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A novel model for prediction of pure laparoscopic liver resection surgical difficulty

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Abstract

Background

Extending the clinical indications for laparoscopic liver resection (LLR) should be carefully considered based on a surgeon’s experience and skill. However, objective indexes to help surgeons assess the estimated difficulty of LLR are scarce. The aim of our study was to develop the first objective numerical rating scale to predict the surgical difficulty of various LLR procedures.

Methods

We performed a retrospective review of the operative outcomes of 187 patients who underwent a pure LLR. First, the value of preoperative factors for predicting surgical time was evaluated by multivariate linear regression analyses, and a scoring system was constructed. Next, the integrity of our predictive linear model was evaluated against the documented operative outcomes for patients forming our study group.

Results

Four predictive factors were identified and scored based on the weighted contribution of each factor predicting surgical time: extent of resection (scored 0, 2, or 3); location of tumor (scored 0, 1, or 2); obesity (scored 0 or 1); and platelet count (scored 0 or 1). The scores were summed to classify surgical difficulty into three levels: low (total score ≤1); medium (total score 2–3); and high (total score ≥4). Operative outcomes, including surgical time, volume of blood loss, length of hospital stay, and rate of morbidity, were significantly different between the three surgical difficulty levels.

Conclusion

Our novel model will be useful for surgeons to predict the difficulty of an LLR procedure relative to their own experience and skill.

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Acknowledgements

The authors would like to thank the staff of the Department of Anesthesiology, Iwate Medical University School of Medicine for their assistance.

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Authors and Affiliations

  1. Department of Surgery, School of Medicine, Iwate Medical University, 19-1, Uchimaru, Morioka City, Iwate, 020-8505, Japan

    Yasushi Hasegawa, Go Wakabayashi, Hiroyuki Nitta, Takeshi Takahara, Hirokatsu Katagiri, Akira Umemura, Kenji Makabe & Akira Sasaki

  2. Department of Surgery, Ageo Central General Hospital, 1-10-10, Kashiwaza, Ageo City, Saitama, 362-8588, Japan

    Go Wakabayashi

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  1. Yasushi Hasegawa
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  2. Go Wakabayashi
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Correspondence to Yasushi Hasegawa.

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Drs. Yasushi Hasegawa, Go Wakabayashi, Hiroyuki Nitta, Takeshi Takahara, Hirokatsu Katagiri, Akira Umemura, Kenji Makabe, and Akira Sasaki have no conflicts of interest or financial ties to disclose.

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Hasegawa, Y., Wakabayashi, G., Nitta, H. et al. A novel model for prediction of pure laparoscopic liver resection surgical difficulty. Surg Endosc 31, 5356–5363 (2017). https://doi.org/10.1007/s00464-017-5616-8

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  • DOI: https://doi.org/10.1007/s00464-017-5616-8

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