Indian Journal of Surgery最新文献

The AJCC 8th edition has included depth of invasion as per the new CAP guidelines as an independent measure of T staging irrespective of tumour size. This aim of this study was to look at the correlation between depth of invasion measured by the new guidelines and neck nodal positivity rate in cases of carcinoma of the tongue. We performed a case series analysis of 131 cases of carcinoma tongue who underwent wide excision and neck dissection at a tertiary cancer care centre in North Kerala, India. Depth of invasion was reported as per the new CAP/AJCC guidelines and its correlation with lymph node positivity rate was assessed. We also looked at the upstaging caused by the addition of depth of invasion to T staging in the AJCC 8th edition. Lymph node positivity correlates well with depth of invasion, and the coefficient of correlation was 0.89 in our study. The lymph node positivity rate exceeded 15% when the depth of invasion exceeded 4 mm. 59.5% of T1 tumours and 28.5% of T2 tumours were upstaged when AJCC 8th edition TNM staging was used instead of 7th edition. Depth of invasion correlates well with lymph node positivity and the addition of depth of invasion in AJCC 8th edition results in upstaging compared to AJCC 7th.

Cattle injuries are common in India. An injury by cattle is more common in rural and agriculture-dependent regions of the country. Injuries can be related to domesticated or stray cattle. This case series presents a detailed analysis of cattle-related injuries in the northern hilly regions of India. The study was conducted in the General Surgery department of a newly established medical college and hospital in the hilly areas of northen India. Mechanisms, anatomical sites, and patterns of injuries were systematically categorized. The findings shed light on the unique challenges and risks posed by interactions with cattle in these regions along with recommendation to make a law for the safety of human beings and animals to prevent life-threatening events from a preventable cause.

Acute pancreatitis is a disorder characterized by acute necro-inflammatory changes of the pancreas and histologically marked by acinar cell destruction. It is one of the most common causes of hospitalization due to abdominal pain. Several classification systems have been proposed to assess the severity and prognosis of acute pancreatitis. Scores such as the Ranson and bedside index for severity in acute pancreatitis (BISAP) are useful for evaluating the severity and mortality of the disease. The revised Atlanta classification mainly focuses on the morphologic criteria for defining the various manifestations of acute pancreatitis outlined principally by means of CT and MRI. A case-series analysis study was conducted under the Department of Surgery, Government Medical College, Jammu, including 57 patients who presented with acute pancreatitis. The BISAP scores, along with Ranson scores and modified CT severity index scores (mCTSI), were calculated and compared using a preformed performa. The sensitivity, specificity, and area under the curve (AUC) of the BISAP and Ranson’s scoring systems were evaluated in patients who received CT scans, with mCTSI serving as the reference standard. The mean age of the study population was 46.49 years SD 14.11 with 14 (24.56%) men and 43 (75.44%) women. The men to women ratio was 0.32. Among the calculous etiology, cholelithiasis was the most common cause of acute pancreatitis, affecting 35 (61.40%) patients, followed by idiopathic acute pancreatitis. Out of 57 patients, 40 patients underwent CT scanning. Out of these 40 patients, 31 (77.5%) were classified as severe according to BISAP score with a cutoff of BISAP score ≥ 2, and 33 (82.5%) were classified as severe according to Ranson scoring system, with a cutoff of Ranson score ≥ 3. The sensitivity and specificity of BISAP were 90.90% and 85.71%, respectively. The sensitivity and specificity of Ranson were 93.93% and 71.42%, respectively. Ranson was more sensitive but less specific than BISAP. In our study, area under curve (AUC) of BISAP was 0.70, and area under curve (AUC) of Ranson was 0.94. Ranson scoring was more accurate than BISAP in predicting severe acute pancreatitis, according to area under curve (AUC). BISAP scoring is comparable to the Ranson score in predicting the severity of acute pancreatitis, with statistically insignificant p-value (p = 0.089). The bedside index for severity in acute pancreatitis (BISAP) offers a straightforward and timely means of identifying severe cases within 24 h of disease onset. Conversely, Ranson’s score retains its value in pinpointing patients at risk of severe acute pancreatitis and ensuing organ failure. In our study, p-value is > 0.05, which indicates that both BISAP and Ranson’s score are equally adept at assessing acute pancreatitis severity, serving as reliable prognostic tools for early patient intervention. However, Ranson’s score boasts superior sensitivity and specificity co

Bariatric surgery has become an effective method for treating severe obesity and its related complications. While the effectiveness and safety of BS have been widely confirmed, micronutrient deficiency has emerged as a long-term complication after surgery. Literature was collected through online searches of PubMed, Cochrane Library, Web of Science, and Embase databases, as well as manual searches. A total of 15 studies, with a sample size of 2993 cases, were included. The studies found that the risk of zinc deficiency increased gradually at 6 months, 1 year, and 2 years after surgery compared to pre-surgery levels. Subgroup analysis revealed that serum zinc levels decreased by 9.40% (95% CI − 16.44%, − 2.36%) at 1 year after laparoscopic sleeve gastrectomy, 9.33% (95% CI − 10.73%, − 7.92%) after Roux-en-Y gastric bypass and one-anastomosis gastric bypass, and 22.30% (95% CI − 30.14%, − 14.46%) after biliopancreatic diversion/duodenal switch. Meanwhile, the total prevalence of zinc deficiency at 1 year after surgery was 26.1%. In conclusion, zinc deficiency worsens and serum zinc levels decrease after bariatric surgery. It is recommended that patients undergoing weight loss surgery undergo regular monitoring of serum zinc levels and receive timely zinc supplementation therapy.

Artificial intelligence (AI), once integrated into medicine, has transformed its role from a mere statistical tool to a sophisticated system capable of guiding surgical procedures and predicting outcomes. AI algorithms utilize machine learning (ML), deep learning, and neural networks to analyze large datasets and identify patterns, ultimately making accurate predictions about patient outcomes. Through continuous learning, adaptation, and updating, these systems assist healthcare professionals in the diagnosis and offer real-time guidance during surgical interventions, reducing surgical error and postoperative complications. This evolution marks a paradigm shift, enhancing precision, efficiency, and, ultimately, patient care in surgery. This review article explores the critical role of AI in predicting surgical complications and discusses associated challenges and ethical considerations.