery Atherosclerosis: A Hospital-Based Follow-Up Study in China

Development of a prediction model for frailty among older Chinese individuals with type 2 diabetes residing in the community

METHODS

The study employed a retrospective survey of 458 older individuals with T2D residing in a Chinese community, conducted between June 2020 and May 2021, to develop a predictive model for frailty. Among the participants, 83 individuals (18.1%) were diagnosed with frailty using modified frailty phenotypic criteria. The predictors of frailty in this community-dwelling older population with T2D were determined using least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression. These predictors were utilized to construct a nomogram. The discrimination, calibration, and medical usefulness of the prediction model were assessed through the C-index, calibration plot, and decision curve analysis (DCA), respectively. Additionally, internal validation of the prediction model was conducted using bootstrapping validation.

RESULTS

The developed nomogram for frailty prediction predominantly incorporated age, smoking status, regular exercise, depression, albumin (ALB) levels, sleep condition, HbA1c, and polypharmacy as significant predictors. Our prediction model demonstrated excellent discrimination and calibration, as evidenced by a C-index of 0.768 (95% CI, 0.714-0.822) and strong calibration. Internal validation yielded a C-index of 0.732, further confirming the reliability of the model. DCA indicated the utility of the nomogram in identifying frailty among the studied population.

CONCLUSION

The development of a predictive model enables a valuable estimation of frailty among community-dwelling older individuals with type 2 diabetes. This evidence-based tool provides crucial guidance to community healthcare professionals in implementing timely preventive measures to mitigate the occurrence of frailty in high-risk patients. By identifying established predictors of frailty, interventions and resources can be appropriately targeted, promoting better overall health outcomes and improved quality of life in this vulnerable population.

Care dependency in older stroke patients with comorbidities: a latent profile analysis

Objectives

To explore latent profiles of care dependency in older stroke patients with comorbidities and to analyze the factors influencing different latent profiles.

Methods

A total of 312 older ischemic stroke patients with comorbidities were included in the analysis. Latent Profile Analysis (LPA) was used to classify the participants into potential subgroups with different types of care dependency. The influencing factors of the classification of care dependency subgroups were determined using multivariate Logistic regression analysis.

Results

The care dependency score of older ischemic stroke patients with comorbidities was (51.35 ± 13.19), and the patients could be classified into 3 profiles, namely Universal dependency (24.0%), Moderate activity-social-learning dependency (28.0%), and Mild activity-social-learning dependency (48.0%); caregiver, BI at admission, and functional impairments were independent factors influencing care dependency (P < 0.05).

Conclusion

There are three latent profiles of care dependency in older ischemic stroke patients with comorbidities. According to the characteristics of various populations, medical staff are able to implement specific interventions to lower the level of dependency and further improve the quality of life of patients.

Inflammation and Adverse Outcomes in Patients With Acute Ischemic Stroke With and Without Chronic Kidney Disease

BACKGROUND

Elevated white blood cell count, fibrinogen levels, and lower levels of albumin signify higher systemic inflammatory response, hypercoagulable state, and poorer nutritional status, respectively. However, a consistent conclusion could not be drawn on whether the association between inflammatory markers and cardiovascular disease was affected by the presence of chronic kidney disease (CKD). We aimed to explore the association between inflammation and adverse outcomes in patients with acute ischemic stroke (AIS), as well as whether this association differs due to the presence of CKD.

METHODS AND RESULTS

This research was based on the Third China National Stroke Registry. The main adverse outcomes were poor functional outcome, stroke recurrence, and combined vascular event after 1 year. Inflammation was defined as the worst quartile of at least 2 of the aforementioned 3 markers. Finally, 8493 patients with AIS were enrolled in this study. The adjusted odds ratios/hazard ratios and 95% CIs of inflammation were 1.58 (1.34-1.86) for poor functional outcomes, 1.25 (1.06-1.47) for stroke recurrence, and 1.25 (1.06-1.46) for combined vascular event. The association between inflammation and adverse outcomes existed only in patients with AIS without CKD, although the interaction between CKD and inflammation was not statistically significant. (P for interaction >0.05).

CONCLUSIONS

Inflammation, which was defined as a combination of fibrinogen, white blood cell count, and albumin, was associated with all 1-year adverse outcomes among patients with AIS. Routine assessment of these biomarkers could become a potential part of the clinical evaluation for patients with AIS, especially those without CKD, aiding clinicians in risk stratification and treatment decision-making.

Lipid Profiles and Atrial Fibrillation in Ischemic Stroke Patients Treated with Thrombectomy: Experience from a Tertiary Italian Stroke Hospital

OBJECTIVES

To assess acute lipid profiles, atrial fibrillation and other cardiovascular risk factors in patients undergoing treatments by thrombectomy (EVT) with acute ischemic stroke (AIS).

METHODS

We performed a retrospective analysis of the lipid profile and vascular risk factor in 1639 consecutive patients with acute ischemic stroke between January 2016 and December 2021. To assess lipid profiles, laboratory tests, including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG), were obtained the day after admission. We also examined the association between lipid profile, AF and EVT in multivariate logistic regression analysis.

RESULTS

Median age of patients was 74 years, 54.9% were males (95% CI 52.5-57.4%), and 26.8% (95% CI, 24.7-29.0%) had AF. EVT patients (n = 370; 22.57 %; 95% CI, 20.6-24.7) showed no difference in age (median 73 years (IQR; 63-80) versus 74 years (IQR; 63-82)), HbA1c levels (median 5.8 (IQR; 5.4-6.2) versus 5.9 (IQR; 5.4-6.4)), TG/HDL ratio (median 2.40 (IQR; 1.65-3.48) versus 2.51 (IQR; 1.73-3.64)), diabetes (OR 0.82; 95% CI 0.61 to 1.08), hypertension (OR 0.87; 95% CI 0.68 to 1.12) and obesity (OR 1.06; 95% CI 0.78 to 1.42) compared to non-EVT patients. Conversely, EVT patients showed lower levels of TC (160 mg/dl (IQR; 139- 187) versus 173 mg/dl (IQR; 148-202); p <0.001), LDL-C (105 mg/dl (IQR; 80-133) versus 113 mg/dl (IQR; 88-142); p <0.01), TG (98 mg/dl (IQR; 76-126) versus 107 mg/dl (IQR; 85-139); p <0.001), non-HDL-C (117 mg/dl (IQR; 94-145) versus 127 mg/dl (IQR; 103-154); p <0.001), HC (8.3 mmol/l (IQR; 6-11) versus 10 mmol/l (IQR; 7.3-13.5); p <0.001) than non-EVT patients. Multivariate logistic regression analysis showed an independent association of EVT with TC (OR 0.99, 95% CI 0.98-0.99), AF (OR 1.79, 95% CI 1.34-2.38), age (OR 0.98, 95% CI 0.96-0.99), and NIHSS (OR 1.17, 95% CI 0.14-1.19).

CONCLUSION

Total cholesterol and all cholesterol-related measures were significantly lower in patients undergoing thrombectomy than in other stroke patients. Conversely, we found that AF was significantly high in patients with EVT, suggesting that hypercholesterolemia could be mainly linked to small-vessel occlusion stroke while large vessel occlusion (LVO) stroke could show different causes. AIS patients may have different pathogenesis and their understanding may improve the discovery of specific and tailored preventive treatments.

The role of high-sensitivity C-reactive protein serum levels in the prognosis for patients with stroke: a meta-analysis

Background

The impact of high-sensitivity C-reactive protein (hs-CRP) as a biomarker of inflammation on the prognosis of stroke patients remains controversial, this study was conducted to evaluate the prognostic value of hs-CRP levels for patients with stroke.

Methods

PubMed, Web of Science, Embase, and Cochrane Library databases were searched from inception to October 28, 2022. Outcome measures were all-cause mortality, recurrent stroke, and poor prognosis. The relationship between the highest versus lowest levels of hs-CRP or per unit increment and outcomes as measured by risk ratio (RR) and corresponding 95% confidence intervals (CI).

Results

A total of 39 articles were eligible for meta-analysis. High hs-CRP levels at admission were associated with mortality among patients with acute ischemic stroke (AIS) [RR = 3.84, 95% CI (2.41 ~ 6.111); p < 0.001], risk of recurrent stroke [RR = 1.88, 95%CI (1.41 ~ 2.52); p < 0.001], and poor prognosis [RR = 1.77, 95% CI (1.59 ~ 1.97); p < 0.001]. The risk ratios for the association of per unit increase in hs-CRP levels with mortality, risk of recurrent stroke, and poor prognosis were as follows, respectively: 1.42 [95% CI (1.19-1.69); p < 0.001], 1.03 [95% CI (1.01-1.04); p = 0.003], and 1.27 [95% CI (1.10-1.47); p = 0.001]. For hemorrhagic stroke (HS), the risk ratios (RR) for the highest versus the lowest (reference) category of hsCRP or per unit increment to all-cause mortality were 4.36 [95% CI (1.38-13.73); p = 0.012] and 1.03 [95% CI (0.98-1.08); p = 0.238].

Conclusion

Hs-CRP levels are strongly associated with mortality, risk of stroke recurrence and poor prognosis in stroke patients. Therefore, hs-CRP levels may contribute to the prognosis prediction of these patients.

The Relationship Between Aortic Arch Calcification and Recurrent Stroke in Patients With Embolic Stroke of Undetermined Source-A Case-Control Study

Background

Aortic arch calcification (AoAC) is associated with plaque development and cardiovascular events. We aimed to estimate the predictive value of AoAC for stroke recurrence in patients with embolic stroke of undetermined source (ESUS).

Methods

Consecutive patients with ESUS who were admitted to our center between October 2019 and October 2020 and who had a 1-year follow-up of stroke recurrence were retrospectively reviewed. According to our AoAC grading scale (AGS), AoAC was classified into four grades based on chest computed tomography (CT) findings: no visible calcification (grade 0), spotty calcification (grade 1), lamellar calcification (grade 2), and circular calcification (grade 3).

Results

Of the 158 patients with ESUS (age, 62.1 ± 14.5 years; 120 men) enrolled, 24 (15.2%) had recurrent stroke within a 1-year follow-up. The Cox regression analysis showed that stroke history [hazard ratio (HR), 4.625; 95% confidence interval (CI), 1.828–11.700, p = 0.001] and AoAC (HR, 2.672; 95% CI, 1.129–6.319; p = 0.025) predicted recurrent stroke. AGS grade 1 was associated with a significantly higher risk of stroke recurrence than AGS grade 0 (HR, 5.033; 95% CI, 1.858–13.635, p = 0.001) and AGS grade 2 plus 3 (HR, 3.388; 95% CI, 1.124–10.206, p = 0.030). In patients with AoAC, receiver operating characteristic (ROC) analysis showed that AGS had a good value in predicting stroke recurrence in patients with ESUS, with an area under curve (AUC) of 0.735 (95% CI = 0.601–0.869, p = 0.005).

Conclusions

Aortic arch calcification, especially spotty calcification, had a good predictive value for stroke recurrence in patients with ESUS.

Atherogenic Index of Plasma Predicts Outcomes in Acute Ischemic Stroke

Aim: The atherogenic index of plasma (AIP) was significantly related to adverse outcomes in patients with cardiovascular disease. Our aim was to investigate the association between AIP and adverse outcomes in acute ischemic stroke.

Methods: Patients with acute ischemic stroke (AIS) admitted between 2015 and 2018 were prospectively enrolled in this study. Functional outcomes were evaluated by the modified Rankin Scale (mRS). Poor outcomes were defined as mRS 3–6. The relationship of AIP with the risk of outcomes was analyzed by multivariate logistic regression models.

Results: A total of 1,463 patients with AIS within 24 h of symptom onset were enrolled. The poor outcome group had a significantly higher level of AIP [0.09 (−0.10 to 0.27) vs. 0.04 (−0.09 to 0.18), p < 0.001] compared with the good outcome group. Multivariable logistic regression analysis showed that higher AIP was associated with poor outcomes in all the stroke patients (OR 1.84, 95% CI, 1.23–2.53, p = 0.007), which was more evident in patients with large-artery atherosclerosis subtype (OR 1.90, 95% CI, 1.53–2.62, p = 0.002), but not in the other subtypes. Receiver operating curve (ROC) analysis revealed that the best predictive cutoff value of AIP was 0.112, with a sensitivity of 70.8% and a specificity of 59.2%, and the area under the ROC curves for AIP was 0.685.

Conclusion: AIP may be an important and independent predictor of the outcome of dysfunction in patients with AIS, especially the stroke subtype of large-artery atherosclerosis.