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Record W1983241574 · doi:10.1111/jgs.12130

Predictive Validity of Different Modified Versions of the Identification of Seniors At Risk

2013· letter· en· W1983241574 on OpenAlexaboutno aff
Fabio Salvi, Andrea Belluigi, Antonio Cherubini

Bibliographic record

VenueJournal of the American Geriatrics Society · 2013
Typeletter
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolypharmacyMedicineTriageEmergency departmentGeriatricsAdverse effectEmergency medicinePsychiatryIntensive care medicineInternal medicine

Abstract

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To the Editor: An emergency department (ED) visit is a sentinel event for declining health status in older adults, and it should prompt appropriate assessment and care. Some screening tools have been suggested to identify older adults at high risk of adverse outcomes after an ED visit.1 The Identification of Seniors at Risk (ISAR), developed in Canada,2, 3 has been validated in elderly Italian adults in the ED, in whom it was able to predict 6-month ED revisit, hospitalization, functional decline, and death,4 as well as, in a recent, larger study, 30-day ED return.5 This tool consists of six yes-or-no items that determine functional status, previous hospital admission, complaints of cognitive and visual impairment, and polypharmacy (>3 drugs). An unresolved concern is the poor performance of the polypharmacy item in predicting adverse ED outcomes.4 A higher threshold for this item has been suggested to improve overall accuracy and specificity of the ISAR6 that would be more consistent with the common definition of polypharmacy (≥5 drugs), so the aim of the current study was to verify the usefulness of increasing the cutoff used to define polypharmacy in the ISAR using a secondary analysis in the individuals in the ED enrolled in the second study.5 Between January and June 2009, triage nurses administered the ISAR to 2,057 elderly adults (≥65). Individuals who were admitted to the hospital or discharged from the ED were enrolled. In the case of repeated ED visits during the enrollment period, only the first was considered. A 6-month follow-up was conducted by consulting hospital and administrative databases and death registers. Three different cutoffs for the polypharmacy item have been considered: more than three different medications everyday (the original ISAR), five or more medications (ISAR5), and eight or more medications (ISAR8). The ISAR was considered positive if the score was 2 or more out of 6, independent of the polypharmacy cutoff used. Sensitivity, specificity, area under the receiver operating characteristic curve (AUC), positive and negative predictive values (PPV, NPV), and odds (ORs) and hazard ratios (HRs) were calculated for admission at index ED visit; in-hospital mortality; 30-day ED return; and 6-month ED revisit, hospital readmission, and mortality. The test was positive in 1,395 patients (68%) with the ISAR, 1,269 (62%) with the ISAR5, and 1,156 (56%) with the ISAR8. Performance of the three ISAR versions is shown in Table 1. All of the ISAR versions were able to predict the need for hospitalization at the index ED visit, in-hospital mortality, ED revisit (within 30 days and 6 months), and 6-month rehospitalization and death, but the ISAR5 had a slight lower sensitivity and a higher specificity than the original ISAR for all of the considered outcomes. The ISAR8 had a further slight loss in sensitivity and a further increase in specificity for all of the outcomes. The usefulness of valid, rapid, low-cost instruments to provide early identification of older people at risk of adverse health outcomes after an ED visit cannot be overemphasized. The ISAR, independent of the cutoff of the polypharmacy item, is able to predict early and late ED return, hospitalization, functional decline, and death within 6 months after an ED visit,2-5 probably because it is able to identify frailty in these individuals.7 A higher cutoff for the polypharmacy item could improve ISAR performance; the current study found a progressive increase in specificity coupled with a slight progressive decrease in sensitivity (Table 1), but AUC, PPV, and NPV were substantially unaffected. The use of different ISAR versions could allow more-appropriate selection of older adults in the ED who could benefit from geriatric interventions, depending on resource availability. Polypharmacy is associated with higher risk of adverse drug reactions, drug interactions, nonadherence, poorer functional status, and various geriatric syndromes, as well as for many adverse health outcomes,8 but there is no consensus as to what number should define polypharmacy. It has been arbitrarily defined as taking from two to nine medications concurrently,9 and a recent article suggested that five or more medications is associated with adverse outcomes in community-dwelling older adults.10 All of these data could help in determining the best cutoff for the ISAR polypharmacy item. In conclusion, the ISAR was confirmed as a good screening tool for frail elderly adults in the ED, allowing their selection for geriatric interventions on the basis of local organizational and economic resources. Further studies are warranted to investigate the role of polypharmacy per se as a risk factor for adverse outcomes after an ED visit. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: F. Salvi wrote the manuscript and collected and analyzed the data. A. Belluigi collected the data. A. Cherubini critically revised the manuscript and gave final approval. Sponsor's Role: No sponsor.

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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)0.005
metaresearch head score (Gemma)0.037
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 score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.037
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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)0.0030.000

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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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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Citations5
Published2013
Admission routes1
Has abstractyes

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