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BACKGROUND: Despite the high incidence of blunt trauma in older adults, there is a lack of evidence-based guidance for computed tomography (CT) imaging in this population. We aimed to identify an algorithm to guide use of a Pan-Scan (Head/C-spine/Torso) or a Selective Scan (Head/C-spine ± Torso). We hypothesized that a patient's initial history and exam could be used to guide imaging. METHODS: We prospectively studied blunt trauma patients aged 65+ at 18 Level I/II trauma centers. Patients presenting >24 h after injury or who died upon arrival were excluded. We collected history and physical elements and final injury diagnoses. Injury diagnoses were categorized into CT body regions of Head/C-spine or Torso (chest, abdomen/pelvis, and T/L spine). Using machine learning and regression modeling as well as a priori clinical algorithms based, we tested various decision rules against our dataset. Our priority was to identify a simple rule which could be applied at the bedside, maximizing sensitivity (Sens) and negative predictive value (NPV) to minimize missed injuries. RESULTS: We enrolled 5,498 patients with 3,082 injuries. Nearly half (47.1%, n = 2,587) had an injury within the defined CT body regions. No rule to guide a Pan-Scan could be identified with suitable Sens/NPV for clinical use. A clinical algorithm to identify patients for Pan-Scan, using a combination of physical exam findings and specific high-risk criteria, was identified and had a Sens of 0.94 and NPV of 0.86 This rule would have identified injuries in all but 90 patients (1.6%) and would theoretically spare 11.9% (655) of blunt trauma patients a torso CT. CONCLUSIONS: Our findings advocate for Head/Cspine CT in all geriatric patients with the addition of torso CT in the setting of positive clinical findings and high-risk criteria. Prospective validation of this rule could lead to streamlined diagnostic care of this growing trauma population. LEVEL OF EVIDENCE: Level 2, Diagnostic Tests or Criteria.
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OBJECTIVE: To determine whether the use of invasively measured hemodynamics improves the prognostic ability of a shock index (SI). BACKGROUND: SI such as Admission-SI, Age-SI, Modified SI (MSI), and Age-MSI predict short-term mortality in ST-elevation myocardial infarction (STEMI). METHODS: Single-center study of 510 patients who underwent primary percutaneous coronary intervention. STEMI SI was defined as age × heart rate (HR) divided by coronary perfusion pressure (CPP). RESULTS: The mean age was 62 ± 14 years, 66% were males with hypertension (69%), tobacco use (38%), diabetes (28%) and chronic kidney disease (6%). The mean HR, systolic blood pressure (SBP), and CPP were 81 ± 18 bpm, 124 ± 28 mmHg, and 52.8 ± 16.3 mmHg, respectively. Patients with STEMI SI ≥182 (n = 51) were more likely to experience a cardiac arrest in the catheterization laboratory (9.8% vs. 2.0%; p = .001), require mechanical circulatory support (47.1% vs. 8.5%; p < .0001) and be treated with vasopressors (56.9% vs. 10.7%; p < .0001) compared to STEMI SI < 182 (n = 459). After multivariate adjustment, patients with STEMI SI ≥182 were 10, 10.1 and 4.8 times more likely to die during hospitalization, at 30 days and at 5 years, respectively. The C statistic of STEMI SI was 0.870, similar to GRACE score (AUC = 0.902; p = .29) and TIMI STEMI score (AUC = 0.895; p = .36). CONCLUSION: STEMI SI is an easy to calculate risk score that identifies STEMI patients at high risk of in-hospital death.