{"id":"https://openalex.org/W7151037104","doi":"https://doi.org/10.1186/s12911-026-03460-x","title":"Latent pain class identification, longitudinal transitions, and machine learning prediction of incident low back pain in middle-aged and older Chinese adults","display_name":"Latent pain class identification, longitudinal transitions, and machine learning prediction of incident low back pain in middle-aged and older Chinese adults","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7151037104","doi":"https://doi.org/10.1186/s12911-026-03460-x","pmid":"https://pubmed.ncbi.nlm.nih.gov/41943141"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-026-03460-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03460-x","pdf_url":null,"source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s12911-026-03460-x","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129457209","display_name":"Junpeng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119028","display_name":"Beijing Anzhen Hospital","ror":"https://ror.org/02h2j1586","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junpeng Liu","raw_affiliation_strings":["Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China","institution_ids":["https://openalex.org/I4210119028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104255143","display_name":"Zhiheng Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119028","display_name":"Beijing Anzhen Hospital","ror":"https://ror.org/02h2j1586","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Zhao","raw_affiliation_strings":["Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China","institution_ids":["https://openalex.org/I4210119028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133044079","display_name":"Shuhuan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119028","display_name":"Beijing Anzhen Hospital","ror":"https://ror.org/02h2j1586","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhuan Li","raw_affiliation_strings":["Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China","institution_ids":["https://openalex.org/I4210119028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103049213","display_name":"Xinglin Liu","orcid":"https://orcid.org/0000-0001-6681-2640"},"institutions":[{"id":"https://openalex.org/I4210119028","display_name":"Beijing Anzhen Hospital","ror":"https://ror.org/02h2j1586","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinglin Liu","raw_affiliation_strings":["Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China","institution_ids":["https://openalex.org/I4210119028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044390120","display_name":"Shude Xu","orcid":"https://orcid.org/0009-0002-1809-4271"},"institutions":[{"id":"https://openalex.org/I4210119028","display_name":"Beijing Anzhen Hospital","ror":"https://ror.org/02h2j1586","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheyang Xu","raw_affiliation_strings":["Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China","institution_ids":["https://openalex.org/I4210119028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133059071","display_name":"Bowen Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119028","display_name":"Beijing Anzhen Hospital","ror":"https://ror.org/02h2j1586","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Lu","raw_affiliation_strings":["Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China","institution_ids":["https://openalex.org/I4210119028"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101536420","display_name":"Xianglong Meng","orcid":"https://orcid.org/0009-0000-2006-304X"},"institutions":[{"id":"https://openalex.org/I4210119028","display_name":"Beijing Anzhen Hospital","ror":"https://ror.org/02h2j1586","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119028"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xianglong Meng","raw_affiliation_strings":["Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China. spinesurgeonmeng@ccmu.edu.cn"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Orthopaedic Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing101118, China. spinesurgeonmeng@ccmu.edu.cn","institution_ids":["https://openalex.org/I4210119028"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101536420"],"corresponding_institution_ids":["https://openalex.org/I4210119028"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36524841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10084","display_name":"Musculoskeletal pain and rehabilitation","score":0.7842000126838684,"subfield":{"id":"https://openalex.org/subfields/2736","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10084","display_name":"Musculoskeletal pain and rehabilitation","score":0.7842000126838684,"subfield":{"id":"https://openalex.org/subfields/2736","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.02850000001490116,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10238","display_name":"Spine and Intervertebral Disc Pathology","score":0.018200000748038292,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/low-back-pain","display_name":"Low back pain","score":0.6818000078201294},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5644000172615051},{"id":"https://openalex.org/keywords/latent-class-model","display_name":"Latent class model","score":0.5321000218391418},{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.4169999957084656},{"id":"https://openalex.org/keywords/longitudinal-study","display_name":"Longitudinal study","score":0.3221000134944916},{"id":"https://openalex.org/keywords/back-pain","display_name":"Back pain","score":0.3001999855041504}],"concepts":[{"id":"https://openalex.org/C2780907711","wikidata":"https://www.wikidata.org/wiki/Q852163","display_name":"Low back pain","level":3,"score":0.6818000078201294},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6119999885559082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.570900022983551},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5644000172615051},{"id":"https://openalex.org/C70727504","wikidata":"https://www.wikidata.org/wiki/Q1806878","display_name":"Latent class model","level":2,"score":0.5321000218391418},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.5214999914169312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44929999113082886},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.43700000643730164},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.4169999957084656},{"id":"https://openalex.org/C2777895361","wikidata":"https://www.wikidata.org/wiki/Q1758614","display_name":"Longitudinal study","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C2776501849","wikidata":"https://www.wikidata.org/wiki/Q5781808","display_name":"Back pain","level":3,"score":0.3001999855041504},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.27720001339912415},{"id":"https://openalex.org/C205545832","wikidata":"https://www.wikidata.org/wiki/Q17156455","display_name":"Young adult","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.25940001010894775}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077272","descriptor_name":"Latent Class Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077272","descriptor_name":"Latent Class Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077272","descriptor_name":"Latent Class Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000095225","descriptor_name":"East Asian People","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000095225","descriptor_name":"East Asian People","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000095225","descriptor_name":"East Asian People","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098404","descriptor_name":"Boosting Machine Learning Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098404","descriptor_name":"Boosting Machine Learning Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098404","descriptor_name":"Boosting Machine Learning Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098412","descriptor_name":"Predictive Learning Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098412","descriptor_name":"Predictive Learning Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098412","descriptor_name":"Predictive Learning Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098429","descriptor_name":"Classification Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098429","descriptor_name":"Classification Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098429","descriptor_name":"Classification Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098437","descriptor_name":"Prediction Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D002681","descriptor_name":"China","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008137","descriptor_name":"Longitudinal Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008137","descriptor_name":"Longitudinal Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008137","descriptor_name":"Longitudinal Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D017116","descriptor_name":"Low Back Pain","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12911-026-03460-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03460-x","pdf_url":null,"source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:41943141","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41943141","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC medical informatics and decision making","raw_type":null},{"id":"pmh:oai:doaj.org/article:0b0510f327074765a7b1cdf95ad75cf8","is_oa":true,"landing_page_url":"https://doaj.org/article/0b0510f327074765a7b1cdf95ad75cf8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Medical Informatics and Decision Making, Vol 26, Iss 1 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13188491","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13188491/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Inform Decis Mak","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12911-026-03460-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-026-03460-x","pdf_url":null,"source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1999253763","display_name":null,"funder_award_id":"62276173","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1754691347","https://openalex.org/W1829624290","https://openalex.org/W2063954261","https://openalex.org/W2090330784","https://openalex.org/W2162951521","https://openalex.org/W2164910451","https://openalex.org/W2617281868","https://openalex.org/W2786697307","https://openalex.org/W2793254343","https://openalex.org/W2800947914","https://openalex.org/W2802074185","https://openalex.org/W2905788968","https://openalex.org/W2911357639","https://openalex.org/W2921927514","https://openalex.org/W2936935304","https://openalex.org/W2981070229","https://openalex.org/W3005437800","https://openalex.org/W3032942076","https://openalex.org/W3038885192","https://openalex.org/W3092849554","https://openalex.org/W3094444362","https://openalex.org/W3108106255","https://openalex.org/W3205974715","https://openalex.org/W3209349540","https://openalex.org/W4211243114","https://openalex.org/W4213157453","https://openalex.org/W4213379505","https://openalex.org/W4294391411","https://openalex.org/W4297369823","https://openalex.org/W4308796746","https://openalex.org/W4313379761","https://openalex.org/W4317107783","https://openalex.org/W4321373155","https://openalex.org/W4365483662","https://openalex.org/W4377289287","https://openalex.org/W4382397129","https://openalex.org/W4390640660","https://openalex.org/W4393074563","https://openalex.org/W4394985550","https://openalex.org/W4399495442","https://openalex.org/W4399922784","https://openalex.org/W4400643003","https://openalex.org/W4400658804","https://openalex.org/W4403701698","https://openalex.org/W4404143643","https://openalex.org/W4409669091","https://openalex.org/W4411624517","https://openalex.org/W4414940147","https://openalex.org/W4415082038","https://openalex.org/W4416771451","https://openalex.org/W7119482745"],"related_works":[],"abstract_inverted_index":{"OBJECTIVE:":[0],"Chronic":[1],"pain":[2,13,37,48,160,170,199,208,216],"is":[3],"common":[4],"among":[5,75],"middle-aged":[6,289],"and":[7,17,30,42,70,84,90,123,140,147,166,179,204,254,282,290,297,305],"older":[8,205,291],"Chinese":[9,292],"adults,":[10],"yet":[11],"latent":[12,36],"patterns,":[14],"temporal":[15,82],"transitions,":[16],"individual":[18],"susceptibility":[19],"factors":[20],"remain":[21,197],"unclear.":[22],"Using":[23],"five":[24],"waves":[25],"of":[26,45,88,256,264,312],"the":[27,85,176,183,224,228,242,261,309],"China":[28],"Health":[29],"Retirement":[31],"Longitudinal":[32],"Study,":[33],"we":[34,94],"assessed":[35,73],"classes,":[38],"their":[39],"dynamic":[40,298],"changes,":[41],"key":[43,310],"predictors":[44,263,268,311],"low":[46],"back":[47],"(LBP)":[49],"in":[50,198,227,288],"adults":[51,206,293],"aged":[52],"\u2265":[53],"45":[54],"years.":[55],"METHODS:":[56],"Latent":[57,77],"class":[58],"analysis":[59,79],"(LCA)":[60],"was":[61,128,171],"used":[62,270],"to":[63,194,212,214,271],"identify":[64],"pain-site":[65],"patterns":[66,287],"at":[67],"each":[68],"wave,":[69,156],"Kendall":[71],"correlations":[72],"associations":[74],"sites.":[76],"transition":[78,181],"(LTA)":[80],"evaluated":[81],"shifts":[83],"modifying":[86],"effects":[87],"age":[89],"sex.":[91],"For":[92],"LBP,":[93],"developed":[95],"machine-learning":[96,238],"models":[97,239],"(logistic":[98],"regression,":[99,139],"random":[100],"forest,":[101],"decision":[102],"tree,":[103],"extreme":[104,141],"gradient":[105,108,142],"boosting,":[106,143],"light":[107],"boosting":[109],"machine,":[110,113],"support":[111],"vector":[112],"artificial":[114,135],"neural":[115,136,221],"network),":[116],"optimized":[117],"through":[118],"multiple":[119,237],"imputation,":[120],"feature":[121],"engineering,":[122],"grid":[124],"search.":[125],"A":[126],"nomogram":[127,274],"constructed":[129],"from":[130],"features":[131],"consistently":[132,240],"important":[133],"across":[134],"network,":[137],"logistic":[138],"followed":[144],"by":[145],"subgroup":[146],"mediation":[148],"analyses.":[149],"RESULTS:":[150],"LCA":[151],"identified":[152,241],"2\u20134":[153],"classes":[154],"per":[155],"summarized":[157],"into":[158],"three":[159],"states:":[161],"widespread":[162],"pain,":[163,165],"localized":[164,215],"no":[167],"pain.":[168],"Lumbar":[169],"most":[172],"common.":[173],"LTA":[174],"confirmed":[175],"three-state":[177],"model":[178],"nine":[180],"pathways;":[182],"no-pain":[184],"state":[185],"showed":[186],"highest":[187],"stability":[188],"(82.3%).":[189],"Men":[190],"were":[191,209,269],"more":[192,210],"likely":[193,211],"enter":[195],"or":[196],"states":[200],"(p":[201,217],"<":[202,218],"0.05),":[203],"without":[207],"shift":[213],"0.05).":[219],"Artificial":[220],"network":[222],"achieved":[223],"best":[225],"performance":[226],"test":[229],"set.":[230],"SHapley":[231],"additive":[232],"explanations":[233],"analyses":[234],"based":[235],"on":[236],"center":[243],"for":[244],"epidemiologic":[245],"studies":[246],"depression":[247],"scale-10":[248],"items,":[249],"cumulative":[250],"chronic":[251,302],"disease":[252,303],"burden,":[253,304],"activities":[255],"daily":[257],"living":[258],"function":[259],"as":[260],"strongest":[262],"LBP.":[265,313],"Seven":[266],"stable":[267],"build":[272],"a":[273],"with":[275],"favorable":[276],"discrimination":[277],"(C-index":[278],"=":[279],"0.783),":[280],"calibration,":[281],"clinical":[283],"utility.":[284],"CONCLUSION:":[285],"Pain":[286],"show":[294],"substantial":[295],"heterogeneity":[296],"transitions.":[299],"Psychological":[300],"status,":[301],"functional":[306],"capacity":[307],"are":[308]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-04-07T00:00:00"}
