CT With CTA Versus MRI in Patients Presenting to the Emergency Department With Dizziness: Analysis Using Propensity Score Matching.

BACKGROUND. CT with CTA is widely used to exclude stroke in patients with dizziness, although MRI has higher sensitivity. OBJECTIVE. The purpose of this article was to compare patients presenting to the emergency department (ED) with dizziness who undergo CT with CTA alone versus those who undergo MRI in terms of stroke-related management and outcomes. METHODS. This retrospective study included 1917 patients (mean age, 59.5 years; 776 men, 1141 women) presenting to the ED with dizziness from January 1, 2018, to December 31, 2021. A first propensity score matching analysis incorporated demographic characteristics, medical history, findings from the review of systems, physical examination findings, and symptoms to construct matched groups of patients discharged from the ED after undergoing head CT with head and neck CTA alone and patients who underwent brain MRI (with or without CT and CTA). Outcomes were compared. A second analysis compared matched patients discharged after CT with CTA alone and patients who underwent specialized abbreviated MRI using multiplanar high-resolution DWI for increased sensitivity for posterior circulation stroke. Sensitivity analyses were performed involving MRI examinations performed as the first or only neuroimaging examination and involving alternative matching and imputation techniques. RESULTS. In the first analysis (406 patients per group), patients who underwent MRI, compared with patients who underwent CT with CTA alone, showed greater frequency of critical neuroimaging results (10.1% vs 4.7%, p = .005), change in secondary stroke prevention medication (9.6% vs 3.2%, p = .001), and subsequent echocardiography evaluation (6.4% vs 1.0%, p < .001). In the second analysis (100 patients per group), patients who underwent specialized abbreviated MRI, compared with patients who underwent CT with CTA alone, showed greater frequency of critical neuroimaging results (10.0% vs 2.0%, p = .04), change in secondary stroke prevention medication (14.0% vs 1.0%, p = .001), and subsequent echocardiography evaluation (12.0% vs 2.0%, p = .01) and lower frequency of 90-day ED readmissions (12.0% vs 28.0%, p = .008). Sensitivity analyses showed qualitatively similar findings. CONCLUSION. A proportion of patients discharged after CT with CTA alone may have benefitted from alternative or additional evaluation by MRI (including MRI using a specialized abbreviated protocol). CLINICAL IMPACT. Use of MRI may motivate clinically impactful management changes in patients presenting with dizziness.

Clinical criteria to exclude acute vascular pathology on CT angiogram in patients with dizziness.

BACKGROUND: Patients presenting to the emergency department (ED) with dizziness may be imaged via CTA head and neck to detect acute vascular pathology including large vessel occlusion. We identify commonly documented clinical variables which could delineate dizzy patients with near zero risk of acute vascular abnormality on CTA. METHODS: We performed a cross-sectional analysis of adult ED encounters with chief complaint of dizziness and CTA head and neck imaging at three EDs between 1/1/2014-12/31/2017. A decision rule was derived to exclude acute vascular pathology tested on a separate validation cohort; sensitivity analysis was performed using dizzy "stroke code" presentations. RESULTS: Testing, validation, and sensitivity analysis cohorts were composed of 1072, 357, and 81 cases with 41, 6, and 12 instances of acute vascular pathology respectively. The decision rule had the following features: no past medical history of stroke, arterial dissection, or transient ischemic attack (including unexplained aphasia, incoordination, or ataxia); no history of coronary artery disease, diabetes, migraines, current/long-term smoker, and current/long-term anti-coagulation or anti-platelet medication use. In the derivation phase, the rule had a sensitivity of 100% (95% CI: 0.91-1.00), specificity of 59% (95% CI: 0.56-0.62), and negative predictive value of 100% (95% CI: 0.99-1.00). In the validation phase, the rule had a sensitivity of 100% (95% CI: 0.61-1.00), specificity of 53% (95% CI: 0.48-0.58), and negative predictive value of 100% (95% CI: 0.98-1.00). The rule performed similarly on dizzy stroke codes and was more sensitive/predictive than all NIHSS cut-offs. CTAs for dizziness might be avoidable in 52% (95% CI: 0.47-0.57) of cases. CONCLUSIONS: A collection of clinical factors may be able to "exclude" acute vascular pathology in up to half of patients imaged by CTA for dizziness. These findings require further development and prospective validation, though could improve the evaluation of dizzy patients in the ED.

Impact of Cannabis Use, Substance Use Disorders, and Psychiatric Diagnoses on COVID-19 Outcomes: A Retrospective Cohort Study.

Objective: While psychiatric disorders have been recognized as a risk factor for COVID-19 outcomes, the impact of substance use disorders (SUD) on COVID-19 outcomes has not, to date, been examined in a systematic manner. We examined the association between SUD (cannabis, cocaine, alcohol, opioid, and benzodiazepine) as well as psychiatric diagnoses (schizophrenia, mood disorders, anxiety disorders) and COVID-19 outcomes in a large, retrospective cohort study.Methods: COVID-19-positive patients admitted to a large health care system in the US between January and December 2020 were included in this study. SUD and psychiatric diagnoses were identified from urine toxicology reports and ICD-10 diagnosis codes in the electronic medical record, respectively. Multivariable logistic regression was performed controlling for potential confounders such as age, race, sex, smoking status, and medical comorbidities. COVID-19-relevant outcomes included mortality, need for intensive care unit (ICU) admission, need for ventilatory support, length of hospitalization, and number of hospitalizations.Results: Among COVID-19 patients (N = 6,291), those with SUD were more likely to require ICU admission (adjusted odds ratio [AOR] = 1.46, P = .003) and ventilatory support (AOR = 1.49, P = .01). The association between SUD and ICU admission was driven by alcohol use disorder (AUD), whereas that between SUD and ventilatory support was driven by both AUD and opioid use disorder (OUD). Patients with SUD were more likely to have a longer mean maximum length of hospitalization (11.32 vs 8.62 days, P < .0001) and a greater mean number of hospital admissions in 2020 (2.96 vs 2.33, P < .0001). These associations were significant for cannabis use disorder, AUD, OUD, and benzodiazepine use disorder. The association with greater number of admissions was also significant for cocaine use disorder. Patients with psychiatric diagnoses were also more likely to have a greater maximum length of hospitalization (11.93 vs 8.39 days, P < .0001) and hospital admissions (2.72 vs 2.31, P < .0001). These associations were significant for schizophrenia, mood disorders, and anxiety disorders.Conclusions: COVID-19 patients with SUD had greater likelihood of requiring critical interventions, such as ICU admission and ventilatory support. SUD and psychiatric diagnoses were also associated with a longer duration of hospitalization and greater number of hospital admissions. These findings identify COVID-19 patients with SUD and psychiatric comorbidities as a high-risk group.

Creating and Validating a Predictive Model for Suitability of Hospital at Home for Patients With Solid-Tumor Malignancies.

PURPOSE: Hospital at home (HaH) is a means of providing inpatient-level care at home. Selection of admissions potentially suitable for HaH in oncology is not well studied. We sought to create a predictive model for identifying admissions of patients with cancer, specifically solid-tumor malignancies, potentially suitable for HaH. METHODS: In this observational study, we analyzed admissions of patients with solid-tumor malignancies and unplanned admissions (January 1, 2015, to June 12, 2019) at an academic, urban cancer hospital. Potential suitability for HaH was the primary outcome. Admissions were considered potentially suitable if they did not involve escalation of care, rapid response evaluation, in-hospital death, telemetry, surgical procedure, consultation to a procedural service, advanced imaging, transfusion, restraints, and nasogastric tube placement. Admission source, patient demographics, vital signs, laboratory test results, comorbidities, admission and active cancer diagnoses, and recent hospital utilization were included as candidate variables in a multivariable logistic regression model. RESULTS: Of 3,322 admissions, 905 (27.2%) patients were potentially suitable for HaH. After variable selection in the derivation cohort (n = 1,097), thirteen factors predicted potential suitability: admission source; temperature and respiratory rate at presentation; hemoglobin; breast cancer, GI cancer, or malignancy of secondary or ill-defined origin; admission for genitourinary, musculoskeletal, or neurologic symptoms, intestinal obstruction or ileus, or evaluation of secondary malignancy; and emergency department visit in prior 90 days. Model c-statistics were 0.71 (95% CI, 0.68 to 0.75) and 0.63 (0.59 to 0.67) in the derivation and validation (n = 1,095) cohorts. CONCLUSION: Hospital admissions of patients potentially suitable for HaH may be identifiable using data available at admission.