397. Impact of School Opening Model on Cases of SARS-CoV-2 in Surrounding Communities: A Nationwide, Retrospective Cohort Study

Abstract Background Early in the COVID-19 pandemic, elementary and secondary schools were closed. There was variation in school opening mode (traditional, hybrid, remote) in fall 2020.The aim of this national, retrospective cohort study is to evaluate the impact of in-person learning on community incidence of SARS-CoV-2 and COVID-19-related deaths. Methods Data were extracted from several data sources. School opening mode was collected from the Burbio school tracker, which tracks school openings in a sample of school districts across the US. Incidence of SARS-CoV-2 and COVID-19 related deaths were obtained from the CDC. Data on community-level SARS-CoV-2 mitigation measures were obtained from the Oxford University COVID-19 Government Response Tracker. The effect of school mode on SARS-CoV-2 cases and deaths/100,000 during the 12-weeks following the start of school was estimated using a log-linear model with state, week, and state-week fixed effects. Models were stratified by 9 US Census divisions and adjusted for variables determined a priori to be potentially associated with the outcome. Results 519 US counties were included (Figure 1); mean cases of COVID-19 were increasing across all regions during the weeks following the start of school, regardless of school mode. Adjusted absolute differences in COVID-19 cases in counties with hybrid and traditional school opening modes relative to fully remote learning models are presented in Figure 2. In the Northeast and Midwest regions of the country, COVID-19 case rates were not statistically different between different school modes. However, in the South and West regions, there was a statistically significant increase in cases per week among counties that opened in an in-person relative to remote learning model, ranging from 17.1 (95% CI: 0.3-33.8) to 24.4 (95% CI: 7.3-41.5) in the South and from 19.0 (95% CI: 8.8-29.3) to 109.2 (95% CI: 50.4-168.0) in the West. There was no impact of school opening mode on COVID-19-related deaths. Figure 1. Map with distribution of counties and school opening mode across the United States Figure 2. Impact of school opening mode on subsequent cases of SARS-CoV-2, stratified by region. Conclusion Impact of school mode on community case-rates of SARS-CoV-2 varied across the US. In some areas of the country, traditional school mode was associated with increases in case rates relative to virtual while there were no differences in other regions. Disclosures All Authors: No reported disclosures

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Association between Race and Cancer-Related Mortality among Patients with Colorectal Cancer in the United States: A Retrospective Cohort Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16020240 ◽

2019 ◽

Vol 16 (2) ◽

pp. 240 ◽

Cited By ~ 6

Author(s):

Sayaf Alshareef ◽

Nasser Alsobaie ◽

Salman Aldeheshi ◽

Sultan Alturki ◽

Juan Zevallos ◽

...

Keyword(s):

Colorectal Cancer ◽

United States ◽

Cohort Study ◽

American Indian ◽

Alaska Native ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

The United States ◽

The Us ◽

Related Mortality

Colorectal cancer (CRC) is the third most common cause of mortality in the United States (US). Differences in CRC mortality according to race have been extensively studied; however, much more understanding with regard to tumor characteristics’ effect on mortality is needed. The objective was to investigate the association between race and mortality among CRC patients in the US during 2007–2014. A retrospective cohort study using data from the Surveillance, Epidemiology, and End Results (SEER) Program, which collects cancer statistics through selected population-based cancer registries during in the US, was conducted. The outcome variable was CRC-related mortality in adult patients (≥18 years old) during 2007–2014. The independent variable was race of white, black, Asian/Pacific Islander (API), and American Indian/Alaska Native (others). The covariates were, age, sex, marital status, health insurance, tumor stage at diagnosis, and tumor size and grade. Bivariate analysis was performed to identify possible confounders (chi-square tests). Unadjusted and adjusted logistic regression models were used to study the association between race and CRC-specific mortality. The final number of participants consisted of 70,392 patients. Blacks had a 32% higher risk of death compared to whites (adjusted odds ratio (OR) 1.32; 95% confidence interval (CI) 1.22–1.43). Corresponding OR for others were 1.41 (95% CI 1.10–1.84). API had nonsignificant adjusted odds of mortality compared to whites (0.95; 95% CI 0.87–1.03). In conclusion, we observed a significant increased risk of mortality in black and American Indian/Alaska Native patients with CRC compared to white patients.

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Overall survival based on oncologist density in the United States: A retrospective cohort study

PLoS ONE ◽

10.1371/journal.pone.0250894 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0250894

Author(s):

Sudeep K. Siddappa Malleshappa ◽

Smith Giri ◽

Smit Patel ◽

Tapan Mehta ◽

Leonard Appleman ◽

...

Keyword(s):

Primary Care ◽

Overall Survival ◽

Cohort Study ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Health Care Services ◽

The United States ◽

Rank Test ◽

Care Services ◽

The Impact

Medically underserved areas (MUA) or health professional shortage areas (HPSA) designations are based on primary care health services availability. These designations are used in recruiting international medical graduates (IMGs) trained in primary care or subspecialty (e.g., oncology) to areas of need. Whether the MUA/HPSA designation correlates with Oncologist Density (OD) and supports IMG oncologists’ recruitment to areas of need is unknown. We evaluated the concordance of OD with the designation of MUAs/HPSAs and evaluated the impact of OD and MUA/HPSA status on overall survival. We conducted a retrospective cohort study of patients diagnosed with hematological malignancies or metastatic solid tumors in 2011 from the Surveillance Epidemiology and End Results (SEER) database. SEER was linked to the American Medical Association Masterfile to calculate OD, defined as the number of oncologists per 100,000 population at the county level. We calculated the proportion of counties with MUA or HPSA designation for each OD category. Overall survival was estimated using the Kaplan-Meier method and compared between the OD category using a log-rank test. We identified 68,699 adult patients with hematologic malignancies or metastatic solid cancers in 609 counties. The proportion of MUA/HPSA designation was similar across counties categorized by OD (93.2%, 95.4%, 90.3%, and 91.7% in counties with <2.9, 2.9–6.5, 6.5–8.4 and >8.4 oncologists per 100K population, p = 0.7). Patients’ median survival in counties with the lowest OD was significantly lower compared to counties with the highest OD (8 vs. 11 months, p<0.0001). The difference remained statistically significant in multivariate and subgroup analysis. MUA/HPSA status was not associated with survival (HR 1.03, 95%CI 0.97–1.09, p = 0.3). MUA/HPSA designation based on primary care services is not concordant with OD. Patients in counties with lower OD correlated with inferior survival. Federal programs designed to recruit physicians in high-need areas should consider the availability of health care services beyond primary care.

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Urine Culture on Admission Impacts Antibiotic Use and Length of Stay: A Retrospective Cohort Study

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2018.55 ◽

2018 ◽

Vol 39 (5) ◽

pp. 547-554 ◽

Cited By ~ 5

Author(s):

Molly J. Horstman ◽

Andrew M. Spiegelman ◽

Aanand D. Naik ◽

Barbara W. Trautner

Keyword(s):

Cohort Study ◽

Length Of Stay ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Urine Culture ◽

Antibiotic Use ◽

The United States ◽

Targeted Interventions ◽

Bed Days ◽

The Impact

OBJECTIVETo examine the impact of urine culture testing on day 1 of admission on inpatient antibiotic use and hospital length of stay (LOS).DESIGNWe performed a retrospective cohort study using a national dataset from 2009 to 2014.SETTINGThe study used data from 230 hospitals in the United States.PARTICIPANTSAdmissions for adults 18 years and older were included in this study. Hospitalizations were matched with coarsened exact matching by facility, patient age, gender, Medicare severity-diagnosis related group (MS-DRG), and 3 measures of disease severity.METHODSA multilevel Poisson model and a multilevel linear regression model were used to determine the impact of an admission urine culture on inpatient antibiotic use and LOS.RESULTSMatching produced a cohort of 88,481 patients (n=41,070 with a culture on day 1, n=47,411 without a culture). A urine culture on admission led to an increase in days of inpatient antibiotic use (incidence rate ratio, 1.26; P<.001) and resulted in an additional 36,607 days of inpatient antibiotic treatment. Urine culture on admission resulted in a 2.1% increase in LOS (P=.004). The predicted difference in bed days of care between admissions with and without a urine culture resulted in 6,071 additional bed days of care. The impact of urine culture testing varied by admitting diagnosis.CONCLUSIONSPatients with a urine culture sent on day 1 of hospital admission receive more days of antibiotics and have a longer hospital stay than patients who do not have a urine culture. Targeted interventions may reduce the potential harms associated with low-yield urine cultures on day 1.Infect Control Hosp Epidemiol 2018;39:547–554

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