Development and internal validation of a clinical prediction model for serious complications after emergency laparotomy.

PURPOSE: Emergency laparotomy (EL) is a common operation with high risk for postoperative complications, thereby requiring accurate risk stratification to manage vulnerable patients optimally. We developed and internally validated a predictive model of serious complications after EL. METHODS: Data for eleven carefully selected candidate predictors of 30-day postoperative complications (Clavien-Dindo grade > = 3) were extracted from the HELAS cohort of EL patients in 11 centres in Greece and Cyprus. Logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) was applied for model development. Discrimination and calibration measures were estimated and clinical utility was explored with decision curve analysis (DCA). Reproducibility and heterogeneity were examined with Bootstrap-based internal validation and Internal-External Cross-Validation. The American College of Surgeons National Surgical Quality Improvement Program's (ACS-NSQIP) model was applied to the same cohort to establish a benchmark for the new model. RESULTS: From data on 633 eligible patients (175 complication events), the SErious complications After Laparotomy (SEAL) model was developed with 6 predictors (preoperative albumin, blood urea nitrogen, American Society of Anaesthesiology score, sepsis or septic shock, dependent functional status, and ascites). SEAL had good discriminative ability (optimism-corrected c-statistic: 0.80, 95% confidence interval [CI] 0.79-0.81), calibration (optimism-corrected calibration slope: 1.01, 95% CI 0.99-1.03) and overall fit (scaled Brier score: 25.1%, 95% CI 24.1-26.1%). SEAL compared favourably with ACS-NSQIP in all metrics, including DCA across multiple risk thresholds. CONCLUSION: SEAL is a simple and promising model for individualized risk predictions of serious complications after EL. Future external validations should appraise SEAL's transportability across diverse settings.

Tumor-activated lymph node fibroblasts suppress T cell function in diffuse large B cell lymphoma.

Recent transcriptomic-based analysis of diffuse large B cell lymphoma (DLBCL) has highlighted the clinical relevance of LN fibroblast and tumor-infiltrating lymphocyte (TIL) signatures within the tumor microenvironment (TME). However, the immunomodulatory role of fibroblasts in lymphoma remains unclear. Here, by studying human and mouse DLBCL-LNs, we identified the presence of an aberrantly remodeled fibroblastic reticular cell (FRC) network expressing elevated fibroblast-activated protein (FAP). RNA-Seq analyses revealed that exposure to DLBCL reprogrammed key immunoregulatory pathways in FRCs, including a switch from homeostatic to inflammatory chemokine expression and elevated antigen-presentation molecules. Functional assays showed that DLBCL-activated FRCs (DLBCL-FRCs) hindered optimal TIL and chimeric antigen receptor (CAR) T cell migration. Moreover, DLBCL-FRCs inhibited CD8+ TIL cytotoxicity in an antigen-specific manner. Notably, the interrogation of patient LNs with imaging mass cytometry identified distinct environments differing in their CD8+ TIL-FRC composition and spatial organization that associated with survival outcomes. We further demonstrated the potential to target inhibitory FRCs to rejuvenate interacting TILs. Cotreating organotypic cultures with FAP-targeted immunostimulatory drugs and a bispecific antibody (glofitamab) augmented antilymphoma TIL cytotoxicity. Our study reveals an immunosuppressive role of FRCs in DLBCL, with implications for immune evasion, disease pathogenesis, and optimizing immunotherapy for patients.

Prospective multicenter external validation of postoperative mortality prediction tools in patients undergoing emergency laparotomy.

BACKGROUND: Accurate preoperative risk assessment in emergency laparotomy (EL) is valuable for informed decision making and rational use of resources. Available risk prediction tools have not been validated adequately across diverse health care settings. Herein, we report a comparative external validation of four widely cited prognostic models. METHODS: A multicenter cohort was prospectively composed of consecutive patients undergoing EL in 11 Greek hospitals from January 2020 to May 2021 using the National Emergency Laparotomy Audit (NELA) inclusion criteria. Thirty-day mortality risk predictions were calculated using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), NELA, Portsmouth Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (P-POSSUM), and Predictive Optimal Trees in Emergency Surgery Risk tools. Surgeons' assessment of postoperative mortality using predefined cutoffs was recorded, and a surgeon-adjusted ACS-NSQIP prediction was calculated when the original model's prediction was relatively low. Predictive performances were compared using scaled Brier scores, discrimination and calibration measures and plots, and decision curve analysis. Heterogeneity across hospitals was assessed by random-effects meta-analysis. RESULTS: A total of 631 patients were included, and 30-day mortality was 16.3%. The ACS-NSQIP and its surgeon-adjusted version had the highest scaled Brier scores. All models presented high discriminative ability, with concordance statistics ranging from 0.79 for P-POSSUM to 0.85 for NELA. However, except the surgeon-adjusted ACS-NSQIP (Hosmer-Lemeshow test, p = 0.742), all other models were poorly calibrated ( p < 0.001). Decision curve analysis revealed superior clinical utility of the ACS-NSQIP. Following recalibrations, predictive accuracy improved for all models, but ACS-NSQIP retained the lead. Between-hospital heterogeneity was minimum for the ACS-NSQIP model and maximum for P-POSSUM. CONCLUSION: The ACS-NSQIP tool was most accurate for mortality predictions after EL in a broad external validation cohort, demonstrating utility for facilitating preoperative risk management in the Greek health care system. Subjective surgeon assessments of patient prognosis may optimize ACS-NSQIP predictions. LEVEL OF EVIDENCE: Diagnostic Test/Criteria; Level II.

The Hellenic Emergency Laparotomy Study (HELAS): A Prospective Multicentre Study on the Outcomes of Emergency Laparotomy in Greece.

BACKGROUND: Emergency laparotomy (EL) is accompanied by high post-operative morbidity and mortality which varies significantly between countries and populations. The aim of this study is to report outcomes of emergency laparotomy in Greece and to compare them with the results of the National Emergency Laparotomy Audit (NELA). METHODS: This is a multicentre prospective cohort study undertaken between 01.2019 and 05.2020 including consecutive patients subjected to EL in 11 Greek hospitals. EL was defined according to NELA criteria. Demographics, clinical variables, and post-operative outcomes were prospectively registered in an online database. Multivariable logistic regression analysis was used to identify independent predictors of post-operative mortality. RESULTS: There were 633 patients, 53.9% males, ASA class III/IV 43.6%, older than 65 years 58.6%. The most common operations were small bowel resection (20.5%), peptic ulcer repair (12.0%), adhesiolysis (11.8%) and Hartmann's procedure (11.5%). 30-day post-operative mortality reached 16.3% and serious complications occurred in 10.9%. Factors associated with post-operative mortality were increasing age and ASA class, dependent functional status, ascites, severe sepsis, septic shock, and diabetes. HELAS cohort showed similarities with NELA patients in terms of demographics and preoperative risk. Post-operative utilisation of ICU was significantly lower in the Greek cohort (25.8% vs 56.8%) whereas 30-day post-operative mortality was significantly higher (16.3% vs 8.7%). CONCLUSION: In this study, Greek patients experienced markedly worse mortality after emergency laparotomy compared with their British counterparts. This can be at least partly explained by underutilisation of critical care by surgical patients who are at high risk for death.

The Effect of Iloprost in the Healing of Colonic Anastomosis in Rats under Chemotherapy with Irinotecan.

PURPOSE: We have investigated the possible positive effect of iloprost in the healing of colonic anastomosis, in rats under intraperitoneal chemotherapy with irinotecan. METHOD: Forty male Wistar rats have been divided into four groups. They underwent a partial colectomy and a termino-terminal anastomosis. They were administered, intraperitoneally, saline (group 1), irinotecan (group 2), iloprost (group 3), or irinotecan and iloprost (Group 4). After the sacrifice of the animals what followed was an autopsy, a macroscopic examination and the measurement of the anastomotic rupture pressure. A portion of the anastomosis was sent over for histological examination and determination of hydroxyproline levels. Results: The frequency of the leakage from the anastomosis was considered as significantly increased in group 2 compared with the other groups. In group 2, a significantly greater degree of adhesions, compared to all the remaining groups, was observed. The bursting pressure of the anastomosis was significantly lower in group 2, as compared with all the remaining groups, and significantly increased in the group 4 compared with group 2. Leukocytosis, fibroblasts, the neocollagen and the levels of hydroxyproline in group 4 showed significantly increased values, compared with group 2. The angiogenesis was significantly increased in groups 3 and 4 compared with group 2. Conclusions: Intraperitoneal administration of iloprost after colectomy, termino-terminal anastomosis and intraperitoneal administration of irinotecan promotes the healing process of the colon anastomoses as it competes the inhibitory effect of irinotecan.

Endometrial adenocarcinoma and mucocele of the appendix: an unusual coexistence.

Appendiceal mucocele is a rare clinical entity, which is however quite often associated with mucinous ovarian tumor. The coexistence of mucinous cystadenoma of the appendix and endometrial adenocarcinoma has not been reported before. A 49-year-old woman presented to our clinic with postmenopausal bleeding and no other symptom. Endometrial biopsy revealed endometrial adenocarcinoma of endometrioid type (grade I). Preoperative CT scanning revealed an appendiceal mucocele, and a colonoscopy confirmed the diagnosis. The patient underwent total abdominal hysterectomy with bilateral salpingo-oophorectomy and appendectomy. The final histopathological examination showed a mucinous cystadenoma of the appendix and confirmed the diagnosis of endometrioid endometrial adenocarcinoma. The coexistence of appendiceal mucocele and female genital tract pathology is rare. However, gynecologists should keep a high level of suspicion for such possible coexistence. Both the diagnostic approach and the therapeutic management should be multidisciplinary, most importantly with the involvement of general surgeons.

Enhancing health care delivery through ambient intelligence applications.

This paper presents the implementation of a smart environment that employs Ambient Intelligence technologies in order to augment a typical hospital room with smart features that assist both patients and medical staff. In this environment various wireless and wired sensor technologies have been integrated, allowing the patient to control the environment and interact with the hospital facilities, while a clinically oriented interface allows for vital sign monitoring. The developed applications are presented both from a patient's and a doctor's perspective, offering different services depending on the user's role. The results of the evaluation process illustrate the need for such a service, leading to important conclusions about the usefulness and crucial role of AmI in health care.