Faculty Bibliography

PURPOSE/OBJECTIVE:To (1) determine if any injury characteristics or radiographic parameters of tibial shaft fractures (TSFs) could predict posterior malleolar fracture (PMF) size, and (2) identify characteristics of PMFs that were fixed versus those that were not in a cohort of ipsilateral TSFs that underwent intramedullary nailing. METHODS:A cross-sectional radiographic study was performed at a single academic institution. Demographic and radiographic parameters of TSFs were recorded, including fracture obliquity angle (FOA) and distance from distal extent of fracture to plafond (DFP). Using CT, the PMFs were evaluated for Haraguchi classification, size measurements, and preoperative displacement. Multivariate regression analysis was used to identify independent predictors of PMF Harachuchi classification, size parameters, and preoperative displacement. Univariate differences between PMF that were fixed and not fixed were identified. RESULTS:47 (50%) PMF underwent surgical fixation with 47 treated conservatively. There were no demographic differences between groups. Multivariate linear regression demonstrated increasing DFP and high energy injury mechanism as independent variables correlated with plafond surface area involvement, PMF height and width on sagittal CT cuts. Increasing DFP alone was correlated with PMF width on axial CT cuts and extent > 50% into incisura. Haraguchi type II fractures were associated with high energy injury mechanism (OR = 4.2 [95% CI = 1.3-14.5]; p = 0.02). Odds of Haraguchi type 3 fractures increased 9% per increased year of age (OR = 1.09 [95% CI = 1.04-1.16]; p = 0.006) and decreased 13% per 1% increase in relative DFP (OR = 0.87 [95% CI = 0.75-0.98]; p = 0.04). CONCLUSIONS:An increasing DFP of TSFs and high energy injury mechanism were independent predictors of PMF size, and high energy injury mechanism was also correlated with Haraguchi type II fracture patterns. Increasing age and decreasing DFP of TSFs predict Haraguchi type III PMF patterns. These radiographic parameters should prompt surgeons to plan for fixation in scenarios in which CT scan is not available. LEVEL OF EVIDENCE/METHODS:Diagnostic Level III.

BACKGROUND:Many initiatives by medical and public health communities at the national, state, and institutional level have been centered around understanding and analyzing critical determinants of population health with the goal of equitable and nondisparate care. In orthopaedic traumatology, several studies have demonstrated that race and socioeconomic status are associated with differences in care delivery and outcomes of patients with hip fractures. However, studies assessing the effectiveness of methods to address disparities in care delivery, quality metrics, and complications after hip fracture surgery are lacking. QUESTIONS/PURPOSES/OBJECTIVE:(1) Are hospital quality measures (such as delay to surgery, major inpatient complications, intensive care unit admission, and discharge disposition) and outcomes (such as mortality during inpatient stay, within 30 days or within 1 year) similar between White and non-White patients at a single institution in the setting of a standardized hip fracture pathway? (2) What factors correlate with aforementioned hospital quality measures and outcomes under the standardized care pathway? METHODS:In this retrospective, comparative study, we evaluated the records of 1824 patients 55 years of age or older with hip fractures from a low-energy mechanism who were treated at one of four hospitals in our urban academic healthcare system, which includes an orthopaedic tertiary care hospital, from the initiation of a standardized care pathway in October 2014 to March 2020. The standardized 4-day hip fracture pathway is comprised of medicine comanagement of all patients and delineated tasks for doctors, nursing, social work, care managers, and physical and occupational therapy from admission to expected discharge on postoperative day 4. Of the 1824 patients, 98% (1787 of 1824) of patients who had their race recorded in the electronic medical record chart (either by communicating it to a medical provider or by selecting their race from options including White, Black, Hispanic, and Asian in a patient portal of the electronic medical record) were potentially eligible. A total of 14% (249 of 1787) of patients were excluded because they did not have an in-state address. Of the included patients, 5% (70 of 1538) were lost to follow-up at 30 days and 22% (336 of 1538) were lost to follow-up at 1 year. Two groups were established by including all patients selecting White as primary race into the White cohort and all other patients in the non-White cohort. There were 1111 White patients who were 72% (801) female with mean age 82 ± 10 years and 427 non-White patients who were 64% (271) female with mean age 80 ± 11 years. Univariate chi-square and Mann-Whitney U tests of demographics were used to compare White and non-White patients and find factors to control for potentially relevant confounding variables. Multivariable regression analyses were used to control for important baseline between-group differences to (1) determine the correlation of White and non-White race on mortality, inpatient complications, intensive care unit (ICU) admissions, and discharge disposition and (2) assess the correlation of gender, socioeconomic status, insurance payor, and the Score for Trauma Triage in the Geriatric and Middle Aged (STTGMA) trauma risk score with these quality measures and outcomes. RESULTS:After controlling for gender, insurer, socioeconomic status and STTGMA trauma risk score, we found that non-White patients had similar or improved care in terms of mortality and rates of delayed surgery, ICU admission, major complications, and discharge location in the setting of the standardized care pathway. Non-White race was not associated with inpatient (odds ratio 1.1 [95% CI 0.40 to 2.73]; p > 0.99), 30-day (OR 1.0 [95% CI 0.48 to 1.83]; p > 0.99) or 1-year mortality (OR 0.9 [95% CI 0.57 to 1.33]; p > 0.99). Non-White race was not associated with delay to surgery beyond 2 days (OR = 1.1 [95% CI 0.79 to 1.38]; p > 0.99). Non-White race was associated with less frequent ICU admissions (OR 0.6 [95% CI 0.42 to 0.85]; p = 0.03) and fewer major complications (OR 0.5 [95% CI 0.35 to 0.83]; p = 0.047). Non-White race was not associated with discharge to skilled nursing facility (OR 1.0 [95% CI 0.78 to 1.30]; p > 0.99), acute rehabilitation facility (OR 1.0 [95% CI 0.66 to 1.41]; p > 0.99), or home (OR 0.9 [95% CI 0.68 to 1.29]; p > 0.99). Controlled factors other than White versus non-White race were associated with mortality, discharge location, ICU admission, and major complication rate. Notably, the STTGMA trauma risk score was correlated with all endpoints. CONCLUSION/CONCLUSIONS:In the context of a hip fracture care pathway that reduces variability from time of presentation through discharge, no differences in mortality, time to surgery, complications, and discharge disposition rates were observed beween White and non-White patients after controlling for baseline differences including trauma risk score. The pathway detailed in this study is one iteration that the authors encourage surgeons to customize and trial at their institutions, with the goal of providing equitable care to patients with hip fractures and reducing healthcare disparities. Future investigations should aim to elucidate the impact of standardized trauma care pathways through the use of the STTGMA trauma risk score as a controlled confounder or randomized trials in comparing standardized to individualized, surgeon-specific care. LEVEL OF EVIDENCE/METHODS:Level III, therapeutic study.

Introduction: The purpose of this study is to assess the effect of radial head/ neck injury in association with proximal ulna fractures. Methods: Between 2006 and 2020, 107 patients presented to our academic medical center for treatment of a proximal ulna fracture and were enrolled into an IRB-approved database. Radiographs, injury details, and surgical interventions were retrospectively reviewed. Patients were classified as having an isolated proximal ulna fracture (PU), a PU fracture with an associated radial head dislocation (M"“D), or a Monteggia fracture with an associated radial head fracture (M"“V). Clinical and functional outcomes were assessed at follow-up to determine what differences exist between fracture patterns. Statistics were generated using Chi-squared tests for categorical variables and one-way ANOVA tests for numerical variables. Results: While all patients ultimately healed, time to radiographic healing in the PU cohort was shorter at 3.57 ± 1.7 months when compared to the M"“V cohort (5.67 ± 3.8 months) (p < 0.05). At follow-up, patients in the M"“V cohort had poorer elbow pronation and supination when compared to the PU and M"“D cohorts (p < 0.05). Patients within the PU cohort had fewer complications than those in the M"“D and M"“V cohorts (p < 0.05). No differences were found between the three cohorts in regard to rates of reoperation, non-union, wound infection, and nerve compression (p > 0.05). Conclusion: The Monteggia fracture with a concomitant radial head/neck fracture is a more disabling injury pattern when compared to an isolated proximal ulna fracture and Monteggia fracture without an associated radial head/neck fracture.

OBJECTIVES/UNASSIGNED:The purpose of this study was to assess the safety and efficacy of outpatient and short-stay surgical nonunion treatment by incorporating minimally invasive surgical techniques, multimodal pain control, and a modernized postoperative protocol. DESIGN/UNASSIGNED:Retrospective case series. SETTING/UNASSIGNED:Tertiary referral hospital and hospital outpatient department. PATIENTS/UNASSIGNED:All consecutive nonunion surgeries performed by 1 surgeon between 2014 and 2019 were identified. Outpatient and short-stay surgeries for patients with nonunion of the tibia and femur were eligible (n = 50). INTERVENTION/UNASSIGNED:Outpatient and short-stay surgical nonunion treatment by incorporating minimally invasive surgical techniques, multimodal pain control, and a modernized postoperative protocol. MAIN OUTCOME MEASUREMENTS/UNASSIGNED:Length of stay, postoperative emergency department visits, all complications, reoperations, and time to union. RESULTS/UNASSIGNED:Fifty patients were eligible, with 32 male patients (64%) and an average age of 46.5 years. The patient cohort consisted of 28 femur (56%) and 22 tibia (44%) nonunions. The average length of stay was 0.36 days. Seven patients (14%) required reoperation, 6 patients because of deep infection and 1 patient because of painful implant removal. Four patients (8%) presented to the emergency department within 1 week of surgery. One patient requiring amputation and patients lost to follow-up were excluded from the union rate calculation. For the remaining patients (46/50), 100% (46/46) united their nonunion. The average time to radiographic union was 7.82 months. CONCLUSIONS/UNASSIGNED:An outpatient pathway is safe and effective for medically appropriate patients undergoing nonunion surgery. Outpatient nonunion surgery is a reasonable alternative that achieves similar outcomes compared with inpatient nonunion studies in the published literature. LEVEL OF EVIDENCE/UNASSIGNED:IV.

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.

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 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.

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.