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Record W4313886224 · doi:10.4212/cjhp.3265

Comparison of a Fully Weight-Based Protocol with a Non–Weight-Based Dosage Titration Protocol for IV Unfractionated Heparin: A Before-and-After Study

2023· article· en· W4313886224 on OpenAlexaffvenue
T. W. M. Cameron, Doson Chua, Stephen Shalansky, Edwin M. Tam, Erica Wang

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2023
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsProvidence Health CareInterior Health
Fundersnot available
KeywordsProtocol (science)TitrationHeparinMedicineChemistryPharmacologyInternal medicineOrganic chemistry

Abstract

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Background: Unfractionated heparin (UFH) is used for the prevention and treatment of arterial or venous thromboembolism. The dosage for IV infusion of UFH is generally based on the patient’s weight, with adjustment to a specific target for activated partial thromboplastin time (aPTT). In May 2019, the UFH protocols at the study institution were changed from being fully weight-based (i.e., for both initial dosing and subsequent dosage titrations) to weight-based initial dosing and non–weight-based dosage titrations, but the relative effectiveness of these 2 approaches was not known. Objectives: The primary objective was to compare the effectiveness in achieving therapeutic aPTT with the fully weight-based and non–weight-based dosage titration protocols. The secondary objective was to compare the effectiveness of the non–weight-based dosage titration protocol with that of the previous fully weight-based one for patients with low-target aPTT. Methods: A single-centre, retrospective, observational before-and-after study was conducted for patients receiving therapeutic UFH for any indication. Patients in the “before” group (fully weight-based protocol) were treated from January 2015 to October 2016, and those in the “after” group (non–weight-based titration) from January to October 2020. Results: From a total of 1969 charts screened, 137 patients treated according to the fully weight-based protocols and 130 patients treated according to the non–weight-based titration protocols were included. In terms of the co-primary objective, the median number of dosage adjustments to achieve therapeutic anticoagulation was 1 in both groups (p = 0.48), and the proportion of patients with therapeutic anticoagulation at 24 h was similar (96.2% [125/130] with the non–weight-based titration protocols versus 99.3% [136/137] with the fully weight-based protocols; p = 0.09). Among patients treated according to the low-target UFH protocols, those with the non–weight-based titration protocol were less likely to have therapeutic anticoagulation at first measurement of aPTT than those with the fully weight-based protocol (37.9% [25/66] versus 44.6% [41/92], p = 0.033). Conclusions: This retrospective, observational, before-and-after study showed that the effectiveness of the non–weight-based dosage titration protocols in achieving therapeutic aPTT was similar to that of fully weight-based UFH protocols. RÉSUMÉ Contexte : L’héparine non fractionnée (HNF) est utilisée pour la prévention et le traitement de la thromboembolie artérielle ou veineuse. La posologie de la perfusion par IV d’HNF se base généralement sur le poids du patient, avec un ajustement à un objectif précis du temps moyen de céphaline activée (TCA). En mai 2019, les protocoles d’HNF de l’établissement à l’étude sont passés d’une approche entièrement basée sur le poids (à la fois pour la posologie initiale et les titrages posologiques ultérieurs) à une posologie initiale basée sur le poids, et à des titrages posologiques non basés sur le poids. Cependant, l’efficacité relative de ces 2 approches était inconnue. Objectifs : L’objectif principal de l’étude consistait à comparer dans quelle mesure les protocoles entièrement basés sur le poids et les protocoles de titrage non basés sur le poids étaient efficaces pour atteindre le TCA thérapeutique. L’objectif secondaire consistait quant à lui à comparer l’efficacité du protocole de titrage de dose non basé sur le poids au protocole précédent entièrement basé sur le poids chez les patients ayant une faible cible de TCA. Méthodes : Une étude monocentrique, rétrospective, observationnelle avant-après a été menée chez des patients recevant de l’HNF thérapeutique, toutes indications confondues. Les patients du groupe « Avant » (protocole entièrement basé sur le poids) ont été traités de janvier 2015 à octobre 2016, et ceux du groupe « Après » (protocole de titrage de dose non basé sur le poids) de janvier à octobre 2020. Résultats : À partir de 1969 dossiers examinés, 137 patients traités selon les protocoles entièrement basés sur le poids et 130 patients traités selon les protocoles d’ajustement posologique non basés sur le poids ont été inclus. En ce qui concerne l’objectif co-principal, le nombre médian d’ajustements posologiques pour obtenir une anticoagulation thérapeutique était de 1 dans les deux groupes (p = 0,48), et la part de patients ayant une anticoagulation thérapeutique à 24 h était similaire (96,2 % [125/130] avec les protocoles non basés sur le poids contre 99,3 % [136/137] avec ceux entièrement basés sur le poids [p = 0,09]). Parmi les patients traités selon les protocoles HNF à faible cible, ceux avec le protocole de titrage non basé sur le poids étaient moins susceptibles de connaître une anticoagulation thérapeutique à la première mesure du TCA que ceux avec le protocole entièrement basé sur le poids (37,9 % [25/66] contre 44,6 % [41/92], p = 0,033). Conclusions : Cette étude rétrospective et observationnelle avant-après a montré que l’efficacité des protocoles d’ajustement posologique non basés sur le poids pour obtenir un TCA thérapeutique était similaire à celle des protocoles d’HNF entièrement basés sur le poids.

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)0.026
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.030
GPT teacher head0.371
Teacher spread0.341 · 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 designNon-randomized trial
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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Citations0
Published2023
Admission routes2
Has abstractyes

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