Sacral nerve stimulation for bowel dysfunction following low anterior resection: a systematic review and meta‐analysis-Reference-Cited by-同舟云学术

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Sacral nerve stimulation for bowel dysfunction following low anterior resection: a systematic review and meta‐analysis

Published:2019-06-13 Issue:11 Volume:21 Page:1240-1248
ISSN:1462-8910
Container-title:Colorectal Disease
language:en
Short-container-title:Colorectal Dis

Author:

Huang Y.¹²³^ORCID,Koh C. E.¹²³

Affiliation:

1. SOuRCe (Surgical Outcomes Research Centre) Royal Prince Alfred Hospital Camperdown New South Wales Australia

2. Department of Colorectal Surgery Royal Prince Alfred Hospital Camperdown New South Wales Australia

3. RPA Institute of Academic Surgery Royal Prince Alfred Hospital Camperdown New South Wales Australia

Publisher

Wiley

Subject

Gastroenterology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/codi.14690

Reference39 articles.

1. Aspects of survival from colorectal cancer in Denmark;Iversen LH;Dan Med J,2012

2. Cancer Survivors in the United States: Prevalence across the Survivorship Trajectory and Implications for Care

3. Anterior resection syndrome

4. Achieving a Complete Colonic Evaluation in Patients With Incomplete Colonoscopy Is Worth the Effort

5. Sacral neurostimulation for low anterior resection syndrome after radical resection for rectal cancer: evaluation of treatment with the LARS score

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1. Risk factors for complications following sacral neuromodulation for faecal incontinence: Long‐term follow‐up;Colorectal Disease;2024-07-12

2. Biofeedback combined with percutaneous electrical pudendal nerve stimulation for the treatment of low anterior rectal resection syndrome: a study protocol for a randomized controlled trial;Trials;2024-07-02

3. Long-term outcomes of sacral neuromodulation for low anterior resection syndrome after rectal cancer surgery;Annals of Coloproctology;2024-06-30

4. Treatment of anterior resection syndrome: A systematic review and network meta-analysis;European Journal of Surgical Oncology;2024-06

5. NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage;Journal of Neural Engineering;2024-06-01

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