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Record W2140724036 · doi:10.1345/aph.1q284

I-SAVE Study: Impact of Sedation, Analgesia, and Delirium Protocols Evaluated in the Intensive Care Unit: An Economic Evaluation

2011· article· en· W2140724036 on OpenAlexaffabout
Don‐Kelena Awissi, Cindy Bégin, Julie Moisan, Jean Lachaîne, Yoanna Skrobik

Bibliographic record

VenueAnnals of Pharmacotherapy · 2011
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsSedationMedicineDeliriumIntensive care unitMechanical ventilationIntensive careAnesthesiaEmergency medicineIncidence (geometry)Intensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Intensive care units (ICUs) account for considerable health care costs. Adequate pain and sedation management is important to clinical care. OBJECTIVE: To determine whether implementing a protocol for management of analgesia, sedation, and delirium in the ICU would save costs. METHODS: With data from the I-SAVE (Impact of Sedation, Analgesia and Delirium Protocols Evaluated in the Intensive Care Unit: an Economic Evaluation) study, a prospective pre- and postprotocol design was used. Between the 2 periods, protocols for systematic management of sedation, analgesia, and delirium were implemented. Cost-effectiveness was calculated by associating the variation of cost and effectiveness measures (proportion of patients within targeted pain, sedation, and delirium goals). Total costs (in 2004 Canadian dollars), by patient, consisted of the sum of sedation, analgesia, and delirium drug acquisition costs during the ICU stay and the cost of the ICU stay. RESULTS: A total of 1214 patients, 604 in the preprotocol group and 610 in the postprotocol group, were included. The mean (SD) ICU length of stay and the duration of mechanical ventilation were shorter among patients of the postprotocol group compared with those of the preprotocol group (5.43 [6.43] and 6.39 [8.05] days, respectively; p = 0.004 and 5.95 [6.80] and 7.27 [9.09] days, respectively; p < 0.009). The incidence of delirium remained the same. The proportion of patients with Richmond Agitation and Sedation (RASS) scores between -1 and +1 increased from 57.0% to 66.2% (p = 0.001), whereas the proportion of patients with a numeric rating scale (NRS) score of 1 or less increased from 56.3% to 66.6% (p < 0.001). The mean total cost of ICU hospitalization decreased from $6212.64 (7846.86) in the preprotocol group to $5279.90 (6263.91) in the postprotocol group (p = 0.022). The cost analyses for pain and agitation management improved; the proportion of patients with RASS scores between -1 and +1 or NRS scores of 1 or less increased significantly in the postprotocol group while costing, on average, $932.74 less per hospitalization. CONCLUSIONS: Establishing protocols for patient-driven management of sedation, analgesia, and delirium is a cost-effective practice and allows savings of nearly $1000 per hospitalization.

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)0.020
metaresearch head score (Gemma)0.040
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.040
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.009
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.261
GPT teacher head0.516
Teacher spread0.255 · 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

Citations84
Published2011
Admission routes2
Has abstractyes

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