Explore the vast range of titles available.

ABSTRACT The lack of effective and consistent research mentorship and research mentor training in both undergraduate medical education (UME) and graduate medical education (GME) is a critical constraint on the development of innovative and high quality medical education research. Clinical research mentors are often not familiar with the nuances and context of conducting education research. Clinician-educators, meanwhile, often lack the skills in developing and conducting rigorous research. Mentors who are not prepared to articulate potential scholarship pathways for their mentees risk limiting the mentee’s progress in early stages of their career. In fact, the relative paucity of experienced medical education research mentors arguably contributes to the perpetuation of a cycle leading to fewer well-trained researchers in medical education, a lack of high quality medical education research, and relative stagnation in medical education innovation. There is a path forward, however. Integration of doctoral-level educators, structured inter-departmental efforts, and external mentorship provide opportunities for faculty to gain traction in their medical education research efforts. An investment in medical education research mentors will ensure rigorous research for high quality innovation in medical education and patient care.

Although acute kidney injury (AKI) is common in heart failure, yet the impact of the onset, timing, and duration of AKI on short-term outcomes is not well studied. AKI was defined as an increase in serum creatinine SCr of ≥0.3 mg/dl or 1.5 times relative to the admission and further categorized as transient AKI (T-AKI: SCr returning to within 10% of baseline); sustained AKI (S-AKI: those with at least 72 hours of hospital stay and did not meet T-AKI); and unknown duration AKI (U-AKI: those with less than 72 hours stay and did not meet T-AKI). Reference category was no AKI (stable or <0.3 mg/dl change in SCr). The main outcome was 30-day all-cause hospital readmission. Unadjusted and adjusted association between AKI category of interest and main outcome was represented as percent and relative risks with 95% CIs. Statistical significance was set at an alpha of 0.05. From the Cerner Health Facts sample, 14,017 of 22,059 available subjects met the eligibility criteria. Approximately, 19.2% of our sample met the primary outcome. Compared with no AKI (readmission rate of 17.7%; 95% CI 16.4% to 18.9%), the adjusted rate of readmission was highest in patients with S-AKI (22.8%, 95% CI 20.8% to 24.8%; p <0.001), followed by 20.2% (95% CI 17.5% to 22.8%; p = 0.05) in T-AKI patients. Compared with no AKI, the adjusted relative risk of 30-day readmission was 1.29 (95% CI 1.17 to 1.42), 1.14 (95% CI 1.00 to 1.31), and 1.12 (95% CI, 1.01 to 1.26) in S-AKI, T-AKI, and U-AKI, respectively. In conclusion, both sustained AKI and patients with transient elevation still remain at a higher risk of readmission within 30 days. Future studies should focus on examining process-of-care after discharge in patients with different patterns of AKI.

Chest pain is the second most common chief complaint for patients undergoing evaluation in emergency departments (ED) in the United States. The American Heart Association recommends immediate physician interpretation of all electrocardiograms (ECG) performed for adults with chest pain within 10 minutes to evaluate for the finding of ST-elevation myocardial infarction (STEMI). The ECG machines provide computerized interpretation of each ECG, potentially obviating the need for immediate physician analysis; however, the reliability of computer-interpreted findings of \"normal\" or \"otherwise normal\" ECG to rule out STEMI requiring immediate intervention in the ED is unknown. We performed a prospective cohort analysis of 2,275 ECGs performed in triage in the adult ED of a single academic medical center, comparing the computerized interpretations of \"normal\" and \"otherwise normal\" ECGs to those of attending cardiologists. ECGs were obtained with a GE MAC 5500 machine and interpreted using Marquette 12SL. In our study population, a triage ECG with a computerized interpretation of \"normal\" or \"otherwise normal\" ECG had a negative predictive value of 100% for STEMI (one-sided, lower 97.5% confidence interval 99.6%). None of the studied patients with these ECG interpretations had a final diagnosis of STEMI, acute coronary syndrome, or other diagnosis requiring emergent cardiac catheterization. In our study population, ECG machine interpretations of \"normal\" or \"otherwise normal\" ECG excluded findings of STEMI. The ECGs with these computerized interpretations could safely wait for physician interpretation until the time of patient evaluation without delaying an acute STEMI diagnosis.

Delays in patient flow in the emergency department (ED) result in patients leaving without being seen (LWBS). This compromises patient experience and quality of care. Our primary goal was to develop a predictive model by evaluating associations between patients LWBS and ED process measures and patient characteristics. This was a cross-sectional study in a 95,000 annual visit adult ED comparing patients LWBS, with controls. Data were drawn from four seasonally adjusted four-week periods (30,679 total visits). Process measures included 1) arrivals per hour; 2) \"door-to-provider\" time; and the numbers of 3) patients in the waiting room; 4) boarding ED patients waiting for an inpatient bed; 5) providers and nurses (RN); and 6) patients per RN. Patient characteristics collected included 1) age; 2) gender; 3) race/ethnicity; 4) arrival mode (walk-in or via emergency medical services [EMS]); and 5) acuity based on Emergency Severity Index (ESI). Univariable analyses included t-tests and Pearson's chi-square tests. We split the data randomly into derivation and validation cohorts. We used backward selection to develop the final derivation model, and factors with a p-value ≤ 0.05 were retained. Estimates were applied to the validation cohort and measures of discrimination (receiver operating characteristic) and model fit were assessed. In the final model, the odds of LWBS increased with the number of patients in the waiting room (odds ratio [OR] 1.05; 95% confidence interval [CI], 1.03 to 1.06); number of boarding patients (OR 1.02; 95% CI, 1.01 to 1.03); arrival rate (OR 1.04; 95% CI, 1.02 to 1.05) and longer \"door-to-provider\" times (test of linear trend in the adjusted OR was p = 0.002). Patient characteristics associated with LWBS included younger age (OR 0.98; 95% CI, 0.98 to 0.99), and lower acuity (higher ESI category) (OR 2.01; 95% CI, 1.84 to 2.20). Arrival by EMS was inversely associated with LWBS (OR 0.29; 0.23 to 0.36). The area under the curve for the final model in the validation cohort was 0.85 (95% CI, 0.84 to 0.86). There was good agreement between the observed and predicted risk. Arrival rate, \"door-to-provider time,\" and the numbers of patients in the waiting room and ED boarders are all associated with patients LWBS.

Introduction: Adult epiglottitis is a disease process distinct from pediatric epiglottitis in microbiology, presentation, and clinical course. While traditionally considered more indolent and benign than in children, adult epiglottitis remains a cause of acute airway compromise with a mortality rate from 1-20%. Our objective was to characterize the disease course and evaluate the rate and type of airway management in this population at a tertiary, academic referral center. Methods: We conducted a retrospective chart review of all adult patients (age ≥ 18) who were definitively diagnosed with infectious “epiglottitis,” “supraglottitis,” or “epiglottic abscess” by direct or indirect laryngoscopy during a nine-year period. Double data abstraction and a standardized data collection form were used to assess patient demographic characteristics, presenting features, and clinical course. The primary outcome was airway intervention by intubation, cricothyroidotomy, or tracheostomy, and the secondary outcome was mortality related to the disease. Results: Seventy patients met inclusion criteria. The mean age was 50.2 years (standard deviation ± 16.7), 60% of the patients were male, and 14.3% were diabetic. Fifty percent had symptoms that were present for ≥ 48 hours; 38.6% had voice changes, 13.1% had stridor, 12.9% had fever, 45.7% had odynophagia, and 47.1% had dysphagia noted in the ED. Twelve patients (17.1%) received an acute airway intervention including three who underwent emergent cricothyroidotomy, and one who had a tracheostomy. Two patients died and one suffered anoxic brain injury related to complications following difficult airway management. Conclusion: In this case series the majority of patients (82.9%) did not require airway intervention, but a third of those requiring intervention (5.7% of total) had a surgical airway performed with two deaths and one anoxic brain injury. Clinicians must remain vigilant to identify signs of impending airway compromise in acute adult epiglottitis and be familiar with difficult and failed airway algorithms to prevent morbidity and mortality in these patients.

Prophylactic indomethacin may decrease Severe Intraventricular Hemorrhage (SIVH). Our goal was to develop a predictive model for SIVH using parameters available by six hours of age. De-identified data for preterm infants born ≤ 34 weeks gestational age was abstracted from Vermont Oxford Network database. Using clinical variables available by 6 hrs of age the model was developed and validated. Statistical methods were used to evaluate the ability of the model to discriminate infants with and without SIVH and, to compare observed and predicted risk. The model achieved excellent discrimination as indicated by ROC curve of 0·85. A good agreement was noted between observed and predicted risk (HLtest: p = 0·22). Application of the model to patients receiving indomethacin suggests a benefit at the highest risk levels. We have developed a valid predictive model for predicting SIVH as well as shown that exposure to indomethacin decreases the incidence of SIVH overall.

Background Approximately 2 million patients present to emergency departments in the USA annually with signs and symptoms of ureterolithiasis (or renal colic , the pain from an obstructing kidney stone). Both ultrasound and CT scan can be used for diagnosis, but the vast majority of patients receive a CT scan. Diagnostic pathways utilizing ultrasound have been shown to decrease radiation exposure to patients but are potentially less accurate. Because of these and other trade-offs, this decision has been proposed as appropriate for Shared Decision-Making (SDM), where clinicians and patients discuss clinical options and their consequences and arrive at a decision together. We developed a decision aid to facilitate SDM in this scenario. The objective of this study is to determine the effects of this decision aid, as compared to usual care, on patient knowledge, radiation exposure, engagement, safety, and healthcare utilization. Methods This is the protocol for an adaptive randomized controlled trial to determine the effects of the intervention—a decision aid (“Kidney Stone Choice”)—on patient-centered outcomes, compared with usual care. Patients age 18–55 presenting to the emergency department with signs and symptoms consistent with acute uncomplicated ureterolithiasis will be consecutively enrolled and randomized. Participants will be blinded to group allocation. We will collect outcomes related to patient knowledge, radiation exposure, trust in physician, safety, and downstream healthcare utilization. Discussion We hypothesize that this study will demonstrate that “Kidney Stone Choice,” the decision aid created for this scenario, improves patient knowledge and decreases exposure to ionizing radiation. The adaptive design of this study will allow us to identify issues with fidelity and feasibility and subsequently evaluate the intervention for efficacy. Trial registration ClinicalTrials.gov NCT04234035 . Registered on 21 January 2020 – Retrospectively Registered

Purpose: To determine the impact of booster COVID-19 vaccination on SARS-CoV-2 symptoms. Background: The Omicron surge of infections provided an opportunity to evaluate symptoms in relation to booster receipt. Methods: At a US medical college, the number, type, and duration of symptoms were evaluated for 476 students or employees, factoring in days between last vaccination and SARS-CoV-2 diagnosis. Results: Compared with vaccinated non-boosted individuals, boosted individuals reported a significantly higher frequency of nasal congestion (57.9% vs. 44.4%, p = 0.018) and nasal congestion and/or sore throat (77.2% vs. 62.0%, p = 0.003); in contrast, the frequency of body/muscle aches was significantly less among boosted individuals (22.1% vs. 32.4%, p = 0.038). With each one week increase in time since booster receipt, the probability of fever increased significantly by 4.4% (OR 1.044, 95% CI 1.01, 1.07, p = 0.001), and the probability of cough increased significantly by 4.8% (OR 1.048, 95% CI 1.01, 10.8, p= 0.010). Conclusions: Within a medical college population, during the first 7 months of the Omicron surge of infections, compared with vaccinated non-boosted individuals, boosted individuals significantly more often reported the following: nasal congestion as well as nasal congestion and/or sore throat. In contrast, body/muscle aches were reported significantly less often. The rates of fever and cough each significantly increased as time since booster dose receipt increased. These data suggest that having had a booster vaccination, as well the timing of receiving it, impacts the clinical manifestations of breakthrough SARS-CoV-2 infections. Additional studies are needed to precisely define SARS-CoV-2 symptoms in relation to booster vaccinations.

Spinal epidural abscess (SEA), a highly morbid and potentially lethal deep tissue infection of the central nervous system has more than tripled in incidence over the past decade. Early recognition at the point of initial clinical presentation may prevent irreversible neurologic injury or other serious, adverse outcomes. To facilitate early recognition of SEA, we developed a predictive scoring model. Using data from a 10-year, retrospective, case-control study of adults presenting for care at a tertiary-care, regional, academic medical center, we used the Integrated Discrimination Improvement Index (IDI) to identify candidate discriminators and created a multivariable logistic regression model, refined based on p-value significance. We selected a cutpoint that optimized sensitivity and specificity. The final multivariable logistic regression model based on five characteristics -patient age, fever and/or rigor, antimicrobial use within 30 days, back/neck pain, and injection drug use - shows excellent discrimination (AUC 0.88 [95% confidence interval {0.84, 0.92}]). We used the model's β coefficients to develop a scoring system in which a cutpoint of six correctly identifies cases 89% of the time. Bootstrapped validation measures suggest this model will perform well across samples drawn from this population. Our predictive scoring model appears to reliably discriminate patients who require emergent spinal imaging upon clinical presentation to rule out SEA and should be used in conjunction with clinical judgment.