Search Results (2,595)

Background/Objectives: Hypercapnic respiratory failure (HRF) is a serious complication of chronic obstructive pulmonary disease (COPD) and is associated with increased morbidity, mortality, and healthcare utilisation. National HRF trends among patients with COPD remain poorly characterised in Lithuania, and the knowledge of prehospital emergency-care professionals regarding oxygen therapy and hypercapnia has not been evaluated. Methods: This study comprised two components. First, a cross-sectional online survey assessed knowledge of COPD, hypercapnia, and oxygen therapy among prehospital emergency-care professionals (EMS physicians, emergency nurses, EMS paramedics, and paramedics); three questionnaire items whose designated correct answers could not be unambiguously supported were excluded from the knowledge score, and the original 10-item score was retained as a sensitivity analysis. Second, nationwide electronic health record data from the Lithuanian national health record system (ESPBI IS, 2020–2023) were analysed retrospectively: patients with COPD and concomitant chronic HRF were identified using ICD-10-AM diagnostic codes, and the number of patients with a recorded J96.11 diagnosis irrespective of underlying disease was obtained as a national denominator. Proportions are reported with 95% confidence intervals and temporal trends as absolute changes in percentage points; multivariable logistic regression was used to estimate odds ratios adjusted for age group and sex. Between-year differences were tested using the χ² test with Holm-adjusted pairwise comparisons, and the association between sex and chronic HRF was expressed as an odds ratio. All tests were two-sided, and p < 0.05 was considered significant. Results: Among the 65 prehospital emergency-care professionals surveyed, knowledge of hypercapnia was relatively high: 78.5% (95% CI 67.0–86.7) correctly defined it and 72.3% (95% CI 60.4–81.7) identified its symptoms, whereas 58.5% (95% CI 46.3–69.6) identified the recommended SpO₂ target range of 88–92%. Respondents answered a median of 5 of the 7 scored knowledge items correctly (IQR 4–6). Total knowledge scores differed by professional role (p = 0.034) but not by years of experience, sex, or frequency of COPD contact; the sensitivity analysis using the original 10-item score gave the same pattern (p = 0.006). In the national electronic health record data, the COPD population increased from 27,239 to 32,446 (+19.1%) between 2020 and 2023, while the number of COPD patients with a recorded chronic HRF diagnosis rose from 160 to 291 (+81.9%). The proportion rose from 0.59% (95% CI 0.50–0.69) to 0.90% (95% CI 0.80–1.01), an absolute increase of 0.31 percentage points (95% CI 0.17–0.45; risk ratio 1.53, 95% CI 1.26–1.85). Men had higher odds than women after adjustment for age (adjusted OR 1.55, 95% CI 1.28–1.88), and adjusted odds were lowest in patients aged 80 years or older. Across the four annual cross-sections, COPD accounted for 41.5% of patient-year observations with a recorded J96.11 diagnosis nationally. Conclusions: Knowledge of COPD, hypercapnia, and oxygen therapy varied among the prehospital emergency-care professionals surveyed, with one of the lowest proportions of correct responses observed for the recommended target oxygen saturation range. National electronic health record data showed an increase in the proportion of patients with COPD who had a recorded diagnosis of chronic HRF between 2020 and 2023. These components were analysed independently, and no relationship between professional knowledge and temporal trends in recorded diagnoses was assessed. The electronic health record findings support continued monitoring and recognition of chronic HRF in COPD, whereas the survey findings support further evaluation of targeted education on oxygen therapy in the prehospital setting. Full article

Point-of-care (POC) diagnostic testing based on microfluidic technology plays an important role in coagulation management. Its precision is, however, limited by the inefficient mixing between blood and solid activators in laminar microfluidic flow. In this study, a novel micromixer incorporating periodic oscillatory flow was developed to enhance blood-activator mixing. A computational fluid dynamic (CFD) model was established to investigate the microscale hydrodynamic characteristics and solid dispersion behavior in the oscillatory multiphase flow system. The numerical predictions were validated against tracer mixing experiments. Sample calculations for the air-liquid-solid flow system demonstrated that the initial loading position of activator particles significantly affected the dispersion efficiency due to the spatial variation in the radial velocity field. Compared with the center-initialized case, the solid dispersion level in the corner-initialized case decreased by approximately 42% after two oscillation cycles. Furthermore, the influence mechanism of oscillation period on solid dispersion was clarified through multi-physics coupling analysis. This study provided new insights into solid–liquid mixing in oscillatory microfluidic systems and established an effective CFD-based framework for optimizing microdevice design and operating conditions. Full article

Mosquito-borne viruses, including dengue, Zika and chikungunya viruses, place a substantial burden on diagnostic services, especially where molecular laboratories are inaccessible or slow to return results. Point-of-care biosensors could reduce turnaround times and bring testing closer to patients in primary care, outbreak response, and field settings. This review critically examines nucleic acid amplification, CRISPR-assisted assays, lateral-flow platforms, microfluidic systems, electrochemical and optical biosensors, paper-based devices, and smartphone-enabled readouts. These technologies are evaluated in terms of sample preparation, analytical sensitivity and specificity, matrix interference, multiplexing, workflow integration, cost, and clinical validation. Overall, nucleic-acid-amplification and CRISPR-assisted platforms often achieve low reported detection limits under controlled conditions; lateral-flow and paper-based devices offer relatively simple and minimally instrumented workflows; and microfluidic, electrochemical, and smartphone-enabled systems support increasing levels of workflow integration, quantitative readout, and connectivity. However, few platforms currently integrate these advantages into a fully integrated and clinically validated “sample-to-result” workflow. Due to sample heterogeneity, viral strains, reference methods, assay conditions, and disparities in reporting practices, conducting meaningful cross-study comparisons remains challenging. Limited comparisons and insufficient prospective clinical and field validation further restrict the assessment of practical diagnostic utility. Therefore, strong analytical performance alone should not be interpreted as evidence of clinical validity. Priority directions include unified definitions of performance and reporting units, standardized validation protocols and external quality assessment, prospective multi-site evaluation using representative populations and specimens, and earlier consideration of manufacturing scalability, reagent stability, quality systems, and applicable regulatory requirements. Future platforms should integrate simplified sample preparation, multiplex detection, objective digital or AI-assisted interpretation, and secure connectivity while demonstrating measurable benefits for patient management and outbreak surveillance. Full article

Cognitive function is central to healthy aging and is an important health outcome for evaluating long-term care policy. This study examines whether exposure to China’s long-term care insurance (LTCI) pilot is associated with cognitive function among adults aged 45 years and older. Using five waves of the China Health and Retirement Longitudinal Study (CHARLS) from 2011, 2013, 2015, 2018, and 2020, we estimate difference-in-differences (DID) models with individual and survey-wave fixed effects. Ten first-batch pilot cities are retained on the basis of implementation timing, with 2011–2015 classified as pre-policy and 2018–2020 as post-policy. Cognitive function is measured by a 0–21 composite score of episodic memory and mental intactness. In the preferred parsimonious specification, LTCI pilot exposure is associated with a 0.478-point reduction in the composite score (city-clustered SE = 0.168), equivalent to approximately 0.128 standard deviations; wild cluster bootstrap inference yields p = 0.008. The estimate remains negative under alternative covariate specifications, exclusion of the 2018 wave, pre-policy PSM-DID, and province-by-wave fixed effects. Event-study estimates are close to zero before the policy and negative thereafter, while city-level placebo estimates are centered near zero. Formal interaction tests indicate heterogeneity by baseline age, marital status, and hukou after false discovery rate adjustment but not by gender or number of children. The interaction with 2015 baseline CES-D is marginally significant (p = 0.063) and is therefore interpreted as exploratory. Overall, the findings suggest a modest negative association between LTCI pilot exposure and the composite cognitive-function score and highlight the value of monitoring domain-specific cognitive outcomes within long-term care policy. Domain-specific estimates diverged: episodic memory increased (beta = 0.300, p < 0.001), whereas mental intactness decreased (beta = −0.812, p < 0.001). In an age-stratified sensitivity analysis based on 2015 pre-policy age, the estimate was not statistically significant among adults aged 45–59 years (beta = 0.168, p = 0.380) but was negative among those aged 60 years or older (beta = −0.362, p = 0.003); the between-group interaction was significant (beta = −0.530, p = 0.040). Full article

This review systematically summarizes recent advances in CRISPR-Cas12b-based pathogen nucleic acid detection. Starting with an overview of conventional nucleic acid detection methods and core CRISPR-Cas mechanisms, we highlight the unique properties that distinguish Cas12b from other Cas effectors. We elaborate on the working principles of the CRISPR-Cas12b system and present comparative structural and functional analyses with other Cas variants to underscore its distinctive molecular architecture and enzymatic properties. A comprehensive evaluation of current applications demonstrates the efficacy of CRISPR-Cas12b-based diagnostics across diverse pathogens, including viruses, bacteria, and parasites, with a specific focus on its integration with isothermal amplification techniques. We further examine the translational potential of CRISPR-based diagnostics in clinical settings, while critically analyzing persistent technical challenges including off-target effects, signal amplification limitations, and sample preparation requirements. Targeted strategic recommendations are proposed to optimize detection sensitivity, develop multiplexed detection platforms, and implement point-of-care testing configurations. This review aims to systematically correlate the unique characteristics of Cas12b with its broad diagnostic applications, thereby addressing key research gaps in its progression toward clinical validation and field deployment. It also provides a targeted framework to accelerate the translation of this technology from laboratory platforms to practical diagnostic solutions. Full article

Background/Objectives: Access to accurate tuberculosis (TB) diagnostics remains limited, particularly in high-burden settings. The Pluslife MTB assay is among the first molecular tests specifically designed for swab-based detection of Mycobacterium tuberculosis complex (MTBC) and offers near point-of-care use. Methods: We conducted a prospective diagnostic accuracy study in South Africa to evaluate the performance of the Pluslife assay on tongue swabs (TSs) and sputum swabs (SSs) among symptomatic and asymptomatic adults. Results were compared against liquid culture as the reference standard and Xpert MTB/RIF Ultra (Xpert Ultra) as a comparator. Operational characteristics and ease-of-use were assessed through structured observation and Likert-scale scoring by testing personnel. Results: Of the 256 participants enrolled, 92 [36%] were people with HIV (PHIV) and 217 were included in the final analysis. Culture confirmed TB in 41/217 (19%). Pluslife on SSs demonstrated a sensitivity of 85% (95% CI: 70.8–94.4), compared to 83% (95% CI: 67.9–92.8), for Xpert Ultra on sputum and detected one additional case (paired analysis, p = 1.000). Sensitivity on TSs was lower (63%, 95% CI: 46.9–77.9), particularly among PHIV. Specificity exceeded 97% across specimen types. Concordance on TSs between Pluslife and Xpert Ultra increased with higher bacterial loads. Operational evaluation showed short hands-on time and high ease-of-use scores, though limitations were noted for patient identifier recording and troubleshooting on the Pluslife MiniDock device. Conclusions: The Pluslife MTB assay on SSs demonstrated good diagnostic accuracy and favorable usability in this study. Tongue swabs remain feasible but less reliable, supporting sputum as the preferred first specimen for TB diagnosis. Full article

Hemoglobin (Hb) and its glycated variant (HbA1c) are essential clinical biomarkers for diagnosing anemia, acute hemorrhage, and long-term glycemic control. The growing demand for decentralized point-of-care (POC) testing has accelerated the development of rapid, inexpensive, and portable electrochemical sensing platforms. These technologies exploit the intrinsic redox activity of the heme prosthetic group, yet achieving efficient direct electron transfer (DET) remains a fundamental challenge because the electroactive iron center is deeply embedded within the globin structure. This review critically examines recent advances in electrochemical Hb sensing, tracing the evolution of electrode architectures from conventional carbon substrates to nanostructured materials, including graphene, MXenes, metal–organic frameworks (MOFs), and molecularly imprinted polymers (MIPs). We compare the advantages and limitations of non-enzymatic biomimetic platforms and affinity-based sensing strategies, including aptamer- and antibody-based biosensors, with emphasis on electron-transfer efficiency, molecular selectivity, analytical performance, and suitability for POC implementation. Beyond analytical performance, we evaluate the principal barriers to clinical translation, including biofouling, whole-blood matrix effects, viscosity-dependent mass transport, manufacturing scalability, and the persistent gap between validation in synthetic media and performance in clinical samples. Finally, we discuss emerging applications in wearable menstrual health monitoring and ingestible gastrointestinal bleeding sensors, highlighting the integration of advanced electrochemical materials with miniaturized electronics as a pathway toward practical, consumer-oriented diagnostics. Full article

Background/Objectives: Dental caries remains one of the most prevalent chronic diseases in childhood, influenced by a combination of hygiene, dietary, and access-related behaviours that are largely shaped by parental involvement. This study aimed to evaluate oral hygiene habits, dietary risk factors, access to dental services, awareness of caries prevention, and the impact of oral health on the child, in relation to parent-reported dental caries in Romanian children and adolescents. Methods: A cross-sectional study was conducted using a structured online questionnaire completed by parents or legal guardians of 508 children and adolescents aged under 18 years. Associations between categorical variables and reported caries were assessed using chi-square tests and Cramér’s V. Ordinal variables were compared using the Mann–Whitney U test. A multivariable logistic regression identified independent predictors of reported caries, with robustness examined through sensitivity analyses. Results: Parent-reported caries was present in 61.2% of children. The strongest associations with caries were the absence of parental supervision during brushing (Cramér’s V = 0.364), the age at which children began brushing unsupervised (V = 0.354), and the reason for the last dental visit (V = 0.426). In the multivariable model, older age, absence of brushing supervision, sweets before bedtime, less frequent dental visits, and rural residence were independent predictors (all p < 0.05; Nagelkerke R² = 0.361). All six assessed dimensions of oral-health impact on the child were significantly associated with caries, with physical discomfort showing the largest effect (V = 0.349). Conclusions: Parent-reported caries risk in this population clustered around a small number of modifiable behaviours rather than any single dominant factor, while reported caries was associated with a substantial burden on children’s daily functioning. These findings point to sustained parental supervision and routine, non-symptomatic dental care as priority targets for future prevention efforts, although intervention studies are needed to confirm their effectiveness. Full article

Automated cybergrooming detection can support the review of large volumes of online communication, but public datasets and detection approaches remain predominantly English-centered. This study presents a reproducible workflow for constructing target-language cybergrooming datasets and detection models from English resources, demonstrated for German. To the best of our knowledge, this is the first published study to construct and systematically evaluate German-language cybergrooming datasets and detection models. Four publicly available English cybergrooming datasets were converted into a shared structure and translated into informal German chat language. Translation quality was estimated using an aggregate of COMETKiwi and MetricX scores termed CometricX. Low-quality messages were retranslated and reevaluated. Cybergrooming messages were additionally augmented through German–Catalan backtranslation. The resulting datasets, with and without augmentation, were used to train and evaluate embedding-based linear support vector machines (SVMs) and ModernBERT models. Evaluation comprised translated test data and 156 manually labeled German conversations from five closed law-enforcement cases. The Perverted Justice Zig ChitChat dataset (PJZC) achieved the highest aggregate quality estimate and the most robust detection performance on real-world German conversations. In contrast, performance on machine-translated test data overestimated real-world detection performance. Furthermore, backtranslation yielded only limited and inconsistent improvements. Overall, the proposed workflow provides a practical starting point for developing target-language cybergrooming detectors while highlighting careful source dataset selection and evaluation on authentic target-language data. Full article

Chronic kidney disease (CKD) requires assessment of both glomerular filtration and kidney damage, particularly albuminuria, for diagnosis, risk stratification, and longitudinal care. Point-of-care testing (POCT) can shorten turnaround time and improve access when conventional laboratory testing is unavailable or would delay a clinical pathway. This narrative review summarizes established and emerging POCT approaches for kidney assessment in CKD, with emphasis on creatinine/eGFR and urine albumin-to-creatinine ratio (UACR), and distinguishes analytical validity from workflow utility and patient-level clinical utility. Evidence is strongest for rapid creatinine measurement in selected workflows, especially pre-imaging assessment and decentralized screening, while quantitative/semiquantitative UACR POCT can support CKD detection when abnormal results are appropriately confirmed. Cystatin C microfluidic systems remain investigational, and kidney injury/stress or molecular biomarkers such as NGAL, KIM-1, L-FABP, [TIMP-2]·[IGFBP7], extracellular vesicles, and microRNAs should be regarded primarily as a research horizon rather than direct measures of GFR. Important implementation requirements include assay-specific validation, calibration traceability, quality assurance, recognition of biological and analytical interference, and confirmation of results near major clinical decision thresholds. Evidence that POCT improves long-term CKD outcomes, safety, adherence, or cost-effectiveness remains limited. Future studies should prioritize prospective clinical utility, implementation, cost-effectiveness, home-use validation, and patient-centered outcomes. Full article

Artificial intelligence (AI) and machine learning (ML) now reach into every stage of AML care. Deep learning models read therapy-relevant mutations directly from bone marrow smears; automated flow cytometry gating reproduces expert calls in under a minute; and the first AI pathology devices for hematology have cleared regulatory review and entered clinical use. Beyond diagnosis, ML captures the age-dependent weight of individual mutations that categorical ELN scoring misses, drug response prediction for venetoclax–azacitidine has been validated across multiple external cohorts, and large language models are being tested for tumor board support and trial matching. The next wave, from clonal architecture modeling and single-cell foundation models to digital twins and reinforcement learning for adaptive dosing, could move AML management from reactive toward predictive, evolution-aware care. This review departs from existing AI-in-hematology surveys in three ways: we (i) restrict the scope to AML and organize the field around clinical decision points rather than technology categories, (ii) grade every tool on a five-tier author-defined clinical readiness level (CRL-AML 1–5), which exposes hundreds of models clustered at CRL-AML 1–2 and none yet in prospective clinical evaluation, and (iii) close with a numbered three-year agenda naming the consortia, datasets, and pragmatic trials needed to carry the field from publication to practice. Full article

Background: Hypertensive retinopathy (HR) is an early marker of hypertension-related end-organ damage, and multi-grade classification is limited by overlap between the early stages. No prior study has reported edge-deployable HR grading from optical coherence tomography (OCT). We assess patient-level–validated four-grade HR classification from en-face OCT with on-device inference. Methods: MobileViT-XXS and EfficientNetV2-B0 were evaluated on 478 en-face OCT images from 221 patients. To avoid leakage, all partitions were patient-level: stratified group 5-fold cross-validation with a patient-disjoint test set. Each model was evaluated as a 5-fold soft-voting ensemble, with inference profiled on an NVIDIA Jetson Orin Nano. Accuracy, weighted F1, quadratic-weighted kappa, and ROC–AUC were reported; the models were compared by McNemar’s test, and clinical utility by referable-HR (Grade ≥ 2) triage. Results: MobileViT-XXS achieved 84.4% accuracy, ROC–AUC 0.944, and quadratic-weighted kappa 0.916, significantly outperforming EfficientNetV2-B0 (McNemar p = 0.013). Mild-grade overlap limited four-class accuracy, but referable-HR triage reached 95.6% accuracy, 95.2% sensitivity, and 95.8% negative predictive value. MobileViT-XXS required only 3.83 MB versus 23.70 MB, and on-device TensorRT FP16 five-fold ensemble inference achieved 10.4 ms (96 FPS) at 8.9 W. Conclusions: Lightweight models enable feasible, power-efficient point-of-care HR triage from en-face OCT; broader multi-center validation is warranted. Full article

Background & Aims: One-carbon metabolism plays a central role in neurotransmitter synthesis, methylation capacity, and neurobiological resilience. Variants in the methylenetetrahydrofolate reductase (MTHFR) gene can reduce enzymatic activity, affecting folate- and methionine-cycle functions and potentially influencing biological pathways relevant to mood and anxiety disorders. Personalised nutraceutical treatment strategies, particularly those addressing methylation capacity through targeted B-vitamin, folate, and adjunctive metabolic interventions are increasingly implemented in integrative clinical practice, yet evidence regarding their clinical outcomes remains limited. Methods: We conducted a retrospective cohort study of 50 adults attending an integrative general practice clinic for anxiety and/or depression. All received personalised nutraceutical treatment informed by clinical assessment, laboratory testing and, for 37/50 patients, MTHFR genotyping. Psychological distress was measured using the Kessler-10 (K10) scale at baseline and approximately three months later. Secondary analyses evaluated whether outcomes differed by MTHFR genotype, whether specific supplements (e.g., L-methylfolate and SAMe) were associated with greater improvement, whether biomarker changes correlated with symptom change, and the safety/tolerability profile. Results: Across the full cohort, mean K10 scores significantly decreased by four points over the treatment period, with 72% of patients showing clinical improvement. Reductions in psychological distress were seen across all MTHFR genotypes, including individuals with homozygous variant genotypes. Supplement-specific analyses showed improvement among those receiving methylfolate or SAMe, although the differences were not statistically significant. Following nutraceutical treatment, biomarker analyses demonstrated significant increases in serum vitamin B12 and modest reductions in homocysteine, but biomarker shifts did not correlate strongly with K10 change. No serious adverse events or clinically significant abnormalities in liver or renal function were identified. Conclusions: In this real-world primary care cohort, personalised nutraceutical treatment, grounded in one-carbon metabolism support and applied alongside usual care, was associated with clinically meaningful reductions in psychological distress. Outcomes were comparable across MTHFR genotypes when treatments were appropriately tailored, suggesting that genotype and biomarker-informed nutraceutical strategies may mitigate potential metabolic disadvantages. These findings support further controlled research into precision nutraceutical psychiatry for anxiety and depression. Secondary analyses of genotype subgroup, specific supplements, and biomarker–outcome associations are reported alongside Benjamini–Hochberg FDR-adjusted p-values and should be interpreted as hypothesis-generating. Full article

Conventional diagnosis of chronic kidney disease (CKD) relies predominantly on invasive blood-based examinations, limiting the scalability of kidney health screening in resource-constrained environments. This study presents embedded engineering framework for non-invasive, breath-based CKD staging framework supported by machine learning and implemented on a low-cost embedded platform. To account for physiological sex differences in baseline creatinine production, estimated glomerular filtration rate (eGFR) values and breath ammonia concentrations were derived from two independent clinical cohorts using sex-specific MDRD equations (incorporating the standard male formula and the $0.742$ female correction factor, respectively) and creatinine–BUN conversion models, with male- and female-parameterized algorithms developed in parallel. The resulting feature space was analyzed using four unsupervised clustering approaches to stratify subjects into five clinically meaningful kidney function stages. Stage-specific ammonia thresholds were implemented within an Arduino Nano-based prototype equipped with an MQ-137 gas sensor and OLED display, enabling real-time point-of-care classification. Dataset-level classification accuracy reached 82% for the male algorithm and 92% for the female algorithm. Hospital-based validation on 29 patients (22 male, 7 female) yielded a real-world testing accuracy of 90.5% ($20/22$) for male patients and 71.4% ($5/7$) for female patients, a discrepancy largely attributable to the small female sample size. Because the current evaluation lacks healthy control subjects and is constrained by sample size, these empirical results serve primarily to demonstrate hardware-software functional integration and real-world deployment feasibility rather than definitive clinical efficacy. Despite these preliminary, sample-limited clinical datasets, results suggest this approach holds promise as an accessible, non-invasive screening complement to conventional diagnostic pathways, particularly in low-resource healthcare settings. Full article

Background and Objectives: Existing severity scores for acute pancreatitis (AP), such as the Ranson, Glasgow-Imrie, APACHE II, BISAP, Balthazar scores, are limited by complexity, delayed availability, or insufficient discriminative accuracy. We aimed to develop a new prognostic score using parameters available at admission in any primary or regional care setting, suitable for early risk stratification and clinical decision-making in AP. Materials and Methods: We conducted a retrospective observational study of 194 patients admitted with acute pancreatitis, classified as mild (MILD, n = 59), moderately severe (n = 82) and severe (n= 53) course, according to the Revised Atlanta Classification. Candidate predictors—including demographic, clinical, inflammatory, nutritional, and radiological variables—were screened using univariable analysis, and independent predictors were identified by backward stepwise logistic regression. Discriminative performance was assessed using receiver operating characteristic (ROC) curve analysis and compared with six established severity scores (Ranson, Glasgow-Imrie, Balthazar, CTSI, BISAP, and HAPS). APACHE II was not included in this comparison because some of its required physiological variables were not consistently available outside the intensive care unit. Results: MODSEV (moderately severe/severe) patients showed significantly higher inflammatory, nutritional, and metabolic derangement at admission than MILD patients. Six variables—admission white blood cell count, blood urea nitrogen (BUN), pleural effusion, admission blood glucose level, platelet-to-lymphocyte ratio (PLR), and serum albumin—were retained in the final logistic regression model (ProbScore2), which demonstrated excellent discriminative ability (AUC = 0.873; 95% CI: 0.819–0.927), showing, within this retrospective cohort, a numerically higher AUC than the Glasgow-Imrie (AUC = 0.832), CTSI (0.775), Balthazar (0.758), BISAP (0.725), Ranson (0.676) and HAPS (0.574). A simplified, unweighted 0–6 point bedside version of the score retained most of this discriminative ability (AUC = 0.852), with an optimal cut-off of ≥3 points yielding a sensitivity of 77.0% and a specificity of 79.7%. Conclusions: ProbScore2, a novel six-variable prognostic score, demonstrated excellent discriminative performance for the early identification of moderately severe/severe acute pancreatitis, with a numerically higher AUC than established severity scoring systems evaluated within this same retrospective, single-center cohort (excluding APACHE II, which could not be calculated for all patients). These comparative findings require confirmation through prospective external validation before any conclusions about generalizable superiority can be drawn. Five of the six components are derived from routine admission blood tests, and the sixth (pleural effusion) requires only a plain chest radiograph rather than cross-sectional imaging. The score and its simplified bedside adaptation can therefore be calculated within hours of admission using resources available even in hospitals without intensive care or advanced, CT-based imaging capabilities. ProbScore2 is not yet ready for routine clinical use; prospective external validation in independent, multicenter cohorts is required before clinical implementation. Full article