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Record W2615529969 · doi:10.1093/ageing/afx055.81

81UNDER-DIAGNOSED COGNITIVE IMPAIRMENT IN RENAL INPATIENTS - A SINGLE CENTRE QIP EXPERIENCE

2017· article· en· W2615529969 on OpenAlexaboutno aff
H Mottershead, Cornelia L. Trimble, Shalini Rajcoomar, Albert Power

Bibliographic record

VenueAge and Ageing · 2017
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCognitive impairmentCognitionPediatricsPsychiatry

Abstract

fetched live from OpenAlex

Cognitive impairment is highly prevalent in patients with chronic kidney disease (CKD), with up to 86% prevalence in haemodialysis (HD) patients [1, 2]. It is a risk factor for prolonged hospitalisation, readmission and mortality [3, 4]. Responding to a Commissioning for Quality and Innovation incentive to identify cognitive impairment in elderly inpatients, we undertook a Quality Improvement Project (QIP) to characterise the presence of cognitive dysfunction in renal inpatients. We prospectively collected clinical data on 33 randomly selected renal inpatients ≥ 65 years old. We recorded demographics, history of cognitive impairment, a Charlson Comorbidity Index (CCI) and a CSHA clinical frailty scale. We performed an Abbreviated Mental Test Score (AMTS) and Montreal Cognitive Assessment (MOCA). DSM-IV criteria were used to define delirium. A 2-cycle QIP was undertaken. The interventions were education at the departmental induction and the introduction of a forcing function for the discharge summary. Data was performed using Microsoft Excel. Mean patient age was 76, 70% male, mean length of stay (LOS) 12 days and 16 were HD patients. Following the QIP all patients had a statement regarding cognitive function on their discharge summary. Only 1patient (3%) had a prior diagnosis of dementia. Mean MOCA score was 23 ± 5.5 and AMTS 8.5 ± 1.8.The number of patients with either a significant AMTS or MOCA was 43% and 54% of these patients had delirium. Given the high prevalence of cognitive impairment in HD and CKD patients, there were fewer renal patients with a prior diagnosis of dementia than expected. Moreover, we found a high level of undiagnosed delirium which confers a morbidity and mortality burden. Of note the CSHA frailty scale and CCI did not correlate with worse AMTS or MOCA results, suggesting that cognitive impairment could not be predicted by frailty and multi-morbidity and further research is required to understand the reasons for this.

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)0.005
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.287
Teacher spread0.260 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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