Development of a prediction model for 1-year poor prognosis in patients with acute ischemic stroke

The systemic inflammation score is a prognostic factor for patients with ischemic stroke who have not undergone intravenous thrombolysis or endovascular thrombectomy therapy

BACKGROUND

The systemic inflammation score (SIS) has been utilised as a representative biomarker for evaluating nutritional and inflammation status. However, the predictive value of SIS has not been reported in patients with acute ischemic stroke (AIS). We aimed to evaluate whether SIS is associated with prognosis in stroke.

METHODS

A total of 4801 patients with AIS were included in the study. The primary outcome was a modified Rankin Scale score>2 at the 3-month follow-up. A total of 4801 patients were randomly allocated into training (n=3361) and validation cohorts (n=1440) at a ratio of 7:3. Model performance was validated using the receiver operating characteristic (ROC) curve and calibration curve. Additionally, a comparison was made between the nomogram and the THRIVE score in regards to their respective predictive capabilities.

RESULTS

Overall, 1091(32.5%) patients in the training cohort and 446 (31.0%) patients in the validation cohort experienced an unfavorable outcome. The multivariate logistic regression analysis revealed that a high SIS, age, NIHSS, diabetes and prior stroke were associated with unfavorable outcome. Our nomogram was developed based on the variables mentioned above. The area under the curve (AUC) of the training set and the validation set are 0.702 and 0.708, respectively, indicating that the model has modest agreement and discrimination. The results of AUC, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) showed that nomogram had significantly higher predictive value than THRIVE scores (all P<0.001). However, unlike the THRIVE publication, all patients who had undergone intravenous thrombolysis or endovascular thrombectomy therapy were excluded in our study. In consequence, our derived THRIVE scores cannot be compared to those in the original THRIVE study.

CONCLUSION

The SIS exhibits potential as a simple prognostic biomarker, and the nomogram, which utilizes the SIS, may serve as a valuable tool for clinicians in the early identification of patients at heightened risk for unfavorable outcomes.

Predicting 10-year stroke mortality: development and validation of a nomogram

Predicting long-term stroke mortality is a clinically important and unmet need. We aimed to develop and internally validate a 10-year ischaemic stroke mortality prediction score. In this UK cohort study, 10,366 patients with first-ever ischaemic stroke between January 2003 and December 2016 were followed up for a median (interquartile range) of 5.47 (2.96-9.15) years. A Cox proportional-hazards model was used to predict 10-year post-admission mortality. The predictors associated with 10-year mortality included age, sex, Oxfordshire Community Stroke Project classification, estimated glomerular filtration rate (eGFR), pre-stroke modified Rankin Score, admission haemoglobin, sodium, white blood cell count and comorbidities (atrial fibrillation, coronary heart disease, heart failure, cancer, hypertension, chronic obstructive pulmonary disease, liver disease and peripheral vascular disease). The model was internally validated using bootstrap resampling to assess optimism in discrimination and calibration. A nomogram was created to facilitate application of the score at the point of care. Mean age (SD) was 78.5 ± 10.9 years, 52% female. Most strokes were partial anterior circulation syndromes (38%). 10-year mortality predictors were: total anterior circulation stroke (hazard ratio, 95% confidence intervals) (2.87, 2.62-3.14), eGFR < 15 (1.97, 1.55-2.52), 1-year increment in age (1.04, 1.04-1.05), liver disease (1.50, 1.20-1.87), peripheral vascular disease (1.39, 1.23-1.57), cancers (1.37, 1.27-1.47), heart failure (1.24, 1.15-1.34), 1-point increment in pre-stroke mRS (1.20, 1.17-1.22), atrial fibrillation (1.17, 1.10-1.24), coronary heart disease (1.09, 1.02-1.16), chronic obstructive pulmonary disease (1.13, 1.03-1.25) and hypertension (0.77, 0.72-0.82). Upon internal validation, the optimism-adjusted c-statistic was 0.76 and calibration slope was 0.98. Our 10-year mortality model uses routinely collected point-of-care information. It is the first 10-year mortality score in stroke. While the model was internally validated, further external validation is also warranted.

Relationship between fasting blood glucose and subsequent vascular events in Chinese patients with mild ischaemic stroke: a cohort study

Objective

To characterise the relationship between fasting blood glucose (FBG) and the incidence of subsequent vascular events (SVE) during the 6 months following a mild ischaemic stroke (MIS) in Chinese patients.

Methods

Data from patients with MIS were retrospectively analysed. The primary endpoint was an SVE during the 6-month follow-up period. The participants were allocated to three groups (tertiles), according to their FBG concentration.

Results

Of the 260 participants, 51 (19.6%) reported an SVE during the follow-up period. The incidence of SVE significantly differed among the tertiles of FBG. The odds ratio (OR) was 2.361 (95% confidence interval [CI]: 1.551–3.594) for FBG as a continuous variable and that for FBG categorised according to tertile was 13.30 (95% CI: 3.519–50.322) in the fully adjusted model. Curve fitting showed that the incidence of SVE gradually increased with increasing FBG, with the highest tertile showing the highest mean incidence (46.7%; 95% CI: 16.2%–79.9%). In addition, participants with or without diabetes mellitus, hypertension, headache, dizziness, mild cognitive impairment or anterior circulation artery lesion showed similar associations between FBG and the incidence of SVE.

Conclusion

FBG is an independent predictor of 6-month SVE risk in Chinese patients with MIS.

Predictors of death within 6 months of stroke onset: A model with Barthel index, platelet/lymphocyte ratio and serum albumin

AIMS

To develop and internally validate a nomogram to predict the risk of death within 6 months of onset of stroke in Chinese. Identifying risk factors with potentially direct effects on the nomogram will improve the quality of risk assessment and help nurses implement preventive measures based on patient-specific risk factors.

DESIGN

A retrospective study.

METHODS

We performed a least absolute shrinkage and selection operator (LASSO) regression modelling and multivariate logistic regression analysis to establish a prediction model of death risk in stroke patients within 6 months of onset. LASSO and time-dependent Cox regression models were further used to analyse the 6-month survival of stroke patients. Data were collected from 21 October 2013-6 May 2019.

RESULTS

The independent predictors of the nomogram were Barthel index (odds ratio (OR) = 0.980, 95% confidence interval (CI) = 0.961-0.998, p = .03), platelet/lymphocyte ratio (OR = 1.005, 95% CI = 1.000-1.010, p = .04) and serum albumin (OR = 0.854, 95% CI = 0.774-0.931, p < .01). This model showed good discrimination and consistency, and its discrimination evaluation C-statistic was 0.879 in the training set and 0.891 in the internal validation set. The DCA indicated that the nomogram had a higher overall net benefit over most of the threshold probability range. The time-dependent Cox regression model established the impact of the time effect of the age variable on survival time.

CONCLUSIONS

Our results identified three predictors of death within 6 months of stroke in Chinese. These predictors can be used as risk assessment indicators to help caregivers performing clinical nursing work, and in clinical practice, it is suggested that nurses should evaluate the self-care ability of stroke patients in detail. The constructed nomogram can help identify patients at high risk of death within 6 months, so that intervention can be performed as early as possible.