Evidence map›Paper›PMID 37600114›Full record

ArticleAnnals of surgery open : perspectives of surgical history, education, and clinical approaches2022

Complexity-Adjusted Learning Curves for Robotic and Laparoscopic Liver Resection: A Word of Caution.

Felix Krenzien, Christian Benzing, Linda Feldbrügge, Santiago Andres Ortiz Galindo, Karl Hillebrandt, Nathanael Raschzok, Nora Nevermann, Philipp Haber, Thomas Malinka, Wenzel Schöning and 2 more

Abstract read
In one paragraph

Article in Annals of surgery open : perspectives of surgical history, education, and clinical approaches, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. International Benchmark Values for Robotic Right Hepatectomy: Multicenter Study From 22 Expert Centers.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Observational
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Felix KrenzienFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Christian BenzingFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Linda FeldbrüggeBerlin Institute of Health (BIH), Berlin, Germany.
Santiago Andres Ortiz GalindoFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Karl HillebrandtFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Nathanael RaschzokFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Nora NevermannFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Philipp HaberFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Thomas MalinkaFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Wenzel SchöningFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Johann PratschkeFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.
Moritz SchmelzleFrom the Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Minimally invasive liver surgery (MILS) has a high variance in the type of resection and complexity, which has been underestimated in learning curve studies in the past. The aim of this work was to evaluate complexity-adjusted learning curves over time for laparoscopic liver resection (LLR) and robotic liver resection (RLR). Methods: Cumulative sum analysis (CUSUM) and complexity adjustment were performed using the Iwate score for LLR and RLR (n = 647). Lowest point of smoothed data was used to capture the cutoff of the increase in complexity. Data were collected retrospectively at the Department of Surgery of the Charité-Universitätsmedizin Berlin. Results: A total of 132 RLR and 514 LLR were performed. According to the complexity-adjusted CUSUM analysis, the initial learning phase was reached after 117 for LLR and 93 procedures for RLR, respectively. With increasing experience, the rate of (extended) right hemihepatectomy multiplied from 8.4% to 18.9% for LLR ( Conclusions: The learning phase for MILS after adjusting for complexity is about 4 times longer than assumed in previous studies, which should urge caution.

Identifiers

PMID37600114
PMCPMC10431481

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.