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Record W1996746689 · doi:10.1097/ccm.0b013e318265f340

Quality of Life Before Intensive Care Using EQ-5D

2012· article· en· W1996746689 on OpenAlexfundno aff
Victor D. Dinglas, Jeneen M. Gifford, Nadia Husain, Elizabeth Colantuoni, Dale M. Needham

Bibliographic record

VenueCritical Care Medicine · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health Research
KeywordsMedicineProxy (statistics)Visual analogue scalePsychological interventionPopulationRetrospective cohort studyEmergency medicineQuality of life (healthcare)EQ-5DProspective cohort studyIntensive careCohortPhysical therapyHealth related quality of lifeIntensive care medicineInternal medicinePsychiatryEnvironmental healthStatistics

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare patients' retrospectively reported baseline quality of life before intensive care hospitalization with population norms and proxy reports. DESIGN: Prospective cohort study. SETTING: Thirteen ICUs at four teaching hospitals in Baltimore, MD. PATIENTS: One hundred forty acute lung injury survivors and their designated proxies. INTERVENTIONS: Around the time of hospital discharge, both patients and proxies were asked to retrospectively estimate patients' baseline quality of life before hospital admission using the EQ-5D quality-of-life instrument. MEASUREMENTS AND MAIN RESULTS: Mean patient-rated EQ-5D visual analog scale scores and utility scores were significantly lower than population norms but were significantly higher than proxy ratings. However, the magnitude of difference in average utility scores between patients and either population norms or proxies was not clinically important. For the five individual EQ-5D domains, κ statistics revealed slight to fair agreement between patients and proxies. Bland-Altman plots demonstrated that for both the visual analog scale and utility scores, proxies underestimated scores when patients reported high ratings and overestimated scores for low patient ratings. CONCLUSIONS: Patients retrospectively reported worse baseline health status before acute lung injury than population norms and better status than proxy reports; however, the magnitude of these differences in health status may not be clinically important. Proxies had only slight to fair agreement with patients in all five EQ-5D domains, attenuating patients' more extreme ratings toward moderate scores. Caution is required when interpreting proxy retrospective reports of baseline health status for survivors of acute lung injury.

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)0.007
metaresearch head score (Gemma)0.060
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.060
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.637
GPT teacher head0.511
Teacher spread0.126 · 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.

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

Citations62
Published2012
Admission routes1
Has abstractyes

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