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Record W2160093433 · doi:10.1186/s13054-015-0922-9

Management and outcome of mechanically ventilated patients after cardiac arrest

2015· article· en· W2160093433 on OpenAlexafffund
Yuda Sutherasan, Óscar Peñuelas, Alfonso Muriel, Maria Vargas, Fernando Frutos–Vivar, Iole Brunetti, Konstantinos Raymondos, Davide D’Antini, Niklas Nielsen, Niall D. Ferguson, Bernd W. Böttiger, Arnaud W. Thille, Andrew R. Davies, Javier Hurtado, Fernando Ríos, Carlos Apezteguía, Damian A. Violi, Nahit Çakar, Marco González, Bin Du, Michaël Kuiper, Marco Antonio Soares, Younsuck Koh, Rui P. Moreno, Pravin Amin, Vinko Tomicić, Luis Soto, Hans‐Henrik Bülow, Antonio Anzueto, Paolo Pelosi

Bibliographic record

VenueCritical Care · 2015
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
FundersInstituto de Salud Carlos IIICanadian Institutes of Health Research
KeywordsMedicineARDSMechanical ventilationPneumoniaOdds ratioSepsisLogistic regressionEmergency medicineRespiratory distressAnesthesiaInternal medicineLung

Abstract

fetched live from OpenAlex

INTRODUCTION: The aim of this study was to describe and compare the changes in ventilator management and complications over time, as well as variables associated with 28-day hospital mortality in patients receiving mechanical ventilation (MV) after cardiac arrest. METHODS: We performed a secondary analysis of three prospective, observational multicenter studies conducted in 1998, 2004 and 2010 in 927 ICUs from 40 countries. We screened 18,302 patients receiving MV for more than 12 hours during a one-month-period. We included 812 patients receiving MV after cardiac arrest. We collected data on demographics, daily ventilator settings, complications during ventilation and outcomes. Multivariate logistic regression analysis was performed to calculate odds ratios, determining which variables within 24 hours of hospital admission were associated with 28-day hospital mortality and occurrence of acute respiratory distress syndrome (ARDS) and pneumonia acquired during ICU stay at 48 hours after admission. RESULTS: Among 812 patients, 100 were included from 1998, 239 from 2004 and 473 from 2010. Ventilatory management changed over time, with decreased tidal volumes (VT) (1998: mean 8.9 (standard deviation (SD) 2) ml/kg actual body weight (ABW), 2010: 6.7 (SD 2) ml/kg ABW; 2004: 9 (SD 2.3) ml/kg predicted body weight (PBW), 2010: 7.95 (SD 1.7) ml/kg PBW) and increased positive end-expiratory pressure (PEEP) (1998: mean 3.5 (SD 3), 2010: 6.5 (SD 3); P <0.001). Patients included from 2010 had more sepsis, cardiovascular dysfunction and neurological failure, but 28-day hospital mortality was similar over time (52% in 1998, 57% in 2004 and 52% in 2010). Variables independently associated with 28-day hospital mortality were: older age, PaO2 <60 mmHg, cardiovascular dysfunction and less use of sedative agents. Higher VT, and plateau pressure with lower PEEP were associated with occurrence of ARDS and pneumonia acquired during ICU stay. CONCLUSIONS: Protective mechanical ventilation with lower VT and higher PEEP is more commonly used after cardiac arrest. The incidence of pulmonary complications decreased, while other non-respiratory organ failures increased with time. The application of protective mechanical ventilation and the prevention of single and multiple organ failure may be considered to improve outcome in patients after cardiac arrest.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.315
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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

Citations66
Published2015
Admission routes2
Has abstractyes

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