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Record W4380852916 · doi:10.1016/j.jiph.2023.06.010

The effect of Telehealth Antimicrobial Stewardship Program (Tele-ASP) on antimicrobial use in a pediatric intensive care unit: Pre- and post-implementation single center study

2023· article· en· W4380852916 on OpenAlexaff
Abdulla Alfraij, Ahmed Abushaisha Abdelmoniem, Mohamed Elseadawy, Mohammad Surour, Mohamed Basuni, Jesse Papenburg, Mohammad Alghounaim

Bibliographic record

VenueJournal of Infection and Public Health · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineAntimicrobial stewardshipPediatric intensive care unitAntimicrobialBronchiolitisEmergency medicineTelehealthPneumoniaIntensive care unitPediatricsIntensive care medicineAntibioticsTelemedicineInternal medicineAntibiotic resistanceHealth careRespiratory system

Abstract

fetched live from OpenAlex

BACKGROUND: Overuse or misuse of antimicrobials is common in pediatric intensive care units (PICU) and may be associated with poor clinical outcomes. Although an antimicrobial stewardship program (ASP) has been found to improve this practice, the required expertise in infectious diseases may be limited in some centers. We aimed to evaluate the effect of telehealth ASP on the rate of PICU antimicrobial use in a center without a local Infectious Diseases consultation service. METHODS: A retrospective cohort study was performed between October 1st, 2018, and October 31st, 2020, in Farwaniya Hospital PICU, a 20-bed unit. All pediatric patients who were admitted to PICU and received systemic antimicrobials during the study period were included and followed until hospital discharge. The ASP team provided weekly prospective audit and feedback on antimicrobial use starting October 8th, 2019. A pediatric infectious diseases specialist joined the ASP rounds remotely. Descriptive analyses and a pre-post intervention comparison of days of therapy (DOT) were used to assess the effectiveness of the ASP intervention. RESULTS: There were 272 and 156 PICU admissions received systemic antimicrobial before and after the initiation of ASP, respectively. Bronchiolitis and pneumonia were the most common admission diagnoses, together compromising 60.7% and 61.2% of cases pre- and post-ASP. The requirement for respiratory support was higher post-ASP (76.5% vs. 91.5%, p < 0.001). Average monthly antimicrobial use decreased from 922 (95%CI 745-1000) to 485 DOT/1000 patient-days (95%CI 246-722, P < 0.05). A decline in DOT was observed across most antibiotic classes, except for ceftriaxone. No effect on the length of PICU stay, length of hospitalization, or mortality was observed. Most (89.7%) ASP recommendations were followed either fully or partially. CONCLUSION: In settings where Infectious Diseases consultation services are unavailable, PICU telehealth ASP can be effectively implemented and associated with significantly reducing antimicrobial use.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.335
Teacher spread0.308 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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