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Record W4299566892 · doi:10.1002/nau.25053

Nurses' role in the management of persons with chronic urogenital pelvic pain syndromes: A scoping review

2022· review· en· W4299566892 on OpenAlexaboutno aff
Stefano Terzoni, Paolo Ferrara, Mauro Parozzi, Federica Colombani, Cristina Mora, Silvia Cilluffo, Anne Destrebecq, Barbara Pinna, Maura Lusignani, Chiara Sighinolfi, Giorgia Gaia, Bernardo Rocco

Bibliographic record

VenueNeurourology and Urodynamics · 2022
Typereview
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePelvic painPhysical therapyCINAHLMultidisciplinary approachBiofeedbackChronic painPsychological interventionNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Pelvic pain has cognitive, behavioral, sexual, and emotional consequences. Nurses involved in pelvic floor rehabilitation clinics have contacts with patients reporting chronic pain and should know the most appropriate service for patient referral, to submit the problem to professionals capable of correctly assessing and managing the condition. Furthermore, in some countries nurses can use conservative methods to treat the painful symptoms inside a multidisciplinary team such as breathing retraining, biofeedback, and noninvasive neuromodulation. This paper aims to provide an overview of the literature regarding the role of rehabilitation nurses in dealing with patients suffering from chronic urogenital pelvic pain or urogenital painful syndromes, inside a multidisciplinary team. METHODS: Scoping review on Pubmed, CINAHL, Embase, Scopus, Web of Science including trials, reviews, case studies or series, and other descriptive studies regarding the role of nurses inside the multidisciplinary team in the management of males and females presenting chronic pelvic pain (CPP) or chronic pelvic pain syndrome (CPPS). RESULTS: The 36 papers included in this review allowed answering research questions in four areas of nursing: collecting basic information, referring the person to appropriate services, evidence-based nursing interventions for CPP and CPPS, and proper documentation. Clinical history and assessment of breathing pattern, Muscular assessment and research of trigger points are the main points of data collection. Techniques for muscular relaxation and breathing retraining are important aspects of treatment, as well as biofeedback and noninvasive neuromodulation where the law allows nurses to practice such techniques. The McGill pain questionnaire and the pain inventory of the International Pain Society allow systematic data collection and handover. CONCLUSION: Rehabilitation nurses work inside multidisciplinary teams when dealing with persons suffering from pelvic pain; further research is needed as our comprehension of the underlying pathophysiological mechanisms of CPP and CPPS evolve.

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)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.001
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 head0.033
GPT teacher head0.347
Teacher spread0.314 · 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 designSystematic review
Domainnot available
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

Citations7
Published2022
Admission routes1
Has abstractyes

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