MétaCan
Menu
Back to cohort
Record W2767663110 · doi:10.18433/j3sq0b

Effectiveness of Pharmacist-led Anticoagulation Management on Clinical Outcomes: A Systematic Review and Meta-Analysis

2017· review· en· W2767663110 on OpenAlexvenueno aff
Kelu Hou, Hui Yang, Zhikang Ye, Ying Wang, Lihong Liu, Xiangli Cui

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2017
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObservational studyPharmacistCochrane LibraryMeta-analysisCohort studySystematic reviewRandomized controlled trialQuality ScoreEmergency medicineCohortInternal medicineMEDLINEIntensive care medicinePharmacyFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: We performed this systematic review and meta-analysis to confirm whether patients benefit more from pharmacist-led anticoagulation management than other models. METHODS: We searched PubMed, Embase, Cochrane Library and reference lists of yielded results conducted up to April 25, 2017. RCTs and observational cohort studies and case-control studies which compared the percentage of time within the target therapeutic range (TTR), the percentage of time within the expanded therapeutic range (TER), haemorrhage events, thrombosis events, mortality, patient satisfaction and/or medicine cost saving of pharmacist-led anticoagulation management with other models, and species were limited to humans. Two investigators evaluated methodology and extracted data from included studies independently. Data analysis were performed by STATA 12.0 software and quality of evidence assessment was performed by GRADEprofiler software. RESULTS: 8 RCTs and 9 observational cohort studies with 9919 patients were included eventually with high quality and no publication bias. In RCTs pooled results, TTR (p=0.548 moderate-quality), TER (p=0.285, moderate-quality), total haemorrhage events (p=0.140, low-quality), minor haemorrhage events (p=0.162, low-quality), major haemorrhage events (p=0.237, low-quality), thrombosis events (p=0.615, low-quality) and mortality (p=0.876, low-quality) was not significant between two groups. In observational studies pooled results, TTR (p=0.000, low-quality) was significant higher in pharmacist-led management group and the risk of total haemorrhage events (p=0.000, moderate-quality), minor haemorrhage events (p=0.000, moderate-quality) and thrombosis events (p=0.000, moderate-quality) were significant lower in pharmacist-led management group. Patient satisfaction and medicine cost saving were descriptively reviewed. CONCLUSIONS: According to the grading of evidence, we concluded that the risk of total haemorrhage events, minor haemorrhage events and thrombosis events significantly decreased in pharmacist-led anticoagulation management group compared with other management models and no significant difference in TTR, TER, major haemorrhage events and mortality between two groups. Longer follow-up period RCT studies with large sample size should be done in the future to confirm effectiveness of pharmacist-led anticoagulation management model. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

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)0.025
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.048
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0240.057
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
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 head0.651
GPT teacher head0.632
Teacher spread0.019 · 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.

Study designMeta-analysis
DomainMethods
GenreReview

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

Citations63
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy & Pharmaceutical SciencesSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207