Comorbidity Patterns in Older Patients Undergoing Hip Fracture Surgery: A Comorbidity Network Analysis Study
Comorbidity network analysis (CNA) is a technique in which mathematical graphs encode correlations (edges) among diseases (nodes) inferred from the disease co-occurrence data of a patient group. The present study applied this network-based approach to identifying comorbidity patterns in older patien...
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Veröffentlicht in: | Clinical nursing research 2024-01, Vol.33 (1), p.70-80 |
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description | Comorbidity network analysis (CNA) is a technique in which mathematical graphs encode correlations (edges) among diseases (nodes) inferred from the disease co-occurrence data of a patient group. The present study applied this network-based approach to identifying comorbidity patterns in older patients undergoing hip fracture surgery. This was a retrospective observational cohort study using electronic health records (EHR). EHR data were extracted from the one University Health System in the southeast United States. The cohort included patients aged 65 and above who had a first-time low-energy traumatic hip fracture treated surgically between October 1, 2015 and December 31, 2018 (n = 1,171). Comorbidity includes 17 diagnoses classified by the Charlson Comorbidity Index. The CNA investigated the comorbid associations among 17 diagnoses. The association strength was quantified using the observed-to-expected ratio (OER). Several network centrality measures were used to examine the importance of nodes, namely degree, strength, closeness, and betweenness centrality. A cluster detection algorithm was employed to determine specific clusters of comorbidities. Twelve diseases were significantly interconnected in the network (OER > 1, p-value 2.5). Cerebrovascular disease, congestive heart failure, and myocardial infarction were identified as the central diseases that co-occurred with numerous other diseases. Two distinct clusters were noted, and the largest cluster comprised 10 diseases, primarily encompassing cardiometabolic and cognitive disorders. The results highlight specific patient comorbidities that could be used to guide clinical assessment, management, and targeted interventions that improve hip fracture outcomes in this patient group. |
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The present study applied this network-based approach to identifying comorbidity patterns in older patients undergoing hip fracture surgery. This was a retrospective observational cohort study using electronic health records (EHR). EHR data were extracted from the one University Health System in the southeast United States. The cohort included patients aged 65 and above who had a first-time low-energy traumatic hip fracture treated surgically between October 1, 2015 and December 31, 2018 (n = 1,171). Comorbidity includes 17 diagnoses classified by the Charlson Comorbidity Index. The CNA investigated the comorbid associations among 17 diagnoses. The association strength was quantified using the observed-to-expected ratio (OER). Several network centrality measures were used to examine the importance of nodes, namely degree, strength, closeness, and betweenness centrality. A cluster detection algorithm was employed to determine specific clusters of comorbidities. Twelve diseases were significantly interconnected in the network (OER > 1, p-value < .05). The most robust associations were between metastatic carcinoma and mild liver disease, myocardial infarction and congestive heart failure, and hemi/paraplegia and cerebrovascular disease (OER > 2.5). Cerebrovascular disease, congestive heart failure, and myocardial infarction were identified as the central diseases that co-occurred with numerous other diseases. Two distinct clusters were noted, and the largest cluster comprised 10 diseases, primarily encompassing cardiometabolic and cognitive disorders. The results highlight specific patient comorbidities that could be used to guide clinical assessment, management, and targeted interventions that improve hip fracture outcomes in this patient group.</description><identifier>ISSN: 1054-7738</identifier><identifier>EISSN: 1552-3799</identifier><identifier>DOI: 10.1177/10547738231209367</identifier><identifier>PMID: 37932937</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Aged ; Associations ; Cancer ; Cerebrovascular disease ; Cerebrovascular Disorders ; Clinical assessment ; Closeness ; Cognitive impairment ; Cohort analysis ; Cohort Studies ; Comorbidity ; Computerized medical records ; Electronic health records ; Fractured hips ; Fractures ; Graphs ; Health records ; Heart attacks ; Heart Failure ; Hip Fractures - epidemiology ; Hip Fractures - surgery ; Hip joint ; Humans ; Liver diseases ; Myocardial Infarction ; Network analysis ; Network centrality ; Older people ; Paraplegics ; Retrospective Studies ; Risk Factors ; Surgery ; United States</subject><ispartof>Clinical nursing research, 2024-01, Vol.33 (1), p.70-80</ispartof><rights>The Author(s) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c320t-7be2c2c5413acbb2d77ee16a506432dd6657885537759abbb1f0e2cceb0461463</cites><orcidid>0000-0001-9491-6519 ; 0000-0001-6860-452X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/10547738231209367$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/10547738231209367$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>315,781,785,21824,27929,27930,31004,43626,43627</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37932937$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Chiyoung</creatorcontrib><creatorcontrib>Wei, Sijia</creatorcontrib><creatorcontrib>McConnell, Eleanor S.</creatorcontrib><creatorcontrib>Tsumura, Hideyo</creatorcontrib><creatorcontrib>Xue, Tingzhong (Michelle)</creatorcontrib><creatorcontrib>Pan, Wei</creatorcontrib><title>Comorbidity Patterns in Older Patients Undergoing Hip Fracture Surgery: A Comorbidity Network Analysis Study</title><title>Clinical nursing research</title><addtitle>Clin Nurs Res</addtitle><description>Comorbidity network analysis (CNA) is a technique in which mathematical graphs encode correlations (edges) among diseases (nodes) inferred from the disease co-occurrence data of a patient group. The present study applied this network-based approach to identifying comorbidity patterns in older patients undergoing hip fracture surgery. This was a retrospective observational cohort study using electronic health records (EHR). EHR data were extracted from the one University Health System in the southeast United States. The cohort included patients aged 65 and above who had a first-time low-energy traumatic hip fracture treated surgically between October 1, 2015 and December 31, 2018 (n = 1,171). Comorbidity includes 17 diagnoses classified by the Charlson Comorbidity Index. The CNA investigated the comorbid associations among 17 diagnoses. The association strength was quantified using the observed-to-expected ratio (OER). Several network centrality measures were used to examine the importance of nodes, namely degree, strength, closeness, and betweenness centrality. A cluster detection algorithm was employed to determine specific clusters of comorbidities. Twelve diseases were significantly interconnected in the network (OER > 1, p-value < .05). The most robust associations were between metastatic carcinoma and mild liver disease, myocardial infarction and congestive heart failure, and hemi/paraplegia and cerebrovascular disease (OER > 2.5). Cerebrovascular disease, congestive heart failure, and myocardial infarction were identified as the central diseases that co-occurred with numerous other diseases. Two distinct clusters were noted, and the largest cluster comprised 10 diseases, primarily encompassing cardiometabolic and cognitive disorders. The results highlight specific patient comorbidities that could be used to guide clinical assessment, management, and targeted interventions that improve hip fracture outcomes in this patient group.</description><subject>Aged</subject><subject>Associations</subject><subject>Cancer</subject><subject>Cerebrovascular disease</subject><subject>Cerebrovascular Disorders</subject><subject>Clinical assessment</subject><subject>Closeness</subject><subject>Cognitive impairment</subject><subject>Cohort analysis</subject><subject>Cohort Studies</subject><subject>Comorbidity</subject><subject>Computerized medical records</subject><subject>Electronic health records</subject><subject>Fractured hips</subject><subject>Fractures</subject><subject>Graphs</subject><subject>Health records</subject><subject>Heart attacks</subject><subject>Heart Failure</subject><subject>Hip Fractures - epidemiology</subject><subject>Hip Fractures - surgery</subject><subject>Hip joint</subject><subject>Humans</subject><subject>Liver diseases</subject><subject>Myocardial Infarction</subject><subject>Network analysis</subject><subject>Network centrality</subject><subject>Older people</subject><subject>Paraplegics</subject><subject>Retrospective Studies</subject><subject>Risk Factors</subject><subject>Surgery</subject><subject>United States</subject><issn>1054-7738</issn><issn>1552-3799</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><recordid>eNp1kV1LwzAUhoMobk5_gDcS8Mabaj6b1rsx1Amigu66JO3ZyOzamaRI_70Z8wvFq5zkfd73hHMQOqbknFKlLiiRQimeMU4ZyXmqdtCQSskSrvJ8N9ZRTzbAAB14vySECEboPhpEnbOcqyGqJ-2qdcZWNvT4UYcArvHYNvihrsBtXiw0weNZE6-L1jYLPLVrfO10GToH-KlzC3D9JR7jn0n3EN5a94LHja57bz1-Cl3VH6K9ua49HH2cIzS7vnqeTJO7h5vbyfguKTkjIVEGWMlKKSjXpTGsUgqAplqSVHBWVWkqVZZJyZWSuTbG0DmJjhIMESkVKR-hs23u2rWvHfhQrKwvoa51A23nC5ZlaS6IEiyip7_QZdu5-OtI5YRnguRURYpuqdK13juYF2tnV9r1BSXFZhXFn1VEz8lHcmdWUH05PmcfgfMt4PUCvtv-n_gOKQiQpg</recordid><startdate>202401</startdate><enddate>202401</enddate><creator>Lee, Chiyoung</creator><creator>Wei, Sijia</creator><creator>McConnell, Eleanor S.</creator><creator>Tsumura, Hideyo</creator><creator>Xue, Tingzhong (Michelle)</creator><creator>Pan, Wei</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>ASE</scope><scope>FPQ</scope><scope>K6X</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9491-6519</orcidid><orcidid>https://orcid.org/0000-0001-6860-452X</orcidid></search><sort><creationdate>202401</creationdate><title>Comorbidity Patterns in Older Patients Undergoing Hip Fracture Surgery: A Comorbidity Network Analysis Study</title><author>Lee, Chiyoung ; Wei, Sijia ; McConnell, Eleanor S. ; Tsumura, Hideyo ; Xue, Tingzhong (Michelle) ; Pan, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c320t-7be2c2c5413acbb2d77ee16a506432dd6657885537759abbb1f0e2cceb0461463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aged</topic><topic>Associations</topic><topic>Cancer</topic><topic>Cerebrovascular disease</topic><topic>Cerebrovascular Disorders</topic><topic>Clinical assessment</topic><topic>Closeness</topic><topic>Cognitive impairment</topic><topic>Cohort analysis</topic><topic>Cohort Studies</topic><topic>Comorbidity</topic><topic>Computerized medical records</topic><topic>Electronic health records</topic><topic>Fractured hips</topic><topic>Fractures</topic><topic>Graphs</topic><topic>Health records</topic><topic>Heart attacks</topic><topic>Heart Failure</topic><topic>Hip Fractures - epidemiology</topic><topic>Hip Fractures - surgery</topic><topic>Hip joint</topic><topic>Humans</topic><topic>Liver diseases</topic><topic>Myocardial Infarction</topic><topic>Network analysis</topic><topic>Network centrality</topic><topic>Older people</topic><topic>Paraplegics</topic><topic>Retrospective Studies</topic><topic>Risk Factors</topic><topic>Surgery</topic><topic>United States</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Chiyoung</creatorcontrib><creatorcontrib>Wei, Sijia</creatorcontrib><creatorcontrib>McConnell, Eleanor S.</creatorcontrib><creatorcontrib>Tsumura, Hideyo</creatorcontrib><creatorcontrib>Xue, Tingzhong (Michelle)</creatorcontrib><creatorcontrib>Pan, Wei</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>British Nursing Index</collection><collection>British Nursing Index (BNI) (1985 to Present)</collection><collection>British Nursing Index</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical nursing research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Chiyoung</au><au>Wei, Sijia</au><au>McConnell, Eleanor S.</au><au>Tsumura, Hideyo</au><au>Xue, Tingzhong (Michelle)</au><au>Pan, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comorbidity Patterns in Older Patients Undergoing Hip Fracture Surgery: A Comorbidity Network Analysis Study</atitle><jtitle>Clinical nursing research</jtitle><addtitle>Clin Nurs Res</addtitle><date>2024-01</date><risdate>2024</risdate><volume>33</volume><issue>1</issue><spage>70</spage><epage>80</epage><pages>70-80</pages><issn>1054-7738</issn><eissn>1552-3799</eissn><abstract>Comorbidity network analysis (CNA) is a technique in which mathematical graphs encode correlations (edges) among diseases (nodes) inferred from the disease co-occurrence data of a patient group. The present study applied this network-based approach to identifying comorbidity patterns in older patients undergoing hip fracture surgery. This was a retrospective observational cohort study using electronic health records (EHR). EHR data were extracted from the one University Health System in the southeast United States. The cohort included patients aged 65 and above who had a first-time low-energy traumatic hip fracture treated surgically between October 1, 2015 and December 31, 2018 (n = 1,171). Comorbidity includes 17 diagnoses classified by the Charlson Comorbidity Index. The CNA investigated the comorbid associations among 17 diagnoses. The association strength was quantified using the observed-to-expected ratio (OER). Several network centrality measures were used to examine the importance of nodes, namely degree, strength, closeness, and betweenness centrality. A cluster detection algorithm was employed to determine specific clusters of comorbidities. Twelve diseases were significantly interconnected in the network (OER > 1, p-value < .05). The most robust associations were between metastatic carcinoma and mild liver disease, myocardial infarction and congestive heart failure, and hemi/paraplegia and cerebrovascular disease (OER > 2.5). Cerebrovascular disease, congestive heart failure, and myocardial infarction were identified as the central diseases that co-occurred with numerous other diseases. Two distinct clusters were noted, and the largest cluster comprised 10 diseases, primarily encompassing cardiometabolic and cognitive disorders. The results highlight specific patient comorbidities that could be used to guide clinical assessment, management, and targeted interventions that improve hip fracture outcomes in this patient group.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>37932937</pmid><doi>10.1177/10547738231209367</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-9491-6519</orcidid><orcidid>https://orcid.org/0000-0001-6860-452X</orcidid></addata></record> |
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subjects | Aged Associations Cancer Cerebrovascular disease Cerebrovascular Disorders Clinical assessment Closeness Cognitive impairment Cohort analysis Cohort Studies Comorbidity Computerized medical records Electronic health records Fractured hips Fractures Graphs Health records Heart attacks Heart Failure Hip Fractures - epidemiology Hip Fractures - surgery Hip joint Humans Liver diseases Myocardial Infarction Network analysis Network centrality Older people Paraplegics Retrospective Studies Risk Factors Surgery United States |
title | Comorbidity Patterns in Older Patients Undergoing Hip Fracture Surgery: A Comorbidity Network Analysis Study |
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