Nutritional support in critically ill patients has been acknowledged as a pillar of ICU care, playing a pivotal role in preserving muscle mass, supporting immune function, and promoting recovery during and after critical illness. Providing effective nutritional support requires adapting it to the patient’s diagnosis, unique characteristics, and metabolic state to minimize the risks of overfeeding or underfeeding while mitigating muscle loss. This level of care requires a comprehensive nutritional assessment and the establishment of a nutrition-focused protocol. Regular, consistent and detailed nutritional evaluation can influence both therapeutic decisions and clinical interventions, thus ensuring that the specific needs of critically ill patients are met from the acute phase through their entire recovery process. Bioelectrical impedance analysis (BIA) is increasingly recognized as a valuable tool for enhancing nutritional care in critically ill patients. By delivering precise, real-time insights into key aspects of body composition, BIA is thought to provide clinicians with a more comprehensive understanding of the complex physiological changes that occur during critical illness. This narrative review highlights the potential of BIA in offering these precise assessments, facilitating the development of more accurate and personalized nutritional strategies for critically ill patients. If BIA can reliably assess dynamic shifts in hydration and tissue integrity, it holds the promise of further advancing individualized care and optimizing clinical outcomes in this vulnerable population.

Background and Objectives: Cystic echinococcosis (CE) remains a significant health concern in endemic areas, including Romania, where hepatic hydatid cysts frequently require surgical treatment. Surgery represents the cornerstone of therapy, particularly in large, complicated, or symptomatic cysts, where medical or minimally invasive options may be insufficient. This study aims to investigate the clinical characteristics, risk factors, and postoperative evolution of patients undergoing surgical intervention for hepatic CE in a tertiary care center over a five-year period. Materials and Methods: This retrospective study examined data from 62 patients who underwent surgical procedures for hepatic CE during a 5-year period. The analysis focused on demographic parameters, cyst morphology, surgical techniques employed, and postoperative complications, with particular attention to the frequency, management, and outcomes of biliary fistulas. Results: The study cohort had an average age of 44.1 years, with a slight predominance of female patients (51.6%). The majority of cysts (62.9%) were located in the right hepatic lobe, with an average diameter of 10.9 cm. Postoperative complications were recorded in 25.8% of cases, with biliary fistulas being the most frequent (12.9%). Patients who developed biliary fistulas presented significantly larger cysts (152.13 ± 105.68 mm vs. 102.20 ± 37.86 mm, p = 0.012) and required an extended length of hospitalization, particularly in high-output cases (29 vs. 9.3 days, p = 0.045). Hospital stays and treatment expenses were notably higher among patients with biliary fistulas. Conclusions: Biliary fistulas were observed exclusively in patients who underwent partial cystectomy. This finding highlights the need for increased caution when performing partial cystectomy, especially in cases involving large or recurrent cysts, where the risk of postoperative biliary fistulas is higher. Tailoring the surgical technique based on cyst characteristics and incorporating intraoperative strategies to manage or prevent biliary leakage may help reduce morbidity. Early identification and multidisciplinary management of high-risk cases are key to improving outcomes in hepatic CE.

Background/Objectives: Emergency surgical patients are at increased risk of acute postoperative delirium. Processed EEG monitoring, such as entropy indices and burst suppression ratio (BSR), may optimize anesthetic dosing, yet their role in non-elective surgery remains underexplored. This retrospective cohort study aimed to examine whether entropy monitoring and intraoperative burst suppression are associated with the incidence of early postoperative delirium during the first 72 h after emergency surgery. Methods: Adult patients undergoing emergency surgery between March 2022 and March 2024 were classified into two groups based on anesthesia records: the entropy-monitored group (EG) and the standard care group without processed EEG (SG). Demographic, intraoperative, and cognitive data (NEECHAM scores during the first 72 h) were extracted from institutional perioperative records. The primary outcome was postoperative delirium (NEECHAM ≤ 24), with secondary analyses examining anesthetic exposure, burst suppression, and intraoperative hemodynamics. Results: Entropy-monitored patients received lower sevoflurane and fentanyl doses and exhibited improved hemodynamic stability, including fewer hypotensive episodes and lower norepinephrine requirements. Early postoperative cognitive dysfunction (NEECHAM ≤ 24) was more frequent among patients with intraoperative burst suppression, with BSR > 15% or suppression duration > 6 min strongly associated with cognitive decline within the first 72 h. Conclusions: In this retrospective cohort, entropy-guided anesthesia was associated with more precise anesthetic titration and more stable hemodynamic parameters. Burst suppression characteristics may serve as indicators of neurocognitive vulnerability rather than solely reflecting direct effects of anesthetic dosing. These results support the use of processed EEG monitoring in emergency surgery, though prospective studies are needed to confirm these findings.

Background/Objectives: Acute gastrointestinal (GI) emergencies require timely and accurate prediction of surgical necessity to avoid delayed intervention and improve patient outcomes. Traditional scoring systems offer limited accuracy and fail to integrate multimodal data. This study aimed to develop and validate an explainable machine learning model for early prediction of surgical necessity in patients presenting with GI emergencies. Methods: A retrospective cohort of 1032 consecutive adult patients admitted with acute GI emergencies at a tertiary referral center (2019–2024) was analyzed. Three predictive models were developed: logistic regression, Random Forest, and XGBoost. Features included clinical, laboratory, and contrast-enhanced CT imaging variables available within the first 24 h. Model performance was evaluated using AUC, sensitivity, specificity, PPV, NPV, and F1-score. Shapley Additive Explanations (SHAP) were applied for global and individual-level interpretability. The study followed STROBE and TRIPOD+AI reporting guidelines. Results: Surgical intervention was required in 312 patients (30.2%). The XGBoost model achieved the highest AUC (0.89; 95% CI: 0.86–0.92), outperforming Random Forest (AUC 0.86) and logistic regression (AUC 0.79), with sensitivity 0.84, specificity 0.81, and NPV 0.90. The most influential predictors were serum lactate, CT findings (free intraperitoneal air, bowel ischemia), IL-6, and shock index. Decision curve analysis confirmed net clinical benefit across threshold probabilities of 10–70%. Subgroup performance remained robust across diagnostic categories (AUC 0.87–0.91). Conclusions: An explainable XGBoost model integrating early clinical, laboratory, and imaging data accurately predicts surgical necessity in GI emergencies and outperforms traditional scoring systems. SHAP-based explainability supports clinical adoption and transparency. Prospective multicenter validation is warranted. The positive predictive value of 0.74 indicates that approximately one in four patients flagged as requiring surgery may not need operative intervention. The model should be regarded as a decision-support adjunct, rather than a standalone surgical decision tool, that is most relevant in settings where immediate experienced surgical judgment is limited.

Background and Objectives: Early identification of patients with acute pancreatitis (AP) who will require operative intervention remains a major clinical challenge. Traditional severity scores and delayed inflammatory biomarkers offer limited early predictive accuracy. This study aimed to evaluate the combined predictive value of IL-6, necrotic burden, and organ failure parameters for determining the need for surgical management in AP. Materials and Methods: We performed a retrospective cohort study of 325 consecutive patients with AP admitted to Floreasca Emergency Hospital between January 2020 and December 2024. Clinical, laboratory, and imaging parameters were collected, including IL-6 at 24 h, CRP at 48–72 h, SOFA and BISAP scores, and morphologic complications. The primary endpoint was the requirement for operative intervention. Univariate and multivariable logistic regression analyses were conducted, and model performance was assessed using ROC curves and calibration testing. Results: Sixty patients (18.5%) underwent surgery for pancreatitis-related complications. Operated patients demonstrated higher IL-6 levels (median 120 vs. 55 pg/mL), necrosis >30% (68.3% vs. 14%), infected necrosis (55% vs. 2.3%), and persistent organ failure (46.7% vs. 9.8%) (all p < 0.001). In multivariable analysis, IL-6 at 24 h (OR 1.35 per 50 pg/mL), necrosis > 30% (OR 4.80), infected necrosis (OR 6.20), persistent organ failure ≥48 h (OR 2.60), SOFA score (OR 1.18 per point), and CRP at 48–72 h (OR 1.09 per 50 mg/L) independently predicted surgery. The final model showed excellent discrimination (AUC 0.88) and good calibration. Conclusions: IL-6-driven inflammatory escalation, combined with necrotic burden and persistent organ dysfunction, provides a robust early predictive framework for identifying AP patients likely to require surgical intervention. Integration of these parameters may improve triage, timing of intervention, and multidisciplinary decision-making in acute pancreatitis.

Oligometastatic colorectal cancer (CRC) refers to a state in which distant metastatic spread is limited to a few sites, offering the potential for curative treatment with aggressive local therapies. The surgical management of oligometastatic CRC has gained increasing attention due to its potential to improve survival. This review explores the evolving role of surgery in the treatment of oligometastatic disease, focusing on the criteria for selecting patients, surgical techniques, and outcomes. While systemic therapy remains essential, surgery can offer long-term survival benefits for appropriately selected patients with limited metastatic disease, particularly those with metastases confined to the liver. Advances in imaging technologies, minimally invasive surgical techniques, and perioperative care have enhanced the safety and efficacy of these procedures. The integration of multimodal therapies, such as chemotherapy, targeted therapy, and immunotherapy, in conjunction with surgery, is also discussed, with a focus on optimizing outcomes. To conclude, surgical resection of liver metastases improves survival compared to systemic therapy alone; thus, resection should be taken into consideration whenever possible. For initially unresectable diseases, personalized conversion therapy is indicated. This review aims to clarify how and when liver resection can first be chosen; when preoperative systemic treatment is needed; and if this is chosen, what is the best approach.