A Practical Clinical Score Predicting Respiratory Failure in COVID-19 Patients.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic resulted in repeated surges of patients, sometimes challenging triage protocols and appropriate control of patient flow. Available models, such as the National Early Warning Score (NEWS), have shown significant limitations. Still, they are used by some centers to triage COVID-19 patients due to the lack of better tools. OBJECTIVES: To establish a practical and automated triage tool based on readily available clinical data to rapidly determine a distinction between patients who are prone to respiratory failure. METHODS: The electronic medical records of COVID-19 patients admitted to the Sheba Medical Center March-April 2020 were analyzed. Population data extraction and exploration were conducted using a MDClone (Israel) big data platform. Patients were divided into three groups: non-intubated, intubated within 24 hours, and intubated after 24 hours. The NEWS and our model where applied to all three groups and a best fit prediction model for the prediction of respiratory failure was established. RESULTS: The cohort included 385 patients, 42 of whom were eventually intubated, 15 within 24 hours or less. The NEWS score was significantly lower for the non-intubated patients compared to the two other groups. Our improved model, which included NEWS elements combined with other clinical data elements, showed significantly better performance. The model's receiver operating characteristic curve had area under curve (AUC) of 0.92 with of sensitivity 0.81, specificity 0.89, and negative predictive value (NPV) 98.4% compared to AUC of 0.63 with NEWS. As patients deteriorate and require further support with supplemental O2, the need for re-triage emerges. Our model was able to identify those patients on supplementary O2 prone to respiratory failure with an AUC of 0.86 sensitivity 0.95, and specificity 0.7 NPV 98.9%, whereas NEWS had an AUC of 0.76. For both groups positive predictive value was approximately 35. CONCLUSIONS: Our model, based on readily available and simple clinical parameters, showed an excellent ability to predict negative outcome among patients with COVID-19 and therefore might be used as an initial screening tool for patient triage in emergency departments and other COVID-19 specific areas of the hospital.

The Predictive Value of Serum ACE2 and TMPRSS2 Concentrations in Patients with COVID-19-A Prospective Pilot Study.

One of the major challenges for healthcare systems during the Coronavirus-2019 (COVID-19) pandemic was the inability to successfully predict which patients would require mechanical ventilation (MV). Angiotensin-Converting Enzyme 2 (ACE2) and TransMembrane Protease Serine S1 member 2 (TMPRSS2) are enzymes that play crucial roles in SARS-CoV-2 entry into human host cells. However, their predictive value as biomarkers for risk stratification for respiratory deterioration requiring MV has not yet been evaluated. We aimed to evaluate whether serum ACE2 and TMPRSS2 levels are associated with adverse outcomes in COVID-19, and specifically the need for MV. COVID-19 patients admitted to an Israeli tertiary medical center between March--November 2020, were included. Serum samples were obtained shortly after admission (day 0) and again following one week of admission (day 7). ACE2 and TMPRSS2 concentrations were measured with ELISA. Of 72 patients included, 30 (41.6%) ultimately required MV. Serum ACE2 concentrations >7.8 ng/mL at admission were significantly associated with the need for MV (p = 0.036), inotropic support, and renal replacement therapy. In multivariate logistic regression analysis, elevated ACE2 at admission was associated with the need for MV (OR = 7.49; p = 0.014). To conclude, elevated serum ACE2 concentration early in COVID-19 illness correlates with respiratory failure necessitating mechanical ventilation. We suggest that measuring serum ACE2 at admission may be useful for predicting the risk of severe disease.

miR-155: A Potential Biomarker for Predicting Mortality in COVID-19 Patients.

COVID-19, a pandemic of severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2), continues to pose diagnostic and therapeutic challenges due to its unpredictable clinical course. Prognostic biomarkers may improve care by enabling quick identification of patients who can be safely discharged home versus those who may need careful respiratory monitoring and support. MicroRNAs (miRNAs) have risen to prominence as biomarkers for many disease states and as tools to assist in medical decisions. In the present study, we aimed to examine circulating miRNAs in hospitalized COVID-19 patients and to explore their potential as biomarkers for disease severity. We studied, by quantitative PCR, the expressions of miR-21, miR-146a, miR-146b, miR-155, and miR-499 in peripheral blood. We found that mild COVID-19 patients had 2.5-fold less circulating miR-155 than healthy people, and patients with a severe COVID-19 disease had 5-fold less circulating miR-155 than healthy people. In addition, we found that miR-155 is a good predictor of COVID-19 mortality. We suggest that examining miR-155 levels in patients' blood, upon admission to hospital, will ameliorate the care given to COVID-19 patients.

The Psychological Effects of Coronavirus Disease 2019 on Health Care Workers in Israel-A Personal Experience.

The pandemic of coronavirus disease 2019 (COVID-19) has had an ongoing global influence with high prevalence of psychological effects on both patients and health-care workers. The effect of anxiety and depression on medical professionals was substantial, as most medical resources have been used for treatment of patients; therefore, the availability of psychological services was insufficient. The situation in Israel was no different, and no society, including my own, was prepared for the psychological toll that COVID-19 has taken on us. This is a narrative of a pediatric intensivist working at the adult COVID-19 critical care unit, and a desperate call to mobilize resources to provide the psychological care that we all need.

Early vs. late tracheostomy in ventilated COVID-19 patients - A retrospective study.

BACKGROUND: Tracheostomy is one of the most common surgical procedures performed on ventilated COVID-19 patients, yet the appropriate timing for operating is controversial. OBJECTIVES: Assessing the effect of early tracheostomy on mortality and decannulation; elucidating changes in ventilation parameters, vasopressors and sedatives dosages immediately following the procedure. METHODS: A retrospective cohort of 38 ventilated COVID-19 patients, 19 of them (50%) underwent tracheostomy within 7 days of intubation (early tracheostomy group) and the rest underwent tracheostomy after 8 days or more (late tracheostomy group). RESULTS: Decannulation rates were significantly higher while mortality rates were non-significantly lower in the early tracheostomy group compared with the late tracheostomy group (58% vs 21% p < 0.05; 42% vs 74% p = 0.1, respectively). Tidal volume increased (446 ml vs 483 ml; p = 0.02) while PEEP (13 cmH20 vs 11.6 cmH2O, p = 0.04) decreased at the immediate time following the procedure. No staff member participating in the procedures was infected with SARS-CoV-2 virus. CONCLUSION: Early tracheostomy might offer improved outcomes with higher decannulation rates and lower mortality rates in ventilated COVID-19 patients, yet larger scale studies are needed. Most likely, early exposure to COVID-19 patients with appropriate personal protective equipment during open tracheostomy does not put the surgical team at risk.