Introduction: Surgical site infections (SSIs) are common complications after surgeries involving musculoskeletal tumors, but we know little about SSI risk factors unique to orthopaedic oncology. A greater understanding of these factors will help risk-stratify patients and guide surgical decision-making. Methods: A retrospective review at a single-institution identified 757 procedures done on 624 over 6 years. The patients had a preoperative diagnosis of a malignant or potentially malignant neoplasm of the bone or soft tissues. Patient-specific and procedure-specific variables and diagnosis of SSI were recorded for each case. Data were analyzed through univariate analysis and multiple logistic regression. Results: On univariate analysis, significant patient-specific risk factors for SSI included malignancy (P < 0.001), smoking history (P = 0.041), and American Society of Anesthesiologists Score (P = 0.002). Significant procedure-specific risk factors for SSI on univariate analysis included surgery time (P < 0.001), estimated blood loss (P < 0.001), blood transfusion volume (P < 0.001), neoadjuvant chemotherapy (P < 0.001), neoadjuvant radiation therapy (P < 0.001), inpatient surgery (P < 0.001), and number of previous surgeries within the study period (P < 0.001). The two factors that independently predicted risk of SSI when controlling for all other variables in a multiple logistic regression were whether the surgery was done on an inpatient basis (P = 0.005) and the number of previous surgeries done on the same site (P = 0.001). Conclusions: We found a number of risk factors that correlate markedly with SSI after orthopaedic oncology surgery. The surgeon can use these risk factors to aid in surgical decision-making.
Background: Several recently published population-based studies have highlighted the association between insurance status and survival in patients with various cancers such as breast, head and neck, testicular, and lymphoma [22, 24, 38, 41]. Generally, these studies demonstrate that uninsured patients or those with Medicaid insurance had poorer survival than did those who had non-Medicaid insurance. However, this discrepancy has not been studied in patients with primary bone and extremity soft-tissue sarcomas, a unique oncological population that typically presents late in the disease course and often requires referral and complex treatment at tertiary care centers–issues that health insurance coverage disparities could aggravate. Questions/purposes (1) What is the relationship between insurance status and cause-specific mortality? (2) What is the relationship between insurance status and the prevalence of distant metastases? (3) What is the relationship between insurance status and the proportion of limb salvage surgery versus amputation? Methods The Surveillance, Epidemiology, and End Results database (SEER) was used to identify a total of 12,008 patients: 4257 patients with primary bone sarcomas and 7751 patients with extremity soft-tissue sarcomas, who were diagnosed and treated between 2007 and 2014. Patients were categorized into one of three insurance groups: insured with non-Medicaid insurance, insured with Medicaid, and uninsured. Patients without information available regarding insurance status were excluded (2.7% [113 patients] with primary bone sarcomas and 3.1% [243 patients] with extremity soft-tissue sarcomas.) The association between insurance status and survival was assessed using a Cox proportional hazards regression analysis adjusted for patient age, sex, race, ethnicity, extent of disease (lymph node and metastatic involvement), tumor grade, tumor size, histology, and primary tumor site. Results Patients with primary bone sarcomas with Medicaid insurance had reduced disease-specific survival than did patients with non-Medicaid insurance (hazard ratio 1.3 [95% confidence interval 1.1 to 1.6]; p = 0.003). Patients with extremity soft-tissue sarcomas with Medicaid insurance also had reduced disease-specific survival compared with those with non-Medicaid insurance (HR 1.2 [95% CI 1.0 to 1.5]; p = 0.019). Patients with primary bone sarcomas (relative risk 1.8 [95% CI 1.3 to 2.4]; p < 0.001) and extremity soft-tissue sarcomas (RR 2.4 [95% CI 1.9 to 3.1]; p < 0.001) who had Medicaid insurance were more likely to have distant metastases at the time of diagnosis than those with non-Medicaid insurance. Patients with primary bone sarcomas (RR 1.8 [95% CI 1.4 to 2.1]; p < 0.001), and extremity soft-tissue sarcomas (RR 2.4 [95% CI 1.9 to 3.0]; p < 0.001) that had Medicaid insurance were more likely to undergo amputation than patients with non-Medicaid insurance. Patients with primary bone and extremity soft-tissue sarcomas who were uninsured were not more likely to have distant metastases at the time of diagnosis and did not have a higher proportion of amputation surgery as compared with patients with non-Medicaid insurance. However, uninsured patients with extremity soft-tissue sarcomas still displayed reduction in disease-specific survival (HR 1.6 [95% CI 1.2 to 2.1]; p = 0.001). Conclusions Disparities manifested by differences in insurance status were correlated with an increased risk of metastasis at the time of diagnosis, reduced likelihood of treatment with limb salvage procedures, and reduced disease-specific survival in patients with primary bone or extremity soft-tissue sarcomas. Although several potentially confounding variables were controlled for, unmeasured confounding played a role in these results. Future studies should seek to identify what factors drive the finding that substandard insurance status is associated with poorer survival after a cancer diagnosis. Candidate variables might include medical comorbidities, treatment delays, time to first presentation to medical care and time to diagnosis, type of treatment received, distance travelled to treatments and transportation barriers, out-of-pocket payment burden, as well as educational and literacy status. These variables are almost certainly associated with socioeconomic deprivation in a vulnerable patient population, and once identified, treatment can become targeted to address these systemic inequities. Level of Evidence Level III, therapeutic study.
The orthopaedic surgery residency selection process has grown more competitive over recent years, with programs receiving an unprecedented number of applications. As an effort to target applications to programs of interest, the American Orthopaedic Association has announced the introduction of a formal preferencesignaling program into the 2022 to 2023 orthopaedic surgery residency selection cycle. This system will allow applicants to assign "signals" to a total of 30 programs. The purpose of this article was to (1) discuss implications of the new preference-signaling program, (2) introduce the framework of the "strategic signaling spear" for applicants to conceptualize the power of all methods of preference-signaling to improve their odds of matching, and (3) describe the role of strong mentorship at all stages of the residency application process. Orthopaedic surgery consistently demonstrates one of the lowest residency match rates of any specialty, resulting in many strong applicants going unmatched every March. 1 In contrast to the 92% to 95% match rate for US seniors across other specialties between 2008 and 2018, orthopaedic surgery residency applicants matched at a rate of roughly 75% to 79%. 1,2 The 2021 to 2022 match cycle yielded the lowest match rate to date with 1,737 applicants vying for only 875 positions. 3,4 Among US medical school graduates, the match rate dropped to 64.0% of those who registered for the National Resident Matching Program. 3 The increase in the number of unmatched orthopaedic surgery applicants over the past several years has been attributed in part to the increasing number of applicants-up to 14% since 2021. 4 This increase in competitiveness has led to increasingly broad application submission. From 2008 to 2022, the mean number of applications submitted by US orthopaedic surgery residency applicants increased from 46.5 to 86.1-nearly half of all 203 orthopaedic residency programs were accredited by the Accreditation Council for Graduate Medical Education. 2,5,6 Largely fueled by the fear of going unmatched, many applicants have felt pressure to apply to more programs with the hope that more applications will increase their odds of matching-regardless of an applicant's genuine interest in the program. 2 Certainly, the "opportunity cost" of going unmatched is
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