Outcome in patients with open abdomen treatment for peritonitis: a multidomain approach outperforms single domain predictions.

Numerous patient-related clinical parameters and treatment-specific variables have been identified as causing or contributing to the severity of peritonitis. We postulated that a combination of clinical and surgical markers and scoring systems would outperform each of these predictors in isolation. To investigate this hypothesis, we developed a multivariable model to examine whether survival outcome can reliably be predicted in peritonitis patients treated with open abdomen. This single-center retrospective analysis used univariable and multivariable logistic regression modeling in combination with repeated random sub-sampling validation to examine the predictive capabilities of domain-specific predictors (i.e., demography, physiology, surgery). We analyzed data of 1,351 consecutive adult patients (55.7% male) who underwent open abdominal surgery in the study period (January 1998 to December 2018). Core variables included demographics, clinical scores, surgical indices and indicators of organ dysfunction, peritonitis index, incision type, fascia closure, wound healing, and fascial dehiscence. Postoperative complications were also added when available. A multidomain peritonitis prediction model (MPPM) was constructed to bridge the mortality predictions from individual domains (demographic, physiological and surgical). The MPPM is based on data of n = 597 patients, features high predictive capabilities (area under the receiver operating curve: 0.87 (0.85 to 0.90, 95% CI)) and is well calibrated. The surgical predictor "skin closure" was found to be the most important predictor of survival in our cohort, closely followed by the two physiological predictors SAPS-II and MPI. Marginal effects plots highlight the effect of individual outcomes on the prediction of survival outcome in patients undergoing staged laparotomies for treatment of peritonitis. Although most single indices exhibited moderate performance, we observed that the predictive performance was markedly increased when an integrative prediction model was applied. Our proposed MPPM integrative prediction model may outperform the predictive power of current models.

Effectiveness of Multi-Prognostic Index in older patients with advanced malignancies treated with immunotherapy.

BACKGROUND: Older adults with cancer are less likely to be offered treatment for cost-benefit concern. The Multi-Prognostic Index (MPI) has been validated in various clinical settings for survival estimation. We aimed to evaluate MPI as a screening tool for older adults with cancer eligible to receive immunotherapy. PATIENTS AND METHODS: Older adults with advanced or metastatic cancer, admitted to the Oncology Day Hospital of the University Hospital of Pisa from January 2017 to May 2018, eligible to receive immunotherapy were prospectively enrolled. In addition to routine oncological evaluation, each patient received a comprehensive geriatric assessment with MPI calculation. Overall survival (Cox-adjusted curve) was stratified by tertiles of MPI score. Drug toxicity was assessed according to the National Cancer Institute Common Terminology Criteria for Adverse Events (Version 4.03: June 14, 2010). RESULTS: Seventy-nine patients [26.6% women, mean age (±SD) 74.0 ±â€¯6.1 years] were enrolled with the following diagnosis: melanoma (51.9%), non-small cell lung cancer (25.3%), renal cell cancer (12.7%), urothelial cancer (8.9%) and Merkel cell carcinoma (1.2%). Median follow-up was 7 months (range 1-35). The patients' survival rate resulted progressively longer proceeding from the first to the third MPI tertile [HR 1.76 (0.49-6.31) Vs 2nd tertile, p < 0.05; HR 5.33 (1.68-16.89) Vs 3rd tertile, p < 0.01]. CONCLUSIONS: MPI score is an effective tool for the stratification of older patients with cancer eligible for immunotherapy with checkpoint inhibitors. Further studies are required to achieve conclusive remarks on MPI usefulness in different underlying tumor types.

Descriptive and correlational study of the epidemiological, clinical and etiological characteristics of peritonitis in the surgical department of the HUEH during the period from January 2013 to December 2018: A protocol study.

INTRODUCTION: Generalized secondary peritonitis is one of the most common emergencies encountered in surgical departments with a mortality of up to 20%. While early prognostic assessment of peritonitis is essential for the objective classification of the severity of the disease, the late presentation of the majority of patients to health facilities affects this situation, further complicating effective management and promoting the occurrence of complications. In Haiti, few studies on surgical pathologies are available, and with regard to peritonitis, only two thesis works have been listed on the subject. This study aims to: explore the demographic, clinical and etiological characteristics of peritonitis in the main referral hospital in the metropolitan region of the Haiti, and evaluate the main delays and its relationship with the severity of the disease by measuring the MPI score. METHODOLOGY: It is a correlational descriptive study, retrospectively carried out over a period of 6 years, from January 2013 to December 2018 in the surgical department of the Hospital of the State University of Haiti. The study population is composed of all patients diagnosed, hospitalized and operated on in the peritonitis ward during the study period Pearson's correlation with α < 0.05 was used as the significance threshold and the correlation of complications and duration of management by Spearman's correlation to assess the relationship between sex, age group, complications and length of hospital stay. A multiple linear regression will be done for the most significant correlations. The comparison of the means was made by the Z test, with α < 0.05 as the significance threshold, and the student T test for variables with two modalities such as complication. The ANOVA test was used to cross-reference dependent and independent variables with more than 2 modalities, and the Pearson chi-square test for qualitative variables with etiological and demographic diagnoses.