ABSTRACT
We used a telephone survey to determine risk factors associated with a positive polymerase chain reaction test of a nasopharyngeal swab for severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) at a community hospital in Central New Jersey during the early stages of the pandemic. We compared survey responses of 176 patients in March 2020. Respondents were asked about their living situation, work environment, use of public transportation and attendance at one or more large gatherings (more than 10 people) in the 3 weeks prior to undergoing COVID testing. We found that those who attended a large gathering in the 3 weeks prior to their COVID test had a 2.50 odds ratio (95% CI 1.19, 5.22) of testing positive after controlling for age, sex, race/ethnicity, occupation, living situation and recent visit to a nursing home. The total number of gatherings attended or the number of people in attendance was not associated with a positive test. An association was also seen for specific job types such as factory workers, construction workers, and facilities managers. Attendance at a gathering of more than ten people was associated with testing positive for COVID-19.
Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19 Testing , Humans , Pandemics , SARS-CoV-2 , Surveys and QuestionnairesABSTRACT
OBJECTIVES: A high-intensity staffing model has been defined as either mandatory intensivist consultation or a closed intensive care unit in which intensivists manage all aspects of patient care. In the current climate of limited healthcare resources, transitioning to a closed intensive care unit model may lead to significant improvements in patient care and resource utilization. METHODS: This is a single-center, retrospective cohort study of all mechanically ventilated intensive care unit admissions in the pre-intensive care unit closure period of 1 October 2014 to 30 September 2015 as compared with the post-intensive care unit closure period of 1 November 2015 to 31 October 2016. Patient demographics as well as outcome data (duration of mechanical ventilation, length of stay, direct costs, complications, and mortality) were abstracted from the electronic health record. All data were analyzed using descriptive and inferential statistics. Regression analyses were used to adjust outcomes for potential confounders. RESULTS: A total of 549 mechanically ventilated patients were included in our analysis: 285 patients in the pre-closure cohort and 264 patients in the post-closure cohort. After adjusting for confounders, there was no significant difference in mortality rates between the pre-closure (40.7%) and post-closure (38.6%) groups (adjusted odds ratio = 0.82; 95% confidence interval = 0.56-1.18; p = 0.283). The post-closure cohort was found to have significant reductions in duration of mechanical ventilation (3.71-1.50 days; p < 0.01), intensive care unit length of stay (5.8-2.7 days; p < 0.01), hospital length of stay (10.9-7.3 days; p < 0.01), and direct hospital costs (US $16,197-US $12,731; p = 0.009). Patient complications were also significantly reduced post-intensive care unit closure. CONCLUSION: Although a closed intensive care unit model in our analysis did not lead to a statistical difference in mortality, it did demonstrate multiple beneficial outcomes including reduced ventilator duration, decreased intensive care unit and hospital length of stay, fewer patient complications, and reduced direct hospital costs.
ABSTRACT
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.
Subject(s)
COVID-19/mortality , Fever/mortality , Hospital Mortality , Intensive Care Units/statistics & numerical data , Respiration, Artificial/mortality , Adult , Aged , COVID-19/therapy , Critical Care Outcomes , Female , Fever/virology , Humans , Male , Middle Aged , Retrospective Studies , Risk Factors , SARS-CoV-2ABSTRACT
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.