Background: Learning curves describe the rate of performance improvements according to the surgeon's caseload, followed by a plateau where limited additional improvements are observed. The aim of this study was to evaluate the learning curve for robotic-assisted transabdominal preperitoneal repair (rTAPP) for inguinal hernias in surgeons already experienced in laparoscopic TAPP.

Methods: The study was approved by local ethic committee. Male patients undergoing rTAPP for inguinal hernia from October 2017 to December 2019 at the Bellinzona Regional Hospital were selected from a prospective database. Demographic and clinical data, including operative time, conversion to laparoscopic or open surgery, intra- and postoperative complications were collected and analyzed.

Results: Over the study period, 170 rTAPP were performed by three surgeons in 132 patients, and mean age was 60.1 ± 13.7 years. The cumulative summation (CUSUM) test showed a significant operative time reduction after the 43 operation, once the 90% proficiency on the logarithmic tendency line was achieved. The corrected operative time resulted 71.1 ± 22.0 vs. 60.8 ± 13.5 min during and after the learning curve (p = 0.011). Only one intraoperative complication occurred during the learning curve and required an orchiectomy. Postoperatively, three complications (one seroma, one hematoma, and one mesh infection) required invasive interventions during the learning curve, while no cases were recorded after it (p = 0.312).

Conclusion: Our study shows that the rTAPP, performed by experienced laparoscopists, has a learning curve which requires 43 inguinal hernia repairs to achieve 90% proficiency and to significantly reduce the operative time.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00464-020-08165-4DOI Listing

Publication Analysis

Top Keywords

learning curve
24
operative time
16
rtapp inguinal
12
curve robotic-assisted
8
robotic-assisted transabdominal
8
transabdominal preperitoneal
8
preperitoneal repair
8
repair rtapp
8
inguinal hernias
8
inguinal hernia
8

Similar Publications

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic models to personalize treatment strategies for IPF patients.

View Article and Find Full Text PDF

Trustworthiness of a machine learning early warning model in medical and surgical inpatients.

JAMIA Open

February 2025

Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN 55905, United States.

Objectives: In the general hospital wards, machine learning (ML)-based early warning systems (EWSs) can identify patients at risk of deterioration to facilitate rescue interventions. We assess subpopulation performance of a ML-based EWS on medical and surgical adult patients admitted to general hospital wards.

Materials And Methods: We assessed the scores of an EWS integrated into the electronic health record and calculated every 15 minutes to predict a composite adverse event (AE): all-cause mortality, transfer to intensive care, cardiac arrest, or rapid response team evaluation.

View Article and Find Full Text PDF

Background: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their simultaneous occurrence are unclear.

View Article and Find Full Text PDF

VASARI 2.0: a new updated MRI VASARI lexicon to predict grading and status in brain glioma.

Front Oncol

December 2024

NeuroRadiology Unit, Ospedale del Mare, Azienda Sanitaria Locale Napoli 1 Centro (ASL NA1 Centro), Naples, Italy.

Introduction: Precision medicine refers to managing brain tumors according to each patient's unique characteristics when it was realized that patients with the same type of tumor differ greatly in terms of survival, responsiveness to treatment, and toxicity of medication. Precision diagnostics can now be advanced through the establishment of imaging biomarkers, which necessitates quantitative image acquisition and processing. The VASARI (Visually AcceSAble Rembrandt Images) manual annotation methodology is an ideal and suitable way to determine the accurate association between genotype and imaging phenotype.

View Article and Find Full Text PDF

Background: Diagnosis of cardiac amyloidosis (CA) is often missed or delayed due to confusion with other causes of increased left ventricular wall thickness. Conventional transthoracic echocardiographic measurements like global longitudinal strain (GLS) has shown promise in distinguishing CA, but with limited specificity. We conducted a study to investigate the performance of a computer vision detection algorithm in across multiple international sites.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!