Limits...
Prediction of in-hospital stroke mortality in critical care unit.

Ho WM, Lin JR, Wang HH, Liou CW, Chang KC, Lee JD, Peng TY, Yang JT, Chang YJ, Chang CH, Lee TH - Springerplus (2016)

Bottom Line: In hemorrhagic stroke, NIHSS score (OR 1.12; 95 % CI 1.09-1.14; P < 0.01), systolic BP (OR 0.25; 95 % CI 0.15-0.41; P < 0.01), heart disease (OR 1.94; 95 % CI 1.11-3.39; P = 0.02) and creatinine (OR 1.16; 95 % CI 1.01-1.34; P = 0.04) were related to in-hospital mortality.Nomograms using these significant predictors were constructed for easy and quick evaluation of in-hospital mortality.Variables in acute stroke can predict in-hospital mortality and help decision-making in clinical practice using nomogram.

View Article: PubMed Central - PubMed

Affiliation: Dementia Center and Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, No.5, Fuxing St., Guishan Dist., Taoyuan City, 333 Taiwan, ROC.

ABSTRACT

Background: Critical stroke causes high morbidity and mortality. We examined if variables in the early stage of critical stroke could predict in-hospital mortality.

Methods: We recruited 611 ischemic and 805 hemorrhagic stroke patients who were admitted within 24 h after the symptom onset. Data were analyzed with independent t test and Chi square test, and then with multivariate logistic regression analysis.

Results: In ischemic stroke, National Institutes of Health Stroke Scale (NIHSS) score (OR 1.08; 95 % CI 1.06-1.11; P < 0.01), white blood cell count (OR 1.11; 95 % CI 1.05-1.18; P < 0.01), systolic blood pressure (BP) (OR 0.49; 95 % CI 0.26-0.90; P = 0.02) and age (OR 1.03; 95 % CI 1.00-1.05; P = 0.03) were associated with in-hospital mortality. In hemorrhagic stroke, NIHSS score (OR 1.12; 95 % CI 1.09-1.14; P < 0.01), systolic BP (OR 0.25; 95 % CI 0.15-0.41; P < 0.01), heart disease (OR 1.94; 95 % CI 1.11-3.39; P = 0.02) and creatinine (OR 1.16; 95 % CI 1.01-1.34; P = 0.04) were related to in-hospital mortality. Nomograms using these significant predictors were constructed for easy and quick evaluation of in-hospital mortality.

Conclusion: Variables in acute stroke can predict in-hospital mortality and help decision-making in clinical practice using nomogram.

No MeSH data available.


Related in: MedlinePlus

Calibration curves in the prediction model of observed and predicted in-hospital mortality. a Calibration curve in ischemic stroke group (Z = 0.65, P = 0.52) shows mild overestimation in high risk group, b calibration curve in hemorrhagic stroke (Z = 0.87, P = 0.36)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4940351&req=5

Fig2: Calibration curves in the prediction model of observed and predicted in-hospital mortality. a Calibration curve in ischemic stroke group (Z = 0.65, P = 0.52) shows mild overestimation in high risk group, b calibration curve in hemorrhagic stroke (Z = 0.87, P = 0.36)

Mentions: Significant variables in univariate analysis were assigned to build up multivariate logistic regression model. In ischemic stroke group, age, gender, NIHSS score, WBC count, BUN and BUN/Cr ratio were chosen as covariates. The systolic BP was added under the consideration of clinical importance. Multivariate analysis (Table 2) showed NIHSS score (OR 1.08; 95 % CI 1.06–1.11; P < 0.01), WBC count (OR 1.11; 95 % CI 1.05–1.18; P < 0.01), systolic BP (OR 0.49; 95 % CI 0.26–0.90; P = 0.02) and age (OR 1.03; 95 % CI 1.00–1.05; P = 0.03) were significantly associated with in-hospital mortality, while BUN/Cr ratio was not. Fitness of the predictive model (Fig. 2a) was well calibrated (Z = 0.65, P = 0.52) with mild overestimation in high risk patients. Discriminative examination showed c-statistic = 0.79. In conversion to nomogram (Fig. 3a), NIHSS score was assigned to be 100 points and the rest of the variables were appointed in proportion to their beta coefficients.Table 2


Prediction of in-hospital stroke mortality in critical care unit.

Ho WM, Lin JR, Wang HH, Liou CW, Chang KC, Lee JD, Peng TY, Yang JT, Chang YJ, Chang CH, Lee TH - Springerplus (2016)

Calibration curves in the prediction model of observed and predicted in-hospital mortality. a Calibration curve in ischemic stroke group (Z = 0.65, P = 0.52) shows mild overestimation in high risk group, b calibration curve in hemorrhagic stroke (Z = 0.87, P = 0.36)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4940351&req=5

Fig2: Calibration curves in the prediction model of observed and predicted in-hospital mortality. a Calibration curve in ischemic stroke group (Z = 0.65, P = 0.52) shows mild overestimation in high risk group, b calibration curve in hemorrhagic stroke (Z = 0.87, P = 0.36)
Mentions: Significant variables in univariate analysis were assigned to build up multivariate logistic regression model. In ischemic stroke group, age, gender, NIHSS score, WBC count, BUN and BUN/Cr ratio were chosen as covariates. The systolic BP was added under the consideration of clinical importance. Multivariate analysis (Table 2) showed NIHSS score (OR 1.08; 95 % CI 1.06–1.11; P < 0.01), WBC count (OR 1.11; 95 % CI 1.05–1.18; P < 0.01), systolic BP (OR 0.49; 95 % CI 0.26–0.90; P = 0.02) and age (OR 1.03; 95 % CI 1.00–1.05; P = 0.03) were significantly associated with in-hospital mortality, while BUN/Cr ratio was not. Fitness of the predictive model (Fig. 2a) was well calibrated (Z = 0.65, P = 0.52) with mild overestimation in high risk patients. Discriminative examination showed c-statistic = 0.79. In conversion to nomogram (Fig. 3a), NIHSS score was assigned to be 100 points and the rest of the variables were appointed in proportion to their beta coefficients.Table 2

Bottom Line: In hemorrhagic stroke, NIHSS score (OR 1.12; 95 % CI 1.09-1.14; P < 0.01), systolic BP (OR 0.25; 95 % CI 0.15-0.41; P < 0.01), heart disease (OR 1.94; 95 % CI 1.11-3.39; P = 0.02) and creatinine (OR 1.16; 95 % CI 1.01-1.34; P = 0.04) were related to in-hospital mortality.Nomograms using these significant predictors were constructed for easy and quick evaluation of in-hospital mortality.Variables in acute stroke can predict in-hospital mortality and help decision-making in clinical practice using nomogram.

View Article: PubMed Central - PubMed

Affiliation: Dementia Center and Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, No.5, Fuxing St., Guishan Dist., Taoyuan City, 333 Taiwan, ROC.

ABSTRACT

Background: Critical stroke causes high morbidity and mortality. We examined if variables in the early stage of critical stroke could predict in-hospital mortality.

Methods: We recruited 611 ischemic and 805 hemorrhagic stroke patients who were admitted within 24 h after the symptom onset. Data were analyzed with independent t test and Chi square test, and then with multivariate logistic regression analysis.

Results: In ischemic stroke, National Institutes of Health Stroke Scale (NIHSS) score (OR 1.08; 95 % CI 1.06-1.11; P < 0.01), white blood cell count (OR 1.11; 95 % CI 1.05-1.18; P < 0.01), systolic blood pressure (BP) (OR 0.49; 95 % CI 0.26-0.90; P = 0.02) and age (OR 1.03; 95 % CI 1.00-1.05; P = 0.03) were associated with in-hospital mortality. In hemorrhagic stroke, NIHSS score (OR 1.12; 95 % CI 1.09-1.14; P < 0.01), systolic BP (OR 0.25; 95 % CI 0.15-0.41; P < 0.01), heart disease (OR 1.94; 95 % CI 1.11-3.39; P = 0.02) and creatinine (OR 1.16; 95 % CI 1.01-1.34; P = 0.04) were related to in-hospital mortality. Nomograms using these significant predictors were constructed for easy and quick evaluation of in-hospital mortality.

Conclusion: Variables in acute stroke can predict in-hospital mortality and help decision-making in clinical practice using nomogram.

No MeSH data available.


Related in: MedlinePlus