Traditional cardiovascular trials combine adverse events into composites, ignoring the clinical importance and weight of endpoints. The Win Ratio (WR) is a contemporary statistical technique overcoming these limitations. We aimed to evaluate outcomes of high-risk percutaneous coronary intervention supported with Impella versus intra-aortic balloon pump, by pooling data from the PROTECT-II and PROTECT-III studies, using the WR. All patients from PROTECT-II RCT (P-II) and patients from PROTECT-III (P-III) who met P-II inclusion/exclusion criteria were pooled. The WR was based on independently adjudicated major adverse cardiac and cerebrovascular events at 90 days with following hierarchy: (1) mortality; (2) stroke; (3) spontaneous myocardial infarction; (4) rehospitalization; and (5) peri-procedural myocardial infarction. All major adverse cardiac and cerebrovascular events were analyzed as time-to-event outcomes, except peri-procedural myocardial infarction (binary endpoint). Sub-analyzes included: (1) complex cases: patients with atherectomy or unprotected left main or chronic total occlusion, (2) all patients excluding firsts from P-II (learning cases); and (3) Impella P-II and P-III cohorts separately. Win statistics (WR, net benefit, and win odds) were calculated. The primary analysis (719 Impella and 211 intra-aortic balloon pump-supported PCI) yielded a WR of 1.691 in favor of Impella (1.314 to 2.176, p < 0.001), with net benefit of 0.166 (0.084 to 0.247, p < 0.001) and win odds of 1.398 (1.187 to 1.645, p < 0.001). The WR, net benefit and win odds for complex cases remained statistically significant in favor of Impella. Excluding first patients resulted in increased win statistics compared to primary analysis. In conclusion, pooled WR analyzes from P-II and P-III studies demonstrated improved high risk PCI outcomes up to 90 days with Impella compared to intra-aortic balloon pump.

Background Identification and referral of at-risk patients from primary care practitioners (PCPs) to eye care professionals remain a challenge. Approximately 1.9 million Americans suffer from vision loss as a result of undiagnosed or untreated ophthalmic conditions. In ophthalmology, artificial intelligence (AI) is used to predict glaucoma progression, recognize diabetic retinopathy (DR), and classify ocular tumors; however, AI has not yet been used to triage primary care patients for ophthalmology referral. Objective This study aimed to build and compare machine learning (ML) methods, applicable to electronic health records (EHRs) of PCPs, capable of triaging patients for referral to eye care specialists. Methods Accessing the Optum deidentified EHR data set, 743,039 patients with 5 leading vision conditions (age-related macular degeneration [AMD], visually significant cataract, DR, glaucoma, or ocular surface disease [OSD]) were exact-matched on age and gender to 743,039 controls without eye conditions. Between 142 and 182 non-ophthalmic parameters per patient were input into 5 ML methods: generalized linear model, L1-regularized logistic regression, random forest, Extreme Gradient Boosting (XGBoost), and J48 decision tree. Model performance was compared for each pathology to select the most predictive algorithm. The area under the curve (AUC) was assessed for all algorithms for each outcome. Results XGBoost demonstrated the best performance, showing, respectively, a prediction accuracy and an AUC of 78.6% (95% CI 78.3%-78.9%) and 0.878 for visually significant cataract, 77.4% (95% CI 76.7%-78.1%) and 0.858 for exudative AMD, 79.2% (95% CI 78.8%-79.6%) and 0.879 for nonexudative AMD, 72.2% (95% CI 69.9%-74.5%) and 0.803 for OSD requiring medication, 70.8% (95% CI 70.5%-71.1%) and 0.785 for glaucoma, 85.0% (95% CI 84.2%-85.8%) and 0.924 for type 1 nonproliferative diabetic retinopathy (NPDR), 82.2% (95% CI 80.4%-84.0%) and 0.911 for type 1 proliferative diabetic retinopathy (PDR), 81.3% (95% CI 81.0%-81.6%) and 0.891 for type 2 NPDR, and 82.1% (95% CI 81.3%-82.9%) and 0.900 for type 2 PDR. Conclusions The 5 ML methods deployed were able to successfully identify patients with elevated odds ratios (ORs), thus capable of patient triage, for ocular pathology ranging from 2.4 (95% CI 2.4-2.5) for glaucoma to 5.7 (95% CI 5.0-6.4) for type 1 NPDR, with an average OR of 3.9. The application of these models could enable PCPs to better identify and triage patients at risk for treatable ophthalmic pathology. Early identification of patients with unrecognized sight-threatening conditions may lead to earlier treatment and a reduced economic burden. More importantly, such triage may improve patients’ lives.

Objectives: Recent clinical studies have shown favorable outcomes for cement augmentation for fixation of trochanteric fracture. We assessed the cost-utility of cement augmentation for fixation of closed unstable trochanteric fractures from the US payer's perspective. Methods: The cost-utility model comprised a decision tree to simulate clinical events over 1 year after the index fixation surgery, and a Markov model to extrapolate clinical events over patients' lifetime, using a cohort of 1,000 patients with demographic and clinical characteristics similar to that of a published randomized controlled trial (age >= 75 years, 83 % female). Model outputs were discounted costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER) over a lifetime. Deterministic and probabilistic sensitivity analyses were performed to assess the impact of parameter uncertainty on results. Results: Fixation with augmentation reduced per-patient costs by $754.8 and had similar per-patient QALYs, compared to fixation without augmentation, resulting in an ICER of -$130,765/QALY. The ICER was most sensitive to the utility of revision surgery, mortality risk ratio after the second revision surgery, mortality risk ratio after successful index surgery, and mortality rate in the decision tree model. The probability that fixation with augmentation was cost-effective compared with no augmentation was 63.4 %, 58.2 %, and 56.4 %, given a maximum acceptable ceiling ratio of $50,000, $100,000, and $150,000 per QALY gained, respectively. Conclusion: Fixation with cement augmentation was the dominant strategy, driven mainly by reduced costs. These results may support surgeons in evidence-based clinical decision making and may be informative for policy makers regarding coverage and reimbursement.

Objectives: To analyze US commercial insurance payments associated with COVID-19 as a function of severity and duration of disease. Study design: Retrospective database analysis. Methods: Patients with COVID-19 between April 1, 2020, and June 30, 2021, in the Merative MarketScan Commercial database were identified and stratified as having asymptomatic, mild, moderate (with and without lower respiratory disease), or severe/critical (S/C) disease based on the severity of the acute COVID-19 infection. Duration of disease (DOD) was estimated for all patients. Patients with DOD longer than 12 weeks were defined as having post-COVID-19 condition (PCC). Outcomes were all-cause payments (ACP) and disease-specific payments (DSP) for the entire DOD. Variables included demographic and comorbidities at the time of acute disease. Adjusted payments by disease severity were estimated using generalized linear models (gamma distribution with log link). Results: A total of 738,339 patients were included (374,401 asymptomatic, 156,220 mild, 180,213 moderate, and 27,505 S/C cases). DSP increased from $217 (95% CI, $214-221) for asymptomatic cases to $2744 (95% CI, $2678-$2811) for moderate cases with lower respiratory disease and $28,250 (95% CI, $26,963-$29,538) for S/C cases. ACP increased from $505 (95% CI, $497-$512) for asymptomatic cases to $46,538 (95% CI, $44,096-$48,979) for S/C cases. The DSP and ACP further increased by $50,736 (95% CI, $45,337-$56,136) and $94,839 (95% CI, $88,029-$101,649), respectively, in S/C cases with PCC vs a DOD of fewer than 4 weeks. Conclusions: COVID-19 payments for S/C cases were more than 10-fold greater than those of moderate cases and further increased by nearly $95,000 in S/C cases with PCC vs a DOD of fewer than 4 weeks.

INTRODUCTION:Racial and ethnic disparities in orthopaedic surgery are well documented. However, the extent to which these persist in fracture care is unknown. This study sought to assess racial disparities in the postoperative surgical and medical management of patients after diaphyseal tibia fracture fixation. METHODS:Patients with surgically treated tibial shaft fractures from October 1, 2015, to December 31, 2020, were identified in the MarketScan® Medicaid Database. Exclusion criteria included concurrent fractures or amputation. Outcomes included 2-year postoperative complications, reoperation rates, and filled prescriptions. Surgically-treated Black and White cohorts were propensity-score matched using nearest-neighbor matching on patient demographics, comorbidities, fracture pattern and severity, and fixation type. Chi-square tests and survival analyses (Kaplan-Meier and Cox proportional hazard models) were conducted. RESULTS:5,472 patients were included, 2,209 Black and 3,263 White patients. After matching, 2,209 were retained in each cohort. No significant differences in complication rates were observed in the matched Black vs White cohorts. Rates of reoperation, however, were significantly lower in Black as compared to White patients (28.5 % vs. 35.5 % rate, risk difference = 7.0 % (95 % confidence interval (CI): 4.2 % to 9.7 %)). Implant removal was also significantly lower in Black (17.9 %) vs. White (25.1 %) patients (Risk difference = 7.2 %, (95 %CI: 4.8 % to 9.6 %)). The adjusted hazard ratio comparing the reoperation rate in Black versus White patients was 0.77 (95 %CI: 0.69-0.82, p < 0.0001). Significantly lower proportions of Black vs White patients filled at least one prescription for benzodiazepine, antidepressants, strong opiates, or antibiotics at every time point post-index. DISCUSSION:Fewer resources were used in post-operative management after surgical treatment of tibial shaft fractures for Black versus White Medicaid-insured patients. These results may be reflective of the undertreatment of complications after tibia fracture surgery for Black patients and highlight the need for further interventions to address racial disparities in trauma care.

Study Design. Retrospective database evaluation. Objectives. To study the association between race, health care insurance, mortality, postoperative visits, and reoperation within a hospital setting in patients with cauda equina syndrome (CES) undergoing surgical intervention. Summary of Background Data. CES can lead to permanent neurological deficits if the diagnosis is missed or delayed. Evidence of racial or insurance disparities in CES is sparse. Materials and Methods. Patients with CES undergoing surgery from 2000 to 2021 were identified from the Premier Health care Database. Six-month postoperative visits and 12-month reoperations within the hospital were compared by race (i.e., White, Black, or Other [Asian, Hispanic, or other]) and insurance (i.e., Commercial, Medicaid, Medicare, or Other) using Cox proportional hazard regressions; covariates were used in the regression models to control for confounding. Likelihood ratio tests were used to compare model fit. Results. Among 25,024 patients, most were White (76.3%), followed by Other race (15.4% [ 8.8% Asian, 7.3% Hispanic, and 83.9% other]) and Black (8.3%). Models with race and insurance combined provided the best fit for estimating the risk of visits to any setting of care and reoperations. White Medicaid patients had the strongest association with a higher risk of 6-month visits to any setting of care versus White patients with commercial insurance (HR: 1.36 (1.26,1.47)). Being Black with Medicare had a strong association with a higher risk of 12-month reoperations versus White commercial patients (HR: 1.43 (1.10,1.85)). Having Medicaid versus Commercial insurance was strongly associated with a higher risk of complication-related (HR: 1.36 (1.21, 1.52)) and ER visits (HR: 2.26 (2.02,2.51)). Medicaid had a significantly higher risk of mortality compared with Commercial patients (HR: 3.19 (1.41,7.20)). Conclusions. Visits to any setting of care, complication-related, ER visits, reoperation, or mortality within the hospital setting after CES surgical treatment varied by race and insurance. Insurance type had a stronger association with the outcomes than race. Level of Evidence. Level—III

AbstractBackground:Spinal fusion surgery (SFS) is one of the most common operations in the United States, >450,000 SFSs are performed annually, incurring annual costs >$10 billion.Objectives:We used a nationwide longitudinal database to accurately assess incidence and payments associated with management of postoperative infection following SFS.Methods:We conducted a retrospective, observational cohort analysis of 210,019 patients undergoing SFS from 2014 to 2018 using IBM MarketScan commercial and Medicaid–Medicare databases. We assessed rates of superficial/deep incisional SSIs, from 3 to 180 days after surgery using Cox proportional hazard regression models. To evaluate adjusted payments for patients with/without SSIs, adjusted for inflation to 2019 Consumer Price Index, we used generalized linear regression models with log-link and γ distribution.Results:Overall, 6.6% of patients experienced an SSI, 1.7% superficial SSIs and 4.9% deep-incisional SSIs, with a median of 44 days to presentation for superficial SSIs and 28 days for deep-incisional SSIs. Selective risk factors included surgical approach, admission type, payer, and higher comorbidity score. Postoperative incremental commercial payments for patients with superficial SSI were $20,800 at 6 months, $26,937 at 12 months, and $32,821 at 24 months; incremental payments for patients with deep-incisional SSI were $59,766 at 6 months, $74,875 at 12 months, and $93,741 at 24 months. Corresponding incremental Medicare payments for patients with superficial incisional at 6, 12, 24-months were $11,044, $17,967, and $24,096; while payments for patients with deep-infection were: $48,662, $53,757, and $73,803 at 6, 12, 24-months.Conclusions:We identified a 4.9% rate of deep infection following SFS, with substantial payer burden. The findings suggest that the implementation of robust evidence-based surgical-care bundles to mitigate postoperative SFS infection is warranted.

BACKGROUND: Treatment for multiple rib fractures includes surgical stabilization of rib fractures (SSRF) or nonoperative management (NOM). Meta-analyses have demonstrated that SSRF results in faster recovery and lower long-term complication rates versus NOM. Our study evaluated postoperative outcomes for multiple rib fracture patients following SSRF versus NOM in a real-world, all-comer study design. METHODS: Multiple rib fracture patients with inpatient admissions in the PREMIER hospital database from October 1, 2015, to September 30, 2020, were identified. Outcomes included discharge disposition, and 3- and 12-month lung-related readmissions. Demographics, comorbidities, concurrent injuries at index, Abbreviated Injury Scale and Injury Severity Scores, and provider characteristics were determined for all patients. Patients were excluded from the cohort if they had a thorax Abbreviated Injury Scale score of <2 (low severity patient) or a Glasgow Coma Scale score of <= 8 (extreme high severity patient). Stratum matching between SSRF and NOM patients was performed using fine stratification and weighting so that all patient data were kept in the final analysis. Outcomes were analyzed using generalized linear models with quasinormal distribution and logit links. RESULTS: A total of 203,450 patients were included, of which 200,580 were treated with NOM and 2,870 with SSRF. Compared to NOM, patients with SSRF had higher rates of home discharge (62% SSRF vs. 58% NOM) and lower rates of lung-related readmissions (3 months, 3.1% SSRF vs. 4.0% NOM; 12 months, 6.2% SSRF vs. 7.6% NOM). The odds ratio (OR) for home or home health discharge in patients with SSRF versus NOM was 1.166 (95% confidence interval [CI], 1.073-1.266; p = 0.0002). Similarly, ORs for lung-related readmission at 3- and 12-month were statistically lower in the patients treated with SSRF versus NOM (OR [3 months], 0.764 [95% CI, 0.606-0.963]; p = 0.0227 and OR [12 months], 0.799 [95% CI, 0.657-0.971]; p = 0.0245). CONCLUSION: Surgical stabilization of rib fractures results in greater odds of home discharge and lower rates of lung-related readmissions compared with NOM at 12 months of follow-up. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level III.

Background Few contemporary US-based long bone non-union analyses have recently been published. Our study was designed to provide a current understanding of non-union risks and costs, from the payers' perspective. Methods The Merative™ MarketScan ® Commercial Claims and Encounters database was used. Patients with surgically treated long bone (femur, tibia, or humerus) fractures in the inpatient setting, from Q4 2015 to most recent, were identified. Exclusion criteria included polytrauma and amputation at index. The primary outcome was a diagnosis of non-union in the 12 and 24 months post-index. Additional outcomes included concurrent infection, reoperation, and total healthcare costs. Age, gender, comorbidities, fracture characteristics, and severity were identified for all patients. Descriptive analyses were performed. Crude and adjusted rates of non-union (using Poisson regressions with log link) were calculated. Marginal incremental cost of care associated with non-union and infected non-union and reoperation were estimated using a generalized linear model with log link and gamma distribution. Results A total of 12,770, 13,504, and 4,805 patients with femoral, tibial, or humeral surgically treated fractures were identified, 74–89% were displaced, and 18–27% were comminuted. Two-year rates of non-union reached 8.5% (8.0%–9.1%), 9.1% (8.6%–9.7%), and 7.2% (6.4%–8.1%) in the femoral, tibial, and humeral fracture cohorts, respectively. Shaft fractures were at increased risk of non-union versus fractures in other sites (risk ratio (RR) in shaft fractures of the femur: 2.36 (1.81–3.04); tibia: 1.95 (1.47–2.57); humerus: 2.02 (1.42–2.87)). Fractures with severe soft tissue trauma (open vs. closed, Gustilo III vs. Gustilo I–II) were also at increased risk for non-union (RR for Gustilo III fracture (vs. closed) for femur: R = 1.96 (1.45–2.58), for tibia: 3.33 (2.85–3.87), RR for open (vs. closed) for humerus: 1.74 (1.30–2.32)). For all fractures, younger patients had a reduced risk of non-union compared to older patients. For tibial fractures, increasing comorbidity (Elixhauser Index 5 or greater) was associated with an increased risk of non-union. The two-year marginal cost of non-union ranged from $33K-$45K. Non-union reoperation added $16K–$34K in incremental costs. Concurrent infection further increased costs by $46K–$86K. Conclusions Non-union affects 7–10% of surgically treated long bone fracture cases. Shaft and complex fractures were at increased risk for non-union.

Non-union is a common complication of femoral and tibial fractures, however risk of non-union is not consistent across all types of femoral or tibial fractures. Our study characterized femoral and tibial fractures and evaluated risk of non-union.

Few contemporary long bone non-union analyses have been documented. Our study was designed to provide a current understanding of non-union rates and risk factors for long bone fractures.