ArticleMedicine2022
Demographic predictors of treatments and surgical complications of lumbar degenerative diseases: An analysis of over 250,000 patients from the National Inpatient Sample.
Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Multi-level posterior cervical-only fusion and instrumentation with versus without extension to C1: A short-term outcomes analysis using a large database.North American Spine Society journal · 2026Article
- Rethinking measurement of movement-evoked pain with digital technology.The journal of pain · 2026Article
- Impact of Age on Hospital Outcomes Following Minimally Invasive Posterior Lumbar Interbody Fusion: Retrospective Analysis of the Nationwide Inpatient Sample Database from 2016 to 2020.JMIR medical informatics · 2026Article
- Rethinking Measurement of Movement-Evoked Pain with Digital Technology.medRxiv : the preprint server for health sciences · 2025Article
- Impact of Sociodemographic and Hospital Factors on Inpatient Bilateral Reduction Mammaplasty: A National Inpatient Sample Analysis.Plastic and reconstructive surgery. Global open · 2024Article
- A New Neuroanesthetic Protocol of Rendering Specialized Care in Treating Degenerative Lumbar Spine Diseases in High-Risk Patients: Prospective Analysis of the Results.Sovremennye tekhnologii v meditsine · 2024Article
- Advances in Osteoporosis Therapy: Focus on Osteoanabolic Agents, Secondary Fracture Prevention, and Perioperative Bone Health.Current osteoporosis reports · 2023Review
- Feasibility, Acceptability and Modification of a Post-surgical Telehealth Mindfulness-Based Intervention to Enhance Recovery After Lumbar Spine Surgery: A Prospective Intervention Study.Global advances in integrative medicine and healthArticle
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
abstractThis was a national database study.To examine the role of comorbidities and demographics on inpatient complications in patients with lumbar degenerative conditions.Degenerative conditions of the lumbar spine account for the most common indication for spine surgery in the elderly population in the United States. Significant studies investigating demographic as predictors of surgical rates and health outcomes for degenerative lumbar conditions are lacking.Data were obtained from the National Inpatient Sample from 2010 to 2014 and International Classification of Diseases, 9th revision, Clinical Modification codes were used to identify patients with a primary diagnosis of degenerative lumbar condition. Patients were stratified based on demographic variables and comorbidity status. Multivariate regression analyses were used to determine whether any individual demographic variables, such as race, sex, insurance, and hospital status predicted postoperative complications.A total of 256,859 patients were identified for analysis. The rate of overall complications was found to be 16.1% with a mortality rate of 0.10%. Female, Black, Hispanic, and Asian/Pacific Islander patients had lower odds of receiving surgical treatment compared to White patients (P<.001). Medicare and Medicaid patients were less likely to be surgically managed than patients with private insurance (OR = 0.75, 0.37; P<.001, respectively). Urban hospitals were more likely to provide surgery when compared to rural hospitals (P < .001). Patients undergoing fusion had more complications than decompression alone (P < .001). Females, Medicare insurance status, Medicaid insurance status, urban hospital locations, and certain geographical locations were found to predict postoperative complications (P < .001).There were substantial differences in surgical management and postoperative complications among individuals of different sex, races, and insurance status. Further investigation evaluating the effect of demographics in spine surgery is warranted to fully understand their influence on patient complications.
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