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P253 Evaluation of the ottawa COPD risk scale (OCRS) at royal stoke university hospital (RSUH), UK in predicting adverse outcome in COPD exacerbation

2019· article· en· W2983130304 on OpenAlexaboutno aff
M Marathe, Soo Oh, Karen Leech, Helen Stone, Imran Hussain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCOPDAdverse effectExacerbationRetrospective cohort studyEmergency medicineEmergency departmentCopd exacerbationInternal medicineAcute exacerbation of chronic obstructive pulmonary disease

Abstract

fetched live from OpenAlex

Background The OCRS is a 10 point score designed to estimate short term adverse outcomes within 14 days (1). The score is made up of admission observations, investigations (including PCO2) and comorbidities. Adverse outcomes include death within 30 days, NIV/intubation, significant coronary events and early readmission. The aim of this project was to validate this score for the population at RSUH, UK and compare it to more established scores such as PEARL. Methods We performed a retrospective review of 129 patients who presented to the emergency department at RSUH in December 2018. We used electronic records to calculate each patient’s OCRS and determine the rate of adverse outcomes. We used the pre-existing BTS COPD audit forms to compare the patient’s PEARL and DECAF scores. Results Figure 1 shows the number of patients per score and the rate of adverse outcomes. 45 patients had no Arterial Blood Gas (ABG) and 42 patients had no electrocardiograms on admission. All 4 patients with OCRS score of 0 who had an adverse outcome had no ABG. The PEARL score gave a more useful estimation of readmission with 7% 30-day-readmission for PEARL score 0 – 1 and 40% 30-day-readmission for PEARL score 5 – 7. The 30 and 90 day readmission rates for the OCRS categories were calculated and showed no correlation. Discussion Although the OCRS does seem to predict adverse outcomes in the highest scores (above 6), it does not help to differentiate between the lower scores. However, there are several limitations to this retrospective study including the inconsistent availability of admission ABGs, particularly in the lower risk groups. If this was available, a clearer risk stratification may have been possible. It is unclear however whether advocating ABGs during a busy acute take purely for the aim of risk stratification is justified. The PEARL score, which was designed to predict re-admission risk, was able to predict more successfully the 30 and 90 day readmission rates. We recommend using this score in supporting discharge and targeting resources aimed at reducing readmission.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.274
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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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