Daily Energy Requirements and Substrate Utilization in Hyper- and Hypometabolism of Obese COVID-19 Patients Measured by Indirect Calorimetry: Two Case Reports
Bibliographic record
Abstract
Despite the belief that critically ill obese patients with coronavirus disease 2019 (COVID-19) have an increased resting energy expenditure (REE), in some specific obese patients, an apparently contradictory reduction in metabolic needs can be observed. A case report of two obese patients with diagnosis of COVID-19 admitted to an intensive care unit was conducted to illustrate this discrepancy. Case 1 is a 16-year-old female (body mass index (BMI) = 44.6 kg/m 2 ), with a medical history of clinical hypothyroidism, who had a remarkable decrease in REE. Case 2 is a 42-year-old male (BMI = 36.6 kg/m 2 ), with a medical history of polytrauma followed by a motorcycle accident showed a classical pattern of hypermetabolism. Indirect calorimetry (IC) was performed during 8 consecutive days for both patients. The different REE in the hypometabolic (case 1) and hypermetabolic (case 2) state was demonstrated by IC measurements. In conclusion, the more frequent usage of IC could avoid the pitfalls of predicting REE equations that could lead to an under or overfeeding. Clin Infect Immun. 2021;6(2):55-59 doi: https://doi.org/10.14740/cii132
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".