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.

The association of early combined lactate and glucose levels with subsequent renal and liver dysfunction and hospital mortality in critically ill patients.

BACKGROUND: The development of renal and liver dysfunction may be accompanied by initially subtle derangements in the gluconeogenetic function. Discrepantly low glucose levels combined with high lactate levels might indicate an impaired Cori cycle. Our objective was to examine the relation between early lactate and glucose levels with subsequent renal and liver dysfunction and hospital mortality in critically ill patients. METHODS: Over a 4-year period (2011 to 2014), all adult patients admitted to our adult 48-bed teaching hospital intensive care unit (ICU) for at least 12 h were retrospectively analyzed. Lactate and glucose were regularly measured with point-of-care analyzers in all ICU patients. Lactate and glucose measurements were collected from 6 h before to 24 h after ICU admission. Patients with fewer than four lactate/glucose measurements were excluded. Patients received insulin according to a computer-guided control algorithm that aimed at a glucose level <8.0 mmol/L. Renal dysfunction was defined as the development of acute kidney injury (AKI) within 7 days, and liver function was based on the maximal bilirubin in the 7-day period following ICU admission. Mean lactate and mean glucose were classified into quintiles and univariate and multivariate analyses were related with renal and liver dysfunction and hospital mortality. Since glucose has a known U-shaped relation with outcome, we also accounted for this. RESULTS: We analyzed 92,000 blood samples from 9074 patients (63% males) with a median age of 64 years and a hospital mortality of 11%. Both lactate quintiles (≤1.0; 1.0-1.3; 1.3-1.7; 1.7-2.3; >2.3 mmol/L) and glucose quintiles (≤7.0; 7.0-7.6; 7.6-8.2; 8.2-9.0; >9.0 mmol/L) were related with outcome in univariate analysis (p < 0.001). Acute Physiology and Chronic Health Evaluation (APACHE) IV, lactate, and glucose were associated with renal and liver dysfunction in multivariate analysis (p < 0.001), with a U-shaped relationship for glucose. The combination of the highest lactate quintile with the lowest glucose quintile was associated with the highest rates of renal dysfunction, liver dysfunction, and mortality (p < 0.001) with a significant interaction between lactate and glucose (p ≤ 0.001). CONCLUSIONS: Abnormal combined lactate and glucose measurements may provide an early indication of organ dysfunction. In critically ill patients a 'normal' glucose with an elevated lactate should not be considered desirable, as this combination is related with increased mortality.

Low Cancer Incidence in Naked Mole-Rats May Be Related to Their Inability to Express the Warburg Effect.

Metabolic flexibility in mammals enables stressed tissues to generate additional ATP by converting large amounts of glucose into lactic acid; however, this process can cause transient local or systemic acidosis. Certain mammals are adapted to extreme environments and are capable of enhanced metabolic flexibility as a specialized adaptation to challenging habitat niches. For example, naked mole-rats (NMRs) are a fossorial and hypoxia-tolerant mammal whose metabolic responses to environmental stressors markedly differ from most other mammals. When exposed to hypoxia, NMRs exhibit robust hypometabolism but develop minimal acidosis. Furthermore, and despite a very long lifespan relative to other rodents, NMRs have a remarkably low cancer incidence. Most advanced cancers in mammals display increased production of lactic acid from glucose, irrespective of oxygen availability. This hallmark of cancer is known as the Warburg effect (WE). Most malignancies acquire this metabolic phenotype during their somatic evolution, as the WE benefits tumor growth in several ways. We propose that the peculiar metabolism of the NMR makes development of the WE inherently difficult, which might contribute to the extraordinarily low cancer rate in NMRs. Such an adaptation of NMRs to their subterranean environment may have been facilitated by modified biochemical responses with a stronger inhibition of the production of CO2 and lactic acid by a decreased extracellular pH. Since this pH-inhibition could be deeply hard-wired in their metabolic make-up, it may be difficult for malignant cells in NMRs to acquire the WE-phenotype that facilitates cancer growth in other mammals. In the present commentary, we discuss this idea and propose experimental tests of our hypothesis.

Early lactate and glucose kinetics following return to spontaneous circulation after out-of-hospital cardiac arrest.

OBJECTIVE: Lactate has been shown to be preferentially metabolized in comparison to glucose after physiological stress, such as strenuous exercise. Derangements of lactate and glucose are common after out-of-hospital cardiac arrest (OHCA). Therefore, we hypothesized that lactate decreases faster than glucose after return-to-spontaneous-circulation (ROSC) after OHCA. RESULTS: We included 155 OHCA patients in our analysis. Within the first 8 h of presentation to the emergency department, 843 lactates and 1019 glucoses were available, respectively. Lactate decreased to 50% of its initial value within 1.5 h (95% CI [0.2-3.6 h]), while glucose halved within 5.6 h (95% CI [5.4-5.7 h]). Also, in the first 8 h after presentation lactate decreases more than glucose in relation to their initial values (lactate 72.6% vs glucose 52.1%). In patients with marked hyperlactatemia after OHCA, lactate decreased expediently while glucose recovered more slowly, whereas arterial pH recovered at a similar rapid rate as lactate. Hospital non-survivors (N = 82) had a slower recovery of lactate (P = 0.002) than survivors (N = 82). The preferential clearance of lactate underscores its role as a prime energy substrate, when available, during recovery from extreme stress.

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.

[The Warburg effect and its role in tumour metabolism: opportunities for new cancer treatments]. / Het Warburg-effect en zijn rol in tumormetabolisme: Mogelijkheden voor nieuwe kankertherapie.

Cancer cells are characterised by altered metabolism compared to healthy tissue. Ninety years ago, the German medical doctor and biochemist Otto Warburg discovered that tumours--when compared to healthy tissue--convert considerably more glucose into lactate, regardless of oxygen presence. This phenomenon is known as the Warburg effect; it is a hallmark of most cancer types and can be well understood by the process of somatic evolution. The Warburg effect explains the significance of the PET scan and may offer opportunities for new treatments of cancer.