A Pilot Feasibility Study of an Online Youth Tobacco Survey Administration among High School Students.

The COVID-19 pandemic restrictions forced many schools to shift to remote or hybrid learning, disrupting surveillance systems such as the New Jersey Youth Tobacco Survey, traditionally administered in schools by paper and pencil. In spring 2021, we conducted a feasibility study among a convenience sample of six public high schools to assess the use of an online survey to allow for remote participation. In each school, 4 to 6 classes were selected randomly, and all students within a sampled class were selected to participate in the survey. A total of 702 students completed surveys. School contacts were asked to provide qualitative feedback about the survey administration. Feedback was generally positive, with a few suggestions for improvement. Approximately 19% of students reported the ever use of e-cigarettes. Among current e-cigarette users, there was a shift in popularity from prefilled or refillable pods or cartridges (23.3%) to disposable e-cigarettes (53.5%). Less than 10% of current e-cigarette users reported using tobacco-flavored e-cigarettes, despite a statewide flavor ban on all other flavors.

Examining the Survey Setting Effect on Current E-Cigarette Use Estimates among High School Students in the 2021 National Youth Tobacco Survey.

The 2021 National Youth Tobacco Survey (NYTS) was completed by youth online during class time, either in school or at home due to the COVID-19 pandemic. Given the role of NYTS data in tobacco regulatory science, it is vital to understand the effect of survey settings (home, school) on tobacco-use estimates. We used a series of multivariable logistic regressions to examine whether survey settings (home vs. school) predicted current e-cigarette use among high school students, controlling for other known predictors of e-cigarette use as well as the pandemic learning model that was dominant in students' counties (e.g., nearly all at-home, majority in school). We observed a significant survey setting effect. Those who completed the survey in school had higher odds of current e-cigarette use than those who completed the same survey at home (AOR = 1.74); this effect was attenuated when we controlled for the pandemic learning model (AOR = 1.38). Moreover, e-cigarette use was independently associated with students' learning model; students whose schools were nearly entirely in-person had the highest odds of e-cigarette use compared to students whose learning model was nearly all at-home (AOR = 1.65). Survey setting is a methodological artifact in the 2021 NYTS. Perceived privacy and peer effects can potentially explain this artifact.

Surgeons in surge - the versatility of the acute care surgeon: outcomes of COVID-19 ICU patients in a community hospital where all ICU patients are managed by surgical intensivists.

BACKGROUND: Reported characteristics and outcomes of critically ill patients with COVID-19 admitted to the intensive care unit (ICU) are widely disparate with varying mortality rates. No literature describes outcomes in ICU patients with COVID-19 managed by an acute care surgery (ACS) division. Our ACS division manages all ICU patients at a community hospital in New Jersey. When that hospital was overwhelmed and in crisis secondary to COVID-19, we sought to describe outcomes for all patients with COVID-19 admitted to our closed ICU managed by the ACS division. METHODS: This was a prospective case series of the first 120 consecutive patients with COVID-19 admitted on March 14 to May 10, 2020. Final follow-up was May 27, 2020. Patients discharged from the ICU or who died were included. Patients still admitted to the ICU at final follow-up were excluded. RESULTS: One hundred and twenty patients were included (median age 64 years (range 25-89), 66.7% men). The most common comorbidities were hypertension (75; 62.5%), obesity (61; 50.8%), and diabetes (50; 41.7%). One hundred and thirteen (94%) developed acute respiratory distress syndrome, 89 (74.2%) had shock, and 76 (63.3%) experienced acute kidney injury. One hundred (83.3%) required invasive mechanical ventilation (IMV). Median ICU length of stay (LOS) was 8.5 days (IQR 9), hospital LOS was 14.5 days (IQR 13). Mortality for all ICU patients with COVID-19 was 53.3% and 62% for IMV patients. CONCLUSIONS: This is the first report of patients with COVID-19 admitted to a community hospital ICU managed by an ACS division who also provided all surge care. Mortality of critically ill patients with COVID-19 admitted to an overwhelmed hospital in crisis may not be as high as initially thought based on prior reports. While COVID-19 is a non-surgical disease, ACS divisions have the capability of successfully caring for both surgical and medical critically ill patients, thus providing versatility in times of crisis. LEVEL OF EVIDENCE: Level V.

Fever in the ICU: A Predictor of Mortality in Mechanically Ventilated COVID-19 Patients.

PURPOSE: While fever may be a presenting symptom of COVID-19, fever at hospital admission has not been identified as a predictor of mortality. However, hyperthermia during critical illness among ventilated COVID-19 patients in the ICU has not yet been studied. We sought to determine mortality predictors among ventilated COVID-19 ICU patients and we hypothesized that fever in the ICU is predictive of mortality. MATERIALS AND METHODS: We conducted a retrospective cohort study of 103 ventilated COVID-19 patients admitted to the ICU between March 14 and May 27, 2020. Final follow-up was June 5, 2020. Patients discharged from the ICU or who died were included. Patients still admitted to the ICU at final follow-up were excluded. RESULTS: 103 patients were included, 40 survived and 63(61.1%) died. Deceased patients were older {66 years[IQR18] vs 62.5[IQR10], (p = 0.0237)}, more often male {48(68%) vs 22(55%), (p = 0.0247)}, had lower initial oxygen saturation {86.0%[IQR18] vs 91.5%[IQR11.5], (p = 0.0060)}, and had lower pH nadir than survivors {7.10[IQR0.2] vs 7.30[IQR0.2] (p < 0.0001)}. Patients had higher peak temperatures during ICU stay as compared to hospital presentation {103.3°F[IQR1.7] vs 100.0°F[IQR3.5], (p < 0.0001)}. Deceased patients had higher peak ICU temperatures than survivors {103.6°F[IQR2.0] vs 102.9°F[IQR1.4], (p = 0.0008)}. Increasing peak temperatures were linearly associated with mortality. Febrile patients who underwent targeted temperature management to achieve normothermia did not have different outcomes than those not actively cooled. Multivariable analysis revealed 60% and 75% higher risk of mortality with peak temperature greater than 103°F and 104°F respectively; it also confirmed hyperthermia, age, male sex, and acidosis to be predictors of mortality. CONCLUSIONS: This is one of the first studies to identify ICU hyperthermia as predictive of mortality in ventilated COVID-19 patients. Additional predictors included male sex, age, and acidosis. With COVID-19 cases increasing, identification of ICU mortality predictors is crucial to improve risk stratification, resource management, and patient outcomes.