The early identification of mortality risk in patients with tuberculosis (TB) and severe malnutrition (BMI <16 kg/m ² ) is critical for optimizing clinical outcomes. In this three-year ambispective study (October 1, 2021–September 30, 2024), conducted at Leamna Hospital, a reference center for the Oltenia Region, Romania, 216 patients with pulmonary tuberculosis were selected from a total of 3,547 TB cases for analysis. We assessed all-cause in-hospital mortality during the index admission only (from admission to discharge); deaths after discharge or during subsequent admissions were excluded, patients transferred without cross-facility linkage were right-censored at transfer, and all analyses used baseline hematological and biochemical parameters obtained before initiation of any treatment. We developed and validated the Immuno-Inflammatory Ratio (IIR), a novel machine-learning–assisted biomarker integrating neutrophils, lymphocytes, and eosinophils. The IIR demonstrated an apparent AUC of 0.9711 with an optimal threshold of 7.44 (sensitivity 99.40%, specificity 91.49%). In regression analyses, the IIR emerged as the strongest independent predictor of mortality (adjusted OR 13.98, p < 0.001), outperforming established indices such as the neutrophil-to-lymphocyte ratio (NLR) and the cumulative inflammatory index (IIC). Given its simplicity and strong discriminatory power, the IIR may support early risk stratification and prioritization of standard interventions (e.g., intensified monitoring, nutritional support, and timely optimization of anti-TB therapy). Prospective multicenter validation and longitudinal assessment of IIR dynamics are warranted to confirm clinical utility and define applications beyond the index admission, including in resource-limited settings.

Background/Objectives: The health of military personnel in modern operational settings is critical for sustaining defense readiness. Extended exposure to extreme conditions can cause oxidative stress and systemic inflammation, potentially affecting performance. To address this problem, we developed an innovative diagnostic tool, the Post-Mission Integrated Risk Index (IIRPM), which integrates hematologic markers with key clinical variables. A novel aspect of the approach is the incorporation of ΔNLR, thus quantifying the change in the neutrophil-to-lymphocyte ratio measured before and after deployment, thereby providing a sensitive indicator of the inflammatory impact of operational stress. Methods: In this retrospective study, we analyzed comprehensive clinical and biological data from 443 military personnel over a ten-year period, with measurements taken before and after missions. We applied robust statistical techniques, including paired t-tests and Pearson correlation analyses, to assess variations in hematologic and metabolic parameters. Data segmentation was performed using Gaussian mixture models, and the predictive performance of the resulting model was validated with a multi-layer perceptron (MLP) neural network. Results: The analysis revealed significant post-mission increases in both the baseline NLR and ΔNLR, accompanied by notable shifts in metabolic markers. Data segmentation identified three distinct profiles: a reference profile characterized by stable immunologic parameters, an acute inflammatory response profile, and a proinflammatory metabolic profile marked by elevated cholesterol levels and higher mean age. Remarkably, the MLP model achieved 100% accuracy on the test set, with an average cross-validation accuracy of 97%. Conclusions: The IIRPM—which incorporates ΔNLR, age, mission duration, and cholesterol levels—offers a novel strategy to assess inflammatory risk among military personnel, thus facilitating personalized preventive interventions. Further validation in multicenter and longitudinal studies is anticipated to consolidate the clinical utility of this tool, ultimately fostering a more adaptive approach in military medicine to address the complex challenges of modern operational theaters.

Background: Early identification of patients who will remain sputum-culture-positive at two months could support risk-adapted tuberculosis (TB) monitoring. We developed a compact baseline score from routine admission data measured before anti-TB therapy. Methods: The cohort comprised 155 adults (62 culture-positive and 93 culture-negative at two months). Random Forest ranking and correlation clustering were used as exploratory selection steps. The complete development pipeline was evaluated by repeated fully nested cross-validation; a secondary conditional analysis held the full-cohort-selected candidate set fixed. Results: The fully nested pipeline yielded a mean test-fold AUC of 0.70 ± 0.09 (fold-level percentile interval 0.53–0.85). Conditional on full-cohort predictor preselection, mean test-fold AUC was 0.74 ± 0.08, and the patient-level mean repeated out-of-fold score AUC was 0.75 (bootstrap 95% CI 0.67–0.83). At provisional thresholds of ≥2, ≥3 and ≥4 points, conditional procedure sensitivity/specificity were 0.90/0.39, 0.80/0.60 and 0.57/0.74, respectively. The conditional repeated out-of-fold Brier score was 0.200, with calibration intercept approximately 0.00 and slope 0.74. Conclusions: TB-CAST is an exploratory score with moderate internal discrimination. The fully nested result is the primary internal estimate for the complete data-driven pipeline; the conditional results and provisional thresholds require prospective external validation before clinical use.

Preoperative risk stratification for laparoscopic cholecystectomy (LC) remains imperfect, particularly in patients with chronic inflammatory remodeling and biliary anatomic variants. Existing tools often focus on acute presentations or intraoperative variables, resulting in uncertainty on how congenital anatomy, recurrent biliary colic, and cystic pediculitis interact. We synthesize a hypothesis-generating conceptual framework and propose an illustrative candidate preoperative rubric for future validation. We performed a structured narrative review of PubMed, Scopus, and Web of Science (January 1990–December 2024; last search: 15 December 2024). Eligible primary studies evaluated clinical history, imaging-defined anatomy, inflammatory biomarkers, and/or operative outcomes (conversion, intraoperative complications, or operative difficulty) in the setting of LC. Acute cholecystitis and chronic/elective cohorts were interpreted separately during the narrative synthesis. Two reviewers screened titles/abstracts and assessed full texts using predefined inclusion/exclusion criteria; due to heterogeneity, no meta-analysis and no formal risk-of-bias tool were applied. The literature supports a plausible vicious cycle in which biliary anatomic variants may impair drainage and promote stasis, recurrent biliary colic, and chronic inflammation, ultimately leading to fibrosis/pediculitis and a “frozen” Calot’s triangle. We translate these signals into an illustrative candidate rubric (0–16 points) spanning three domains: clinical history (0–6), imaging (0–6), and inflammatory biomarkers (0–4). Weights and cut-offs (low: 0–4; moderate: 5–9; high: 10–16) were chosen a priori for conceptual clarity and are not data-derived. This review provides a conceptual map and a candidate variable set to support hypothesis generation, standardized data collection, and staged validation. The rubric is not validated and must not be used for clinical decision-making. Planned next steps include feasibility-oriented derivation, followed by prospective multicenter external validation and impact assessment.