COVID 19 and the risk of gastro-intestinal perforation: A case series and literature review.

BACKGROUND: COVID19 is a viral disease with pneumonia as its most common presentation. Many presentations and complications have been reported, but gastro-intestinal perforation has not received much attention. METHODS: three cases from our hospital are presented, and the current literature was reviewed. RESULTS, CASES: All three patients were admitted to the ICU with respiratory failure due to COVID19 pneumonia and intubated. Our first patient was treated with steroids, and subsequently diagnosed with rectal perforation on day 34 of his hospital admission. The second patient was treated with steroids and tocilizumab, and diagnosed with colonic perforation 1 day after neostigmine administration, on day 14 of his hospital admission. Our third patient was treated with steroids and tocilizumab, and diagnosed colonic perforation 4 days after neostigmine administration, on day 14 of his hospital admission. RESULTS, LITERATURE: 25 more cases were found in current literature, both upper GI and lower GI perforations, either as a presenting symptom or during the course of hospitalization. These were often associated with treatment with steroids, interleukin 6 inhibitors, or both. CONCLUSIONS: Gastro-intestinal perforation is a rare but dangerous complication of COVID19. Treatment with tocilizumab and steroids may both increase the risk of this complication, and hamper diagnosis.

Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.

OBJECTIVES: As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN: Multicenter retrospective cohort study. SETTING: Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS: One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS: We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio2, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao2/Fio2 ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS: This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse.

BACKGROUND: The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients. METHODS: The DDW is a growing electronic health record database of critically ill COVID-19 patients in the Netherlands. All adult ICU patients on IMV were eligible for inclusion. Transfers, patients admitted for less than 24 h, and patients still admitted at time of data extraction were excluded. Predictors were selected based on the literature, and included medication dosage and fluid balance. Multiple algorithms were trained and validated on up to three sets of observations per patient on day 1, 7, and 14 using fivefold nested cross-validation, keeping observations from an individual patient in the same split. RESULTS: A total of 1152 patients were included in the model. XGBoost models performed best for all outcomes and were used to calculate predictor importance. Using Shapley additive explanations (SHAP), age was the most important demographic risk factor for the outcomes upon start of IMV and throughout its course. The relative probability of death across age values is visualized in Partial Dependence Plots (PDPs), with an increase starting at 54 years. Besides age, acidaemia, low P/F-ratios and high driving pressures demonstrated a higher probability of death. The PDP for driving pressure showed a relative probability increase starting at 12 cmH2O. CONCLUSION: Age is the most important demographic risk factor of ICU mortality, ICU-free days and ventilator-free days throughout the course of invasive mechanical ventilation in critically ill COVID-19 patients. pH, P/F ratio, and driving pressure should be monitored closely over the course of mechanical ventilation as risk factors predictive of these outcomes.

Prolonged Unconsciousness Following Severe COVID-19.

OBJECTIVE: We report a case series of patients with prolonged but reversible unconsciousness after coronavirus disease 2019 (COVID-19)-related severe respiratory failure. METHODS: A case series of patients who were admitted to the intensive care unit due to COVID-19-related acute respiratory failure is described. RESULTS: After cessation of sedatives, the described cases all showed a prolonged comatose state. Diagnostic neurologic workup did not show signs of devastating brain injury. The clinical pattern of awakening started with early eye opening without obeying commands and persistent flaccid weakness in all cases. Time between cessation of sedatives to the first moment of being fully responsive with obeying commands ranged from 8 to 31 days. CONCLUSION: Prolonged unconsciousness in patients with severe respiratory failure due to COVID-19 can be fully reversible, warranting a cautious approach for prognostication based on a prolonged state of unconsciousness.