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神经性厌食症患者极低体重时的骨密度。

Bone mineral density at extremely low weight in patients with anorexia nervosa.

机构信息

Clinical Nutrition unit, Paul Brousse University Hospital (AP-HP), Villejuif, France.

GHU Paris Psychiatrie et Neurosciences, CMME, Hôpital Sainte-Anne, Paris, France.

出版信息

Clin Endocrinol (Oxf). 2021 Sep;95(3):423-429. doi: 10.1111/cen.14498. Epub 2021 May 30.

DOI:10.1111/cen.14498
PMID:33982330
Abstract

OBJECTIVE

Low bone mineral density (BMD) is a frequent and invalidating consequence of chronic undernourishment in patients with anorexia nervosa (AN). The aim of this study was to assess prevalence and clinic-biological correlates of low BMD and fractures in extremely undernourished inpatients with AN.

DESIGN

Retrospective cohort study.

PATIENTS AND MEASUREMENTS

This study included 97 extremely malnourished female inpatients with AN consecutively admitted over 2 years. Clinical-biological variables, history of fractures and BMD by dual-energy X-ray absorptiometry (DXA) were examined to find predictors of low BMD and fractures.

RESULTS

The prevalence of low BMD was of 51% for lumbar spine and 38% for femoral neck. Z-scores were lower at lumbar spine (-2.2 ± 1.2 SD) than at femoral neck (-1.9 ± 0.9 SD) (P<.01). Fragility fractures were reported by 10% of patients. BMD was mainly predicted by FFM, illness duration, age at onset and restricting AN (P<.05). Fractures were predicted by sodium concentrations, femoral neck Z-score and illness duration (P<.03).

CONCLUSION

Extremely severe patients with AN have high prevalence of low BMD, predicted by severity and chronicity of malnutrition.

摘要

目的

低骨密度(BMD)是神经性厌食症(AN)患者慢性营养不良的常见且致残后果。本研究旨在评估极度营养不良的 AN 住院患者低 BMD 和骨折的患病率及临床生物学相关性。

设计

回顾性队列研究。

患者和测量方法

本研究纳入了 2 年内连续收治的 97 名极度营养不良的女性 AN 住院患者。检查了临床生物学变量、骨折史和双能 X 线吸收法(DXA)的 BMD,以寻找低 BMD 和骨折的预测因素。

结果

腰椎的低 BMD 患病率为 51%,股骨颈为 38%。腰椎处的 Z 分数(-2.2±1.2 SD)低于股骨颈处(-1.9±0.9 SD)(P<.01)。10%的患者报告有脆性骨折。FFM、病程、发病年龄和限制型 AN 主要预测 BMD(P<.05)。骨折主要由血清钠浓度、股骨颈 Z 分数和病程预测(P<.03)。

结论

患有严重 AN 的极度严重患者存在低 BMD 的高患病率,这可由营养不良的严重程度和慢性程度来预测。

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