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Record W4367056083 · doi:10.1016/j.medin.2023.04.010

Debilidad pulmonar asociada a COVID-19 (DPAC): revisión sistemática y metaanálisis

2023· article· es· W4367056083 on OpenAlexaboutno aff
Pablo Redruello‐Guerrero, Marta Ruiz del Pino, Carmen Jiménez-Gutiérrez, Paula Jiménez-Gutiérrez, Ana Carrascos-Cáliz, Alejandro Romero-Linares, Antonio Jesús Láinez Ramos‐Bossini, Mario Rivera‐Izquierdo, Antonio Cárdenas-Cruz

Bibliographic record

VenueMedicina Intensiva · 2023
Typearticle
Languagees
FieldMedicine
TopicPneumothorax, Barotrauma, Emphysema
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePneumothoraxPneumomediastinumIntensive care unitMechanical ventilationCoronavirus disease 2019 (COVID-19)Critically illInternal medicineSurgeryDisease

Abstract

fetched live from OpenAlex

Evaluar la mortalidad y diversos factores clínicos derivados del desarrollo de neumotórax (NTX) y/o neumomediastino (NMD) atraumáticos en pacientes críticos como consecuencia de la debilidad pulmonar asociada a la COVID-19 (DPAC). Revisión sistemática con metaanálisis. Unidad de cuidados intensivos (UCI). Investigaciones originales en las que se evaluase a pacientes, con o sin necesidad de ventilación mecánica invasiva (VMI), con diagnóstico de COVID-19 que hubiesen desarrollado NTX o NMD atraumáticos al ingreso o durante su estancia hospitalaria. Se obtuvieron los datos de interés de cada artículo que fueron analizados y evaluados por la Escala Newcastle-Ottawa. El riesgo de las variables de interés principales se evaluó por los datos derivados de los estudios que incluyeron a pacientes que desarrollaron NTX o NMD atraumáticos. Mortalidad, estancia media en la UCI y PaO2/FiO2 media en el momento diagnóstico. Se recogieron datos de 12 estudios longitudinales. En el metaanálisis se incluyeron datos de un total de 4.901 pacientes, entre los cuales 1.629 presentaron un episodio de NTX y 253 de NMD atraumáticos. A pesar de encontrar asociaciones significativamente fuertes, la alta heterogeneidad entre los estudios hace que la interpretación de los resultados deba hacerse con cautela. La mortalidad de los pacientes con COVID-19 fue mayor en los que desarrollaron NTX y/o NMD atraumáticos con respecto a los que no lo hicieron. La media del índice PaO2/FiO2 fue menor en los pacientes que desarrollaron NTX y/o NMD atraumáticos. Proponemos agrupar bajo el término DPAC estos casos. To assess mortality and different clinical factors derived from the development of atraumatic pneumothorax (PNX) and/or pneumomediastinum (PNMD) in critically ill patients as a consequence of COVID-19-associated lung weakness (CALW). Systematic review with meta-analysis. Intensive care unit (ICU). Original research evaluating patients, with or without the need for protective invasive mechanical ventilation (IMV), with a diagnosis of COVID-19 who had developed atraumatic PNX or PNMD on admission or during their hospital stay. Data of interest were obtained from each article and analysed and assessed by the Newcastle-Ottawa Scale. The risk of the variables of interest was assessed by data derived from studies including patients who developed atraumatic PNX or PNMD. Mortality, mean ICU length of stay and mean PaO2/FiO2 at diagnosis. Data were collected from 12 longitudinal studies. Data from a total of 4,901 patients were included in the meta-analysis. A total of 1,629 patients had an episode of atraumatic PNX and 253 patients had an episode of atraumatic PNMD. Despite finding significantly strong associations, the high heterogeneity between studies means that interpretation of the results should be made with caution. Mortality of COVID-19 patients was higher in those who developed atraumatic PNX and/or PNMD compared to those who did not. The mean PaO2/FiO2 index was lower in patients who developed atraumatic PNX and/or PNMD. We propose to group these cases under the term CAPD.

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)0.004
metaresearch head score (Gemma)0.044
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.476
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.009

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 head0.065
GPT teacher head0.370
Teacher spread0.305 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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