MétaCan
Menu
Back to cohort

Characteristics and outcomes for critically ill patients with prolonged intensive care unit stays*

2005· article· en· W2008895901 on OpenAlexaff
Claudio M. Martin, Andrea D. Hill, Karen E. A. Burns, Liddy M. Chen

Bibliographic record

VenueCritical Care Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsLawson Health Research Institute
Fundersnot available
KeywordsMedicineIntensive care unitObservational studyIntensive careEmergency medicineIntervention (counseling)Critically illIntensive care medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

LEARNING OBJECTIVES On completion of this article, the reader should be able to: Define prolonged intensive care unit stay patients. Define characteristics of prolonged stay patients. Use this information in a clinical setting. Dr. Chen has disclosed that she is an employee of EMD Pharmaceuticals, Inc. The remaining authors have disclosed that they have no financial relationships with or interests in any commercial companies pertaining to this educational activity. Wolters Kluwer Health has identified and resolved all faculty conflicts of interest regarding this educational activity. Visit the Critical Care Medicine Web site (www.ccmjournal.org) for information on obtaining continuing medical education credit. Objective: Prolonged stay in the intensive care unit (ICU) is associated with high mortality, morbidity, and costs. Identifying those patients who are most likely to benefit from an extended ICU stay would be helpful in guiding clinical decisions. We sought to describe the characteristics and outcomes for a heterogeneous group of patients who required a prolonged ICU stay. Design: Observational study. Setting: Adult ICUs of three teaching and five community hospitals. Patients: The study group comprised 5,881 patients consecutively admitted to the ICUs during a 10-month period. Measurements and Main Results: A prolonged stay was defined as one >21 days at teaching hospitals and >10 days at community hospitals. For patients meeting the criteria of prolonged stay, Therapeutic Intervention Scoring System (TISS) score and Multiple Organ Dysfunction Score (MODS) were measured prospectively from days 10 and 21 in community and teaching hospitals, respectively, and retrospectively before this. Prolonged-stay patients represented 5.6% of ICU admissions and 39.7% of ICU bed-days. Compared with short-stay patients, they were significantly older and had higher admission Acute Physiology and Chronic Health Evaluation (APACHE) II scores (p < .01). ICU and hospital mortality for prolonged-stay patients were 24.4% and 35.2%, respectively, compared with 11% and 15.9% for short-stay patients (p < .001). Mean admission TISS and MODS scores for prolonged-stay patients were 30.8 (sd, 11.1) and 4.8 (sd, 3.3) respectively. For prolonged-stay patients the dominant reason for ICU care was multiple organ failure (37.8%), ventilator support (30.7%), or nonventilated single organ failure (31.5%). Hospital mortality was highest in the group with multiple organ failure (53%). Conclusions: We developed a method to broadly classify a heterogeneous population of prolonged-stay ICU patients on the basis of MODS and the ICU interventions received. Mortality among prolonged-stay patients was highest for those with multiple organ failure. Future research should evaluate whether the proposed classification system can be used to influence the delivery of ICU care.

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)0.000
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.054
GPT teacher head0.363
Teacher spread0.309 · 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

Citations129
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCritical Care MedicineSame topicSepsis Diagnosis and TreatmentFrench-language works237,207