Schäfer Ingmar, Kaduszkiewicz Hanna, Wagner Hans-Otto, Schön Gerhard, Scherer Martin, van den Bussche Hendrik
Department of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistr, 52, Hamburg 20246, Germany.
BMC Public Health. 2014 Dec 16;14:1285. doi: 10.1186/1471-2458-14-1285.
Multimorbidity is highly prevalent in the elderly and relates to many adverse outcomes, such as higher mortality, increased disability and functional decline. Many studies tried to reduce the heterogeneity of multimorbidity by identifying multimorbidity clusters or disease combinations, however, the internal structure of multimorbidity clusters and the linking between disease combinations and clusters are still unknown. The aim of this study was to depict which diseases were associated with each other on person-level within the clusters and which ones were responsible for overlapping multimorbidity clusters.
The study analyses insurance claims data of the Gmünder ErsatzKasse from 2006 with 43,632 female and 54,987 male patients who were 65 years and older. The analyses are based on multimorbidity clusters from a previous study and combinations of three diseases ("triads") identified by observed/expected ratios ≥ 2 and prevalence rates ≥ 1%. In order to visualise a "disease network", an edgelist was extracted from these triads, which was analysed by network analysis and graphically linked to multimorbidity clusters.
We found 57 relevant triads consisting of 31 chronic conditions with 200 disease associations ("edges") in females and 51 triads of 29 diseases with 174 edges in males. In the disease network, the cluster of cardiovascular and metabolic disorders comprised 12 of these conditions in females and 14 in males. The cluster of anxiety, depression, somatoform disorders, and pain consisted of 15 conditions in females and 12 in males.
We were able to show which diseases were associated with each other in our data set, to which clusters the diseases were assigned, and which diseases were responsible for overlapping clusters. The disease with the highest number of associations, and the most important mediator between diseases, was chronic low back pain. In females, depression was also associated with many other diseases. We found a multitude of associations between disorders of the metabolic syndrome of which hypertension was the most central disease. The most prominent bridges were between the metabolic syndrome and musculoskeletal disorders. Guideline developers might find our approach useful as a basis for discussing which comorbidity should be addressed.
多病共存现象在老年人中极为普遍，且与许多不良后果相关，如更高的死亡率、残疾增加和功能衰退。许多研究试图通过识别多病共存集群或疾病组合来减少多病共存的异质性，然而，多病共存集群的内部结构以及疾病组合与集群之间的联系仍然未知。本研究的目的是描述在集群内个体层面上哪些疾病相互关联，以及哪些疾病导致了重叠的多病共存集群。
该研究分析了2006年Gmünder ErsatzKasse的保险理赔数据，涉及43632名65岁及以上的女性患者和54987名男性患者。分析基于先前研究中的多病共存集群以及通过观察/预期比率≥2和患病率≥1%确定的三种疾病组合（“三联征”）。为了可视化“疾病网络”，从这些三联征中提取了一个边列表，并通过网络分析进行分析，并以图形方式与多病共存集群相联系。
我们在女性中发现了57个相关三联征，由31种慢性病组成，有200种疾病关联（“边”）；在男性中发现了51个由29种疾病组成的三联征，有174条边。在疾病网络中，心血管和代谢紊乱集群在女性中包含其中12种疾病，在男性中包含14种疾病。焦虑、抑郁、躯体形式障碍和疼痛集群在女性中由15种疾病组成，在男性中由12种疾病组成。
我们能够展示数据集中哪些疾病相互关联、这些疾病被分配到哪些集群以及哪些疾病导致了重叠集群。关联数量最多且是疾病之间最重要中介的疾病是慢性腰痛。在女性中，抑郁症也与许多其他疾病相关。我们发现代谢综合征的疾病之间存在大量关联，其中高血压是最核心的疾病。最显著的桥梁存在于代谢综合征和肌肉骨骼疾病之间。指南制定者可能会发现我们的方法有助于作为讨论应处理哪些合并症的基础。
