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A magnetic resonance imaging-based decision-making tool for predicting complex anal fistulas healing in the early postoperative period.
Xu, Hao; Xiao, Guo-Zhong; Zheng, Yi-Hui; Fu, Yuan-Ji; Zhong, Sheng-Lan; Ren, Dong-Lin; Li, Wen-Ru; Lin, Hong-Cheng.
Afiliação
  • Xu H; Department of Anorectal, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, 200434, China.
  • Xiao GZ; Department of Anorectal Surgery, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.
  • Zheng YH; Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Yuancun Er Heng Lu, No. 26, Guangzhou, 510655, China.
  • Fu YJ; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, China.
  • Zhong SL; Guangdong Institute of Gastroenterology, Guangzhou, 510655, China.
  • Ren DL; Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Yuancun Er Heng Lu, No. 26, Guangzhou, 510655, China.
  • Li WR; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, China.
  • Lin HC; Guangdong Institute of Gastroenterology, Guangzhou, 510655, China.
BMC Gastroenterol ; 23(1): 372, 2023 Oct 31.
Article em En | MEDLINE | ID: mdl-37907854
ABSTRACT

BACKGROUND:

Magnetic resonance imaging (MRI) has excellent accuracy in diagnosing preoperative lesions before anal fistula surgery. However, MRI is not good in identifying early recurrent lesions and effective methods for quantitative assessment of fistula healing are still warranted. This retrospective study aimed to develop and validate a specific MRI-based nomogram model to predict fistula healing during the early postoperative period.

METHODS:

Patients with complex cryptoglandular anal fistulas who underwent surgery between January 2017 and October 2020 were included in this study. MRI features and clinical parameters were analyzed using univariate and multivariate logistic regression analysis. A nomogram for predicting fistula healing was constructed and validated.

RESULTS:

In total, 200 patients were included, of whom 186 (93%) were male, with a median age of 36 (18-65) years. Of the fistulas, 58.5% were classified as transsphincteric and 19.5% as suprasphincteric. The data were randomly divided into the training cohort and testing cohort at a ratio of 73. Logistic analysis revealed that CNR, ADC, alcohol intake history, and suprasphincteric fistula were significantly correlated with fistula healing. These four predictors were used to construct a predictive nomogram model in the training cohort. AUC was 0.880 and 0.847 for the training and testing cohorts, respectively. Moreover, the decision and calibration curves showed high coherence between the predicted and actual probabilities of fistula healing.

CONCLUSIONS:

We developed a predictive model and constructed a nomogram to predict fistula healing during the early postoperative period. This model showed good performance and may be clinically utilized for the management of anal fistulas.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Canal Anal / Fístula Retal Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Canal Anal / Fístula Retal Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2023 Tipo de documento: Article