Exploratory analysis on the usage of Pi-score algorithm over endoscopic stone treatment step 1 protocol.


Journal

Minerva urology and nephrology
ISSN: 2724-6442
Titre abrégé: Minerva Urol Nephrol
Pays: Italy
ID NLM: 101777299

Informations de publication

Date de publication:
10 2021
Historique:
pubmed: 5 8 2020
medline: 15 12 2021
entrez: 5 8 2020
Statut: ppublish

Résumé

The Performance Improvement score (Pi-score) has been proven to be reliable to measure performance improvement during E-BLUS hands-on training sessions. Our study is aimed to adapt and test the score to EST s1 (Endoscopic Stone Treatment step 1) protocol, in consideration of its worldwide adoption for practical training. The Pi-score algorithm considers time measurement and number of errors from two different repetitions (first and fifth) of the same training task and compares them to the relative task goals, to produce an objective score. Data were obtained from the first edition of 'ART in Flexible Course', during four courses in Barcelona and Milan. Collected data were independently analyzed by the experts for Pi assessment. Their scores were compared for inter-rater reliability. The average scores from all tutors were then compared to the PI-score provided by our algorithm for each participant, in order to verify their statistical correlation. Kappa statistics were used for comparison analysis. Sixteen hands-on training expert tutors and 47 3 Our exploratory study demonstrates that Pi-score can be effectively adapted to EST s1. Our algorithm successfully provided an objective score that equals the average performance improvement scores assigned by of a cohort of experts, in relation to a small amount of training attempts.

Sections du résumé

BACKGROUND
The Performance Improvement score (Pi-score) has been proven to be reliable to measure performance improvement during E-BLUS hands-on training sessions. Our study is aimed to adapt and test the score to EST s1 (Endoscopic Stone Treatment step 1) protocol, in consideration of its worldwide adoption for practical training.
METHODS
The Pi-score algorithm considers time measurement and number of errors from two different repetitions (first and fifth) of the same training task and compares them to the relative task goals, to produce an objective score. Data were obtained from the first edition of 'ART in Flexible Course', during four courses in Barcelona and Milan. Collected data were independently analyzed by the experts for Pi assessment. Their scores were compared for inter-rater reliability. The average scores from all tutors were then compared to the PI-score provided by our algorithm for each participant, in order to verify their statistical correlation. Kappa statistics were used for comparison analysis.
RESULTS
Sixteen hands-on training expert tutors and 47 3
CONCLUSIONS
Our exploratory study demonstrates that Pi-score can be effectively adapted to EST s1. Our algorithm successfully provided an objective score that equals the average performance improvement scores assigned by of a cohort of experts, in relation to a small amount of training attempts.

Identifiants

pubmed: 32748615
pii: S0393-2249.20.03747-9
doi: 10.23736/S2724-6051.20.03747-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

662-667

Auteurs

Domenico Veneziano (D)

Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal - info@domenicoveneziano.it.
ICVS/3B's Associate Laboratory, Braga, Portugal - info@domenicoveneziano.it.
Department of Urology and Kidney Transplant, Grande Ospedale Metropolitano, Reggio Calabria, Italy - info@domenicoveneziano.it.

Giulio Patruno (G)

Department of Urology, San Giovanni Addolorata Hospital, Rome, Italy.

Michele Talso (M)

Department of Urology, ASST Vimercate, Vimercate, Monza-Brianza, Italy.

Theodore Tokas (T)

Department of Urology and Andrology, General Hospital, Hall in Tirol, Austria.

Silvia Proietti (S)

Department of Urology, San Raffaele-Turro Hospital, Milan, Italy.

Angelo Porreca (A)

Department of Urology, Policlinico Abano Terme, Abano Terme, Padua, Italy.

Guido Kamphuis (G)

Department of Urology, AMC University Hospital, Amsterdam, The Netherlands.

Shekhar Biyani (S)

Department of Urology, St. James's University Hospital Leeds Teaching Hospitals NHS, Leeds, UK.

Esteban Emiliani (E)

Department of Urology, Fundaciò Puigvert, Barcelona, Spain.

Marcos Cepeda Delgado (M)

Department of Urology, Rio Hortega University, Valladolid, Spain.

Lopez M de Mar Perez (LM)

Department of Urology, Jesús Usón Center of Minimally Invasive Surgery, Caceres, Spain.

Roberto Miano (R)

Department of Urology, University of Rome Tor Vergata, Rome, Italy.

Stefania Ferretti (S)

Department of Urology, Parma University Hospital, Parma, Italy.

Nicola Macchione (N)

Department of Urology, San Paolo Hospital, Milan, Italy.

Panagiotis Kallidonis (P)

Department of Urology, University of Patras, Patras, Greece.

Emanuele Montanari (E)

Department of Urology, University Polyclinic Hospital, Milan, Italy.

Giovanni Tripepi (G)

Institute of Clinical Physiology (IFC), National Research Council (CNR), Reggio Calabria, Italy.

Achilles Ploumidis (A)

Department of Urology, Athens Medical Centre, Athens, Greece.

Giovanni Cacciamani (G)

USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Estevao Lima (E)

Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.
ICVS/3B's Associate Laboratory, Braga, Portugal.

Bhaskar Somani (B)

Department of Urology, University of Southampton, Southampton, UK.

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