Dataset Information

Obesity and early reoperation rate after elective lumbar spine surgery: a population-based study.

ABSTRACT: STUDY DESIGN: Population-based retrospective cohort study. CLINICAL QUESTION: Are patients with a body mass index (BMI) of 35 or more who undergo elective lumbar spine surgery at increased risk of post-surgical complications, as evidenced by reoperation within a 3-month period? METHODS: The Alberta Health and Wellness Administrative database was queried to identify patients who underwent elective lumbar spine surgery over a 24-month period. This same database was used to classify subjects as obese (BMI ≥35) and non-obese (BMI <35) and to determine who underwent repeated surgical intervention. The rate of reoperation was determined for both the obese and non-obese groups; further analyses were performed to determine whether certain subjects were at increased risk of reoperation. RESULTS: The point estimate for relative risk for requiring reoperation was 1.73 (95% confidence interval, 1.03-2.90) for obese subjects compared with non-obese subjects. The adjusted point estimate shows that deformity correction surgery is predictive for early reoperation while obesity is not. CONCLUSIONS: In obese subjects we observed an increased complication rate after elective lumbar spine surgery, as evidenced by reoperation rates within 3 months. When we considered other possible associations with reoperation, in adjusted analysis, deformity surgery was found to be predictive of early reoperation.Final class of evidence-prognosisSTUDY DESIGNProspective CohortRetrospective Cohort•Case controlCase seriesMETHODSPatients at similar point in course of treatment•F/U ≥ 85%•Similarity of treatment protocols for patient groups•Patients followed up long enough for outcomes to occur•Control for extraneous risk factorsOverall class of evidenceIIIThe definiton of the different classes of evidence is available on page 55.

SUBMITTER: Gaudelli C

PROVIDER: S-EPMC3516454 | biostudies-other | 2012 May

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundThere is limited data available on the use of orthoses across varying elective spine surgeries. When previously studied in 2009, inconsistent lumbar postoperative bracing practices were reported. The present study aimed to provide a ten-year update regarding postoperative bracing practices after elective lumbar surgery among United States (U.S.) spine surgeons.MethodsA questionnaire was distributed to attendees of the Lumbar Spine Research Society Annual Meeting (April 2019). The questionnaire collected demographic information, and asked surgeons to identify if they used orthoses postoperatively after ten elective lumbar surgeries. Information regarding type of brace, duration of use, and reason for bracing was also collected. Chi-square tests and one-way analysis of variance (ANOVA) were used for comparisons.ResultsSeventy-three of 88 U.S. attending surgeons completed the questionnaire (response rate: 83%). The majority of respondents were orthopaedic surgery-trained (78%), fellowship-trained (84%), and academic surgeons (73%). The majority of respondents (60%) did not use orthoses after any lumbar surgery. Among the surgeons who braced, the overall bracing frequency was 26%. This rate was significantly lower than that reported in the literature ten years earlier (p<0.0001). Respondents tended to use orthoses most often after stand-alone lateral interbody fusions (43%) (p<0.0001). The average bracing frequency after lumbar fusions (34%) was higher than the average bracing frequency after non-fusion surgeries (16%) (p<0.0001). The most frequently utilized brace was an off the shelf lumbar sacral orthosis (66%), and most surgeons braced patients to improve pain (42%). Of surgeons who braced, most commonly did so for 2-4 months (57%).ConclusionMost surgeon respondents did not prescribe orthoses after varying elective lumbar surgeries, and the frequency overall was lower than a similar study conducted in 2009. There continues to be inconsistencies in postoperative bracing practices. In an era striving for evidence-based practices, this is an area needing more attention.

Project description:Study designRetrospective administrative database review.ObjectiveAnalyze patterns of opioid use in patients undergoing lumbar surgery and determine associated risk factors in a Medicaid population.Summary of background dataOpioid use in patients undergoing surgery for degenerative lumbar spine conditions is prevalent and impacts outcomes. There is limited information defining the scope of this problem in Medicaid patients.Materials and methodsLongitudinal cohort study of adult South Carolina (SC) Medicaid patients undergoing lumbar surgery from 2014 to 2017. All patients had continuous SC Medicaid coverage for 15 consecutive months, including six months before and nine months following surgery. The primary outcome was a longitudinal assessment of postoperative opioid use to determine trajectories and group-based membership using latent modeling. Univariate and multivariable modeling was conducted to assess risk factors for group-based trajectory modeling and chronic opioid use (COU).ResultsA total of 1455 surgeries met inclusion criteria. Group-based trajectory model demonstrated patients fit into five groups; very low use (23.4%), rapid wean following surgery (18.8%), increasing use following surgery (12.9%), slow wean following surgery (12.6%) and sustained high use (32.2%). Variables predicting membership in high opioid use included preoperative opioid use, younger age, longer length of stay, concomitant medications, and readmissions. More than three quarter of patients were deemed COUs (76.4%). On bivariate analysis, patients with degenerative disk disease were more likely to be COUs (24.8% vs. 18.6%; P =0.0168), more likely to take opioids before surgery (88.5% vs. 61.9%; P <0.001) and received higher amounts of opioids during the 30 days following surgery (mean morphine milligram equivalents 59.6 vs. 25.1; P <0.001).ConclusionsMost SC Medicaid patients undergoing lumbar elective lumbar spine surgery were using opioids preoperatively and continued long-term use postoperatively at a higher rate than previously reported databases. Preoperative and perioperative intake, degenerative disk disease, multiple prescribers, depression, and concomitant medications were significant risk factors.

Project description:BackgroundIn the context of increased attention afforded to hospital efficiency and improved but safe patient throughput, decreasing unnecessary hospital length of stay (LOS) is imperative. Given that lumbar spine procedures may be among a hospital's most profitable services, identifying patients at risk of increased healthcare resource utilization prior to surgery is a valuable opportunity to develop targeted pre- and peri-operative intervention and quality improvement initiatives. The purpose of the present investigation was to examine patient factors that predict prolonged LOS as well as discharge disposition following elective, posterior, lumbar spine surgery.MethodsWe employed a retrospective cohort analysis on 779 consecutive patients treated with lumbar surgery without fusion. Our primary outcome measures were extended LOS (three or more midnights) and discharge disposition. Patient sociodemographic, procedural, and discharge characteristics were adjusted for in our analysis. Sociodemographic variables included Area of Deprivation Index (ADI), a comprehensive metric of socioeconomic status, utilizing income, education, employment, and housing quality based on patient zip code. Multivariable logistic regression and ordinal logistic regression analyses were performed to assess whether covariates were independently predictive of extended LOS and discharge disposition, respectively.Results779 patients were studied, with a median age of 66 years (±15) and a median LOS of 1 midnight (range, 1-10 midnights). Patients in the most disadvantaged ADI quintile (adjusted odds ratio, aOR 2.48 95% CI 1.15-5.47), those who underwent a minimally-invasive or tubular retractor surgery (aOR 3.03 95% CI 1.02-8.56), those who had an intra-operative drain placed (aOR 4.46 95% CI 2.53-7.26), who had a cerebrospinal fluid leak (aOR 3.46 95% CI 1.55-7.58), who were discharged anywhere but home (aOR 17.11 95% CI 9.24-33.00), and those who were evaluated by physical therapy (aOR 7.23 95% CI 2.13-45.30) or OT (aOR 2.20 95% CI 1.13-4.22) had a significantly increased chance of an extended LOS. Preoperative opioid use was not associated with an increased LOS following surgery (aOR 1.12 95% CI 0.56-1.46). Extended LOS was not associated with post-discharge emergency department representation or unplanned readmission within 90 days following discharge (p=0.148). Patients who were older (aOR 1.99 95% CI 1.62-2.48), in higher quintiles on ADI (3rd quintile; aOR 1.90 95% CI 1.12-3.23, 4th quintile; aOR 1.79, 95% CI 1.05-3.05, 5th quintile; aOR 2.16 95% CI 1.26-3.75), who had a CSF leak (aOR 2.18 95% CI 1.22-3.86), or who had a longer procedure duration (aOR 1.38 95% CI 1.17-1.62) were more likely to require additional services or be sent to a subacute facility upon discharge.ConclusionsPatient sociodemographics, along with procedural factors, and discharge disposition were all associated with an increased likelihood of prolonged LOS and resource intensive discharges following elective lumbar spine surgery. Several of these factors could be reliably identified pre-operatively and may be amenable to targeted preoperative intervention. Improving discharge disposition planning in the peri-operative period may allow for more efficient use of hospitalization and inpatient and post-acute resources.

Project description:BackgroundPrediction calculators can help set outcomes expectations following orthopaedic surgery, however effective implementation strategies for these tools are unknown. This study evaluated provider and patient perspectives on clinical implementation of web-based prediction calculators developed using national prospective spine surgery registry data from the Quality Outcomes Database.MethodsWe conducted semi-structured interviews in two health systems, Vanderbilt University Medical Center (VUMC) and Duke University Health System (DUHS) of orthopedic and neurosurgery health care providers (VUMC: n = 19; DUHS: n = 6), health care administrators (VUMC: n = 9; DUHS: n = 9), and patients undergoing elective spine surgery (VUMC: n = 16). Qualitative template analysis was used to analyze interview data, with a focus on end-user perspectives regarding clinical implementation of web-based prediction tools.ResultsHealth care providers, administrators and patients overwhelmingly supported the use of the calculators to help set realistic expectations for surgical outcomes. Some clinicians had questions about the validity and applicability of the calculators in their patient population. A consensus was that the calculators needed seamless integration into clinical workflows, but there was little agreement on best methods for selecting which patients to complete the calculators, timing, and mode of completion. Many interviewees expressed concerns that calculator results could influence payers, or expose risk of liability. Few patients expressed concerns over additional survey burden if they understood that the information would directly inform their care.ConclusionsInterviewees had a largely positive opinion of the calculators, believing they could aid in discussions about expectations for pain and functional recovery after spine surgery. No single implementation strategy is likely to be successful, and strategies vary, even within the same healthcare system. Patients should be well-informed of how responses will be used to deliver better care, and concerns over how the calculators could impact payment and liability should be addressed prior to use. Future research is necessary to determine whether use of calculators improves management and outcomes for people seeking a surgical consult for spine pain.

Dataset Information

Obesity and early reoperation rate after elective lumbar spine surgery: a population-based study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets