Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19.

Background The prognosis of hospitalized patients with severe coronavirus disease 2019 (COVID-19) is difficult to predict, and the capacity of intensive care units was a limiting factor during the peak of the pandemic and is generally dependent on a country's clinical resources. Purpose To determine the value of chest radiographic findings together with patient history and laboratory markers at admission to predict critical illness in hospitalized patients with COVID-19. Materials and Methods In this retrospective study, which included patients from March 7, 2020, to April 24, 2020, a consecutive cohort of hospitalized patients with real-time reverse transcription polymerase chain reaction-confirmed COVID-19 from two large Dutch community hospitals was identified. After univariable analysis, a risk model to predict critical illness (ie, death and/or intensive care unit admission with invasive ventilation) was developed, using multivariable logistic regression including clinical, chest radiographic, and laboratory findings. Distribution and severity of lung involvement were visually assessed by using an eight-point scale (chest radiography score). Internal validation was performed by using bootstrapping. Performance is presented as an area under the receiver operating characteristic curve. Decision curve analysis was performed, and a risk calculator was derived. Results The cohort included 356 hospitalized patients (mean age, 69 years ± 12 [standard deviation]; 237 men) of whom 168 (47%) developed critical illness. The final risk model's variables included sex, chronic obstructive lung disease, symptom duration, neutrophil count, C-reactive protein level, lactate dehydrogenase level, distribution of lung disease, and chest radiography score at hospital presentation. The area under the receiver operating characteristic curve of the model was 0.77 (95% CI: 0.72, 0.81; P < .001). A risk calculator was derived for individual risk assessment: Dutch COVID-19 risk model. At an example threshold of 0.70, 71 of 356 patients would be predicted to develop critical illness, of which 59 (83%) would be true-positive results. Conclusion A risk model based on chest radiographic and laboratory findings obtained at admission was predictive of critical illness in hospitalized patients with coronavirus disease 2019. This risk calculator might be useful for triage of patients to the limited number of intensive care unit beds or facilities. © RSNA, 2020 Online supplemental material is available for this article.

Ischemic priapism as a model of exhausted metabolism.

In vivo metabolic studies typically concern complex open systems. However, a closed system allows better assessment of the metabolic limits. Ischemic priapism (IP) constitutes a special model of the compartment syndrome that allows direct sampling from a relatively large blood compartment formed by the corpora cavernosa (CC). The purpose of our study was to measure metabolic changes and the accumulation of end products within the CC during IP. Blood gas and biochemical analyses of aspirates of the CC were analyzed over an 8-year period. Mean ± SD pH, pCO2 , pO2 , O2 -saturation, lactate, and glucose of the aspirated blood were determined with a point-of-care analyzer. Forty-seven initial samples from 21 patients had a pH of 6.91 ± 0.16, pCO2 of 15.3 ± 4.4 kPa, pO2 of 2.4 ± 2.0 kPa, and an O2 -saturation of 19 ± 24% indicating severe hypoxia with severe combined respiratory and metabolic acidosis. Glucose and lactate levels were 1.1 ± 1.5 and 14.6 ± 4.8 mmol/L, respectively. pH and pCO2 were inversely correlated (R2  = 0.86; P < 0.001), glucose and O2 -saturation were positively correlated (R2  = 0.83; P < 0.001), and glucose and lactate were inversely correlated (R2  = 0.72; P < 0.001). The positive correlation of CO2 and lactate (R2  = 0.69; P < 0.001) was similar to that observed in vitro, when blood was titrated with lactic acid. The observed combined acidosis underscores that IP behaves as a closed system where severe hypoxia and glycopenia coexist, indicating that virtually all energy reserves have been consumed.