Medical Comorbidities Are Independent Preoperative Risk Factors for Surgical Infection After Total Joint Arthroplasty

Everhart, Joshua S.; Altneu, Eric; Calhoun, Jason H.

doi:10.1007/s11999-013-2923-9

Cited by 135 publications

(68 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Patients undergoing orthopaedic surgery often have multiple coexisting medical conditions (comorbidities) [13,21,24,28,39,45,58]. Preoperative risk assessment can help with decision-making and management strategies [11,37,50].…”

Section: Introductionmentioning

confidence: 99%

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

Menendez

Neuhaus

Dijk

et al. 2014

Clinical Orthopaedics &Amp; Related Research

431

292

View full text Add to dashboard Cite

Background Scores derived from comorbidities can help with risk adjustment of quality and safety data. The Charlson and Elixhauser comorbidity measures are wellknown risk adjustment models, yet the optimal score for orthopaedic patients remains unclear. Questions/purposes We determined whether there was a difference in the accuracy of the Charlson and Elixhauser comorbidity-based measures in predicting (1) in-hospital mortality after major orthopaedic surgery, (2) in-hospital adverse events, and (3) nonroutine discharge. Methods Among an estimated 14,007,813 patients undergoing orthopaedic surgery identified in the National Hospital Discharge Survey (1990Survey ( -2007, 0.80% died in the hospital. The association of each Charlson comorbidity measure and Elixhauser comorbidity measure with mortality was assessed in bivariate analysis. Two main multivariable logistic regression models were constructed, with in-hospital mortality as the dependent variable and one of the two comorbidity-based measures (and age, sex, and year of surgery) as independent variables. A base model that included only age, sex, and year of surgery also was evaluated. The discriminative ability of the models was quantified using the area under the receiver operating characteristic curve (AUC). The AUC quantifies the ability of our models to assign a high probability of mortality to patients who die. Values range from 0.50 to 1.0, with 0.50 indicating no ability to discriminate and 1.0 indicating perfect discrimination. Results Elixhauser comorbidity adjustment provided a better prediction of in-hospital case mortality (AUC, 0.86; 95% CI, 0.86-0.86) compared with the Charlson model (AUC, 0.83; 95% CI, and to the base model with no comorbidities (AUC, 0.81; 95% CI, 0.81-0.81). In terms of relative improvement in predictive performance, the Elixhauser measure performed 60% better than the Charlson score in predicting mortality. The Elixhauser model discriminated inpatient morbidity better than the Charlson measure, but the discriminative ability of the model was poor and the difference in the absolute improvement in predictive power between the two models (AUC, 0.01) is of dubious clinical importance. Both comorbidity models exhibited the same degree of discrimination for estimating nonroutine discharge (AUC, 0.81; 95% CI, 0.81-0.82 for both models). Conclusions Provider-specific outcomes, particularly inpatient mortality, may be evaluated differently depending on the comorbidity risk adjustment model selected. Future research assessing and comparing the performance of the

show abstract

Section: Introductionmentioning

confidence: 99%

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

Menendez

Neuhaus

Dijk

et al. 2014

Clinical Orthopaedics &Amp; Related Research

431

292

View full text Add to dashboard Cite

show abstract

“…However, morbid obesity is associated with a higher risk of postoperative complications [6,21,24]. In addition, super obesity (BMI C 50 kg/m 2 ) has been reported to pose an even more substantial risk compared with the risk in patients who are less obese (BMI \ 50 kg/m 2 ) [8,15,23]. However, few peer-reviewed studies have addressed the surgical dilemma regarding whether to perform THA on patients who are morbidly obese or super obese [2,6,16,23].…”

Section: Introductionmentioning

confidence: 99%

Surgical Risks and Costs of Care are Greater in Patients Who Are Super Obese and Undergoing THA

Meller¹,

Toossi

Gonzalez

et al. 2016

Clinical Orthopaedics &Amp; Related Research

View full text Add to dashboard Cite

Background Patients with morbid obesity, defined as a BMI greater than 40 kg/m 2 , and super obesity, defined as a BMI greater than 50 kg/m 2 , increasingly present for total hip replacement. There is disagreement in the literature whether these individuals have greater surgical risks and costs for the episode of care, and the magnitude of those risks and costs. There also is no established threshold for obesity as defined by BMI in identifying increased complications, risks, and costs of care. Until recently, analysis of higher BMI data was limited to small cohorts from hospital-based data banks, based on BMI or height and weight only, often as part of a multivariate analysis. On October 1, 2010 the Centers for Medicare & Medicaid Services added a fifth digit to the BMI data, V85.xx, in the Medicare data bank, which allowed data mining of cases of patients with higher BMI. To our knowledge, our study is the first large retrospective Medicare data mining study, which allows us to examine BMI levels greater than 40 and 50 kg/m 2 to delineate risks, complications, and costs for these patients. Questions/purposes We sought to quantify (1) the surgical risk, and (2) the costs associated with complications after THA in patients who were morbidly obesity (BMI C 40 kg/m 2 ) or super obese (BMI C 50 kg/m 2 ). Methods This is a retrospective study of patients, using Medicare hospital claims data, who underwent THA. The ICD-9 Clinical Modification (CM) diagnosis code V85.4x was used to identify patients with morbid obesity and with super obesity from October 1, 2010 through December 31, 2014. Patients without any BMI-related diagnosis codes were used as the control group. Twelve complications occurring during the 90 days after THA were analyzed using multivariate Cox models adjusting for patient demographic, comorbidities, and institutional factors. In addition, hospital charges and payments were compared from primary surgery through the subsequent 90 days.Each author certifies that he or she, or a member of his or her immediate family, has no funding or commercial associations (eg, consultancies, stock ownership, equity interest, patent/licensing arrangements, etc) that might pose a conflict of interest in connection with the submitted article. All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research 1 editors and board members are on file with the publication and can be viewed on request. Each author certifies that his or her institution approved or waived approval for the human protocol for this investigation and that all investigations were conducted in conformity with ethical principles of research. This study was performed via electronic collaboration at the authors' institutions. (HR, 3.91; 95% CI, 3.14-4.86; p \ 0.001). In addition, patients with morbid obesity had increased risk of deep vein thrombosis (HR, 1.43; 95% CI, 1.14-1.79; p \ 0.002), pulmonary embolism (HR, 1.57; 95% CI, 1.25-1.99; p \ 0.001), implant failure (HR, 1.48; 95% CI, 1.3-1.68; p \ 0.001), acute ...

show abstract

“…Modifiable risk factors such as obesity (body mass index N 35 kg/m 2 ), alcohol abuse, smoking, and intravenous drug use have been associated with an increased risk of PJI [6][7][8][9][10][11]. Nonmodifiable risk factors include age at the time of surgery [4,12] and sex [13,14].…”

mentioning

confidence: 99%

The Effect of Implementing a Multimodal Approach on the Rates of Periprosthetic Joint Infection After Total Joint Arthroplasty

Yoo

Maltenfort

et al. 2016

The Journal of Arthroplasty

View full text Add to dashboard Cite

Medical Comorbidities Are Independent Preoperative Risk Factors for Surgical Infection After Total Joint Arthroplasty

Cited by 135 publications

References 31 publications

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

Surgical Risks and Costs of Care are Greater in Patients Who Are Super Obese and Undergoing THA

The Effect of Implementing a Multimodal Approach on the Rates of Periprosthetic Joint Infection After Total Joint Arthroplasty

Contact Info

Product

Resources

About