The architecture of co-morbidity networks of physical and mental health conditions in military veterans

被引:5
作者
Alexander-Bloch, Aaron F. [1 ,2 ]
Raznahan, Armin [3 ]
Shinohara, Russell T. [4 ]
Mathias, Samuel R. [5 ]
Bathulapalli, Harini [6 ,7 ]
Bhalla, Ish P. [8 ]
Goulet, Joseph L. [6 ,7 ]
Satterthwaite, Theodore D. [1 ]
Bassett, Danielle S. [1 ,9 ,10 ,11 ,12 ,13 ]
Glahn, David C. [5 ]
Brandt, Cynthia A. [6 ,7 ]
机构
[1] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA
[2] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA
[3] NIMH, Dev Neurogen Unit, Human Genet Branch, Intramural Program, Bethesda, MA USA
[4] Univ Penn, Dept Biostat Epidemiol & Informat, Philadelphia, PA 19104 USA
[5] Harvard Med Sch, Dept Psychiat, Boston Childrens Hosp, Boston, MA 02115 USA
[6] US Dept Vet Affairs VA Connecticut Healthcare Sys, West Haven, CT USA
[7] Yale Univ, Sch Med, Yale Ctr Med Informat, New Haven, CT USA
[8] Univ Calif Los Angeles, Natl Clinician Scholars Program, Los Angeles, CA USA
[9] Univ Penn, Dept Bioengn, Philadelphia, PA 19104 USA
[10] Univ Penn, Dept Elect & Syst Engn, Philadelphia, PA 19104 USA
[11] Univ Penn, Dept Phys & Astron, Philadelphia, PA 19104 USA
[12] Univ Penn, Dept Neurol, Philadelphia, PA 19104 USA
[13] Santa Fe Inst, Santa Fe, NM 87501 USA
来源
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2020年 / 476卷 / 2239期
基金
美国国家卫生研究院;
关键词
network science; co-morbidity; veterans; psychiatry; modularity; POSTTRAUMATIC-STRESS-DISORDER; REGULARIZATION PATHS; COMMUNITY STRUCTURE; GENDER-DIFFERENCES; DEPRESSION; DISEASE; COMORBIDITY; ALCOHOL; PAIN; SEX;
D O I
10.1098/rspa.2019.0790
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Co-morbidity between medical and psychiatric conditions is commonly considered between individual pairs of conditions. However, an important alternative is to consider all conditions as part of a co-morbidity network, which encompasses all interactions between patients and a healthcare system. Analysis of co-morbidity networks could detect and quantify general tendencies not observed by smaller-scale studies. Here, we investigate the co-morbidity network derived from longitudinal healthcare records from approximately 1 million United States military veterans, a population disproportionately impacted by psychiatric morbidity and psychological trauma. Network analyses revealed marked and heterogenous patterns of co-morbidity, including a multi-scale community structure composed of groups of commonly co-morbid conditions. Psychiatric conditions including posttraumatic stress disorder were strong predictors of future medical morbidity. Neurological conditions and conditions associated with chronic pain were particularly highly co-morbid with psychiatric conditions. Across conditions, the degree of co-morbidity was positively associated with mortality. Co-morbidity was modified by biological sex and could be used to predict future diagnostic status, with out-of-sample prediction accuracy of 90-92%. Understanding complex patterns of disease co-morbidity has the potential to lead to improved designs of systems of care and the development of targeted interventions that consider the broader context of mental and physical health.
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页数:23
相关论文
共 81 条
[21]   Metabolic and cardiovascular adverse effects associated with antipsychotic drugs [J].
De Hert, Marc ;
Detraux, Johan ;
van Winkel, Ruud ;
Yu, Weiping ;
Correll, Christoph U. .
NATURE REVIEWS ENDOCRINOLOGY, 2012, 8 (02) :114-126
[22]  
De Meo P., 2011, Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA), P88, DOI 10.1109/ISDA.2011.6121636
[23]   Posttraumatic Stress Disorder, Cardiovascular, and Metabolic Disease: A Review of the Evidence [J].
Dedert, Eric A. ;
Calhoun, Patrick S. ;
Watkins, Lana L. ;
Sherwood, Andrew ;
Beckham, Jean C. .
ANNALS OF BEHAVIORAL MEDICINE, 2010, 39 (01) :61-78
[24]   Does rejection hurt? An fMRI study of social exclusion [J].
Eisenberger, NI ;
Lieberman, MD ;
Williams, KD .
SCIENCE, 2003, 302 (5643) :290-292
[25]  
Elixhauser A, 2005, CLIN CLASSIFICATIONS
[26]   Subgraph centrality and clustering in complex hyper-networks [J].
Estrada, E ;
Rodríguez-Velázquez, JA .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2006, 364 (581-594) :581-594
[27]   Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007-2008 credit crisis [J].
Fenn, Daniel J. ;
Porter, Mason A. ;
McDonald, Mark ;
Williams, Stacy ;
Johnson, Neil F. ;
Jones, Nick S. .
CHAOS, 2009, 19 (03)
[28]   Neuroinflammation at the interface of depression and cardiovascular disease: Evidence from rodent models of social stress [J].
Finnell, Julie E. ;
Wood, Susan K. .
NEUROBIOLOGY OF STRESS, 2016, 4 :1-14
[29]  
Folino F, 2010, LECT NOTES COMPUTER, V6266
[30]   Resolution limit in community detection [J].
Fortunato, Santo ;
Barthelemy, Marc .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2007, 104 (01) :36-41