Inspiring Active Citizenship in the Community from within the Classroom

This project presents an alternative to contemporary civic education courses and methods in an attempt to inspire students to become Active Citizens. Fighting against common sentiments surrounding contemporary politics such as divisiveness, polarization, apathy, and disenfranchisement, this project provides a framework for students to engage at the local level in an effective and genuine way

Preserving Creativity in Medicine

Imagination and creativity are essential traits that medicine, and medical insurers, must again learn to recognize and rewar

Traditional Cardiovascular Risk Factors as Predictors of Cardiovascular Events in the U.S. Astronaut Corps

Risk prediction equations from the Framingham Heart Study are commonly used to predict the absolute risk of myocardial infarction (MI) and coronary heart disease (CHD) related death. Predicting CHD-related events in the U.S. astronaut corps presents a monumental challenge, both because astronauts tend to live healthier lifestyles and because of the unique cardiovascular stressors associated with being trained for and participating in space flight. Traditional risk factors may not hold enough predictive power to provide a useful indicator of CHD risk in this unique population. It is important to be able to identify individuals who are at higher risk for CHD-related events so that appropriate preventive care can be provided. This is of special importance when planning long duration missions since the ability to provide advanced cardiac care and perform medical evacuation is limited. The medical regimen of the astronauts follows a strict set of clinical practice guidelines in an effort to ensure the best care. The purpose of this study was to evaluate the utility of the Framingham risk score (FRS), low-density lipoprotein (LDL) and high-density lipoprotein levels, blood pressure, and resting pulse as predictors of CHD-related death and MI in the astronaut corps, using Cox regression. Of these factors, only two, LDL and pulse at selection, were predictive of CHD events (HR(95% CI)=1.12 (1.00-1.25) and HR(95% CI)=1.70 (1.05-2.75) for every 5-unit increase in LDL and pulse, respectively). Since traditional CHD risk factors may lack the specificity to predict such outcomes in astronauts, the development of a new predictive model, using additional measures such as electron-beam computed tomography and carotid intima-media thickness ultrasound, is planned for the future

Effect of Lateral Sliding Calcaneus Osteotomy on Tarsal Tunnel Pressure

Background: Lateral sliding calcaneus osteotomies are common procedures to correct hindfoot varus deformities. Shifting the calcaneal tuberosity laterally (lateralization) can lead to tarsal tunnel pressure increase and tibial nerve palsy. The purpose of this cadaveric biomechanical study was to investigate the correlation of lateralization and pressure increase underneath the flexor retinaculum. Methods: The pressure in the tarsal tunnel of 12 Thiel-fixated human cadaveric lower legs was measured in different foot positions and varying degrees of calcaneal lateralization. Results: The mean pressure increased from plantarflexion (PF) to neutral position (NP) and from NP to hindfoot dorsiflexion (DF), and with increasing amounts of lateralization of the calcaneal tuberosity. The mean baseline pressure in PF was 1.5, in NP 2.2, and in DF 6.5 mmHg and increased to 8.1 in PF, 18.4 in NP, and 33.1 mmHg with 12 mm of lateralization. The release of the flexor retinaculum significantly lowered the pressure. Conclusion: Increasing pressures were found in the tarsal tunnel with increasing lateralization of the tuberosity and with both dorsiflexion and plantarflexion of the ankle. Clinical Relevance: A pre-emptive release of the flexor retinaculum for a lateralization of the calcaneal tuberosity of more than 8 mm should be considered, especially if specific patient risk factors are present. No tibial nerve palsy should be expected with 4 mm of lateralization

Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data

BACKGROUND: Accurate, timely and automated identification of patients at high risk for severe clinical deterioration using readily available clinical information in the electronic medical record (EMR) could inform health systems to target scarce resources and save lives. METHODS: We identified 7,466 patients admitted to a large, public, urban academic hospital between May 2009 and March 2010. An automated clinical prediction model for out of intensive care unit (ICU) cardiopulmonary arrest and unexpected death was created in the derivation sample (50% randomly selected from total cohort) using multivariable logistic regression. The automated model was then validated in the remaining 50% from the total cohort (validation sample). The primary outcome was a composite of resuscitation events, and death (RED). RED included cardiopulmonary arrest, acute respiratory compromise and unexpected death. Predictors were measured using data from the previous 24 hours. Candidate variables included vital signs, laboratory data, physician orders, medications, floor assignment, and the Modified Early Warning Score (MEWS), among other treatment variables. RESULTS: RED rates were 1.2% of patient-days for the total cohort. Fourteen variables were independent predictors of RED and included age, oxygenation, diastolic blood pressure, arterial blood gas and laboratory values, emergent orders, and assignment to a high risk floor. The automated model had excellent discrimination (c-statistic=0.85) and calibration and was more sensitive (51.6% and 42.2%) and specific (94.3% and 91.3%) than the MEWS alone. The automated model predicted RED 15.9 hours before they occurred and earlier than Rapid Response Team (RRT) activation (5.7 hours prior to an event, p=0.003) CONCLUSION: An automated model harnessing EMR data offers great potential for identifying RED and was superior to both a prior risk model and the human judgment-driven RRT

Persistent depression affects adherence to secondary prevention behaviors after acute coronary syndromes

Background: The persistence of depressive symptoms after hospitalization is a strong risk factor for mortality after acute coronary syndromes (ACS). Poor adherence to secondary prevention behaviors may be a mediator of the relationship between depression and increased mortality. Objective: To determine whether rates of adherence to risk reducing behaviors were affected by depressive status during hospitalization and 3 months later. Design: Prospective observational cohort study. Setting: Three university hospitals. Participants: Five hundred and sixty patients were enrolled within 7 days after ACS. Of these, 492 (88%) patients completed 3-month follow-up. Measurements: We used the Beck Depression Inventory (BDI) to assess depressive symptoms in the hospital and 3 months after discharge. We assessed adherence to 5 risk-reducing behaviors by patient self-report at 3 months. We used χ2 analysis to compare differences in adherence among 3 groups: persistently nondepressed (BDI<10 at hospitalization and 3 months); remittent depressed (BDI ≥10 at hospitalization; <10 at 3 months); and persistently depressed patients (BDI ≥10 at hospitalization and 3 months). Results: Compared with persistently nondepressed, persistently depressed patients reported lower rates of adherence to quitting smoking (adjusted odds ratio [OR] 0.23, 95% confidence interval [95% CI] 0.05 to 0.97), taking medications (adjusted OR 0.50, 95% CI 0.27 to 0.95), exercising (adjusted OR 0.57, 95% CI 0.34 to 0.95), and attending cardiac rehabilitation (adjusted OR 0.5, 95% CI 0.27 to 0.91). There were no significant differences between remittent depressed and persistently nondepressed patients. Conclusions: Persistently depressed patients were less likely to adhere to behaviors that reduce the risk of recurrent ACS. Differences in adherence to these behaviors may explain in part why depression predicts mortality after ACS. Key Words: cardiovascular diseases, depression, medication adherence, prevention, self car