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Record W2167975469 · doi:10.1093/jac/45.3.387

Use of a treatment protocol in the management of community-acquired lower respiratory tract infection

2000· article· en· W2167975469 on OpenAlexfundno aff
Fahad As Al-Eidan, James C. McElnay, Michael Scott, Mary P. Kearney, J. Corrigan, J. McConnell

Bibliographic record

VenueJournal of Antimicrobial Chemotherapy · 2000
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
FundersQueen's University
KeywordsMedicineLower respiratory tract infectionRespiratory tract infectionsEmergency medicineClinical trialPharmacyProtocol (science)Intensive care medicinePediatricsInternal medicineRespiratory systemFamily medicineAlternative medicine

Abstract

fetched live from OpenAlex

The aim of the present study was to examine the impact of an antimicrobial prescribing protocol on clinical and economic outcome measures in hospitalized patients with community-acquired lower respiratory tract infection (LRTI). The study was performed as a prospective controlled clinical trial within the medical wards at Antrim Area Hospital, Northern Ireland. Data were collected on all hospitalized adult patients with a primary diagnosis of LRTI during the period December 1994 to February 1995 (normal hospital practice; control group; n = 112). After an LRTI management protocol (medical, microbiological and pharmacy staff) had been developed, all hospitalized adult patients with a primary diagnosis of LRTI over the period December 1995 to February 1996 formed the intervention group (treated according to the protocol; n = 115). The results showed a statistically significant impact of the protocol in terms of clinical and economic outcome measures. Patients treated using the algorithmic prescribing protocol had significant reductions in length of hospital stay (geometric mean 4.5 versus 9.2 days), iv drug administration (34.8% versus 61.6%), duration of iv therapy (geometric mean 2.1 versus 5.7 days) and treatment failures (7.8% versus 31.3%). Healthcare costs were also significantly reduced. The use of the protocol was a major factor in streamlining the prescribing of antimicrobial therapy for community-acquired LRTI and led to more cost-effective patient management.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

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

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 head0.053
GPT teacher head0.339
Teacher spread0.287 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations50
Published2000
Admission routes1
Has abstractyes

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