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Record W4226321927 · doi:10.1111/ijun.12306

Degarelix administration technique optimisation: Consensus findings of an international Delphi nurse panel

2022· article· en· W4226321927 on OpenAlexaboutno aff
Paula Allchorne, Sacha Ali, Philip Cornford

Bibliographic record

VenueInternational Journal of Urological Nursing · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInjection siteDelphi methodSubcutaneous injectionInternal medicine

Abstract

fetched live from OpenAlex

Abstract What steps involved in degarelix (Firmagon®, Ferring Pharmaceuticals) administration and patient care do specialist nurses consider most important to reduce the risk of associated injection site reactions, and are there any variations in administration and materials used to support optimal injection technique? Degarelix is a GnRH antagonist indicated for the first‐line treatment of advanced prostate cancer that effectively suppresses testosterone production in the testes without an initial testosterone surge and possible subsequent disease flare—both typical features associated with GnRH agonists. However, injection site reactions can occur after subcutaneous injection of degarelix, which are unpleasant for patients and may represent a limiting factor for its use by healthcare professionals. The objective of this study was to reach consensus on key steps involved in degarelix administration and patient care to minimise injection site reaction risk. Injection site reactions have been associated with subcutaneous injection of degarelix in several published studies; they are usually transient, mild‐to‐moderate, and occur mainly with the initial dose. Information on prevention is limited, one research group suggesting that the injection method may contribute to injection site reaction risk, and another describing specific injection techniques and strategies developed by Canadian nurses and physicians aiming to prevent degarelix injection site reactions. An online pre‐meeting survey regarding degarelix administration and injection site reactions was conducted to gather insights from 11 international specialist nurses. Survey results supported the development of 25 best practice consensus statements for the in‐person Delphi meeting (Warsaw, Poland), attended by 15 international specialist nurses. Statements focused on degarelix reconstitution, administration and patient care. Participants voted anonymously and collated responses were discussed after each voting round to understand if consensus could be achieved. If no consensus was reached after the first voting round, up to two more voting rounds were considered. Consensus was defined as “agreement” or “disagreement” by ≥75% of nurses, with ≤15% having the opposite opinion. In the pre‐meeting survey, nurses reported that they observed injection site reactions in up to a third of treated patients after degarelix injection, and all agreed that the administration technique was, to some degree, related to the development of injection site reactions; a variety of materials were being used as guidance. In the Delphi study, consensus was reached on 5 of 9 statements related to reconstitution steps and 14 of 16 statements related to administration steps and patient care, all of which were considered to be important in the prevention of injection site reactions. This study confirmed country‐specific variations in the degarelix administration technique and highlighted pivotal steps that may potentially contribute to injection site reactions. Importantly, all nurses agreed that technique optimisation holds the potential to reduce the occurrence of such reactions (“yes,” 45%; “possibly,” 55%; “no,” 0%). The findings should be considered along with other available materials and guidance to help reduce the risk of injection site reactions in patients with advanced prostate cancer treated with degarelix.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.063
GPT teacher head0.390
Teacher spread0.327 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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