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.

BackgroundReported 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.MethodsThis 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.ResultsOne 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.ConclusionsThis 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 evidenceLevel V.

Background: Historically, procalcitonin(PCT) has been used as a predictor of bacterial infection and to guide antibiotic therapy in hospitalized patients. The purpose of this study was to determine PCT's diagnostic utility in predicting secondary bacterial pneumonia in critically ill patients with severe COVID-19 pneumonia. Methods: A retrospective cohort study was conducted in COVID-19 adults admitted to the ICU between March 2020, and March 2021. All included patients had a PCT level within 72 h of presentation and serum creatinine of <1.5mg/dL. A PCT threshold of 0.5ng/mL was used to compare patients with high( ≥ 0.5ng/mL) versus low(< 0.5ng/mL) PCT. Bacterial pneumonia was defined by positive respiratory culture. A receiver operating characteristics (ROC) curve was utilized to evaluate PCT as a diagnostic test for bacterial pneumonia, with an area under the curve(AUC) threshold of 0.7 to signify an accurate diagnostic test. A multivariable model was constructed to identify variables associated with in-hospital mortality. Results: There were 165 patients included: 127 low PCT versus 38 high PCT. There was no significant difference in baseline characteristics, vital signs, severity of disease, or outcomes among low versus high PCT groups (all p > 0.05). While there was no difference in bacterial pneumonia in low versus high groups (34(26.8%) versus 12(31.6%), p  = 0.562), more patients in the high PCT group had bacteremia (19(15%) versus 11(28.9%), p  = 0.050). Sensitivity was 26.1% and specificity was 78.2% for PCT to predict bacterial pneumonia coinfection in ICU patients with COVID-19 pneumonia. ROC yielded an AUC 0.54 ( p = 0.415). After adjusting for LDH>350U/L and creatinine in multivariable regression, PCT did not enhance performance of the regression model. Conclusions: PCT offers little to no predictive utility in diagnosing concomitant bacterial pneumonia in critically ill patients with COVID-19 nor in predicting increased severity of disease or worse outcomes including mortality.