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Tokyo Classification Based Decision-Making Algorithm For Acute Cholecystitis: A Prospective Validation Study

Shaheen Akbar, Dharamveer Jajra, Udesh Rajpurohit, Manohar L. Dawan, Sunder Kishore, Diwan Singh Jakhar

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New Indian Journal of Surgery 17(2):p 49-57, April-June 2026. | DOI: https://doi.org/10.21088/nijs.0976.4747.17226.2

How Cite This Article:

Shaheen Akbar, Dharamveer Jajra, Udesh Rajpurohit, et al. Robotic Inguinal Hernia Repair: Tokyo Classification Based Decision- Making Algorithm For Acute Cholecystitis: A Prospective Validation Study. New Indian J Surg. 2025; 17(2): 49-58.

Timeline

Received : April 29, 2026         Accepted : June 02, 2026          Published : June 30, 2026

Abstract

Background: Acute cholecystitis remains a common surgical emergency with variable management approaches. The Tokyo Guidelines 2018 (TG18) provide a standardized severity grading system and treatment algorithm, yet prospective validation comparing TG18-guided management with traditional clinical judgment remains limited. This study aimed to validate the clinical utility of TG18-based decision-making in improving patient outcomes. Methods: This prospective comparative study was conducted at the Department of General Surgery, Sardar Patel Medical College, Bikaner. A total of 124 patients with acute cholecystitis were randomized into two groups: Group A (n=83) managed according to TG18 protocol, and Group B (n=41) managed using traditional clinical judgment. Primary outcome was total complication rate. Secondary outcomes included specific complications (bile leak, ICU requirement, post-operative infection, 30-day readmission) and length of hospital stay. Statistical analysis included chi-square test, t-test, and multivariate logistic regression. Results: Tokyo severity grade distribution was comparable between groups (p=0.624). Total complication rate was significantly lower in Group A compared to Group B (16.9% vs 43.9%, p=0.001; OR 3.84, 95% CI 1.67–8.82). Bile leak occurred in 1.2% versus 31.7% (p<0.001), ICU requirement in 4.8% versus 26.8% (p=0.001), and 30-day readmission in 1.2% versus 12.2% (p=0.014). Mean hospital stay was significantly shorter in Group A (4.4±1.6 vs 11.0±4.8 days, p<0.001). Laparoscopic cholecystectomy rate was higher in Group A (69.9% vs 29.3%, p<0.001). Multivariate analysis confirmed TG18 guidance as independently protective (adjusted OR 2.89, 95% CI 1.12–7.46, p=0.028). Conclusion: TG18-guided management significantly reduces complications and hospital stay in acute cholecystitis. Implementation of Tokyo Guidelines 2018 as standard protocol is recommended for optimal patient outcomes.


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Data Sharing Statement

There are no additional data available. All raw data and code are available upon request.

Funding

This research received no funding.

Author Contributions

All authors contributed significantly to the work and approve its publication.

Ethics Declaration

This article does not involve any human or animal subjects, and therefore does not require ethics approval.

Acknowledgements

We would like to express our gratitude to the patients, their families, and all those who have contributed to this study.

Conflicts of Interest

No conflicts of interest in this work.


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Cite this article

Shaheen Akbar, Dharamveer Jajra, Udesh Rajpurohit, et al. Robotic Inguinal Hernia Repair: Tokyo Classification Based Decision- Making Algorithm For Acute Cholecystitis: A Prospective Validation Study. New Indian J Surg. 2025; 17(2): 49-58.


Licence:

Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)

This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.


Received Accepted Published
April 29, 2026 June 02, 2026 June 30, 2026

DOI: https://doi.org/10.21088/nijs.0976.4747.17226.2

Keywords

Acute cholecystitisTokyo Guidelines 2018Laparoscopic cholecystectomySeverity gradingClinical decision-makingSurgical outcomesProspective study

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Received April 29, 2026
Accepted June 02, 2026
Published June 30, 2026

licence


Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)

This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.


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