Study protocol for the Innovative Support for Patients with SARS-COV-2 Infections Registry (INSPIRE): A longitudinal study of the medium and long-term sequelae of SARS-CoV-2 infection.

BACKGROUND: Reports on medium and long-term sequelae of SARS-CoV-2 infections largely lack quantification of incidence and relative risk. We describe the rationale and methods of the Innovative Support for Patients with SARS-CoV-2 Registry (INSPIRE) that combines patient-reported outcomes with data from digital health records to understand predictors and impacts of SARS-CoV-2 infection. METHODS: INSPIRE is a prospective, multicenter, longitudinal study of individuals with symptoms of SARS-CoV-2 infection in eight regions across the US. Adults are eligible for enrollment if they are fluent in English or Spanish, reported symptoms suggestive of acute SARS-CoV-2 infection, and if they are within 42 days of having a SARS-CoV-2 viral test (i.e., nucleic acid amplification test or antigen test), regardless of test results. Recruitment occurs in-person, by phone or email, and through online advertisement. A secure online platform is used to facilitate the collation of consent-related materials, digital health records, and responses to self-administered surveys. Participants are followed for up to 18 months, with patient-reported outcomes collected every three months via survey and linked to concurrent digital health data; follow-up includes no in-person involvement. Our planned enrollment is 4,800 participants, including 2,400 SARS-CoV-2 positive and 2,400 SARS-CoV-2 negative participants (as a concurrent comparison group). These data will allow assessment of longitudinal outcomes from SARS-CoV-2 infection and comparison of the relative risk of outcomes in individuals with and without infection. Patient-reported outcomes include self-reported health function and status, as well as clinical outcomes including health system encounters and new diagnoses. RESULTS: Participating sites obtained institutional review board approval. Enrollment and follow-up are ongoing. CONCLUSIONS: This study will characterize medium and long-term sequelae of SARS-CoV-2 infection among a diverse population, predictors of sequelae, and their relative risk compared to persons with similar symptomatology but without SARS-CoV-2 infection. These data may inform clinical interventions for individuals with sequelae of SARS-CoV-2 infection.

Characterizing non-heroin opioid overdoses using electronic health records.

INTRODUCTION: The opioid epidemic is a modern public health emergency. Common interventions to alleviate the opioid epidemic aim to discourage excessive prescription of opioids. However, these methods often take place over large municipal areas (state-level) and may fail to address the diversity that exists within each opioid case (individual-level). An intervention to combat the opioid epidemic that takes place at the individual-level would be preferable. METHODS: This research leverages computational tools and methods to characterize the opioid epidemic at the individual-level using the electronic health record data from a large, academic medical center. To better understand the characteristics of patients with opioid use disorder (OUD) we leveraged a self-controlled analysis to compare the healthcare encounters before and after an individual's first overdose event recorded within the data. We further contrast these patients with matched, non-OUD controls to demonstrate the unique qualities of the OUD cohort. RESULTS: Our research confirms that the rate of opioid overdoses in our hospital significantly increased between 2006 and 2015 (P < 0.001), at an average rate of 9% per year. We further found that the period just prior to the first overdose is marked by conditions of pain or malignancy, which may suggest that overdose stems from pharmaceutical opioids prescribed for these conditions. CONCLUSIONS: Informatics-based methodologies, like those presented here, may play a role in better understanding those individuals who suffer from opioid dependency and overdose, and may lead to future research and interventions that could successfully prevent morbidity and mortality associated with this epidemic.

Significant but reasonable radiation exposure from computed tomography-related medical imaging in the ICU.

Admission to an intensive care unit (ICU) is associated with increased medical imaging and radiation exposure, yet few studies have estimated the risk of cancer associated with these examinations. The purpose of this study was to review computed tomography (CT) scans performed on patients admitted to two urban academic ICUs, predict their radiation exposure, and calculate their estimated lifetime attributable risk of cancer (LAR). An electronic chart review was performed on all CT scans performed between January 2007 and December 2011. The estimated effective dose of radiation was calculated for each CT, and the LAR for each patient was predicted. Mean radiation exposure was 22.2 ± 25.0 mSv with a mean LAR of 0.1 ± 0.2 % and a median of 0.6 % with a range of <0.001 to 3.4 %. Our cohort received radiation doses higher than recommended by guidelines; however, the critical nature of their admission may have warranted these imaging studies. Estimated risk of cancer in this population was overall low.

Radiation exposure among patients with the highest CT scan utilization in the emergency department.

The risk of cancer from computed tomography (CT) scan radiation is a rising concern in the medical field. Our objectives were to determine how many patients received more than ten CT scans in an academic emergency department (ED) over the course of 7 years and to quantify their radiation exposure and lifetime attributable risk of cancer. An electronic chart review was performed at our urban academic institution with an annual census of 110,000 patients. All patients who underwent a CT scan performed during ED management between the dates of January 2001 and December 2007 were identified. Specific predetermined data elements (e.g., subject demographics, type of CT scan) were extracted by two researchers blinded to hypothesis, using a preformatted data form. After identifying patients with more than ten CTs performed during the study period, radiation exposure was calculated based on accepted and reported radiation doses for the respective anatomic CTs, and lifetime attributable cancer risk was calculated based on the seventh report of the Biological Effects of Ionizing Radiation (BEIR VII) projections. Over the 7-year study period, 24,393 patients received 34,671 CT scans. The vast majority of patients (17,909) received a single CT. Twenty-six (0.1 %) patients received more than ten CTs totaling 374 scans with an average radiation exposure of 83.4 mSv. The maximum lifetime attributable risk for any individual in this cohort was 1.7 % above the baseline cancer risk. Among those undergoing CT imaging in our ED, high-exposure patients (greater than ten scans) constituted a significant minority, while more than one in four patients underwent more than one CT scan during the study period. While the presumed overall risk of radiation-induced cancer continues to be low, it is important for the emergency physician to use clinical knowledge as well as concern for the patient when utilizing radiographic imaging. Increasing attributable cancer risk may have important public health implications in the future, regardless of the low individual risk.