What If We Do Not Operate? Outcomes of Nonoperatively Managed Emergency General Surgery Patients.

INTRODUCTION: Although two-thirds of patients with emergency general surgery (EGS) conditions are managed nonoperatively, their long-term outcomes are not well described. We describe outcomes of nonoperative management in a cohort of older EGS patients and estimate the projected risk of operative management using the NSQIP Surgical Risk Calculator (SRC). MATERIALS AND METHODS: We studied single-center inpatients aged 65 y and more with an EGS consult who did not undergo an operation (January 2019-December 2020). For each patient, we recorded the surgeon's recommendation as either an operation was "Not Needed" (medical management preferred) or "Not Recommended" (risk outweighed benefits). Our main outcome of interest was mortality at 30 d and 1 y. Our secondary outcome of interest was SRC-projected 30-day postoperative mortality risk (median % [interquartile range]), calculated using hypothetical low-risk and high-risk operations. RESULTS: We included 204 patients (60% female, median age 75 y), for whom an operation was "Not Needed" in 81% and "Not Recommended" in 19%. In this cohort, 11% died at 30 d and 23% died at 1 y. Mortality was higher for the "Not Recommended" cohort (37% versus 5% at 30 d and 53% versus 16% at 1 y, P < 0.05). The SRC-projected 30-day postoperative mortality risk was 3.7% (1.3-8.7) for low-risk and 5.8% (2-11.8) for high-risk operations. CONCLUSIONS: Nonoperative management in older EGS patients is associated with very high risk of short-term and long-term mortality, particularly if a surgeon advised that risks of surgery outweighed benefits. The SRC may underestimate risk in the highest-risk patients.

Development of Imaging Criteria for Geriatric Blunt Trauma Patients.

INTRODUCTION: Current decision tools to guide trauma computed tomography (CT) imaging were not validated for use in older patients. We hypothesized that specific clinical variables would be predictive of injury and could be used to guide imaging in this population to minimize risk of missed injury. METHODS: Blunt trauma patients aged 65 y and more admitted to a Level 1 trauma center intensive care unit from January 2018 to November 2020 were reviewed for histories, physical examination findings, and demographic information known at the time of presentation. Injuries were defined using the patient's final abbreviated injury score codes, obtained from the trauma registry. Abbreviated injury score codes were categorized by corresponding CT body region: Head, Face, Chest, C-Spine, Abdomen/Pelvis, or T/L-Spine. Variable groupings strongly predictive of injury were tested to identify models with high sensitivity and a negative predictive value. RESULTS: We included 608 patients. Median age was 77 y (interquartile range, 70-84.5) and 55% were male. Ground-level fall was the most common injury mechanism. The most commonly injured CT body regions were Head (52%) and Chest (42%). Variable groupings predictive of injury were identified in all body regions. We identified models with 97.8% sensitivity for Head and 98.8% for Face injuries. Sensitivities more than 90% were reached for all except C-Spine and Abdomen/Pelvis. CONCLUSIONS: Decision aids to guide imaging for older trauma patients are needed to improve consistency and quality of care. We have identified groupings of clinical variables that are predictive of injury to guide CT imaging after geriatric blunt trauma. Further study is needed to refine and validate these models.

Post-Trauma Discharge Instructions: Are We Dropping the Ball?

INTRODUCTION: Complex follow-up plans for polytrauma patients are compiled at the end of hospitalization into discharge instructions. We sought to identify how often patient discharge instructions incorrectly communicated specialist recommendations. We hypothesized that patients with more complex hospitalizations would have more discharge instruction errors (DI-errors). METHODS: We reviewed adult trauma inpatients (March 2017-March 2018), excluding those who left against medical advice or were expected to follow up outside our system. Complex hospitalizations were represented using injury severity (ISS), hospital length of stay (LOS), intensive care unit length of stay (iLOS), and number of consultants (NC). We recorded the type of consultant (surgical or nonsurgical), and consultant recommendations for follow-up. DI-errors were defined as either follow-up necessary but omitted or follow-up not necessary yet present on the instructions. Patients with DI-errors were compared to patients without DI-errors. Groups were compared using Wilcoxon rank sum or chi-square (alpha <.05). RESULTS: We included 392 patients (median age 45 [IQR 26-58], ISS 14 [10-21], LOS 6 [3-11]). 55 patients (14%) had DI-errors. Factors associated with DI-errors included the total number of consultants and use of nonsurgical consultants. ISS, LOS, iLOS, were not associated with DI-errors. CONCLUSION: Common measures of admission complexity were not associated with DI-errors, although the number and type of consultants were associated with DI-errors. Non-surgical specialty consultant recommendations were more likely to be omitted. It is crucial for patients to receive accurate discharge instructions, and systematic processes are needed to improve communication with the patients at discharge.

Race and trauma mortality: The effect of hospital-level Black-White patient race distribution.

BACKGROUND: Race-related health disparities have been well documented in the United States. In some settings, Black patients have better outcomes in hospitals that serve high proportions of Black patients. We hypothesized that Black trauma patients would have lower mortality in high Black-serving (H-BS) hospitals. METHODS: We identified all adult patients with Black or White race and with an Injury Severity Score of ≥4 from the 2017 National Inpatient Sample. We collected hospital identifier, mechanism, age, sex, comorbidities, urban-rural location, insurance, zip code income quartile, and injury severity calculated from International Classification of Diseases, Tenth Revision, codes. We used a previously published method to group hospitals by proportion of Black patients served: HB-S (top 5%), medium Black serving (5-25%), and low Black serving (L-BS; bottom 75%). Adjusted logistic regression using an interaction variable between race and hospital service rank (reference: White patients in H-BS) was used to identify factors associated with mortality. RESULTS: We analyzed 184,080 trauma patients (median age, 72 years [interquartile range, 55-84 years]; Injury Severity Score, 9 [4-10]), of whom 11.7% were Black. Overall mortality was 4%. Of 2,376 hospitals, 126 (5.3%) were H-BS and 469 (19.7%) were medium Black serving. Furthermore, 29.8% of Black and 3.6% of White patients were treated at H-BS hospitals, while 71.7% of White and 23.6% of Black patients were treated at L-BS hospitals (p < 0.001). Black patients had the lowest mortality at H-BS hospitals (odds ratio [OR], 0.76 [0.64-0.92]) and the highest mortality (OR, 1.43 [1.13-1.80]) at L-BS hospitals. White patients had the lowest mortality at L-BS hospitals (OR, 0.76 [0.64-0.92]). CONCLUSION: After adjusting for patient and hospital factors, disparities exist such that Black and White patients have the best outcomes in hospitals that treat those patients most frequently, suggesting potential for racial bias at the institutional level. Further efforts must be made to promote equitable treatment at all hospitals and reduce these disparities. LEVEL OF EVIDENCE: Prognostic and Epidemiologic; Level IV.