Evidence map›Paper›PMID 38183571›Full record

ArticleDrugs - real world outcomes2024

Evaluation of Triple Whammy Prescriptions After the Implementation of a Drug Safety Algorithm.

Hendrike Dahmke, Jana Schelshorn, Rico Fiumefreddo, Philipp Schuetz, Ali Reza Salili, Francisco Cabrera-Diaz, Carla Meyer-Massetti, Claudia Zaugg

Open access · goldAbstract read
In one paragraph

Article in Drugs - real world outcomes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Hendrike Dahmke *Hospital Pharmacy, Kantonsspital Aarau AG, Aarau, Switzerland. hendrike.dahmke@ksa.ch.ORCID http://orcid.org/0000-0002-8716-8660
Jana Schelshorn *Hospital Pharmacy, Kantonsspital Aarau AG, Aarau, Switzerland.ORCID http://orcid.org/0009-0001-2318-7029
Rico FiumefreddoMedical University Clinic, General Internal and Emergency Medicine, Kantonsspital Aarau AG, Aarau, Switzerland.
Philipp SchuetzMedical University Clinic, General Internal and Emergency Medicine, Kantonsspital Aarau AG, Aarau, Switzerland.
Ali Reza SaliliPinmed Gemeinschaftspraxis, Wallisellen, Switzerland.
Francisco Cabrera-DiazHospital Pharmacy, General University Hospital of Ciudad Real, Ciudad Real, Spain.ORCID http://orcid.org/0000-0003-2666-086X
Carla Meyer-MassettiClinical Pharmacology and Toxicology, Department of General Internal Medicine, Inselspital-University Hospital Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0002-3523-5729
Claudia ZauggHospital Pharmacy, Kantonsspital Aarau AG, Aarau, Switzerland.ORCID http://orcid.org/0009-0001-9875-2125
Kantonsspital Aarau · CHUniversity of Bern · CHHospital General Universitario de Ciudad Real · ESUniversity of Basel · CH

Funding

GSASA Research Grant 2020
6 · The paper itself

Abstract

BACKGROUND AND

objectiveThe term triple whammy (TW) refers to the concomitant use of non-steroidal anti-inflammatory drugs, diuretics, and angiotensin system inhibitors; this combination significantly increases the risk of acute kidney injury (AKI). To prevent this serious complication, we developed an electronic algorithm that detects TW prescriptions in patients with additional risk factors such as old age and impaired kidney function. The algorithm alerts a clinical pharmacist who then evaluates and forwards the alert to the prescribing physician.

methodsWe evaluated the performance of this algorithm in a retrospective observational study of clinical data from all adult patients admitted to the Cantonal Hospital of Aarau in Switzerland in 2021. We identified all patients who received a TW prescription, had a TW alert, or developed AKI during TW therapy. Algorithm performance was evaluated by calculating the sensitivity and specificity as a primary endpoint and determining the acceptance rate among clinical pharmacists and physicians as a secondary endpoint.

resultsAmong 21,332 hospitalized patients, 290 patients had a TW prescription, of which 12 patients experienced AKI. Overall, 216 patients were detected by the alert algorithm, including 11 of 12 patients with AKI; the algorithm sensitivity is 88.3% with a specificity of 99.7%. Physician acceptance was high (77.7%), but clinical pharmacists were reluctant to forward the alerts to prescribers in some cases.

conclusionThe TW algorithm is highly sensitive and specific in identifying patients with TW therapy at risk for AKI. The algorithm may help to prevent AKI in TW patients in the future.

Identifiers

PMID38183571
PMCPMC10928054
OpenAlexW4390639224

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.