Arterial Injury Portends Worse Soft Tissue Outcomes and Delayed Coverage in Open Tibial Fractures
OBJECTIVES/OBJECTIVE:To investigate if any injury to the three primary branches of the popliteal artery in open tibia fractures lead to increased soft-tissue complications, particularly in the area of the affected angiosome. DESIGN/METHODS:Retrospective cohort comparative study. SETTING/METHODS:Two academic level one trauma centersPatients/Participants: Sixty-eight adult patients with open tibia fractures with a minimum one-year follow up. INTERVENTION/METHODS:N/A. MAIN OUTCOME MEASUREMENTS/METHODS: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:Eleven (15.1%) tibia fractures had confirmed arterial injuries via CTA (7), direct intraoperative visualization (3), intraoperative angiogram (3). Ten (91.0%) were treated with ligation and 1 (9.1%) was directly repaired by vascular surgery. Ultimately, 6 (54.5%) achieved radiographic union and 4 (36.4%) required amputation performed at a mean of 2.62 Â± 2.04 months, with one patient going on to nonunion diagnosed at 10 months. Patients with arterial injury had significantly higher rates of wound healing complications, FRI, nonunion, amputation rates, return to the OR, and increased time to coverage or closure. After multivariate regression, arterial injury was associated with higher odds of wound complications, FRI, and nonunion. Ten (90.9%) patients with arterial injury had open wounds in the region of the compromised angiosome, with 7 (70%) experiencing wound complications, 6 (60%) FRIs, and 3 (30%) undergoing amputation. CONCLUSIONS:Arterial injuries in open tibia fractures with or without repair, have significantly higher rates of wound healing complications, FRI, delayed time to final closure, and need for amputation. Arterial injuries appear to effect wound healing in the affected angiosome. LEVEL OF EVIDENCE/METHODS:Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.
Preoperative echocardiogram does not increase time to surgery in hip fracture patients with prior percutaneous coronary intervention
BACKGROUND:The purpose of this study was to (1) assess the effect of preoperative echocardiogram on time to surgery and (2) assess the outcomes of patients with a previous percutaneous coronary intervention (PCI). METHODS:Demographic, clinical, quality and cost data were obtained and a validated risk predictive tool (STTGMA) was calculated for each of a consecutive series of hip fracture patients. Comparative analyses of patients who had an echocardiogram prior to surgery or a PCI prior to hospitalization were performed. RESULTS:Between 2014 and 2020, 2625 patients presented to our institution with a hip fracture. From this cohort 471 patients underwent a preoperative transthoracic echocardiogram (TTE), 30 who had a history of a PCI, and an additional 26 who had a history of PCI but did not undergo a preoperative TTE. Those undergoing a preoperative TTE had similar time (days) to surgery (1.73 vs 1.77, pâ€‰=â€‰0.86) and 30-day mortality (4% vs 7%, pâ€‰=â€‰0.545) regardless of PCI history. PCI patients who underwent a preoperative TTE experienced increased rates of 1-year mortality (27% vs 10%, pâ€‰=â€‰0.007) and major complications (23% vs 12%, pâ€‰=â€‰0.08) compared to those without a PCI history. PCI patients undergoing a preoperative TTE had a similar time (days) to surgery (1.77 vs 1.48, .pâ€‰=â€‰0.397) compared to PCI patients without a preoperative TTE. Patients who underwent a preoperative TTE had higher rates of 90-day readmission (31.0% vs 8.0%, pâ€‰=â€‰0.047) and 1-year mortality (26.7% vs 3.8%, pâ€‰=â€‰0.029). CONCLUSIONS:Having a preoperative TTE does not affect surgical wait times in hip fracture patients regardless of PCI history, but it may not improve mortality outcomes or reduce postoperative complications in patients with a history of a PCI.
No Differences Between White and Non-White Patients in Terms of Care Quality Metrics, Complications, and Death After Hip Fracture Surgery When Standardized Care Pathways are Used
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 Â± 10 years and 427 non-White patients who were 64% (271) female with mean age 80 Â± 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.
Value-Based Care in Orthopedic Trauma
The advent of value-based care as a component of the United States health care system is part of a broader paradigm shifting away from fee-for-service payment models in favor of alternative reimbursement incentives tied to quality and outcome metrics. Bundled care models, gainsharing agreements, and other cost containment measures, although promising, may induce unintended systemwide consequences for orthopedic trauma surgeons who often specialize in tending to costly multiply injured patients and marginalized populations. This article reviews facets of value-based care applicable to orthopedic trauma surgery with an emphasis on public health and ethical considerations for policymakers and orthopedic surgeons.
Total hip arthroplasty for hip fractures in patients older than 80 years of age: a retrospective matched cohort study
INTRODUCTION/BACKGROUND:Increasing age and hip fractures are considered risk factors for post-operative complications in total hip arthroplasty (THA). Consequently, older adults undergoing THA due to hip fracture may have different outcomes and require additional healthcare resources than younger patients. This study aimed to identify the influence of age on discharge disposition and 90-day outcomes of THA performed for hip fractures in patientsâ€‰â‰¥â€‰80Â years to those agedâ€‰<â€‰80. MATERIALS AND METHODS/METHODS:A retrospective review of 344 patients who underwent primary THA for hip fracture from 2011 to 2021 was conducted. Patientsâ€‰â‰¥â€‰80Â years old were propensity-matched to a control groupâ€‰<â€‰80Â years old. Patient demographics, length of stay (LOS), discharge disposition, and 90-day post-operative outcomes were collected and assessed using Chi-square and independent sample t tests. RESULTS:A total of 110 patients remained for matched comparison after propensity matching, and the average age in the younger cohort (YC, nâ€‰=â€‰55) was 67.69â€‰Â±â€‰10.48, while the average age in the older cohort (OC, nâ€‰=â€‰55) was 85.12â€‰Â±â€‰4.77 (pâ€‰â‰¤â€‰0.001). Discharge disposition differed between the cohorts (pâ€‰=â€‰0.005), with the YC being more likely to be discharged home (52.7% vs. 27.3%) or to an acute rehabilitation center (23.6% vs. 16.4%) and less likely to be discharged to a skilled nursing facility (21.8% vs. 54.5%). 90-day revision (3.6% vs. 1.8%; pâ€‰=â€‰0.558), 90-day readmission (10.9% vs. 14.5%; pâ€‰=â€‰0.567), 90-day complications (pâ€‰=â€‰0.626), and 90-day mortality rates (1.8% vs 1.8%; pâ€‰=â€‰1.000) did not differ significantly between cohorts. CONCLUSION/CONCLUSIONS:While older patients were more likely to require a higher level of post-hospital care, outcomes and perioperative complication rates were not significantly different compared to a younger patient cohort. Payors need to consider patients' age in future payment models, as discharge disposition comprises a large percentage of post-discharge expenses. LEVEL OF EVIDENCE/METHODS:Level III, Retrospective Cohort Study.
Nonunion of conservatively treated humeral shaft fractures is not associated with anatomic location and fracture pattern
INTRODUCTION/BACKGROUND:Humeral shaft fractures make up 1-3% of all fractures and are most often treated nonoperatively; rates of union have been suggested to be greater than 85%. It has been postulated that proximal third fractures are more susceptible to nonunion development; however, current evidence is conflicting and presented in small cohorts. It is our hypothesis that anatomic site of fracture and fracture pattern are not associated with development of nonunion. MATERIALS AND METHODS/METHODS:In a retrospective cohort study, 147 consecutive patients treated nonoperatively for a humeral shaft fracture were assessed for development of nonunion during their treatment course. Their charts were reviewed for demographic and radiographic parameters such as age, sex, current tobacco use, diabetic comorbidity, fracture location, fracture pattern, AO/OTA classification, and need for intervention for nonunion. RESULTS:One hundred and forty-seven patients with 147 nonoperatively treated humeral shaft fractures were eligible for this study and included: 39 distal, 65 middle, and 43 proximal third fractures. One hundred and twenty-six patients healed their fractures by a mean 16â€‰Â±â€‰6.4Â weeks. Of the 21 patients who developed a nonunion, two were of the distal third, 10 of the middle third, and nine were of the proximal third. In a binomial logistic regression analysis, there were no differences in age, sex, tobacco use, diabetic comorbidity, fracture pattern, anatomic location, and OTA fracture classification between patients in the union and nonunion cohorts. CONCLUSIONS:Fracture pattern and anatomic location of nonoperatively treated humeral shaft fractures were not related to development of fracture nonunion.
Research During Orthopaedic Training
By the end of their training, all orthopaedic residents should be competent in understanding musculoskeletal research enough to navigate the literature and base clinical decisions on it. To accomplish this, the Accreditation Council for Graduate Medical Education requires involvement in scholarly activity. For those interested in academics and having additional involvement in research, there can be many benefits including professional achievement and intellectual /personal satisfaction. A number of potential career models exist for those interested in being engaged in musculoskeletal research, so trainees should seek the training and level of involvement in research that will help them achieve their individual academic goals. To that end, trainees should become involved with research early and identify research mentors in their field of interest (at home or from afar). Training programs and faculty members should create a milieu conducive to research productivity and support and equip trainees who have such aspirations.
Wound Closure Following Intervention for Closed Orthopedic Trauma
The method of skin closure and post-operative wound management has always been important in orthopedic surgery and plays an even larger role now that surgical site infection (SSI) is a national healthcare metric for both surgeons and hospitals. Wound related issues remain some of the most feared complications following orthopedic trauma procedures and are associated with significant morbidity. In order to minimize the risk of surgical site complications, surgeons must be familiar with the physiology of wound healing as well as the patient and surgical factors affecting healing potential. The goal of all skin closure techniques is to promote rapid healing with acceptable cosmesis, all while minimizing risk of infection and dehiscence. Knowledge of the types of closure material, techniques of wound closure, surgical dressings, negative pressure wound therapy, and other local modalities is important to optimize wound healing. There is no consensus in the literature as to which closure method is superior but the available data can be used to make informed choices. Although often left to less experienced members of the surgical team, the process of wound closure and dressing the wound should not be an afterthought, and instead must be part of the surgical plan. Wounds that are in direct communication with bony fractures are particularly at risk due to local tissue trauma, resultant swelling, hematoma formation, and injured vasculature.
Trauma Risk Score Matching for Observational Studies in Orthopedic Trauma
OBJECTIVES/OBJECTIVE:To determine if matching by trauma risk score is non-inferior to matching by chronic comorbidities and/or a combination of demographic and patient characteristics in observational studies of acute trauma in a hip fracture model. DESIGN/METHODS:Retrospective cohort study SETTING: Level-1 Trauma Center PATIENTS: 1,590 hip fracture [AO/OTA 31A and 31B] patients age 55 and over treated between October 2014 and February 2020 at 4 hospitals within a single academic medical center. INTERVENTION/METHODS:Repeatedly matching randomized subsets of patients by (1) Score for Trauma Triage in Geriatric and Middle-Aged (STTGMA), (2) Charlson Comorbidity Index (CCI), or (3) a combination of sex, age, CCI and body mass index (BMI). MAIN OUTCOME MEASUREMENTS/METHODS:"Matching failures" where rate of significant differences in variables of matched cohorts exceeds the 5% expected by chance. RESULTS:STTGMA and combination matching resulted in no "matching failures". Matching by CCI alone resulted in "matching failures" of BMI, ASA class, STTGMA, major complications, sepsis, pneumonia, acute respiratory failure, and 90-day readmission. CONCLUSIONS:STTGMA matching in observational cohort studies is less likely to yield significant differences of demographics and outcomes than CCI matching. STTGMA matching is noninferior to matching a combination of demographic variables optimized for each treatment cohort. STTGMA matching is apt to reflect equipoise of health at admission and outcome likelihood in observational cohort studies of orthopedic trauma, while maintaining consistent weighting of demographic and injury characteristic variables that may expand the generalizability of these studies. LEVEL OF EVIDENCE/METHODS:Level III.
Trauma risk score matching for observational studies in orthopedic trauma dataset and code
The dataset presented was collected via retrospective review from an orthopedic trauma database approved by the institutional review board at the author's institution from patients treated at any of the four hospitals serviced by the academic orthopedic surgery department. Femoral neck and intertrochanteric hip fracture patients from low energy mechanisms admitted between October 2014 and February 2020, were selected if they were age 55 or older and had recorded sex, body mass index (BMI), Charlson Comorbidity Index (CCI), American Society of Anaesthesiologists (ASA) physical status classification, Glasgow Coma Score, Abbreviated Injury Severity score for the chest, head and neck, and extremities, and ambulation status prior to injury. The resultant 1,590 subject dataset may be analysed via the supplied R statistical code to determine the frequency of equipoise in baseline and outcome variables from propensity matching via three matching schemes. The code implements three matching schemes including matching by (1) The Score for Trauma Triage in Geriatric and Middle-Aged (STTGMA) (2) CCI alone, or (3) a combination of sex, age, CCI and BMI. The code selects a subset of ten percent of hip fracture patients by a pseudorandom number generator (PRNG). The code matches the remaining patients 1:1 to the selected patients by propensity score generated by logistic regression of STTGMA, CCI, or a combination of sex, age, CCI and BMI using greedy nearest neighbor matching without replacement by the MatchIt package for R software. The code then compares matched cohorts by Chi-square, Fisher, or Mann-Whitney U test with significance level of 0.05 representing a 5% chance of significant differences due to random sampling of subjects. The supplied code repeats the random selection, matching and testing process 100,000 times for each matching method. The resultant code output is the frequency of significantly different demographic or outcome parameters among matched cohorts by matching method. This data and statistical code have reuse potential to explore alternative matching schemes. The supplied baseline variables should be robust enough to derive alternative risk scores for each patient which may be included as a matching variable for comparison. The authors also look forward to unexpected ways that this data may be used by readers.