Rationale and Design of Healthy at Home for COPD: an Integrated Remote Patient Monitoring and Virtual Pulmonary Rehabilitation Pilot Study

Chronic Obstructive Pulmonary Disease (COPD) is a common, costly, and morbid condition. Pulmonary rehabilitation, close monitoring, and early intervention during acute exacerbations of symptoms represent a comprehensive approach to improve outcomes, but the optimal means of delivering these services is uncertain. Logistical, financial, and social barriers to providing healthcare through face-to-face encounters, paired with recent developments in technology, have stimulated interest in exploring alternative models of care. The Healthy at Home study seeks to determine the feasibility of a multimodal, digitally enhanced intervention provided to participants with COPD longitudinally over six months. This paper details the recruitment, methods, and analysis plan for the study, which is recruiting 100 participants in its pilot phase. Participants were provided with several integrated services including a smartwatch to track physiological data, a study app to track symptoms and study instruments, access to a mobile integrated health program for acute clinical needs, and a virtual comprehensive pulmonary support service. Participants shared physiologic, demographic, and symptom reports, electronic health records, and claims data with the study team, facilitating a better understanding of their symptoms and potential care needs longitudinally. The Healthy at Home study seeks to develop a comprehensive digital phenotype of COPD by tracking and responding to multiple indices of disease behavior and facilitating early and nuanced responses to changes in participants' health status. This study is registered at Clinicaltrials.gov (NCT06000696).

Association of neighborhood-level sociodemographic factors with Direct-to-Consumer (DTC) distribution of COVID-19 rapid antigen tests in 5 US communities

BACKGROUND

Many interventions for widescale distribution of rapid antigen tests for COVID-19 have utilized online, direct-to-consumer (DTC) ordering systems; however, little is known about the sociodemographic characteristics of home-test users. We aimed to characterize the patterns of online orders for rapid antigen tests and determine geospatial and temporal associations with neighborhood characteristics and community incidence of COVID-19, respectively.

METHODS

This observational study analyzed online, DTC orders for rapid antigen test kits from beneficiaries of the Say Yes! Covid Test program from March to November 2021 in five communities: Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O'ahu, Hawaii; and Ann Arbor/Ypsilanti, Michigan. Using spatial autoregressive models, we assessed the geospatial associations of test kit distribution with Census block-level education, income, age, population density, and racial distribution and Census tract-level Social Vulnerability Index. Lag association analyses were used to measure the association between online rapid antigen kit orders and community-level COVID-19 incidence.

RESULTS

In total, 164,402 DTC test kits were ordered during the intervention. Distribution of tests at all sites were significantly geospatially clustered at the block-group level (Moran's I: p < 0.001); however, education, income, age, population density, race, and social vulnerability index were inconsistently associated with test orders across sites. In Michigan, Georgia, and Kentucky, there were strong associations between same-day COVID-19 incidence and test kit orders (Michigan: r = 0.89, Georgia: r = 0.85, Kentucky: r = 0.75). The incidence of COVID-19 during the current day and the previous 6-days increased current DTC orders by 9.0 (95% CI = 1.7, 16.3), 3.0 (95% CI = 1.3, 4.6), and 6.8 (95% CI = 3.4, 10.2) in Michigan, Georgia, and Kentucky, respectively. There was no same-day or 6-day lagged correlation between test kit orders and COVID-19 incidence in Indiana.

CONCLUSIONS

Our findings suggest that online ordering is not associated with geospatial clustering based on sociodemographic characteristics. Observed temporal preferences for DTC ordering can guide public health messaging around DTC testing programs.

Performance of Rapid Antigen Tests to Detect Symptomatic and Asymptomatic SARS-CoV-2 Infection : A Prospective Cohort Study

BACKGROUND

The performance of rapid antigen tests (Ag-RDTs) for screening asymptomatic and symptomatic persons for SARS-CoV-2 is not well established.

OBJECTIVE

To evaluate the performance of Ag-RDTs for detection of SARS-CoV-2 among symptomatic and asymptomatic participants.

DESIGN

This prospective cohort study enrolled participants between October 2021 and January 2022. Participants completed Ag-RDTs and reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 every 48 hours for 15 days.

SETTING

Participants were enrolled digitally throughout the mainland United States. They self-collected anterior nasal swabs for Ag-RDTs and RT-PCR testing. Nasal swabs for RT-PCR were shipped to a central laboratory, whereas Ag-RDTs were done at home.

PARTICIPANTS

Of 7361 participants in the study, 5353 who were asymptomatic and negative for SARS-CoV-2 on study day 1 were eligible. In total, 154 participants had at least 1 positive RT-PCR result.

MEASUREMENTS

The sensitivity of Ag-RDTs was measured on the basis of testing once (same-day), twice (after 48 hours), and thrice (after a total of 96 hours). The analysis was repeated for different days past index PCR positivity (DPIPPs) to approximate real-world scenarios where testing initiation may not always coincide with DPIPP 0. Results were stratified by symptom status.

RESULTS

Among 154 participants who tested positive for SARS-CoV-2, 97 were asymptomatic and 57 had symptoms at infection onset. Serial testing with Ag-RDTs twice 48 hours apart resulted in an aggregated sensitivity of 93.4% (95% CI, 90.4% to 95.9%) among symptomatic participants on DPIPPs 0 to 6. When singleton positive results were excluded, the aggregated sensitivity on DPIPPs 0 to 6 for 2-time serial testing among asymptomatic participants was lower at 62.7% (CI, 57.0% to 70.5%), but it improved to 79.0% (CI, 70.1% to 87.4%) with testing 3 times at 48-hour intervals.

LIMITATION

Participants tested every 48 hours; therefore, these data cannot support conclusions about serial testing intervals shorter than 48 hours.

CONCLUSION

The performance of Ag-RDTs was optimized when asymptomatic participants tested 3 times at 48-hour intervals and when symptomatic participants tested 2 times separated by 48 hours.

PRIMARY FUNDING SOURCE

National Institutes of Health RADx Tech program.

Design and implementation of a digital site-less clinical study of serial rapid antigen testing to identify asymptomatic SARS-CoV-2 infection

Background

Rapid antigen detection tests (Ag-RDT) for SARS-CoV-2 with emergency use authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals when used serially. We aim to describe a novel study design that was used to generate regulatory-quality data to evaluate the serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals.

Methods

This prospective cohort study used a siteless, digital approach to assess longitudinal performance of Ag-RDT. Individuals over 2 years old from across the USA with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study. Participants throughout the mainland USA were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days. Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported.

Key Results

A total of 7361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 US states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide.

Conclusions

The digital site-less approach employed in the "Test Us At Home" study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19 and can be adapted across research disciplines to optimize study enrollment and accessibility.

Performance of Rapid Antigen Tests Based on Symptom Onset and Close Contact Exposure: A secondary analysis from the Test Us At Home prospective cohort study

Background

The performance of rapid antigen tests for SARS-CoV-2 (Ag-RDT) in temporal relation to symptom onset or exposure is unknown, as is the impact of vaccination on this relationship.

Objective

To evaluate the performance of Ag-RDT compared with RT-PCR based on day after symptom onset or exposure in order to decide on 'when to test'.

Design Setting and Participants

The Test Us at Home study was a longitudinal cohort study that enrolled participants over 2 years old across the United States between October 18, 2021 and February 4, 2022. All participants were asked to conduct Ag-RDT and RT-PCR testing every 48 hours over a 15-day period. Participants with one or more symptoms during the study period were included in the Day Post Symptom Onset (DPSO) analyses, while those who reported a COVID-19 exposure were included in the Day Post Exposure (DPE) analysis.

Exposure

Participants were asked to self-report any symptoms or known exposures to SARS-CoV-2 every 48-hours, immediately prior to conducting Ag-RDT and RT-PCR testing. The first day a participant reported one or more symptoms was termed DPSO 0, and the day of exposure was DPE 0. Vaccination status was self-reported.

Main Outcome and Measures

Results of Ag-RDT were self-reported (positive, negative, or invalid) and RT-PCR results were analyzed by a central laboratory. Percent positivity of SARS-CoV-2 and sensitivity of Ag-RDT and RT-PCR by DPSO and DPE were stratified by vaccination status and calculated with 95% confidence intervals.

Results

A total of 7,361 participants enrolled in the study. Among them, 2,086 (28.3%) and 546 (7.4%) participants were eligible for the DPSO and DPE analyses, respectively. Unvaccinated participants were nearly twice as likely to test positive for SARS-CoV-2 than vaccinated participants in event of symptoms (PCR+: 27.6% vs 10.1%) or exposure (PCR+: 43.8% vs. 22.2%). The highest proportion of vaccinated and unvaccinated individuals tested positive on DPSO 2 and DPE 5-8. Performance of RT-PCR and Ag-RDT did not differ by vaccination status. Ag-RDT detected 78.0% (95% Confidence Interval: 72.56-82.61) of PCR-confirmed infections by DPSO 4. For exposed participants, Ag-RDT detected 84.9% (95% CI: 75.0-91.4) of PCR-confirmed infections by day five post-exposure (DPE 5).

Conclusions and Relevance

Performance of Ag-RDT and RT-PCR was highest on DPSO 0-2 and DPE 5 and did not differ by vaccination status. These data suggests that serial testing remains integral to enhancing the performance of Ag-RDT.

Performance of Rapid Antigen Tests to Detect Symptomatic and Asymptomatic SARS-CoV-2 Infection

Background

Performance of rapid antigen tests for SARS-CoV-2 (Ag-RDT) varies over the course of an infection, and their performance in screening for SARS-CoV-2 is not well established. We aimed to evaluate performance of Ag-RDT for detection of SARS-CoV-2 for symptomatic and asymptomatic participants.

Methods

Participants >2 years old across the United States enrolled in the study between October 2021 and February 2022. Participants completed Ag-RDT and molecular testing (RT-PCR) for SARS-CoV-2 every 48 hours for 15 days. This analysis was limited to participants who were asymptomatic and tested negative on their first day of study participation. Onset of infection was defined as the day of first positive RT-PCR result. Sensitivity of Ag-RDT was measured based on testing once, twice (after 48-hours), and thrice (after 96 hours). Analysis was repeated for different Days Post Index PCR Positivity (DPIPP) and stratified based on symptom-status.

Results

In total, 5,609 of 7,361 participants were eligible for this analysis. Among 154 participants who tested positive for SARS-CoV-2, 97 were asymptomatic and 57 had symptoms at infection onset. Serial testing with Ag-RDT twice 48-hours apart resulted in an aggregated sensitivity of 93.4% (95% CI: 89.1-96.1%) among symptomatic participants on DPIPP 0-6. Excluding singleton positives, aggregated sensitivity on DPIPP 0-6 for two-time serial-testing among asymptomatic participants was lower at 62.7% (54.7-70.0%) but improved to 79.0% (71.0-85.3%) with testing three times at 48-hour intervals.

Discussion

Performance of Ag-RDT was optimized when asymptomatic participants tested three-times at 48-hour intervals and when symptomatic participants tested two-times separated by 48-hours.

Finding a Needle in a Haystack: Design and Implementation of a Digital Site-less Clinical Study of Serial Rapid Antigen Testing to Identify Asymptomatic SARS-CoV-2 Infection

Background

Rapid antigen tests (Ag-RDT) for SARS-CoV-2 with Emergency Use Authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals when used serially.

Objective

To describe a novel study design to generate regulatory-quality data to evaluate serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals.

Design

Prospective cohort study using a decentralized approach. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days.

Setting

Participants throughout the mainland United States were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Ag-RDTs were completed at home, and molecular comparators were shipped to a central laboratory.

Participants

Individuals over 2 years old from across the U.S. with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study.

Measurements

Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported.

Key Results

A total of 7,361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 U.S. states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide.

Limitations

New, complex workflows required significant operational and data team support. Conclusions: The digital site-less approach employed in the 'Test Us At Home' study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19, and can be adapted across research disciplines to optimize study enrollment and accessibility.

Association of Mass Distribution of Rapid Antigen Tests and SARS-CoV-2 Prevalence: Results from NIH-CDC funded Say Yes! Covid Test program in Michigan

Importance

Wide-spread distribution of diagnostics is an integral part of the United States’ COVID-19 strategy; however, few studies have assessed the effectiveness of this intervention at reducing transmission of community COVID-19.

Objective

To assess the impact of the Say Yes! Covid Test (SYCT!) Michigan program, a population-based program that distributed 20,000 free rapid antigen tests within Ann Arbor and Ypsilanti, Michigan in June-August 2021, on community prevalence of SARS-CoV-2.

Design

This ecological study analyzed cases of SARS-CoV-2 from March to October 2021 reported to the Washtenaw County Health Department.

Setting

Washtenaw County, Michigan.

Participants

All residents of Washtenaw County.

Interventions

Community-wide distribution of 500,000 rapid antigen tests for SARS-CoV-2 to residents of Ann Arbor and Ypsilanti, Michigan. Each household was limited to one test kit containing 25 rapid antigen tests.

Main Outcome and Measures

Community prevalence of SARS-CoV-2, as measured through 7-day average cases, in Ann Arbor and Ypsilanti was compared to the rest of Washtenaw County. A generalized additive model was fitted with non-parametric trends for control and relative differences of trends in the pre-intervention, intervention, and post-intervention periods to compare intervention municipalities of Ann Arbor and Ypsilanti to the rest of Washtenaw County. Model results were used to calculate average cases prevented in the post-intervention period.

Results

In the post-intervention period, there were significantly lower standardized average cases in the intervention communities of Ann Arbor/Ypsilanti compared to the rest of Washtenaw County (p<0.001). The estimated standardized relative difference between Ann Arbor/Ypsilanti and the rest of Washtenaw County was -0.016 cases per day (95% CI: -0.020 to -0.013), implying that the intervention prevented 40 average cases per day two months into the post-intervention period if trends were consistent.

Conclusions and Relevance

Mass distribution of rapid antigen tests may be a useful mitigation strategy to combat community transmission of SARS-CoV-2, especially given the recent relaxation of social distancing and masking requirements.

Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative

OBJECTIVE

In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations.

MATERIALS AND METHODS

We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using 4 federated Common Data Models. N3C data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements.

RESULTS

Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source Common Data Model conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness, and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback.

DISCUSSION

We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for DQ improvement that will support improved research analytics locally and in aggregate.

CONCLUSION

By combining rapid, continual assessment of DQ with a large volume of multisite data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.

Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing.

Time-Course of Cause-Specific Hospital Admissions During Snowstorms: An Analysis of Electronic Medical Records From Major Hospitals in Boston, Massachusetts

With global climate change, more frequent severe snowstorms are expected; however, evidence regarding their health effects is very limited. We gathered detailed medical records on hospital admissions (n = 433,037 admissions) from the 4 largest hospitals in Boston, Massachusetts, during the winters of 2010-2015. We estimated the percentage increase in hospitalizations for cardiovascular and cold-related diseases, falls, and injuries on the day of and for 6 days after a day with low (0.05-5.0 inches), moderate (5.1-10.0 inches), or high (>10.0 inches) snowfall using distributed lag regression models. We found that cardiovascular disease admissions decreased by 32% on high snowfall days (relative risk (RR) = 0.68, 95% confidence interval (CI): 0.54, 0.85) but increased by 23% 2 days after (RR = 1.23, 95% CI: 1.01, 1.49); cold-related admissions increased by 3.7% on high snowfall days (RR = 3.7, 95% CI: 1.6, 8.6) and remained high for 5 days after; and admissions for falls increased by 18% on average in the 6 days after a moderate snowfall day (RR = 1.18, 95% CI: 1.09, 1.27). We did not find a higher risk of hospitalizations for injuries. To our knowledge, this is the first study in which the time course of hospitalizations during and immediately after snowfall days has been examined. These findings can be translated into interventions that prevent hospitalizations and protect public health during harsh winter conditions.

The critical components of an electronic care plan tool for primary care: an exploratory qualitative study

BACKGROUND

A critical need exists for effective electronic tools that facilitate multidisciplinary care for complex patients in patient-centered medical homes.Objective To identify the essential components of a primary care (PC) based electronic care plan (ECP) tool that facilitates coordination of care for complex patients.

METHOD

Three focus groups and nine semi-structured interviews were conducted at an academic PC practice in order to identify the ideal components of an ECP.

RESULTS

Critical components of an ECP identified included: 1) patient background information, including patient demographics, care team member designation and key patient contacts, 2) user- and patient-centric task management functionalities, 3) a summary of a patient's care needs linked to the responsible member of the care team and 4) integration with the electronic medical record. We then designed an ECP mockup incorporating these components.

CONCLUSION

Our investigation identified key principles that healthcare software developers can integrate into PC and patient-centered ECP tools.

Abstract 147: Do Billing Data Accurately Describe Causes Of Readmission After PCI? An Analysis Of A Large PCI Readmission Database

Introduction: Early readmission after PCI can be a useful performance measure, particularly if the reasons for readmission are related to patient management (e.g. angina, stent thrombosis or bleeding). Prior studies on readmission have used principal billing discharge diagnosis, but the validity of billing codes for this purpose is unclear.

Methods: PCI patients readmitted within 30 days of discharge at the Massachusetts General Hospital (January 2007-December 2011) and Brigham and Women’s Hospital (June 2009-December 2011), were identified, and their medical records reviewed by a cardiologist. For each readmission, the principal billing discharge diagnosis of the readmission was compared to the primary diagnosis of the readmission as determined by the chart review. The accuracy of billing discharge diagnoses for readmissions due to chest pain or other symptoms concerning for angina and vascular access complications was assessed.

Results: Of 9081 patients undergoing PCI and surviving to hospital discharge, 1011 (11.1%) were readmitted to the index hospital within 30 days. After excluding repeat readmissions, 894 readmissions were reviewed and of those, 754 (84.3%) could be matched to billing diagnoses. For each reason for readmission, corresponding billing diagnoses were diverse (Table 1).

The sensitivity and specificity of billing code 414.01 for a readmission for chest pain or other symptoms concerning for angina were 0.36 and 0.85, respectively. The sensitivity and specificity of billing code 997.2 (Peripheral vascular complications, not elsewhere classified) for a bleeding or vascular complication of PCI were 0.28 and 0.997, respectively.

Conclusions: The diversity of ICD-9 codes does not allow straightforward categorization of principal diagnoses of readmission from billing data. More complex algorithms need to be developed and validated to reliably derive reasons for readmission after PCI from billing data.

Abstract 71: Causes of 30-day Readmission Rates after Percutaneous Coronary Intervention - Lessons from Direct Chart Review

Background: Policymakers have designated 30-day readmission after percutaneous coronary intervention (PCI) as an important quality metric. Nevertheless, detailed descriptions of the causes and preventability of readmissions after PCI are lacking, leading some to question the usefulness of readmission as a quality metric. Determination of the causes of 30-day readmissions can help clarify the clinical validity of this measure and enable hospitals to develop strategies to reduce readmission rates.

Methods: We identified all readmissions after PCI at the Massachusetts General Hospital occurring within 30 days of discharge from 2007 - 2011. For patients with multiple readmissions, only the first readmission was included. Detailed patient medical record reviews were conducted to ascertain documented reasons for readmission.

Results: Among 5573 patients receiving PCI, we identified 651 readmissions within 30 days for medical record review representing 625 unique readmitted patients (11.2%). Of these, 241 readmissions (37.0%) were for the evaluation of chest pain, pressure, or other symptoms concerning for angina without an immediately obvious stent thrombosis. Of those, 21 required repeat PCI (8.7%) and 3 (1.2%) required CABG. Forty patients (6.1%) were readmitted for planned, staged procedures in the absence of new symptoms (“staged PCI”); 18 patients (2.8%) were readmitted non-urgently for peripheral vascular procedures or surgery unrelated to the PCI procedure; 24 patients (3.7%) were admitted for vascular or bleeding complications of the PCI procedure.

Conclusions: In this single center study, the largest proportion of readmissions after PCI is due to symptoms that prompt concern for angina, the overwhelming majority of which (90.0%) do not require repeat revascularization. Hospitals may be able to minimize 30-day readmission rates after PCI substantially by postponing non-urgent, non-coronary procedures after PCI. Transferring the evaluation of low-risk chest pain to the outpatient setting or to emergency department observation units could dramatically reduce 30 day readmission rates after PCI.

Table 1: Main reason for readmission (N = 651)

Chest pain or other symptoms concerning for angina - 238 (36.6%)

** Subset of those patients who received repeat PCI - 21 (3.2%)

Staged PCI - 40 (6.1%)

Stent thrombosis - 19 (2.9%)

Sudden cardiac death - 4 (0.6%)

Elective peripheral procedure or surgery not related to PCI - 18 (2.8%)

Elective CABG - 14 (2.2%)

** Subset of those patients with failed PCI - 10 (1.5%)

** Subset of those patients with staged CABG after PCI - 4 (0.6%)

Vascular/bleeding complication of PCI - 24 (3.7%)

Atrial fibrillation - 11 (1.7%)

Congestive heart failure - 39 (6.0%)

Cholecystitis or cholangitis - 7 (1.1%)

Gastrointestinal hemorrhage - 25 (3.8%)

Venous thromboembolism - 6 (0.9%)

Pneumonia - 10 (1.5%)

Urinary tract infection - 9 (1.4%)

Improving diabetes population management efficiency with an informatics solution

Despite intensive resource use for diabetes management in the U.S., our care continues to fall short of evidence-based goals, partly due to system inefficiencies. Diabetes registries are increasingly being utilized as a critical tool for population level disease management by providing real-time data. Since the successful adoption of a diabetes registry depends on how well it integrates with disease management workflows, we optimized our current diabetes management workflow and designed our registry application around it.

Web-based residency training program reviews influence applicants who use them

Scutwork.com is an online, peer-based residency review system. We report preliminary results of an online survey designed to investigate the impact of Scutwork on the residency application process. Overall, 68% of respondents believe that the reviews influenced their decision-making and 91% would use Scutwork again. These results and others reported below suggest that Scutwork may play a significant role in the residency selection process.

Cell-surface protein disulfide isomerase catalyzes transnitrosation and regulates intracellular transfer of nitric oxide

Since thiols can undergo nitrosation and the cell membrane is rich in thiol-containing proteins, we considered the possibility that membrane surface thiols may regulate cellular entry of NO. Recently, protein disulfide isomerase (PDI), a protein that catalyzes thio-disulfide exchange reactions, has been found on the cell-surface membrane. We hypothesized that cell-surface PDI reacts with NO, catalyzes S-nitrosation reactions, and facilitates NO transfer from the extracellular to intracellular compartment. We observed that PDI catalyzes the S-nitrosothiol-dependent oxidation of the heme group of myoglobin (15-fold increase in the rate of oxidation compared with control), and that NO reduces the activity of PDI by 73.1 +/- 21.8% (P < 0.005). To assess the role of PDI in the cellular action of NO, we inhibited human erythroleukemia (HEL) cell-surface PDI expression using an antisense phosphorothioate oligodeoxynucleotide directed against PDI mRNA. This oligodeoxynucleotide decreased cell-surface PDI content by 74.1 +/- 9.3% and PDI folding activity by 46.6 +/- 3.5% compared with untreated or "scrambled" phosphorothioate oligodeoxynucleotide-treated cells (P < 0.0001). This decrease in cell-surface PDI was associated with a significant decrease in cyclic guanosine monophosphate (cGMP) generation after S-nitrosothiol exposure (65.4 +/- 26.7% reduction compared with control; P < 0.05), with no effect on cyclic adenosine monophosphate (cAMP) generation after prostaglandin E1 exposure. These data demonstrate that the cellular entry of NO involves a transnitrosation mechanism catalyzed by cell-surface PDI. These observations suggest a unique mechanism by which extracellular NO gains access to the intracellular environment.