Construction and validation of a malnutrition risk prediction model for patients recovering from stroke

RAO Zhenzhen; LI Yaling; SUN Yinxia; YUAN Jie; ZHAN Yan; LI Jiuhu; CHEN Lei

doi:10.16766/j.cnki.issn.1674-4152.004114

Volume 23 Issue 8

Aug. 2025

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Article Navigation > Chinese Journal of General Practice > 2025 > 23(8): 1275-1279

RAO Zhenzhen, LI Yaling, SUN Yinxia, YUAN Jie, ZHAN Yan, LI Jiuhu, CHEN Lei. Construction and validation of a malnutrition risk prediction model for patients recovering from stroke[J]. Chinese Journal of General Practice, 2025, 23(8): 1275-1279. doi: 10.16766/j.cnki.issn.1674-4152.004114

Citation:

RAO Zhenzhen, LI Yaling, SUN Yinxia, YUAN Jie, ZHAN Yan, LI Jiuhu, CHEN Lei. Construction and validation of a malnutrition risk prediction model for patients recovering from stroke[J]. Chinese Journal of General Practice, 2025, 23(8): 1275-1279. doi: 10.16766/j.cnki.issn.1674-4152.004114

Citation:

RAO Zhenzhen, LI Yaling, SUN Yinxia, YUAN Jie, ZHAN Yan, LI Jiuhu, CHEN Lei. Construction and validation of a malnutrition risk prediction model for patients recovering from stroke[J]. Chinese Journal of General Practice, 2025, 23(8): 1275-1279. doi: 10.16766/j.cnki.issn.1674-4152.004114

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Construction and validation of a malnutrition risk prediction model for patients recovering from stroke

doi: 10.16766/j.cnki.issn.1674-4152.004114

RAO Zhenzhen^{1, 2}
, LI Yaling^{3
,
,}
, SUN Yinxia¹
, YUAN Jie⁴
, ZHAN Yan³
, LI Jiuhu⁵
, CHEN Lei⁵

1.
School of Nursing, Hubei University of Medicine, Shiyan, Hubei 442000, China

Funds:

21D074

YC2022021

Received Date: 2024-01-26
Available Online: 2025-10-31

Abstract

Abstract

Objective Analyzing risk factors for malnutrition in patients recovering from stroke, constructing a nomogram model, and validating its predictive effect. Methods A total of 254 stroke recovery patients were admitted to Taihe hospital in Shiyan City from December 2021 to November 2022. Among them, 178 cases from December 2021 to July 2022 were used as the modeling group, and 76 cases from August to November 2022 were used as the validation group. The data in the modeling group were analyzed using one-way analysis and logistic regression analysis to determine the malnutrition risk factors in patients recovering from stroke. Constructed a column-line diagram model and verified the effect. Results The incidence of malnutrition risk in patients recovering from stroke was 60.24% (153/254). The incidences of malnutrition risk were 61.80% (110/178) and 56.58% (43/76) in the modeling and validation groups, respectively. The age (OR=1.086, P < 0.001), mRS score (OR=1.756, P=0.001), and ALB level (OR=0.842, P=0.012) were independent influencing factors for the risk of malnutrition in patients recovering from stroke. The model was constructed as follows: Logit(P)=0.402+0.083×age+0.563×mRS score-0.172×ALB level. The AUCs of the modeling and validation group models were 0.844 (95% CI: 0.788-0.900) and 0.831 (95% CI: 0.740-0.921), respectively. Conclusion The older the age, the higher the mRS score, and the lower the ALB level, the greater the risk of malnutrition in patients recovering from stroke. This risk prediction model constructed in this study has good discrimination and calibration, and can be used as a reference tool to facilitate early identification of malnutrition risk in patients recovering from stroke by clinical health care professionals.
- Stroke,
- Convalescence,
- Malnutrition,
- Prediction model,
- Nomogram

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References(22)

References

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