Phenotypic Disease Network Analysis to Identify Comorbidity Patterns in Hospitalized Patients with Ischemic Heart Disease Using Large-Scale Administrative Data

Abstract

Ischemic heart disease (IHD) exhibits elevated comorbidity. However, few studies have systematically analyzed the comorbid status of IHD patients with respect to the entire spectrum of chronic diseases. This study applied network analysis to provide a complete picture of physical and mental comorbidities in hospitalized patients with IHD using large-scale administrative data. Hospital discharge records from a provincial healthcare database of IHD inpatients (n = 1,035,338) and one-to-one matched controls were included in this retrospective analysis. We constructed the phenotypic disease networks in IHD and control patients and further assessed differences in comorbidity patterns. The community detection method was applied to cluster diagnoses within the comorbidity network. Age- and sex-specific patterns of IHD comorbidities were also analyzed. IHD inpatients showed 50% larger comorbid burden when compared to controls. The IHD comorbidity network consisted of 1941 significant associations between 71 chronic conditions. Notably, the more densely connected comorbidities in IHD patients were not within the highly prevalent ones but the rarely prevalent ones. Two highly interlinked communities were detected in the IHD comorbidity network, where one included hypertension with heart and multi-organ failures, and another included cerebrovascular diseases, cerebrovascular risk factors and anxiety. Males exhibited higher comorbid burden than females, and thus more complex comorbidity relationships were found in males. Sex-specific disease pairs were detected, e.g., 106 and 30 disease pairs separately dominated in males and females. Aging accounts for the majority of comorbid burden, and the complexity of the comorbidity network increased with age. The network-based approach improves our understanding of IHD-related comorbidities and enhances the integrated management of patients with IHD.

Phenotypic Disease Network-Based Multimorbidity Analysis in Idiopathic Cardiomyopathy Patients with Hospital Discharge Records

“…These are complex, system-level illnesses that impact a wide range of physiological and biomolecular processes, and hence, co-occur with a wide range of other disorders. Although the comorbidities of patients with ICM remained unknown according to the limited sample size of rare diseases, the network-based comorbidities analysis for cardiovascular diseases [ 24 , 30 , 31 , 40 ] has long existed. A cross-sectional study [ 21 ] on 34,099 discharged patients in Mexico discovered that cardiovascular disease (CVD) comorbidity networks were significantly localized in prominent conditions such as cardiac arrhythmias, heart failure, chronic renal disease, hypertension, and ischemic disorders.…”

“…Ageing was responsible for the majority of comorbidities in ICM patients, which is comparable to how other chronic illnesses develop (e.g., ischemic heart disease patients [ 24 ], and chronic obstructive pulmonary disease [ 47 ]). We discovered that age influenced the comorbidity pattern in ICM patients.…”

“…Hidalgo et al [ 23 ] utilized a network analysis to track the development of the illness. Zhou et al [ 24 ] applied the phenotypic disease network for comorbidity patterns of ischemic heart disease. A network-based analysis was used in a case-control cohort study for the examination of COPD comorbidities [ 25 ].…”

Network-Based Methods for Approaching Human Pathologies from a Phenotypic Point of View

“…The pair information was then used to construct a Phenotypic Disease Network (PDN), which showed phenotypes belonging to specific disease families tending to be close in the PDN. This work has been heavily cited, and similar approaches have been applied to a range of other diseases, including ischemic heart disease [ 78 ], in which a PDN of comorbid phenotypes was built for sufferers of this disease. It has also been recently applied to look at comorbidity in depression [ 79 ], for which the authors used Pearson’s correlation to measure comorbidity between a large spectrum of phenotypic conditions.…”

Type two diabetes mellitus and microvascular complications in patients with coronary artery disease: prevalence, prognosis and choice of antithrombotic therapy

“…наряду с тем, что у больных ибС самой частой сопутствующей патологией, как было найдено в одном из больших мета-анализов наблюдательных исследований, является перенесённый им и Сд 2 типа, данная патология характеризуется высокой частотой регистрации коморбидных заболеваний в целом [74]. в одном из сетевых анализов сопутствующих физических и психических заболеваний с использованием крупномасштабных административных баз данных среди 1035338 госпитализированных пациентов с ибС при выписке среднее количество сопутствующих заболеваний составило 5, а доля пациентов, по крайней мере с двумя сопутствующими заболеваниями, -90,59% [75]. мужчины демонстри-ровали большее количество сопутствующих заболеваний, чем женщины, особенно у лиц старше 70 лет.…”