Development and Validation of a Clinical-Based Signature to Predict the 90-Day Functional Outcome for Spontaneous Intracerebral Hemorrhage

Xiaoyu Huang; Dan Wang; Qiaoying Zhang; Yaqiong Ma; Shenglin Li; Hui Zhao; Juan Deng; Jingjing Yang; JiaLiang Ren; Min Xu; Huaze Xi; Fukai Li; Hongyu Zhang; Yijing Xie; Long Yuan; Yucheng Hai; Mengying Yue; Qing Zhou; Junlin Zhou

doi:10.3389/fnagi.2022.904085

Development and Validation of a Clinical-Based Signature to Predict the 90-Day Functional Outcome for Spontaneous Intracerebral Hemorrhage

Front Aging Neurosci. 2022 May 9:14:904085. doi: 10.3389/fnagi.2022.904085. eCollection 2022.

Authors

Xiaoyu Huang^{1

2

3

4}, Dan Wang¹, Qiaoying Zhang⁵, Yaqiong Ma^{2

6}, Shenglin Li^{1

2

3

4}, Hui Zhao^{1

2

3

4}, Juan Deng^{1

2

3

4}, Jingjing Yang^{1

2

3

4}, JiaLiang Ren⁷, Min Xu^{1

2

3

4}, Huaze Xi^{1

2

3

4}, Fukai Li^{1

2

3

4}, Hongyu Zhang^{1

2

3

4}, Yijing Xie^{1

2

3

4}, Long Yuan^{1

2

3

4}, Yucheng Hai¹, Mengying Yue¹, Qing Zhou^{1

2

3

4}, Junlin Zhou^{1

3

4}

Affiliations

¹ Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China.
² Second Clinical School, Lanzhou University, Lanzhou, China.
³ Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China.
⁴ Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China.
⁵ Department of Radiology, Xi'an Central Hospital, Xi'an, China.
⁶ Department of Radiology, Gansu Provincial Hospital, Lanzhou, China.
⁷ GE Healthcare, Beijing, China.

Abstract

We aimed to develop and validate an objective and easy-to-use model for identifying patients with spontaneous intracerebral hemorrhage (ICH) who have a poor 90-day prognosis. This three-center retrospective study included a large cohort of 1,122 patients with ICH who presented within 6 h of symptom onset [training cohort, n = 835; internal validation cohort, n = 201; external validation cohort (center 2 and 3), n = 86]. We collected the patients' baseline clinical, radiological, and laboratory data as well as the 90-day functional outcomes. Independent risk factors for prognosis were identified through univariate analysis and multivariate logistic regression analysis. A nomogram was developed to visualize the model results while a calibration curve was used to verify whether the predictive performance was satisfactorily consistent with the ideal curve. Finally, we used decision curves to assess the clinical utility of the model. At 90 days, 714 (63.6%) patients had a poor prognosis. Factors associated with prognosis included age, midline shift, intraventricular hemorrhage (IVH), subarachnoid hemorrhage (SAH), hypodensities, ICH volume, perihematomal edema (PHE) volume, temperature, systolic blood pressure, Glasgow Coma Scale (GCS) score, white blood cell (WBC), neutrophil, and neutrophil-lymphocyte ratio (NLR) (p < 0.05). Moreover, age, ICH volume, and GCS were identified as independent risk factors for prognosis. For identifying patients with poor prognosis, the model showed an area under the receiver operating characteristic curve of 0.874, 0.822, and 0.868 in the training cohort, internal validation, and external validation cohorts, respectively. The calibration curve revealed that the nomogram showed satisfactory calibration in the training and validation cohorts. Decision curve analysis showed the clinical utility of the nomogram. Taken together, the nomogram developed in this study could facilitate the individualized outcome prediction in patients with ICH.

Keywords: Glasgow Coma Scale; outcome; perihematomal edema; spontaneous intracerebral hemorrhage; stroke.