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J Indian Assoc Pediatr Surg ; 29(3): 256-260, 2024.
Article in English | MEDLINE | ID: mdl-38912021

ABSTRACT

Introduction: Ladd's procedure, originally described in 1936 for the treatment of malrotation, does not traditionally include appendectomy as a standard step. We conducted a multinational survey to investigate the current consensus on the role of appendectomy in Ladd's procedure. Methodology: An anonymous online survey was distributed to pediatric surgeons worldwide. The survey collected demographic data and explored surgical preferences related to the management of malrotation. Open-ended questions were used to assess the opinions regarding the necessity of appendectomy, decision-making factors, and complications associated with appendectomy during Ladd's procedure. Results: A total of 343 responses were received from 46 countries. Of the respondents, 319 (93%) were consultants and 24 (7%) were residents/trainees. When asked about the choice between open and laparoscopic Ladd's procedure, 292 (85%) preferred open surgery. Overall, 184 (53%) respondents favored appendectomy in both open and laparoscopic Ladd's procedure. Furthermore, 172 (50%) surgeons advocated for appendectomy in all malrotation cases, citing concerns about potential future appendicitis. While differences existed between all comparisons, none of them reached statistical significance. The factors influencing the decision to preserve the appendix included the risk of postoperative complications and the potential future use of the appendix as a surgical conduit. The surgical complications following appendectomy included surgical site infections in 14 (33%) patients, adhesive obstruction in 13 (31%) patients, intrabdominal abscesses in 10 (24%) patients, and fecal fistulas in 5 (12%) patients. Conclusion: The majority of surgeons aim to perform appendectomy in all malrotation cases, considering the potential risks and benefits of this approach. These findings offer valuable insights for clinical practice and may inform future guidelines and decision-making algorithms.

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