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Record W2317239321 · doi:10.1097/ccm.0000000000001522

Validation of the Critical Care Pain Observation Tool in Critically Ill Patients With Delirium

2016· article· en· W2317239321 on OpenAlexaffabout
Salmaan Kanji, Heather MacPhee, Avinder Singh, Christel Johanson, Jennifer Fairbairn, Tammy Lloyd, Robert MacLean, Erin Rosenberg

Bibliographic record

VenueCritical Care Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineDeliriumIntensive carePhysical therapyDiscriminant validityPain assessmentProspective cohort studyIntensive care medicineEmergency medicinePatient satisfactionPain managementInternal medicineSurgeryInternal consistency

Abstract

fetched live from OpenAlex

OBJECTIVES: The 2013 clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the ICU suggest that pain be routinely assessed using a validated pain assessment tool. Currently available tools have only been evaluated in nondelirious critically ill patients, yet delirium can affect as many as 80% of ICU patients. The validated pain assessment tool adopted by our institution is the Critical Care Pain Observation Tool, and the objective of this study was to investigate the validity of this tool in patients with evidence of delirium. DESIGN: Prospective cohort study. SETTING: Two ICUs within a Canadian tertiary healthcare center. PATIENTS: Forty consecutive adult patients deemed delirious on the day of enrollment using the Confusion Assessment Method for ICU. MEASUREMENTS AND MAIN RESULTS: Serial Critical Care Pain Observation Tool assessments were conducted simultaneously by study personnel and objective nurses at baseline and after nonpainful and painful stimuli. Subjective opinions about pain and objective physical variables (including mean arterial pressure, heart rate, respiratory rate, and oxygen saturation) were collected at the same time points. Discriminant validity was described using paired t tests, whereas internal consistency was described using the Cronbach α statistic. Responsiveness of the Critical Care Pain Observation Tool was measured by effect size, and reliability was described as the agreement between raters. Comparisons between the Critical Care Pain Observation Tool and the subjective assessments and objective measurements were based on positive and negative percent agreement. Critical Care Pain Observation Tool demonstrated excellent discriminant validity as evidenced by a highly statistically and clinically significant change in mean Critical Care Pain Observation Tool scores between baseline and painful procedures (mean difference, 3.13 ± 1.56; p < 0.001; Cohen D, 2.0). Interrater agreement was also excellent (κ > 0.6), and scores between raters were highly correlated (r = 0.957). The Critical Care Pain Observation Tool possessed a high level of internal consistency (overall Cronbach α, 0.778). Percent agreement was found to be greater between the Critical Care Pain Observation Tool and the nurse's subjective opinion of the presence or absence of pain when compared with that between the Critical Care Pain Observation Tool and physiologic variables (80.5% vs 67.5%, respectively). CONCLUSIONS: The Critical Care Pain Observation Tool is a valid pain assessment tool in noncomatose, delirious adult ICU patients who are unable to reliably self-report the presence or absence of pain.

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)0.280
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 score0.280
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.280
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.020
GPT teacher head0.297
Teacher spread0.277 · 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

Citations50
Published2016
Admission routes2
Has abstractyes

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