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心力衰竭患者的液体状态评估:马斯特里赫特失代偿问卷的初步验证

Fluid status assessment in heart failure patients: pilot validation of the Maastricht Decompensation Questionnaire.

作者信息

Gingele Arno J, Beckers Fabienne, Boyne Josiane J, Brunner-La Rocca Hans-Peter

机构信息

Department of Cardiology, Maastricht University Medical Centre, Maastricht, The Netherlands.

出版信息

Neth Heart J. 2025 Jan;33(1):7-13. doi: 10.1007/s12471-024-01921-4. Epub 2024 Dec 10.

Abstract

BACKGROUND

eHealth products have the potential to enhance heart failure (HF) care by identifying at-risk patients. However, existing risk models perform modestly and require extensive data, limiting their practical application in clinical settings. This study aims to address this gap by validating a more suitable risk model for eHealth integration.

METHODS

We developed the Maastricht Decompensation Questionnaire (MDQ) based on expert opinion to assess HF patients' fluid status using common signs and symptoms. Subsequently, the MDQ was administered to a cohort of HF outpatients at Maastricht University Medical Centre. Patients with ≥ 10 MDQ points were categorised as 'decompensated', patients with < 10 MDQ points as 'not decompensated'. HF nurses, blinded to MDQ scores, served as the gold standard for fluid status assessment. Patients were classified as 'correctly' if MDQ and nurse assessments aligned; otherwise, they were classified as 'incorrectly'.

RESULTS

A total of 103 elderly HF patients were included. The MDQ classified 50 patients as 'decompensated', with 17 of them being correctly classified (34%). Additionally, 53 patients were categorised as 'not decompensated', with 48 of them being correctly classified (90%). The calculated area under the curve was 0.69 (95% confidence interval: 0.57-0.81; p < 0.05). Cronbach's alpha reliability coefficient for the MDQ was 0.85.

CONCLUSIONS

The MDQ helps identify decompensated HF patients through clinical signs and symptoms. Further trials with larger samples are needed to confirm its validity, reliability and applicability. Tailoring the MDQ to individual patient profiles may improve its accuracy.

摘要

背景

电子健康产品有潜力通过识别高危患者来改善心力衰竭(HF)护理。然而,现有的风险模型表现一般,且需要大量数据,限制了它们在临床环境中的实际应用。本研究旨在通过验证一个更适合电子健康整合的风险模型来填补这一空白。

方法

我们基于专家意见开发了马斯特里赫特失代偿问卷(MDQ),以使用常见体征和症状评估HF患者的液体状态。随后,MDQ应用于马斯特里赫特大学医学中心的一组HF门诊患者。MDQ得分≥10分的患者被归类为“失代偿”,得分<10分的患者被归类为“未失代偿”。对MDQ得分不知情的HF护士作为液体状态评估的金标准。如果MDQ和护士的评估一致,则患者被分类为“正确”;否则,他们被分类为“错误”。

结果

共纳入103例老年HF患者。MDQ将50例患者分类为“失代偿”,其中17例分类正确(34%)。此外,53例患者被归类为“未失代偿”,其中48例分类正确(90%)。计算得到的曲线下面积为0.69(95%置信区间:0.57 - 0.81;p<0.05)。MDQ的Cronbach's alpha信度系数为0.85。

结论

MDQ有助于通过临床体征和症状识别失代偿的HF患者。需要进行更大样本量的进一步试验来确认其有效性、可靠性和适用性。根据个体患者情况调整MDQ可能会提高其准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7304/11695504/5ec566e9c0c9/12471_2024_1921_Fig1_HTML.jpg

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