Faculty Bibliography

Introduction/UNASSIGNED:The purpose of this study was to investigate the effect of delayed closures, whether delayed primary closure (DPC) or split-thickness skin grafting (STSG), of operatively treated forearm fractures on short-term soft tissue outcomes. Methods/UNASSIGNED:In this retrospective cohort comparative study of two academic-level one trauma centers from 2010 to 2020, adult patients with diaphyseal forearm fractures who underwent open reduction and internal fixation (ORIF) were either closed primarily at index surgery, or underwent delayed closure, either with DPC or with a STSG. Primary outcome measures were soft-tissue outcomes as measured by wound healing (delayed healing, dehiscence, or skin breakdown) and fracture-related infection (FRI) at time of final follow-up. Results/UNASSIGNED:Eighty-one patients with 81 diaphyseal forearm fractures underwent ORIF with a mean follow-up of 14.3 months. Forty-one fractures (50.6%) were open injuries. Thirteen patients (16.0%) were unable to be closed primarily and underwent an average of 2.46 ± 0.7 surgeries including final coverage, with an average of 4.31 ± 2.8 days to final coverage. Four patients (30.8%) underwent DPC and 9 (69.2%) underwent STSG. Five (6.6%) patients in the delayed closure group had pre-operative compartment syndrome and underwent formal two-incision fasciotomies. There were no significant differences between delayed versus primary closure in wound healing complication rates, FRI, or radiographic union. Conclusions/UNASSIGNED:Diaphyseal forearm fractures that undergo ORIF have equivalent short-term soft tissue outcomes when closed primarily at index surgery or when closed in a delayed fashion.

Background/UNASSIGNED:The purpose of this study was to determine the impact of surgeon volume on outcomes following ankle fracture fixation. Methods/UNASSIGNED:Over 7 years, 362 patients who met inclusion criteria (>18 years with rotational ankle fractures) were identified and treated by orthopaedic surgeons at several hospitals within an academic medical center and were retrospectively reviewed. Surgeons that completed less than 24 ankle fixations per year (<90th percentile) during the study period were classified as low-volume (LV) and surgeons completing 24 or more ankle fixations per year (>90th percentile) were classified as high-volume (HV). Chart review was conducted to gather data regarding perioperative, radiographic, inpatient, and long-term outcome data (average 12-month follow-up). Results/UNASSIGNED:< .05). Conclusion/UNASSIGNED:In this single-center study, we found that patients treated by LV surgeons took 30% longer to heal radiographically and had greater reoperation rates than those treated by HV surgeons. Additionally, patients treated by high-volume surgeons had more anatomic postoperative radiographic ankle mortise reductions and was less cost-effective than when performed by high-volume surgeons. Level of Evidence/UNASSIGNED:Level III, retrospective comparative study.

INTRODUCTION/BACKGROUND:The purpose of this study was to assess how quality and volume of common orthopaedic care varies across private, municipal, and federal healthcare delivery systems (HDSs). METHODS:Hip and knee arthroplasty, knee and shoulder arthroscopy, and hip fracture repair were audited over a two-year period. Electronic medical records were reviewed for demographics, diagnosis, lengths of stay (LoSs), surgical wait times, inpatient complication, readmission, and revision surgery rates. Multivariate regression controlled for differences in age, sex, diagnosis, and Charlson Comorbidity Index to determine how HDS correlated with surgical wait time, length of stay, complication rates, readmission, and revision surgery. RESULTS:The 5,696 included patients comprise 87.4% private, 8.6% municipal, and 4.0% federal HDSs. Compared with private HDS for arthroplasty, federal surgical wait times were 18 days shorter (95% CI = 9 to 26 days, P < 0.001); federal LoS was 4 days longer (95% CI = 3.6 to 4.3 days, P < 0.001); municipal LoS was 1 day longer (95% CI = 0.8 to 1.4, P < 0.001); municipal 1-year revision surgery odds were increased (odds ratio [OR] = 2.8, 95% CI = 1.3 to 5.4, P = 0.045); and complication odds increased for municipal (OR = 12.2, 95% CI = 5.2 to 27.4, P < 0.001) and federal (OR = 12.0, 95% CI = 4.5 to 30.8, P < 0.001) HDSs. Compared with private HDS for arthroscopy, municipal wait times were 57 days longer (95% CI = 48 to 66 days, P < 0.001) and federal wait times were 34 days longer (95% CI = 21 to 47 days, P < 0.001). Compared with private HDS for fracture repair, municipal wait times were 0.6 days longer (95% CI = 0.2 to 1.0, P = 0.02); federal LoS was 7 days longer (95% CI = 3.6 to 9.4 days, P < 0.001); and municipal LoS was 4 days longer (95% CI = 2.4 to 4.8, P < 0.001). Only private HDS fracture repair patients received bone health consultations. DISCUSSION/CONCLUSIONS:The private HDS provided care for a markedly larger volume of patients seeking orthopaedic care. In addition, private HDS patients experienced reduced surgical wait times, LoSs, and complication odds for inpatient elective cases, with better referral patterns for nonsurgical orthopaedic care after hip fractures within the private HDS. These results may guide improvements for federal and municipal HDSs.

PURPOSE/OBJECTIVE:Chronic use of selective serotonin reuptake inhibitors (SSRIs) for the treatment of depression has been linked to an imbalance in bone metabolism leading to osteoporosis. More recently, the use of SSRIs in murine models has been shown to delay bone healing both in vivo and in vitro by decreasing the osteoblastic differentiation and mineralization. The purpose of this study was to evaluate whether or not chronic use of SSRI's in nonunion patients increases their time to union after surgical intervention. METHODS:We retrospectively analyzed 343 patients in a nonunion database to determine which patients were on SSRI medication. Of these patients, 139 could be contacted and of those 102 were not taking SSRIs and 37 were taking SSRIs. Patient's time to union from nonunion surgical intervention between each cohort at our institution was recorded as the primary outcome. Patient's medical comorbidities that could affect union rates such as diabetes and smoking status were also noted. Baseline Short Musculoskeletal Function Assessment (SMFA) index for bother and function were recorded from the time of nonunion surgery as well as last follow-up. RESULTS:Compared to recent census data, we found significantly more patients in the nonunion cohort using SSRIs (26.6%) than patients in the general population using any type of antidepressant (11%). There was no significant difference in the patients' baseline characteristics other than patients on SSRI treatment had a higher body mass index (BMI) and age (p = 0.048 and p = 0.043, respectively). There was no significant difference noted in the fracture types (p = 0.2063). Patients on SSRIs had a higher SMFA bother index and function index on follow-up (p = 0.0103, p = 0.0147). Patients in the SSRI group had a mean time to union from nonunion surgery of 6.1 months compared to 6.0 in patients without SSRI usage (p = 0.74). These did not reach statistical significance when subcohort analysis for long bone fractures was performed for the femur, tibia, and humerus. CONCLUSION/CONCLUSIONS:To our knowledge, this is the first clinical study to investigate the effects of SSRIs on fracture healing. While in vivo and in vitro murine models have shown that SSRIs can have a deleterious effect on osteoblastic activity, our retrospective analysis did not show a significant difference in time to union between patients with chronic SSRI use and patients who have not been on SSRIs. However, this investigation did show a higher incidence of SSRI use in the nonunion cohort when compared to the general population. In the context of the recent animal model study, this may point to a negative effect of SSRI use on the acute fracture healing process.

BACKGROUND:The ability to predict long-term outcomes following surgical fixation of proximal humerus fractures would help identify patients at risk of poor functional outcomes. The purpose of this study was to develop a simple score based on preoperative data that can accurately predict functional outcomes for patients following operative management of proximal humerus fractures. METHODS:Over a 12-year period, all proximal humerus fractures surgically treated with a locked proximal humerus plate at a single institution were enrolled in a prospective database. Inclusion criteria in this analysis were any patient with a minimum of a one-year functional outcome score. Patients were assigned to the poor outcome cohort if their Disabilities of the Arm, Shoulder, and Hand (DASH) score at that time point was greater than 10 points above the mean DASH score. Logistic regression was used to build a predictive formula for cohort membership using p < 0.15 and an area under the receiver operator characteristic curve (AUROC) value was calculated to define the overall predictive capacity. RESULTS:A total of 165 patients with an average age of 60.91±13.5 years met the inclusion criteria, with 47 (28.5%) patients assigned to the poor outcome group and 118 (71.5%) patients assigned to the good outcome group. Older age (p = 0.088), BMI (p = 0.019), age-adjusted CCI (p = 0.001), non-Caucasian race (p = 0.017), no college degree (p < 0.0005), unemployed (p < 0.0005), and worker's compensation case (p = 0.002) were found to be significant predictors of poorer outcome and were used to create a final formula through logistic regression which predicted the probability of a poor outcome (Nagelkerke R Square = 0.403; Hosmer and Lemeshow = 0.902; AUROC = 0.839 [CI: 0.762-0.917]). Once each patient was assigned a score, cutoff values were defined that divided the cohort into three groups. High-risk patients had a score above 50%, and 19 (73.1%) of these patients had a poor outcome. CONCLUSIONS:The POSY score is a tool that can predict the functional outcome at one year or greater following surgical intervention for a proximal humerus fracture. Patients who score above 50% are considered at high risk for a poor functional outcome. In the era of value-based care, the POSY score may be used to direct resource utilization while improving outcomes.

Background The incidence of geriatric hip fractures, respiratory infections (e.g., coronavirus disease 2019 (COVID-19), influenza), and mortality is higher during the fall and winter. The purpose of this study is to assess whether the addition of seasonality to a validated geriatric inpatient mortality risk tool will improve the predictive capacity and risk stratification for geriatric hip fracture patients. We hypothesize that seasonality will improve the predictive capacity. Methodology Between October 2014 and August 2021, 2,421 patients >55-year-old treated for hip fracture were analyzed for demographics, date of presentation, COVID-19 status (for patients after February 2020), and mortality. Patients were grouped by season based on their admission dates into the following four cohorts: fall (September-November), winter (December-February), spring (March-May), and summer (June-August). Patients presenting during the fall/winter and spring/summer were compared. The baseline Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool for hip fractures (STTGMAHIP_FX_SCORE) and the seasonality iteration (STTGMA_SEASON) were also compared. Sub-analysis was conducted on 687 patients between February 2020 and August 2021 amid the COVID-19 pandemic. The baseline score (STTGMAHIP_FX_SCORE) and the COVID-19 iteration (STTGMACOVID_ORIGINAL_2020) were modified to include seasonality (STTGMA_COVID/SEASON). Patients were stratified by risk score and compared. The predictive ability of the models was compared using DeLong's test. Results For the overall cohort, patients who presented during the fall/winter had a higher rate of inpatient mortality (2.87% vs. 1.25%, p < 0.01). STTGMA_SEASON improved the predictive capacity for inpatient mortality compared to STTGMAHIP_FX_SCORE but not significantly (0.773 vs. 0.672, p = 0.105) On sub-analysis, regression weighting showed a coefficient of 0.643, with fall and winter having a greater absolute effect size (fall = 2.572, winter = 1.929, spring = 1.286, summer = 0.643). STTGMA_COVID/SEASON improved the predictive capacity for inpatient mortality compared to STTGMAHIP_FX_SCORE (0.882 vs. 0.581, p < 0.01) and STTGMACOVID_ORIGINAL_2020 (0.882 vs. 0.805, p = 0.04). The highest risk quartile contained 89.5% of patients who expired during their index inpatient hospitalization (p < 0.01) and 68.2% of patients who died within 30 days of discharge (p < 0.01). Conclusions Seasonality may play a role in both the incidence and impact of COVID-19 and additional respiratory infections. Including seasonality improves the predictive capacity and risk stratification of the STTGMA tool during the COVID-19 pandemic. This allows for effective triage and closer surveillance of high-risk geriatric hip fracture patients by better accounting for the increased respiratory infection incidence and the associated mortality risk seen during fall and winter.

Background Smoking, obesity, and being below a healthy body weight are known to increase all-cause mortality rates and are considered modifiable risk factors. The purpose of this study is to assess whether adding these risk factors to a validated geriatric inpatient mortality risk tool will improve the predictive capacity for hip fracture patients. We hypothesize that the predictive capacity of the Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool will improve. Methodology Between October 2014 and August 2021, 2,421 patients >55-years-old treated for hip fractures caused by low-energy mechanisms were analyzed for demographics, injury details, hospital quality measures, and mortality. Smoking status was recorded as a current every-day smoker, former smoker, or never smoker. Smokers (current and former) were compared to non-smokers (never smokers). Body mass index (BMI) was defined as underweight (<18.5 kg/m²), healthy weight (18.5-24.9 kg/m²), overweight (25.0-24.9 kg/m²), or obese (>30 kg/m²). The baseline STTGMA tool for hip fractures (STTGMAHIP_FX_SCORE) was modified to include patients' BMI and smoking status (STTGMA_MODIFIABLE), and new mortality risk scores were calculated. Each model's predictive ability was compared using DeLong's test by analyzing the area under the receiver operating curves (AUROCs). Comparative analyses were conducted on each risk quartile. Results A comparison of smokers versus non-smokers demonstrated that smokers experienced higher rates of inpatient (p = 0.025) and 30-day (p = 0.048) mortality, myocardial infarction (p < 0.01), acute respiratory failure (p < 0.01), and a longer length of stay (p = 0.014). Comparison among BMI cohorts demonstrated that underweight patients experienced higher rates of pneumonia (p = 0.033), decubitus ulcers (p = 0.046), and the need for an intensive care unit (ICU) (p < 0.01). AUROC comparison demonstrated that STTGMA_MODIFIABLE significantly improved the predictive capacity for inpatient mortality compared to STTGMAHIP_FX_SCORE (0.792 vs. 0.672, p = 0.0445). Quartile stratification demonstrated the highest risk cohort had a longer length of stay (p < 0.01), higher rates of inpatient (p < 0.01) and 30-day mortality (p < 0.01), and need for an ICU (p < 0.01) compared to the minimal risk cohort. Patients in the lowest risk quartile were most likely to be discharged home (p < 0.01). Conclusions Smoking, obesity, and being below a healthy body weight increase the risk of perioperative complications and poor outcomes. Including smoking and BMI improves the STTGMAHIP_FX_SCORE tool to predict mortality and risk stratify patient outcomes. Because smoking, obesity, and being below a healthy body weight are modifiable patient factors, providers can counsel patients and implement lifestyle changes to potentially decrease their risk of longer-term poor outcomes, especially in the setting of another fracture. For patients who are former smokers, providers can use this information to encourage continued restraint and healthy choices.

PURPOSE/UNASSIGNED:The purpose of this study was to investigate if early postoperative ambulation metrics affect hospital quality measures and 1-year outcomes in operative hip fracture patients. METHODS/UNASSIGNED:A consecutive series of hip fracture patients [OTA/AO 31A, 31B, 32A-C] who underwent operative treatment were reviewed for demographic and clinical data. Chart review was performed to determine participation with physical therapy [PT] and ambulation distance on postoperative day (POD) 1, 3, and 5. POD1 ambulators and non-ambulators were statistically compared. Outcome correlates of postoperative ambulation distance were investigated by univariate and multivariate linear and logistic regression. RESULTS/UNASSIGNED: = 0.0353). CONCLUSIONS/UNASSIGNED:Failure to ambulate on POD1 following hip fracture surgery in >55 years is associated with an increased risk of in-hospital complications and mortality. Every effort should be made address this modifiable risk factor and mobilise patients on POD1 to improve patient outcomes.

Background:Patients with psychiatric comorbidities represent a significant subset of those sustaining pilon fractures. The purpose of this study is to examine the association of psychiatric comorbidities (PC) in patients with pilon fractures and clinical outcomes. Methods:A multi-institution, retrospective review was conducted. Inclusion/exclusion criteria were skeletally mature patients with a tibia pilon fracture (OTA Type 43B/C) who underwent definitive fracture fixation utilizing open reduction internal fixation (ORIF) with a minimum of 24 weeks of follow-up. Patients were stratified into two groups for comparison: PC group and no PC group. Results:There were 103 patients with pilon fractures that met the inclusion/exclusion criteria of this study. Of these patients, 22 (21.4%) had at least one psychiatric comorbidity (PC) and 81 (78.6%) did not have psychiatric comorbidities (no PC). There was a higher percentage of female patients (PC: 59.1% vs no PC: 25.9%, p=0.0.005), smokers (PC: 40.9% vs no PC: 16.0%, p=0.02), and drug users (PC: 22.7% vs no PC: 8.6%, p=0.08) amongst PC patients. Fracture comminution (PC: 54.5% vs no PC: 32.1%, p=0.05) occurred more frequently in PC patients. The PC group had a higher incidence of weightbearing noncompliance (22.7% vs 7.5%, p=0.04) and reoperation (PC: 54.5% vs no PC: 29.6%, p=0.03). Conclusion:.