Algorithm for diagnosis of postoperative urinary retention through bedside bladder ultrasound: a methodological study
Abstract Objective To develop and validate a clinical algorithm for the nursing diagnosis of urinary retention using bedside bladder ultrasound in adult patients in the immediate postoperative period of hip or knee arthroplasty. Methods Methodological study to develop a practical implementation product that was developed in two stages: (1) elaboration and formatting of the algorithm and (2) validation of the content of the algorithm; this was elaborated by 127 experts from all over Brazil in the period from May to August 2022, using the Content Validation Index (CVI) and considering values ≥0.80 as acceptable. Results The algorithm was submitted to expert evaluation, being validated with an overall CVI of 0.842 in both groups of experts, with (CVI=0.848) or without (CVI=0.822) experience in bladder ultrasound, presenting satisfactory agreement rates. Conclusion The algorithm was validated with high agreement by a relevant number of experts. It can be implemented in postoperative lower limb arthroplasty treatment units. Its use makes it possible to identify the nursing diagnosis of urinary retention and supports decision-making on the safe performance of bladder catheterization based on the estimated urinary volume using bedside bladder ultrasonography.
Authors
- José Melquíades Ramalho Neto (ORCID: https://orcid.org/0000-0002-4720-9085)
- Priscilla Alfradique de Souza (ORCID: https://orcid.org/0000-0002-4625-7552)
- Graziele Ribeiro Bitencourt (ORCID: https://orcid.org/0000-0002-9130-9307)
- Carlos Alexandre dos Santos Farias (ORCID: https://orcid.org/0000-0002-7426-5912)
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Universidade Federal da Paraíba (BR)
- Universidade Federal do Estado do Rio de Janeiro (BR)
Publication Details
- Journal
- Acta Paulista de Enfermagem
- Published
- 2025-01-01
- DOI
- https://doi.org/10.37689/acta-ape/2025ao0003223i
- Primary Topic
- Urinary Tract Infections Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00