Establishment of a regression equation for risk factors of refeeding syndrome in critically ill elderly patients and analysis of intervention measures

SU Yan; XU Jiuyun; LEI Hailu; LIU Xiaobei

doi:10.7619/jcmp.20232622

Journal of Clinical Medicine in Practice > 2024 > 28(1): 123-128. > DOI: 10.7619/jcmp.20232622

SU Yan, XU Jiuyun, LEI Hailu, LIU Xiaobei. Establishment of a regression equation for risk factors of refeeding syndrome in critically ill elderly patients and analysis of intervention measures[J]. Journal of Clinical Medicine in Practice, 2024, 28(1): 123-128. DOI: 10.7619/jcmp.20232622

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Establishment of a regression equation for risk factors of refeeding syndrome in critically ill elderly patients and analysis of intervention measures

1.
Intensive Care Unit, Anqing Municipal Hospital in Anhui Province, Anqing, Anhui, 246000
2.
Anhui Medical College, Anqing, Anhui, 246000

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Received Date: August 16, 2023
Revised Date: October 15, 2023
Available Online: January 22, 2024

Graphical Abstract

Abstract

Abstract

Objective
To establish a regression equation for risk factors of refeeding syndrome (RFS) in critically ill elderly patients and analyze the relevant intervention measures.
Methods
Clinical materials of 154 critically ill elderly patients treated in Intensive Care Unit (ICU) from January 2021 to March 2023 were retrospectively analyzed, and they were divided into RFS group (n=51) and non-RFS group (n=103) according to incidence condition of RFS. The influencing factors of RFS were analyzed by Logistic regression model; the predictive values of predictors for RFS were analyzed by receiver operating characteristic (ROC) curve; the relevant Logistic regression equations were constructed and verified, and relevant nursing interventions were formulated.
Results
The incidence of RFS in critically ill elderly patients was correlated with the Acute Physiology and Chronic Health Evaluation Ⅱ (APACHE Ⅱ) score, the Nutritional Risk Screening 2002 (NRS2002) score, invasive mechanical ventilation, fasting time before feeding, D-dimer level, nutritional intake methods, and pre-feeding blood phosphorus, potassium and magnesium levels (P < 0.05). Logistic regression analysis showed that APACHE Ⅱ score, NRS2002 score, nutrient intake methods and pre-feeding blood phosphorus and potassium levels were the independent risk factors of RFS in critically ill elderly patients (P < 0.05). The ROC curve results showed that the values of area under the curve (AUC) of APACHE Ⅱ score, NRS2002 score, nutritional intake methods, pre-feeding blood phosphorus and potassium levels, and the combined predictor in predicting the incidence of RFS in critically ill elderly patients were 0.754, 0.723, 0.707, 0.783, 0.774 and 0.859, respectively (P < 0.05). The Logistic regression equation for RFS was as follow: L=0.085×APACHE Ⅱ score-0.337×NRS 2002 score+0.537×nutrient intake methods-0.776×pre-feeding blood phosphorus level-0.207×pre-feeding blood potassium level+0.942. The predictive value of this equation was good, and targeted nursing interventions could be formulated based on this equation.
Conclusion
The regression equation of risk factors can be used for clinical prediction of the RFS risk in critically ill elderly patients, and clinical nursing interventions can be formulated based on the regression equation to prevent the occurrence of RFS.
- critically ill elderly patients,
- refeeding syndrome,
- risk factors,
- regression equation,
- nursing interventions

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References (27)

References

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Establishment of a regression equation for risk factors of refeeding syndrome in critically ill elderly patients and analysis of intervention measures