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Background <p>Quantifying learning in robotic pancreaticoduodenectomy (RPD) can be challenging because case selection and conversions complicate the interpretation of full-procedure metrics. MyIntuitive intraoperative telemetry provides objective, process-level signals that may help to capture proficiency gains.</p> Methods <p>We analysed 100 consecutive RPD attempts by a single surgeon (January 2022–August 2025). The primary outcome was Full-Case idle time from MyIntuitive telemetry among completed robotic cases. Key secondary telemetry outcomes included console time, active time, arm-specific activity, and instrument exchanges. As secondary corroboration on an intention-to-treat (ITT) basis, the probability of robotic completion (no conversion) was modelled across case order with risk-adjusted (RA)-CUSUM and spline logistic regression; conversions were characterised by timing and reason on video review.</p> Results <p>Telemetry demonstrated marked efficiency gains across the curve. Idle time fell from 42 to 32&#xa0;min (<i>P</i> = 0.001), console time from 470 to 395&#xa0;min (<i>P</i> &lt; 0.001), and active time from 428 to 365&#xa0;min (<i>P</i> &lt; 0.001) between the initial (cases 1–60) and proficiency (&gt; 60) phases; Arm-4 active time decreased from 40 to 17&#xa0;min (<i>P</i> = 0.027). The RA-CUSUM of idle time showed a proficiency inflection near cases 50–60. Supportive resection-phase telemetry showed shorter time to complete mesopancreas dissection (from 323 to 215&#xa0;min, <i>P</i> = 0.002). On ITT analysis, conversion occurred in 17% overall, declining from 23.3 to 7.5% after case 60 (<i>P</i> = 0.033); no emergency conversions occurred. Perioperative outcomes included POPF 29%, postpancreatectomy haemorrhage 8%, ≥ Clavien–Dindo III 22%, reoperation 9%, 90-day readmission 9%, 90-day mortality 2%, and median length of stay 16&#xa0;days.</p> Conclusion <p>A telemetry-based primary endpoint (MyIntuitive idle time) sensitively tracks the RPD learning curve and, with risk-adjusted CUSUM, identifies a proficiency threshold around ~ 60 cases. Secondary ITT completion trends and conversion mapping corroborate the telemetry signal. This telemetry-first framework provides objective, phase-specific insight to guide coaching and programme maturation in complex robotic pancreatic surgery.</p>

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MyIntuitive telemetry identifies proficiency thresholds in robotic pancreaticoduodenectomy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月5日

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  • Carolina González-Abós,
  • Luis Guillermo Reyes,
  • Claudia Lorenzo,
  • Fabio Ausania

摘要

Background

Quantifying learning in robotic pancreaticoduodenectomy (RPD) can be challenging because case selection and conversions complicate the interpretation of full-procedure metrics. MyIntuitive intraoperative telemetry provides objective, process-level signals that may help to capture proficiency gains.

Methods

We analysed 100 consecutive RPD attempts by a single surgeon (January 2022–August 2025). The primary outcome was Full-Case idle time from MyIntuitive telemetry among completed robotic cases. Key secondary telemetry outcomes included console time, active time, arm-specific activity, and instrument exchanges. As secondary corroboration on an intention-to-treat (ITT) basis, the probability of robotic completion (no conversion) was modelled across case order with risk-adjusted (RA)-CUSUM and spline logistic regression; conversions were characterised by timing and reason on video review.

Results

Telemetry demonstrated marked efficiency gains across the curve. Idle time fell from 42 to 32 min (P = 0.001), console time from 470 to 395 min (P < 0.001), and active time from 428 to 365 min (P < 0.001) between the initial (cases 1–60) and proficiency (> 60) phases; Arm-4 active time decreased from 40 to 17 min (P = 0.027). The RA-CUSUM of idle time showed a proficiency inflection near cases 50–60. Supportive resection-phase telemetry showed shorter time to complete mesopancreas dissection (from 323 to 215 min, P = 0.002). On ITT analysis, conversion occurred in 17% overall, declining from 23.3 to 7.5% after case 60 (P = 0.033); no emergency conversions occurred. Perioperative outcomes included POPF 29%, postpancreatectomy haemorrhage 8%, ≥ Clavien–Dindo III 22%, reoperation 9%, 90-day readmission 9%, 90-day mortality 2%, and median length of stay 16 days.

Conclusion

A telemetry-based primary endpoint (MyIntuitive idle time) sensitively tracks the RPD learning curve and, with risk-adjusted CUSUM, identifies a proficiency threshold around ~ 60 cases. Secondary ITT completion trends and conversion mapping corroborate the telemetry signal. This telemetry-first framework provides objective, phase-specific insight to guide coaching and programme maturation in complex robotic pancreatic surgery.