ArticleSurgical endoscopy2026
Internal validation of the Tampa Robotic Difficulty Scoring System: real-time assessment of the novel robotic scoring system in predicting financial costs of hepatectomy.
Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe robotic approach in hepatectomy is becoming increasingly prevalent, necessitating a dedicated difficulty scoring system tailored for robotic operations. The Tampa Robotic Difficulty Score serves this purpose by offering a novel robotic-specific scoring system designed to enhance preoperative surgical planning and predict potential technical challenges in robotic hepatectomies. Following its conceptualization, we sought to internally validate the Tampa Difficulty Score by correlating it with financial variables based on our recent cohort of patients, extending the score's applicability beyond clinical outcomes alone to encompass economic or financial factors.
methodsWe retrospectively applied the Tampa Difficulty Score to our latest cohort of 124 patients who underwent robotic hepatectomy. Patients were stratified into four technical difficulty levels: Group 1 (1-8, n = 16), Group 2 (9-24, n = 86), Group 3 (25-32, n = 17), and Group 4 (33-49, n = 5). We then examined the association between the groups and various financial metrics, including total hospital charges, variable costs, fixed costs, and hospital reimbursements. A one-way ANOVA was utilized for comparisons among the groups. Data are presented as median (mean ± standard deviation). Statistical significance was accepted at p ≤ 0.05.
resultsAnalysis revealed a significant association between the Tampa Difficulty Score and financial metrics. With an increase in difficulty score, there was a significant increase in total hospital charges (p < 0.001), variable costs (p < 0.001), and fixed direct (p < 0.001) and indirect costs (p = 0.017). In contrast, hospital reimbursements did not linearly increase with the procedural complexity, leading to a non-proportionate financial burden on healthcare facilities, specifically seen in the most complex cases (Group 4).
conclusionsThe Tampa Difficulty Score has demonstrated its utility not only in predicting perioperative clinical outcomes in patients undergoing robotic hepatectomy but also in projecting the financial impacts of robotic hepatectomy to payors and providing institution. This dual predictive capacity is valuable in preoperative surgical planning, resource allocation, and financial risk assessment. External validation of the Tampa Difficulty Score is an important next step to confirm its effectiveness in other healthcare settings and economic structures.
Indexed as
Identifiers
41545571What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.