OBJECTIVE: Primary biliary cholangitis is a chronic and progressive autoimmune liver disease, whose prognosis can be improved by normalizing alkaline phosphatase and bilirubin. While ursodeoxycholic acid (UDCA) is first line standard of care, approximately 40 % of patients exhibit incomplete response. We aimed to identify prognostic markers for deep response to UDCA therapy at presentation.
METHODS: Data from the Brazilian Cholestasis Study Group cohort were analyzed retrospectively. Patients were assessed for deep response, defined as normal alkaline phosphatase and bilirubin, after 1 year of UDCA treatment. Additionally, the performance of the UDCA response score in predicting deep response was evaluated.
RESULTS: A total of 297 patients were analyzed, with 57.2 % achieving an adequate response according to the Toronto criteria, while 22.9 % reached deep response. Cirrhosis (OR 0.460; 95 % CI 0.225-0.942; p = 0.034) and elevated baseline alkaline phosphatase levels (OR 0.629; 95 % CI 0.513-0.770; p < 0.001) were associated with reduced odds of deep response. The UDCA response score exhibited moderate discrimination power (AUROC = 0.769) but lacked calibration.
CONCLUSIONS: Baseline ALP and liver fibrosis emerge as the most important prognostic factors to predict normalization of alkaline phosphatase and bilirubin after UDCA. The UDCA response score was inadequate for predicting deep response in the Brazilian PBC population.

BACKGROUND: Leaflet thrombosis (LT) is a multifaceted and underexplored condition that can manifest following transcatheter aortic valve implantation (TAVI). The objective of this study was to formulate a prediction model based on laboratory assessments and clinical parameters, providing additional guidance and insight into this relatively unexplored aspect of post-TAVI complications.
METHODS: The present study was an observational prospective hypothesis-generating study, including 101 patients who underwent TAVI and a screening for LT (the primary endpoint) by multidetector computed tomography (MDCT). All images were acquired on a third-generation dual-source CT system. Levels of von Willebrand factor (vWF) activity, hemoglobin (Hb), and lactate dehydrogenase (LDH) were measured among other parameters. A predictive score utilizing binary logistic regression, Kaplan-Meier time-to-event analysis, and receiver operating characteristics (ROC) analysis was established.
RESULTS: LT (11 subclinical and 2 clinical) was detected in 13 of 101 patients (13%) after a median time to screening by MDCT of 105 days (IQR, 98-129 days). Elevated levels of vWF activity (> 188%) pre-TAVI, decreased Hb values (< 11.9 g/dL), as well as increased levels of LDH (> 312 U/L) post-TAVI and absence of oral anticoagulation (OAC) were found in patients with subsequent LT formation as compared to patients without LT. The established EFFORT score ranged from - 1 to 3 points, with an increased probability for LT development in patients with ≥ 2 points (85.7% of LT cases) vs < 2 points (14.3% of LT cases; p < 0.001). Achieving an EFFORT score of ≥ 2 points was found to be significantly associated with a 10.8 times higher likelihood of developing an LT (p = 0.001). The EFFORT score has an excellent c-statistic (area under the curve (AUC) = 0.89; 95% CI 0.74-1.00; p = 0.001) and a high negative predictive value (98%).
CONCLUSIONS: An EFFORT score might be a helpful tool to predict LT development and could be used in risk assessment, if validated in confirmatory studies. Therefore, the score has the potential to guide the stratification of individuals for the planning of subsequent MDCT screenings.

BACKGROUND: No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery.
METHODS: In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score.
RESULTS: The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P < 0.05).
CONCLUSIONS: The AKI-Pro score is a new clinical tool that could assist clinicians to identify early AKI patients at high risk for AKI progression or death.

BACKGROUND: The Assessment of Blood Consumption (ABC) score is used to predict massive transfusions (MT). However, its diagnostic performance has not been widely examined, especially when used as an objective tool to enroll patients in multi-center clinical trials. The purpose of this study was to evaluate the performance of the ABC score in enrolling patients in the Pragmatic Randomized Optimal Platelet and Plasma Ratios (PROPPR) trial. We hypothesized the ABC score would have a similar diagnostic performance to predict the need for massive transfusion as previous studies.
METHODS: This is a retrospective analysis of the PROPPR trial. Patients were enrolled either on the basis of an ABC score ≥2, or by Physician Gestalt, when the ABC score was <2. We calculated the sensitivity, specificity, positive (PPV) and negative (NPV) predictive values and likelihood ratios of the ABC score (≥2) for predicting MT (>10 units of red blood cells/24 h or transfusion of >3 units of red blood cells within the first hour).
RESULTS: Of the 680 patients, 438 patients (64 %) had an ABC score of ≥2 and 242 (36 %) had an ABC score of <2. An ABC score of ≥2 had 66.8 % sensitivity and 37.0 % specificity for predicting the need for MT, with a PPV of 88.2 % and NPV of 13.1 %. Similarly, an ABC≥2 had 65.6 % sensitivity and 44.6 % specificity for predicting the need for >3 units RBCs in 1 hour, with a PPV of 89.5 % and NPV of 15.3 %.
CONCLUSIONS: The ABC score had lower performance than previously reported for predicting MT, when applied to PROPPR trial patients. The performance for predicting the need for a 3-unit red blood cell transfusion (or more) in the first hour was slightly higher.
METHODS: Level III, Prognostic.

BACKGROUND: A score to predict the association between unexplained osteoporosis and an underlying systemic Mastocytosis (SM) is lacking.
OBJECTIVE: This study aimed at identifying criteria able to predict the diagnosis of SM without skin involvement and provide an indication for bone marrow (BM) assessment.
METHODS: We included 139 adult patients with unexplained osteoporosis and suspected SM. After BM evaluation, 63 patients (45.3 %) were diagnosed with SM, while the remaining 76 patients (54.7 %) negative for clonal mast cell (MC) disorders, constituted our control group. Univariate and multivariate analysis identified three independent predictive factors: age (<54 years: +1 point, >64 years: -1 point), serum basal tryptase (sBT) levels >19 ng/mL (+2 points) and vertebral fractures (+2 points).
RESULTS: These variables were used to build the OSTEO-score, able to predict the diagnosis of SM before BM assessment with a sensitivity of 73.5 % and a specificity of 67.1 %. Patients with a score < 3 had a lower probability of having SM compared to patients with a score ≥ 3 (28.5 % and 71.4 %, respectively, p < 0.0001). When sBT levels were corrected for the presence of hereditary alpha-tryptasemia (HαT) using the BST calculater (https://bst-calculater.niaid.nih.gov/) recently published [1,2], the sensitivity of ΗαT-adjusted OSTEO-score increased to 87.8 %, and the specificity reached 76.1 %. Also, the positive predictive value of a score ≥ 3 increased to 85.2 %.
CONCLUSIONS: Further studies are needed to validate these results and characterize the role of tryptase genotyping in patients with unexplained osteoporosis in reducing the risk of misdiagnosing patients with SM. Our proposed scoring model allows the identification of patients with the highest probability of having SM, avoiding unnecessary BM studies.

BACKGROUND: Mechanical ventilation significantly improves patient survival but is associated with complications, increasing healthcare costs and morbidity. Identifying optimal weaning times is paramount to minimize these risks, yet current methods rely heavily on clinical judgment, lacking specificity.
METHODS: This study introduces a novel multiparametric predictive score, the MUSVIP (MUltiparametric Score for Ventilation discontinuation in Intensive care Patients), aimed at accurately predicting successful extubation. Conducted at Santo Stefano Hospital\'s ICU, this single-center, observational, prospective cohort study will span over 12 months, enrolling adult patients undergoing invasive mechanical ventilation. The MUSVIP integrates variables measured before and during a spontaneous breathing trial (SBT) to formulate a predictive score.
RESULTS: Preliminary analyses suggest an Area Under the Curve (AUC) of 0.815 for the MUSVIP, indicating high predictive capacity. By systematically applying this score, we anticipate identifying patients likely to succeed in weaning earlier, potentially reducing ICU length of stay and associated healthcare costs.
CONCLUSIONS: This study\'s findings could significantly influence clinical practices, offering a robust, easy-to-use tool for optimizing weaning processes in ICUs.

Background and Aims: Cardiovascular disease and colorectal cancer (CRC) are significant health problems and share some risk factors. The aim of our study was to develop and validate a predictive score for advanced colorectal neoplasia (CRN) based on risk factors for cardiovascular disease and CRC. Materials and Methods: A cross-sectional study comprising a derivation cohort and an external validation cohort of 1049 and 308 patients, respectively. A prediction score for advanced CRN (CRNAS: Colorectal Neoplasia Advanced Score) was developed from a logistic regression model, comprising sex, age, first-degree family history for CRC, systolic and diastolic blood pressure, total cholesterol, HDL cholesterol, body mass index, diabetes, smoking, and antihypertensive treatment. Other cardiovascular risk scores (Framingham-Wilson, REGICOR, SCORE, and FRESCO) were also used to predict the risk of advanced CRN. The discriminatory capacity of each score was evaluated using the area under the curve (AUC). Results: CRN were found in 379 subjects from the derivation cohort (36%), including 228 patients (22%) with an advanced CRN. Male sex, age, diabetes, and smoking were identified as independent risk factors for advanced CRN. The newly created score (CRNAS) showed an AUC of 0.68 (95% CI: 0.64-0.73) for advanced CRN, which was better than cardiovascular risk scores (p < 0.001). In the validation cohort, the AUC of CRNAS for advanced CRN was 0.67 (95% CI: 0.57-0.76). Conclusions: The newly validated CRNAS has a better discriminatory capacity to predict advanced CRN than cardiovascular scores. It may be useful for selecting candidates for screening colonoscopy, especially in those with cardiovascular risk factors.

BACKGROUND: Several risk stratification scores have been suggested to aid prognostication and guide treatment strategies for brain metastases (BMs). However, the current scores do not focus on the specific neurosurgical population, therefore not predicting short-term mortality and postoperative performance status.
METHODS: This retrospective observational study of 362 consecutive patients treated with surgery for BMs aims to identify the factors associated with post-surgical outcomes and propose a surgery-specific prognostic score for patients with BMs candidate for open surgery.
RESULTS: Factors significantly associated with OS and performance status in multivariate analysis were age, KPS, surgical site, synchronous debut of BM, number, tumor volume, seizure, extra-cranial metastases, and deep-seated location. The variables were incorporated into the Anamnestic Radiological Metastases Outcome Surgical score (ARMO-S). The values range between 0 and 10. Patients were divided into two groups (low-risk and high-risk) based on each significant subgroup\'s median survival and performance status with an optimal cutoff value determined as 4. The two groups have significant differences in OS (9.6 versus 14 months, p = 0.0048) postoperative KPS (90 versus 70, p = 0.012) and KPS at last follow-up evaluation (75 versus 30, p < 0.001) CONCLUSION: ARMO-S is a simple and comprehensive score for BM patients selected for neurosurgery, as it incorporates the main factors of the most important prognostic scores, implementing them with more surgery-specific predictive elements such as tumor location and volume, presence of seizures at onset, and involvement of eloquent brain areas.

Hydrocephalus following brain tumor surgery is found, although cause of hydrocephalus is optimally eradicated. This study aimed to investigate factors associated with development of postoperative hydrocephalus that requires shunt procedure and generate predictive scoring model of this condition. Demographic, clinical, radiographic, treatment, laboratory, complication, and postoperative data were collected. Binary logistic regression was used to investigate final model for generating predictive scoring system of postoperative hydrocephalus. A total of 179 patients undergoing brain tumor surgery were included. Forty-five (25.1%) patients had postoperative hydrocephalus that required shunt surgery. In univariate analysis, several factors were found to be associated with postoperative hydrocephalus. Strong predictors of postoperative hydrocephalus revealed in multivariate analysis included tumor recurrence before surgery (odds ratio [OR], 4.38; 95% confidence interval [CI], 1.28-14.98; p  = 0.018), preoperative hydrocephalus (OR, 6.52; 95% CI, 2.44-17.46; p  < 0.001), glial tumor (OR, 3.76; 95% CI, 1.14-12.43; p  = 0.030), metastasis (OR, 5.19; 95% CI, 1.72-15.69; p  = 0.004), intraventricular hemorrhage (OR, 7.08; 95% CI, 1.80-27.82; p  = 0.005), and residual tumor volume (OR, 1.05; 95% CI, 1.01-1.09; p  = 0.007). A cutoff predictive score with the best area under curve and optimum cutoff point was utilized for discriminating patients with high risk from individuals with low risk in occurrence of postoperative hydrocephalus. This study reported predictive factors strongly associated with development of postoperative hydrocephalus. Predictive scoring system is useful for identifying patients with an increased risk of postoperative hydrocephalus. Patients classified in the high-risk group require closed surveillance of the hydrocephalus.

OBJECTIVE: To develop a predictive scoring system to identify traumatic cervical spine injury patients at a high risk of having multilevel noncontiguous spinal fractures.
METHODS: This 12-year retrospective observational cohort study included 588 traumatic cervical spine-injured patients. Patients were categorized into two groups: patients with multilevel noncontiguous spinal fractures and patients without this remote injury. Potential risk factors were examined using multivariable analysis to derive a predictive risk score from independent predictors. Results are presented as odds ratio with a 95% confidence interval (95% CI). The accuracy of the calculated predicted score was demonstrated by the area under the receiver operating characteristic curve (AuROC).
RESULTS: The incidence of noncontiguous fracture among the patients was 17% (100 of 588). The independent risk factors associated with multilevel noncontiguous spinal fractures were motor weakness, intracranial injury, intrathoracic injury, and intraabdominal injury. The AuROC of the prediction score was 0.74 (95% CI 0.69, 0.80). The patients were classified into three groups, low-risk group (score< 1), moderate-risk group (score 1-2.5), and high-risk group (score≥ 3), based on the predicted risk of multilevel noncontiguous spinal fractures.
CONCLUSIONS: This tool can potentially help preventing the missed diagnosis of cervical spine injuries with multilevel noncontiguous spinal fractures. CT scans or MRI of the entire spine to investigate remote multilevel noncontiguous spinal fractures may have a role in cervical spine-injured patients who have at least one of the independent risk factors and are strongly suggested for patients with scores in the high-risk group.