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Preoperative Predictive Model for Intraoperative and Postoperative Major Complications After Total Hip Arthroplasty: Is Neuraxial Anesthesia Protective?
Session: MP-06b
Fri, Nov 16, 10:30 am-12:15 pm
Cibolo 3

Please note, medically challenging cases are removed three months after the meeting and scientific abstracts after three years.

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Preoperative Predictive Model for Intraoperative and Postoperative Major Complications After Total Hip Arthroplasty: Is Neuraxial Anesthesia Protective?

Ahmad Elsharydah, MD, MBA, Frederick C. Li, MD, Abu Minhajuddin, PhD, Girish P. Joshi, MBBS, MD, FFARCSI

Department of Anesthesiology and Pain Management, University of Texas Southwestern Medical Center, Dallas, Texas

Background:

Total hip arthroplasty (THA) is one of the most commonly performed orthopedic procedures in the United States1. With an improvement in life expectancy and the aging of the "baby boomer" generation, the demand for total hip arthroplasty is anticipated to rise and create substantial impact on health care economics. There is a growing body of evidence supporting that neuraxial anesthesia is associated with improved outcomes in patients undergoing total joint arthroplasty2-8. However, regional anesthesia, it continues to be underutilized. Moreover, it appears utilization of neuraxial anesthesia is lower in the USA compared to internationally, where regional anesthesia appears to be more utilized for orthopedic procedures9. This study aimed to develop a predictive model for intraoperative and postoperative (within 72 hours) major complications (MC) and determine the influence of neuraxial anesthesia on perioperative outcome utilizing the information from the American College of Surgeons – National Surgical Quality Improvement Program (ACS-NSQIP) database. Hope to provide more individualized medicine and simplify the decision making process for deciding between general anesthesia and neuraxial anesthesia in elective THA.

Methods:

• Data from NSQIP for 2006-2016 were queried for adult patients (18 years and older) who underwent primary elective THA.
• Only cases performed under general (GA) or neuraxial (spinal or epidural) anesthesia were included.
• Trauma, emergent, and cases with bleeding disorders and coagulations abnormalities were excluded. Cases with missing data were also excluded.
• The pre-operative information explored included type of anesthesia, age, gender, BMI, smoking history, chronic use of steroids, and several comorbidities.
• The primary outcome was the occurrence of a composite of intraoperative and postoperative (within 72 hours) MCs or mortality. The composite included one or a combination of the following: acute myocardial infarction, cardiac arrest requiring CPR, pneumonia or unplanned intubation, progressive renal insufficiency, acute renal failure, cerebrovascular accident, sepsis or septic shock, deep venous thrombosis requiring therapy, pulmonary embolism or death.
• Univariate and multivariate logistic regression and bootstrap analyses (internal validation) were used on a training set to select the strongest predictors for intraoperative and postoperative complications (trained model). The trained model was applied to the test set for external validation of the model.
• Model performance was evaluated with the area under the receiver operating characteristic (ROC) Curve (AUC) for discrimination and the Hosmer-Lemeshow (HL) test for goodness-of-fit.
• The study was considered to be exempt from review by our institutional review board.
• All analyses were done using the SAS 9.4 software (SAS Inc., Cary, NC). Two-tailed p-value of 0.05 was considered statistically significant.
 
Results:
 
• 104,404 cases (GA=58%, NA=42%) met the study criteria (68,907 in the training set and 35,497 in the test set).
• The overall incidence of MCs was 0.62%.
• The final model had seven predictors for MCs including: age ≥65 years, COPD, CHF, HTN, creatinine ≥2, CAD, and diabetes (Table 1).
• NA decreased the risk of MCs by ~49% (OR 0.51 [95% CL, 0.41–0.63], p<0.001) when compared to GA.
• The model had a fair discrimination ability with an AUC value of 0.67 (95% CL 0.65–0.70) on the training sample and 0.65 (95% CL 0.61–0.69) on the test sample, with no difference between the 2 ROC curves (p=0.993) (Figure 1).
• The model had a good calibration for the data in both the training and test samples indicated by non-significant high p values from the HL test (p=0.811 and 0.107 for the training and test set, respectively) (Figure 2).
 
Discussion:
 
• In our study of large, multi-center surgical data from over 600 participating hospitals, we found evidence that utilization of neuraxial anesthesia vs general anesthesia is associated with superior perioperative outcomes for primary elective THA
• The strongest predictors of our model included CHF, creatinine > 2, COPD, and CAD.
• Our data may lead to better decision-making regarding the choice of anesthesia for the patient and surgeon as well as the planning for post-operative care for this common procedure.
• More research is needed to identify the patients who benefit the most from a specific type of anesthesia for THA (personalized or precision anesthesia). More research is also needed to study potential mechanisms for the beneficial effects of neuraxial anesthesia.
• Limitations: retrospective nature, potentially introducing misclassification and coding errors; detailed clinical information (blood loss, intraoperative details) and their impact on outcome cannot be taken into consideration; did not study incidence of complications associated directly with the use of the types of anesthesia  (i.e. PDPH, epidural/spinal hematomas and neuropraxias, oropharyngeal damage with intubation process, failure to intubate).
 
References:
 
1.Kurtz S, Ong K, Lau E, Mowat F, Halpern M. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007;89(4):780-5.
2.Memtsoudis SG, Sun X, Chiu YL, Stundner O, Liu SS, Banerjee S, et al. Perioperative comparative effectiveness of anesthetic technique in orthopedic patients. Anesthesiology 2013;118:1046–58.
3.Memtsoudis SG, Sun X, Chiu YL, Stundner O, Liu SS, Banerjee S, et al. Perioperative comparative effectiveness of anesthetic technique in orthopedic patients. Anesthesiology 2013;118:1046–58.
4.Hu S, Zhang ZY, Hua YQ, Li J, Cai ZD. A comparison of regional and general anaesthesia for total replacement of the hip or knee: a meta-analysis. J Bone Joint Surg Br. 2009;91(7):935-42.
5.Urwin SC, Parker MJ, Griffiths R. General versus regional anaesthesia for hip fracture surgery: a meta-analysis of randomized trials. Br J Anaesth. 2000;84(4):450-5.
6.Mauermann WJ, Shilling AM, Zuo Z. A comparison of neuraxial block versus general anesthesia for elective total hip replacement: a meta-analysis. Anesth Analg. 2006;103(4):1018-25
7.Donauer K, Bomberg H, Wagenpfeil S, Volk T, Meissner W, Wolf A. Regional vs. General Anesthesia for Total Knee and Hip Replacement: An Analysis of Postoperative Pain Perception from the International PAIN OUT Registry. Pain Pract. 2018;
8.Greimel F, Maderbacher G, Zeman F, Grifka J, Meissner W, Benditz A. No Clinical Difference Comparing General, Regional, and Combination Anesthesia in Hip Arthroplasty: A Multicenter Cohort-Study Regarding Perioperative Pain Management and Patient Satisfaction. J Arthroplasty. 2017;32(11):3429-3433.
9.Cozowicz C, Poeran J, Memtsoudis SG. Epidemiology, trends, and disparities in regional anaesthesia for orthopaedic surgery. Br J Anaesth. 2015;115 Suppl 2:ii57-67
10.Shiloach M, Frencher SK Jr, Steeger JE, et al. Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg 2010; 210: 6–16
11.American College of Surgeons. American College of Surgeons National Surgical Quality Improvement Program Participant Use Data File. Chicago, IL: Copyright © 1996–2018 by the American College of Surgeons
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