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Construction and evaluation of a model for predicting the deterioration of neurological function in the early stage of acute ischemic stroke
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Yong-jia MAO1, Peng LUO1, Shi-xian MAO3, De-xin YE1, Rong LONG1, Chun-yuan LU1, Jiang-ping ZHANG1, 2
Modern Preventive Medicine | 2024, 51(1) : 166 - 172
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Modern Preventive Medicine | 2024, 51(1): 166-172
Clinical Medicine and Prevention
Construction and evaluation of a model for predicting the deterioration of neurological function in the early stage of acute ischemic stroke
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Yong-jia MAO1, Peng LUO1, Shi-xian MAO3, De-xin YE1, Rong LONG1, Chun-yuan LU1, Jiang-ping ZHANG1, 2
Affiliations
  • School of Public Health, Guizhou Medical University, Key Laboratory of Environmental Pollution and Disease Surveillance, Ministry of Education, Guiyang, Guizhou 561113, China
Published: 2024-01-10 doi: 10.20043/j.cnki.MPM.202306126
Outline
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Objective

To explore the risk factors of early neurological deterioration (END) in patients with acute ischemic stroke(AIS) and establish a predictive model.

Methods

In total 622 AIS patients treated in Baiyun Hospital affiliated to Guizhou Medical University from January 2018 to December 2022 were selected and divided into END group (n=127) and non-END group (n=495) according to the diagnostic criteria of outcome events. The clinical baseline data, laboratory data, and imaging data of the patients were retrospectively collected. Based on the Logistic regression algorithm, risk factors for the development of END were investigated. The prediction model was constructed and nomogram was drawn, and the prediction value of the model was evaluated by discrimination, calibration, and clinical applicability.

Results

Multivariate Logistic regression analysis showed that heart rhythm, middle cerebral artery stenosis, carotid artery stenosis, admission NHISS score, fibrinogen, albumin, and brain natriuretic peptide (BNP) were independent risk factors for END. The prediction model was developed using Stata software, and a nomogram was created. Verification set analysis revealed that the predictive model predicted the risk of END with good discrimination, accuracy, and clinical applicability, with an AUC of 0.888 (95%CI: 0.821-0.955), slope of the calibration curve which was close to 1, and net benefit of the clinical decision curve that exceeded the two reference lines.

Conclusion

The model constructed in this study has high degree of discrimination, calibration, and clinical applicability and has good comprehensive prediction efficiency, which has a certain clinical application value for the early prediction of END.

Acute ischemic stroke  /  Early neurological deterioration  /  Risk factors  /  Predictive model
Yong-jia MAO, Peng LUO, Shi-xian MAO, De-xin YE, Rong LONG, Chun-yuan LU, Jiang-ping ZHANG. Construction and evaluation of a model for predicting the deterioration of neurological function in the early stage of acute ischemic stroke[J]. Modern Preventive Medicine, 2024 , 51 (1) : 166 -172 . DOI: 10.20043/j.cnki.MPM.202306126
Year 2024 volume 51 Issue 1
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doi: 10.20043/j.cnki.MPM.202306126
  • Receive Date:2023-06-10
  • Online Date:2026-03-19
  • Published:2024-01-10
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  • Received:2023-06-10
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    School of Public Health, Guizhou Medical University, Key Laboratory of Environmental Pollution and Disease Surveillance, Ministry of Education, Guiyang, Guizhou 561113, China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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