Journal of Digestive Diseases最新文献

Slow transit constipation (STC) is a chronic colonic motility disorder characterized by markedly delayed transit, leading to reduced bowel movements, abdominal discomfort, and significant quality-of-life impairment. It predominantly affects women and is associated with abnormalities in enteric neuronal signaling, smooth muscle contractility, interstitial cells of Cajal, gut peptides, bile acid homeostasis, and autonomic regulation. Secondary causes of constipation and structural lesions must be excluded before the diagnosis of STC, with colonic transit studies serving as the gold standard. Complementary investigations such as anorectal manometry and defecography help detect coexisting outlet obstruction, which can alter management. The treatment of STC should follow a stepwise approach, beginning with dietary and lifestyle modification, osmotic and stimulant laxatives, and prokinetics such as prucalopride. Secretagogues and bile acid modulators may offer additional benefit. Biofeedback therapy is primarily indicated for overlapping dyssynergic defecation. For refractory STC, interventional therapies, such as fecal microbiota transplantation, acupuncture, sacral nerve stimulation, and transanal irrigation, are found to have equivocal outcomes. Antegrade continence enema procedures can be an alternative for patients unsuitable for colectomy. Surgical options, including subtotal colectomy with ileosigmoid or cecorectal anastomosis, and total colectomy with ileorectal anastomosis, are reserved for carefully selected patients with medically intractable symptoms, following thorough physiological evaluation. Although advances in understanding STC pathophysiology are guiding novel therapeutic development, robust randomized controlled trials remain scarce. Optimal care requires multidisciplinary collaboration between gastroenterologists, colorectal surgeons, and pelvic floor specialists to ensure accurate diagnosis, tailored treatment, and improved long-term outcomes.

Objectives: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that inevitably leads to swallowing difficulties as the disease progresses. Percutaneous endoscopic gastrostomy (PEG) is recommended for optimal supportive management of dysphagia among these patients. We aimed to investigate PEG-related complications and risk factors in patients with ALS.

Methods: Medical records of the ALS patients who underwent PEG from March 2006 to February 2025 in a single tertiary care center were retrospectively reviewed. PEG-related complications and risk factors were assessed through chart review, endoscopic reports and images, radiological findings, and follow-up data.

Results: Altogether 501 ALS patients (262 men) underwent PEG, of whom 60 developed early complications and 82 developed late complications, including 11 patients who developed both. Pneumoperitoneum was more common in underweight patients (p = 0.004), and wound infection was more common in patients with pre-PEG ileus (p = 0.044). Multivariate analysis revealed that low albumin level, long procedure time, and ileus were significantly associated with early complications. Obesity and ileus were independent risk factors for buried bumper syndrome. Those with an internal bolster at the upper body of the stomach and with an external bolster in the midline of the abdomen were at significant risk of inadvertent PEG removal.

Conclusions: Albumin and body mass index extremes are predictors of complications, and care is needed when PEG is performed on patients with pre-PEG ileus. To reduce such risks, the PEG tube should not be inserted into the upper body of the stomach or the midline of the abdomen.

Objectives: To identify the risk factors for the survival of colorectal cancer (CRC) patients with type 2 diabetes mellitus (T2DM), compare the predictive performance of models based on different algorithms, and develop a risk score system to predict the survival risk of the target population.

Methods: We analyzed data from the Hong Kong Hospital Authority Data Collaboration Laboratory (HADCL), including 10 749 CRC patients with T2DM from 2000 to 2020. We employed traditional statistical methods and machine learning algorithms to compare their performance using the area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) analysis was conducted to identify risk factors and attribute model outputs. A risk score system was developed using the AutoScore-Survival package for risk stratification.

Results: Key predictors of CRC survival among T2DM patients included age at cancer diagnosis, sex, T2DM duration, alcohol consumption, central obesity, hypertension, levels of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and serum potassium, and anti-lipid drug usage. Among the models assessed, the random survival forest showed the best performance. The risk score system was calibrated as follows: age at diagnosis, T2DM duration, LDL-C, glycated hemoglobin, creatinine, and body mass index. The AUCs for 1, 3, and 5 years of the tuned risk score system were 0.746, 0.718, and 0.677, respectively.

Conclusions: The random survival forest model provides superior survival prediction compared to other models evaluated. A validated risk score system has been established, facilitating risk stratification for clinicians to manage these patients.