MétaCan
Menu
Back to cohort
Record W3172135127 · doi:10.14740/cii132

Daily Energy Requirements and Substrate Utilization in Hyper- and Hypometabolism of Obese COVID-19 Patients Measured by Indirect Calorimetry: Two Case Reports

2021· article· en· W3172135127 on OpenAlexvenueno aff
Aníbal Basile-Filho, Amanda Alves Silva Mazzoni, Vivian Caroline Siansi, Daniela Alari Chedid, Tiago Henrique Garcia da Silva, Carolina Hunger Malek-Zadeh, Marcelo Lorencini Puga, Alessandra Fabiane Lago

Bibliographic record

VenueClinical Infection and Immunity · 2021
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsnot available
Fundersnot available
KeywordsHypermetabolismResting energy expenditureMedicineIntensive care unitPolytraumaBody mass indexCoronavirus disease 2019 (COVID-19)Medical historyEnergy expenditureInternal medicinePediatricsDiseaseEmergency medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.129
GPT teacher head0.399
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueClinical Infection and ImmunitySame topicClinical Nutrition and GastroenterologyFrench-language works237,207