Yusop Nooreena, Mat Samsiah, Mustafar Ruslinda, Ismail Muhammad Ishamuddin
Faculty of Nursing, University College of MAIWP International (UCMI), Kuala Lumpur, Malaysia.
Department of Medicine, Faculty of Medicine, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Front Nephrol. 2025 Aug 27;5:1624880. doi: 10.3389/fneph.2025.1624880. eCollection 2025.
Acute Kidney Injury (AKI) is a common yet preventable complication among surgical patients, contributing to increased morbidity, prolonged hospital stays, and higher healthcare costs. Early detection is critical; however, the absence of a standardized nursing-led risk assessment tool for AKI limits proactive intervention in clinical practice.
This study aimed to develop and evaluate the Nursing Risk Assessment for Acute Kidney Injury tool, integrating the Fuzzy Logic Model (FLM) to enhance interpretive accuracy and improve nursing-led AKI risk detection and decision-making.
A Design and Development Research (DDR) framework was employed in three phases. Phase 1 involved a needs analysis using a focus group discussion to explore the necessity of AKI assessment among surgical nurses. Phase 2 focused on tool development through expert consensus (surgeon, nephrologist, nursing academician, and experienced nurse) and evidence synthesis via a systematic literature review. In Phase 3, the Nursing Risk Assessment-AKI tool was evaluated through a quasi-experimental design at Hospital Canselor Tuanku Muhriz (HCTM), Kuala Lumpur, involving 75 surgical nurses assessing 200 patients.
Post-intervention analysis indicated increased nursing confidence, with 95.7% expressing positive perception of tool use. The FLM-supported tool demonstrated a predictive accuracy of 81.3%; however, the potential for false positives or negatives remains, especially given the single-center context. Fuzzy logic stratified patients into risk groups: at risk (33.5%), borderline (20.5%), and no risk (46.0%). ANOVA analysis revealed significant differences (p < 0.05) between AKI risk and factors such as age, gender, comorbidities, clinical/laboratory parameters, surgery types, and nephrotoxic agent usage.
While initial findings support the usability and clinical feasibility of the NURA-AKI tool, further multicenter validation is needed. The tool is designed to complement nurse judgment, promoting early AKI detection and structured risk communication in surgical care without replacing clinical autonomy.
急性肾损伤（AKI）是外科患者中常见但可预防的并发症，会导致发病率增加、住院时间延长和医疗成本升高。早期检测至关重要；然而，缺乏标准化的由护士主导的AKI风险评估工具限制了临床实践中的积极干预。
本研究旨在开发和评估急性肾损伤护理风险评估工具，整合模糊逻辑模型（FLM）以提高解释准确性，并改善由护士主导的AKI风险检测和决策。
采用设计与开发研究（DDR）框架，分为三个阶段。第一阶段通过焦点小组讨论进行需求分析，以探讨外科护士进行AKI评估的必要性。第二阶段专注于通过专家共识（外科医生、肾病学家、护理学者和经验丰富的护士）进行工具开发，并通过系统文献综述进行证据综合。在第三阶段，在吉隆坡的敦库穆赫里兹医院（HCTM）通过准实验设计对急性肾损伤护理风险评估工具进行评估，75名外科护士对200名患者进行评估。
干预后分析表明护士的信心增强，95.7%的人对工具使用表示积极看法。FLM支持的工具显示预测准确率为81.3%；然而，假阳性或假阴性的可能性仍然存在，特别是考虑到单中心背景。模糊逻辑将患者分为风险组：有风险（33.5%）、临界（20.5%）和无风险（46.0%）。方差分析显示AKI风险与年龄、性别、合并症、临床/实验室参数、手术类型和肾毒性药物使用等因素之间存在显著差异（p < 0.05）。
虽然初步结果支持急性肾损伤护理风险评估工具（NURA-AKI）的可用性和临床可行性，但需要进一步进行多中心验证。该工具旨在补充护士的判断，促进外科护理中AKI的早期检测和结构化风险沟通，而不取代临床自主权。
