Early Detection Of Patients Research Articles

MOVING DIAGNOSIS OF LIVER FIBROSIS INTO THE COMMUNITY.

Chronic liver diseases (CLD) are a leading cause of death worldwide, with alcohol consumption and metabolic risk factors as the two reasons accounting for the majority of cases of CLD in many developed countries. Currently there is a lack of specific strategies for early diagnosis of CLD and consequently most cases are diagnosed in advanced stages of the disease, which is associated with negative consequences for disease management and prognosis. Screening for CLD is based on either detection of chronic viral hepatitis B and C, or detection of liver fibrosis in patients with steatotic liver disease related to alcohol or metabolic dysfunction. There are non-invasive tools available for detection of liver fibrosis, including serological and imaging-based tests. Clinical practice guidelines recommend screening for liver fibrosis using algorithms that combine different non-invasive tests, with widely available but low accuracy tests such as FIB-4 for a first screening step in primary care setting, and other tests with less availability but higher accuracy, such as Transient Elastography or Enhanced Liver Fibrosis Test as a second step. There are different pathways for early detection of patients with CLD from primary to specialized care, where primary care providers are key for early detection, management and referral of patients. In addition, intervention on metabolic risk factors and alcohol consumption should be carried out in collaboration between specialized therapy and primary care. This review describes liver fibrosis from the community perspective, highlighting gaps in knowledge on how to define the optimal combination of tests, target population, the ideal pathway of care for CLD, and how to increase implementation of programs for early diagnosis of liver diseases in clinical practice.

Relationship of left ventricular longitudinal strain to coronary artery calcium load in patients with newly diagnosed type 2 diabetes mellitus

Abstract Introduction Cardiovascular complications commonly manifest after longstanding Type 2 Diabetes Mellitus. Newly diagnosed Type 2 Diabetes Mellitus (NDT2DM) is much less studied. The coronary artery computed tomography calcium score (CTCS) has become a widely accessible, accurate, and reliable tool for assessing the risk of major cardiovascular events, particularly in asymptomatic individuals. Additionally, myocardial strain, specifically echocardiographic Global Longitudinal Strain (GLS), measures the systolic function of the left ventricle (LV), enabling the early detection of systolic dysfunction. GLS is also increasingly recognized for its prognostic value in coronary artery disease. Purpose The objective of this study was to analyze the relationship and predictors of subclinical calcified atherosclerotic plaques in coronary arteries, measured by CTCS, to LV longitudinal strain in patients with NDT2DM. Methods In this prospective cross-sectional study 101 patients with NDT2DM, according to the criteria of the American Diabetes Association, were included. CTCS was performed on all patients by 64-slice cardiac CT, with a thickness of 2-5 mm. The Agatston method was used to determine the CTCS. For Speckle Tracking Echocardiography, images from the apical four-chamber, three-chamber and two-chamber views with ECG gating were attained. The endocardial border was manually adjusted at end-systole. The software system automatically generated the strain values for each segment, the average LV GLS, end-diastolic, end-systolic LV volumes and LV ejection fraction. With Spearman’s correlation test we analysed the relationship between LV longitudinal strain parameters and the level of CTCS. We also performed the multiple regression analysis to identify LV longitudinal strain predictors for high CTCS. Results Mean age was 54.4 ± 11.6 years, 53 (52.5%) were males, and mean time since diagnosis of diabetes was 2.8 ± 5.3 months. Only 8 (7.9%) patients did not have calcified atherosclerotic plaques or a CTCS of zero, 7 (6.9%) a CTCS of 1-10, 43 (42.6%) a CTCS of 11-100, 23 (22.8%) a CTCS 101-400 and 20 (19.8%) patients had CTCS >400. The mean total volume of calcium in these patients was 210. LAD had the highest CTCS, followed by RCA, LCx and left main coronary artery. Table 1 shows the correlation between CTCS and LV longitudinal strain parameters, while table 2 depicts predictors for higher CTCS. Conclusions LVGLS does not appear to correlate with the coronary artery calcium burden in patients with NDT2DM. However, regional LV longitudinal strain may serve as a predictor for asymptomatic calcified coronary artery plaques. Given that the LAD exhibits the highest CTCS, the predictive regions might correspond to this affected artery. Thus, a comprehensive analysis of both global and regional LV longitudinal strain could be beneficial for the early detection of patients at risk for cardiovascular complications. Correlation of CTCS and LV strain LV strain predictors for CTCS

Clinical Case of a Patient with Acute Tricuspid Valve Infective Endocarditis and A Multiplex Approach to Evaluation of The Complication Risk

Infective endocarditis (IE) is characterized by the difficulty of diagnosis, treatment and risk assessment of an unfavorable prognosis. Currently there are no approved scales and calculators for the risk of complications and death that help the practitioner make decisions, especially in patients with isolated right-sided IE. For right-sided IE, the timing of successful surgical treatment remains uncertain. Previously developed risk calculators (Italian Rizzi calculator and French Hubert) are poorly validated in a wide population of patients with IE, especially for right-sided IE. One of the required parameters of calculators is the determination of etiological affiliation. However, with negative results of microbiological studies reaching 56-83 %, this parameter becomes uninformative. Moreover, existing risk assessment tools do not take into account the activity of the disease (including laboratory activity), which intuitively is an important guideline for every doctor in decision-making. At the moment, there is a great need for the introduction of molecular biological methods to improve the quality of etiological diagnosis and in-depth study of possible biomarkers from simple (neutrophil/lymphocytic, platelet/lymphocytic and systemic immuno-inflammatory index) to more complex (neutrophil extracellular traps, cytokine profile). We present a clinical case of a young patient with acute tricuspid valve IE with giant vegetation (28 mm), complicated by severe valvular insufficiency without signs of heart failure, recurrent embolic syndrome in the pulmonary artery system with the formation of pulmonary hypertension, determining indications for cardiac surgical treatment. The etiological affiliation of IE to Staphylococcus aureus was established only by PCR. The urgent timing of intervention was determined based on an increase in new markers — neutrophil/lymphocytic index ≥20.0, systemic immuno-inflammatory index ≥2314.0 and neutrophil extracellular traps ≥14.2, indicating an extremely high risk of death. A fundamental pathohistological study of the tissue material revealed a low content of intact CD86+ proinflammatory macrophages, probably associated with their excessive destruction and uncontrolled release of copious amounts of proinflammatory cytokines, which led to rapid and severe damage to the tricuspid valve. Thus, modern management of patients with IE should be multiplex using current methods of etiological and imaging diagnostics, and aimed at early detection of patients at adverse risk for a timely differentiated approach to conservative or cardiac surgical treatment tactics.

Monocyte to High-Density Lipoprotein Ratio Is Associated With Carotid Plaque: ARetrospective Cohort Study.

The level of monocyte to high-density lipoprotein ratio (MHR) is associated with cardiovascular diseases. Carotid plaque (CP) is an independent risk factor for cardiovascular diseases. However, evidence for association of MHR with risk of CP is scarce. This study involved 5260 participants aged >18 years old from the Dalian health management cohort in 2014 to 2022. The subjects were stratified into 4 groups based on the quartile of the MHR at baseline. Multivariable-adjusted Cox regression models were used to calculate the MHR-associated risk of incident CP. The mean age of the population was 46.14 years and 58.8% (n=3093) of the participants were male. Seven hundred fifty-nine (14.4%) of participants developed new-onset CP. During the follow-up of 9725 person-years, the MHR at quartile 4 group experienced a significantly higher incidence of CP than the MHR at quartile 1 group (56.9 versus 101.5 per 1000 person-years; log-rank P <0.001). Compared with the MHR at quartile 1 group, the MHR at quartile 4 group had the highest CP risk (hazard ratio. 1.389 [95% CI, 1.059-1.823]) and 10-year cardiovascular risk (China-PAR Project score: odds ratio, 1.975 [95% CI, 1441-2.708 in men]; odds ratio, 6.015 [95% CI, 1.949-18.564 in women) (P <0.001). Meanwhile, similar results were observed in multiple sensitivity analyses. Elevated MHR was associated with the risk of CP. The assessment and management of MHR is helpful for the early detection of patients with CP and the primary prevention of cardiovascular diseases.

Machine Learning Models for the Early Real-Time Prediction of Deterioration in Intensive Care Units-A Novel Approach to the Early Identification of High-Risk Patients.

Background Predictive machine learning models have made use of a variety of scoring systems to identify clinical deterioration in ICU patients. However, most of these scores include variables that are dependent on medical staff examining the patient. We present the development of a real-time prediction model using clinical variables that are digital and automatically generated for the early detection of patients at risk of deterioration. Methods Routine monitoring data were used in this analysis. ICU patients with at least 24 h of vital sign recordings were included. Deterioration was defined as qSOFA ≥ 2. Model development and validation were performed internally by splitting the cohort into training and test datasets and validating the results on the test dataset. Five different models were trained, tested, and compared against each other. The models were an artificial neural network (ANN), a random forest (RF), a support vector machine (SVM), a linear discriminant analysis (LDA), and a logistic regression (LR). Results In total, 7156 ICU patients were screened for inclusion in the study, which resulted in models trained from a total of 28,348 longitudinal measurements. The artificial neural network showed a superior predictive performance for deterioration, with an area under the curve of 0.81 over 0.78 (RF), 0.78 (SVM), 0.77 (LDA), and 0.76 (LR), by using only four vital parameters. The sensitivity was higher than the specificity for the artificial neural network. Conclusions The artificial neural network, only using four automatically recorded vital signs, was best able to predict deterioration, 10 h before documentation in clinical records. This real-time prediction model has the potential to flag at-risk patients to the healthcare providers treating them, for closer monitoring and further investigation.

Molecular analysis of mucopolysaccharidosis type VI in Iranian patients; the influence of founder effect and consanguinity.

Mucopolysaccharidosis type VI (MPS VI), also known as Manteaux-Lamy syndrome, is an autosomal recessive lysosomal storage disorder caused by deficiency of the enzyme arylsulfatase B(ARSB). This syndrome is progressive and affects many tissues and organs, leading to inflammation and scarring. The classic clinical features of Maroteaux-Lamy syndrome are significant impairment of the osteoarticular system with dysostosis multiplex, short stature and motor dysfunction. The rate at which symptoms appear and worsen can vary between affected individuals. Mutations in the ARSB gene are responsible for MPS VI. We investigated the clinical presentation and molecular basis of patients with MPS VI for the first time in Yazd province, Iran. Of the 52 people who took part in this project, there were 13 probands. Whole exome sequencing (WES) was performed in 2 of them and the nominated mutation in the ARSB (c.430G > A) was verified by Sanger sequencing in the remaining patients. All patients had parental consanguinity, except for one family in which the parents were unrelated. All patients were of Fars ethnicity and had characteristic phenotypes such as severe short stature, cardiac involvement, coarse facial features, and corneal opacities. Sequence analysis of the ARSB gene revealed a pathogenic homozygous missense mutation c.430G > A (p. Gly144Arg) in all patients. This type of mutation influenced the phenotypes of the severe patients. These results expand the genetic databases of Iranian patients with MPS VI and would be very helpful for the high-risk families to accelerate the detection of carriers and to perform prenatal testing for the disorder in this population in a cost-effective manner. There is a possibility that other unknown mutations are responsible for the disease. The decision to screen for and detect carriers of this disease at a national level is awaited. The results of the present study could be an asset for married families in part of the city of Meybod. The results offer a way for early detection of patients and carriers of the disease.

Prognostic value of coronary calcification detected via non-electrocardiogram-gated computed tomography in patients with cardiovascular disease: A retrospective cohort study

BackgroundThe correlation between coronary artery calcification (CAC) detected via electrocardiogram-gated computed tomography (ECG-gated CT) and future cardiovascular events has been well-established. Non-ECG-gated CT is simple and widely used, making it suitable for screening. However, the correlation between CAC observed via non-ECG-gated CT and cardiovascular and non-cardiovascular events remains unclear. Therefore, we examined the association between coronary calcification detected via non-ECG-gated CT and prognosis. MethodsThis non-randomized, retrospective cohort study included 353 consecutive patients with cardiovascular diseases (male/female 229/124; mean age, 68.6 ± 12.7 years) who underwent non-ECG-gated CT between October 1, 2017 and May 31, 2021. Correlations between the Agatston score and cardiovascular and non-cardiovascular events were evaluated. The Agatston scores were divided into three tertiles (low, intermediate, and high) and compared. The primary endpoint was composite cardiovascular events, including cardiac death, myocardial infarction, hospitalization for congestive heart failure, stroke, and unplanned cardiac surgery. The secondary endpoint was composite non-cardiovascular events, including non-cardiovascular death, cancer development, and hospitalization for a non-cardiovascular worsening event. ResultsDuring the median follow-up period of 16.9 (interquartile range, 2.2–38.6) months, 83 patients reached the primary endpoint, while 81 patients reached the secondary endpoint. Kaplan–Meier analysis indicated that patients with high Agatston scores had a significantly higher incidence of cardiovascular and non-cardiovascular events than those with low Agatston scores (p < 0.001). ConclusionsIn this study, the Agatston score obtained using non-ECG-gated CT predicted cardiovascular and non-cardiovascular events. Non-ECG-gated CT can be easily performed, aiding early detection in patients with high event rates.

Substance P and stress are associated with the development of chronic urticaria

Introduction. Allergic diseases are a pressing challenge in practical healthcare, attracting increased attention of various medical specialists. The pathogenesis of stress-induced urticaria is driven by neurogenic immune inflammation, accompanied by an increase in the level of neuropeptide substance P (SP).Objective. Assessment of the relationship between stress factors and substance P levels with the purpose of justifying the use of SP as a biomarker for assessing the clinical course and prognosis of the disease in patients with chronic urticaria.Materials and methods. The study was involved 165 adults aged 18–68 years. The main group included 97 patients with the confirmed diagnosis of chronic urticaria (CU) who were treated in a hospital setting in the period from 2018 to 2023. The comparison group included 68 practically healthy individuals, comparable in gender and age with the study group of patients. The level of substance P in the blood serum was estimated by immunoenzymatic techniques (Infinite F50 Tecan, Austria), using a CEA393Hu test system. Statistical processing of the results was performed using the STATA 18 software package (StataCorp LLC).Results. An increase in the production of substance P to 220.62 pg/mL in CU patients, compared to 96.57 pg/mL in the reference group (p &lt; 0.001), was observed. The logistic regression revealed an association between stress and substance P levels in CU patients. Thus, an increase in the concentration of substance P by 1 pg/mL led to a 1.02-fold increase in the CU risk. The CU risk increased by 3 times in the presence of a stress situation as a trigger.Conclusions. The constructed multivariant logistic regression model produced positive values of the model parameters (p ≤ 0.01). This indicates the correlation between the increased blood levels of substance P under the impact of stress factors and the risk of chronic urticaria development. The data obtained suggests that the concentration of substance P in the blood of CU patients can be considered as a potential diagnostic biomarker. This biomarker can be recommended for extending panel screening tests to clarify the pathogenesis of the disease, thus improving the differential diagnosis of the disease and facilitating early detection of patients with stress-induced urticaria.

Development and validation of a nomogram for obesity and related factors to detect gastric precancerous lesions in the Chinese population: a retrospective cohort study.

The purpose of this study was to construct a nomogram to identify patients at high risk of gastric precancerous lesions (GPLs). This identification will facilitate early diagnosis and treatment and ultimately reduce the incidence and mortality of gastric cancer. In this single-center retrospective cohort study, 563 participants were divided into a gastric precancerous lesion (GPL) group (n=322) and a non-atrophic gastritis (NAG) group (n=241) based on gastroscopy and pathology results. Laboratory data and demographic data were collected. A derivation cohort (n=395) was used to identify the factors associated with GPLs to develop a predictive model. Then, internal validation was performed (n=168). We used the area under the receiver operating characteristic curve (AUC) to determine the discriminative ability of the predictive model; we constructed a calibration plot to evaluate the accuracy of the predictive model; and we performed decision curve analysis (DCA) to assess the clinical practicability predictive model. Four -predictors (i.e., age, body mass index, smoking status, and -triglycerides) were included in the predictive model. The AUC values of this predictive model were 0.715 (95% CI: 0.665-0.765) and 0.717 (95% CI: 0.640-0.795) in the derivation and internal validation cohorts, respectively. These values indicated that the predictive model had good discrimination ability. The calibration plots and DCA suggested that the predictive model had good accuracy and clinical net benefit. The Hosmer-Lemeshow test results in the derivation and validation cohorts for this predictive model were 0.774 and 0.468, respectively. The nomogram constructed herein demonstrated good performance in terms of predicting the risk of GPLs. This nomogram can be beneficial for the early detection of patients at high risk of GPLs, thus facilitating early treatment and ultimately reducing the incidence and mortality of gastric cancer.

Novel Biomarkers as Potential Predictors of Decompensated Advanced Chronic Heart Failure-Single Center Study.

Background/Objectives: Heart failure (HF) remains a major therapeutic and diagnostic challenge nowadays. Albeit, acute decompensated HF is associated with several clinical signs such as dyspnea or edema, it remains a challenge to use easy accessible and suitable tools, such as biomarkers, to distinguish between patients at risk for an acute decompensation of their heart failure and compensated, stable HF patients. Existing biomarkers, such as natriuretic peptides or troponin, are not specific and can be elevated due to several other disease conditions, such as myocardial infarction, atrial fibrillation, or valve diseases. Therefore, the aim of this study was to analyze the predictive potential of four novel cardiovascular biomarkers-the soluble urokinase-type plasminogen activator receptor (suPAR), heart-type fatty acid binding protein (H-FABP), vascular cell adhesion molecule 1 (VCAM-1), and growth/differentiation factor 15 (GDF-15) for the detection of cardiac decompensation in patients with HF. Methods: In this study, 146 patients were prospectively enrolled and the serum biomarker concentrations were analyzed using Enzyme Linked Immunosorbent Assay (ELISA). We correlated the biomarker concentrations with clinical and biochemical parameters of all patients and the predictive value for detection of cardiac decompensation was assessed. Results: A significant increase in the levels of suPAR (1.6-fold-change, p < 0.0001), H-FABP (2.2-fold-change, p = 0.0458), VCAM-1 (1.6-fold-change, p < 0.0001), and GDF-15 (1.7-fold-change, p = 0.0009) was detected in all patients with acute decompensated HF in comparison to patients with compensated HF. Univariate logistic regression analysis revealed a significant association of biomarker plasma concentration with the risk for a cardiac decompensation (suPAR: p < 0.0001; VCAM-1: p < 0.0001, H-FABP: p = 0.0458; GDF-15: p = 0.0009). Conclusions: In conclusion, the investigated novel cardiovascular biomarkers suPAR, GDF-15, VCAM-1, and H-FABP could be a valuable tool to facilitate therapeutic decisions in patients with heart failure and suspicion of a cardiac decompensation. Parameters such as renal function should be taken into account. Further studies on novel biomarkers are required to find reliable, sensitive, and specific tools that will enable the early detection of patients with acute decompensation.

Abstract 4136678: Detecting Myosteatosis-Related Low Physical Function in Heart Failure Patients Using Abdominal Computed Tomography and Plasma Amino Acid Profile

Background: Evaluation of sarcopenia requires quantifying appendicular skeletal muscle mass and functional capacity, but resource constraints often limit feasibility. Alterations in muscle quality, especially intramuscular lipid infiltration (i.e., myosteatosis), and systemic metabolic derangements are associated with disability. Hypothesis: Opportunistic CT imaging and plasma amino acid profiling could identify low physical function in patients with heart failure (HF). Methods: We retrospectively examined 220 HF patients (74 ± 13 years old; 59% male) who underwent plasma amino acid profiling, abdominal CT imaging, and dual-energy X-ray absorptiometry (DXA) scan within two months. Myosteatosis was evaluated using single-slice CT imaging at the L3/4 level and quantified as mean muscle attenuation (MMA). Physical function was assessed by the short physical performance battery (SPPB), with low physical function defined as SPPB ≤9. Results: CT-derived single-slice areas of skeletal muscle and adipose tissue were highly correlated with DXA-derived appendicular skeletal muscle mass and total fat mass. Logistic regression analyses revealed that higher age and lower MMA, but not skeletal muscle area, were significantly associated with low physical function independently of NT-proBNP. Subjects with MMA below the median value (32.0 HU for males and 23.7 HU for females) had higher odds of low physical function (adjusted OR 2.04, 95% CI 1.04-3.96). Ten amino acids and the Fischer ratio were significantly correlated with MMA levels. Multivariate regression analyses, adjusted for potential confounders including age, gender, and body mass index, demonstrated that serum albumin and Fischer ratio were independent determinants of MMA levels. When serum albumin and Fischer ratio were dichotomized by their median values (3.6 mg/dL and 3.23, respectively), the prevalence of low physical function was significantly higher in subjects with low albumin and low Fischer ratio, but not in those with low levels of only either parameter, compared to those with high albumin and high Fischer ratio (adjusted OR 2.36, 95% CI 1.02-5.49). Conclusions: Myosteatosis assessed by single-slice abdominal CT imaging is an independent determinant of low physical function in HF patients. Combined with an assessment of serum albumin and Fischer ratio, these simple biomarkers could facilitate the early detection of patients at risk for developing frailty.

Phase 3 validation of PAaM for hepatocellular carcinoma risk stratification in cirrhosis

Hepatocellular carcinoma (HCC) risk stratification is an urgent unmet need for cost-effective HCC screening and early detection in patients with cirrhosis to improve poor HCC prognosis. Molecular (prognostic liver secretome signature with α-fetoprotein) and clinical (aMAP [age, male sex, albumin-bilirubin, and platelets] score) variable-based scores were integrated into PAaM (prognostic liver secretome signature with α-fetoprotein plus age, male sex, albumin-bilirubin, and platelets), which was subsequently validated in 2 phase 3 biomarker validation studies: the statewide Texas HCC Consortium and nationwide HCC Early Detection Strategy prospective cohorts, following the prospective specimen collection, retrospective blinded evaluation design. The associations between baseline PAaM and incident HCC were assessed using Fine-Gray regression, with overall death and liver transplantation as competing events. Of 2156 patients with cirrhosis in the Texas HCC Consortium, PAaM identified 404 (19%) high-risk, 903 (42%) intermediate-risk, and 849 (39%) low-risk patients with annual HCC incidence rates of 5.3%, 2.7%, and 0.6%, respectively. Compared with low-risk patients, high- and intermediate-risk groups had sub-distribution hazard ratios for incident HCC of 7.51 (95% CI, 4.42-12.8) and 4.20 (95% CI, 2.52-7.01), respectively. Of 1328 patients with cirrhosis in the HCC early detection strategy, PAaM identified 201 high-risk (15%), 540 intermediate-risk (41%), and 587 low-risk (44%) patients, with annual HCC incidence rates of 6.2%, 1.8%, and 0.8%, respectively. High- and intermediate-risk groups were associated with sub-distribution hazard ratios for incident HCC of 6.54 (95% CI, 3.85-11.1) and 1.77 (95% CI, 1.02-3.08), respectively. Subgroup analysis showed robust risk stratification across HCC etiologies, including metabolic dysfunction-associated steatotic liver disease and cured hepatitis C infection. PAaM enables accurate HCC risk stratification in patients with cirrhosis from contemporary etiologies.

Early detection of patients with narcotic use disorder using a modified morphine equivalent daily dose score based on an analysis of real-world prescription patterns: a retrospective cohort study

Early detection of patients with narcotic use disorder using a modified morphine equivalent daily dose score based on an analysis of real-world prescription patterns: a retrospective cohort study

Efficacy of Early Warning Scores as the Prediction Tool for Detecting Patients With Acute Deterioration in a High Dependent Unit.

Background Early detection and response to patient deterioration are essential to prevent serious outcomes such as unplanned intensive care unit (ICU) transfers and cardiac arrests. Rapid response systems (RRS) have been implemented globally, leading to a reduction in in-hospital mortality. In high-dependency units (HDUs), where patient monitoring is more frequent than in general wards, but staffing levels are lower than in intensive care units (ICUs), the challenge of identifying deteriorating patients persists. The Early Warning Score System (EWSS), including the National EWS (NEWS) and the artificial intelligence (AI)-based Visensia Safety Index (VSI), offer tools for early detection of patients' exacerbations. This study evaluates the effectiveness of NEWS and VSI in predicting patient deterioration in an HDU in Japan. Methods This single-center retrospective cohort study was conducted at a 344-bed acute care hospital. The study population included patients admitted to the HDU between September 27, 2019, and December 31, 2019. Study outcomes were unexpected ICU admission, endotracheal intubation, de novo use of vasopressors, de novo use of non-invasive positive pressure ventilation (NPPV), cardiac arrest, and the composite outcome (any of these outcomes). The predictive accuracy of the National Early Warning Score (NEWS) and the Visensia Safety Index (VSI) for detecting outcomes within 24 hours from each time point was analyzed. Results A total of 356 patients were included, with a median age of 76 years old (interquartile range (IQR): 64-84) and a median HDU stay of 2.0 days (IQR: 2.0-3.0). Among the 2648 analyzed vital sign sets, the median NEWS score was 5.0 (IQR: 3.0-7.0) and the median VSI score was 1.1 (IQR: 0.7-1.9). Twenty-six patients (7.3%) experienced outcomes. Among these, 13 (3.7%) required unexpected ICU transfers, 6 (1.7%) required endotracheal intubation, 15 (4.2%) required de novo vasopressor use, and 7 (2.0%) required de novo NPPV. NEWS could predict unexpected ICU admissions with good accuracy (the area under the curve (AUC) 0.834), as well as de novo vasopressor use (AUC 0.765) and the composite outcome (AUC 0.701). VSI also demonstrated modest predictive efficacy for unexpected ICU transfers (AUC 0.767), endotracheal intubation (AUC 0.712), and de novo vasopressor use (AUC 0.733). Based on ROC analysis, the appropriate threshold for NEWS ranged between 6.0 and 8.0, and the optimal threshold for VSI was found to be 1.5. Chronologically, NEWS remained stable before the occurrence of outcomes, whereas VSI showed a significant upward trend, suggesting that VSI may be more sensitive to detecting early deterioration. Conclusions In this study, both NEWS and VSI demonstrated modest accuracy in predicting unexpected ICU admission and vasopressor use in an HDU. While NEWS high risk (7≥) is an appropriate cutoff value for detecting adverse outcomes, particularly lowering the VSI cutoff to 1.5, may enhance the identification of high-risk patients.

Nailfold videocapillaroscopy abnormalities and vascular manifestations in Behçet's syndrome.

To evaluate microcirculation abnormalities and their clinical association in patients with BS, especially with vascular manifestations. A cross-sectional study was carried out using nailfold videocapillaroscopy (NVC) to evaluate the microcirculation in patients with BS. A total of 65 patients were included in the study. Thirty-four (52.3%) were men, and 84.6% were European Caucasian. Vascular involvement was present in 24 (36.9%) patients. Qualitative abnormalities in NVC were observed in 47.7% of patients. The most frequent were tortuous and branched capillaries (21.5%), followed by microhaemorrhage (12.3%), enlarged capillary (7.7%) and giant capillary (3.1%). We found a significant relationship between the presence of tortuous and branched capillaries and previous superficial thrombophlebitis (ST) (p=0.025). The presence of ≥2 qualitative abnormalities in NVC was associated with vascular involvement (p=0.031), mainly with venous thrombotic events (p=0.024) and particularly with ST (p=0.003). No specific Cutolo's pattern was observed. No association was observed between NVC and Raynaud's phenomenon or ANA, although patients with positive ANA presented more frequent non-specific capillaroscopic abnormalities (p=0.003). The presence of ≥2 qualitative abnormalities in NVC is associated with Vasculo-Behçet. NVC might be a potential tool for early detection of patients at risk of vascular events.

Clinical cases of verruciform epidermodysplasia of Lewandovski—Luts

Data from the medical literature and own observations of veruciform epidermodysplasia of Lewandovski — Luts (VEDLL) indicate that there are many issues that need to be resolved or clarified. They relate, in particular, to carrying out genetic research — in order to prove the phenomenon and regularities of heredity of dermatosis. The detection of a benign neoplastic formation in one of our patients — esophageal leiomyoma — obliges doctors to carefully examine patients with VEDLL, even without complaints about disorders of one or another body system. Does such a case not suggest the possibility of neoplastic transformation of a benign nature and not only from the side of the skin (papillomas and warts)? Can HPV for VEDLL cause, in addition to skin carcinoma, the occurrence of internal organ tumors? An important task of dermatologists is the early detection of patients among children, who often have common forms of wart-like efflorescences. It can be assumed that in some patients, the disease is latent for some time and manifests itself only under the influence of adverse factors (inadequate insolation, stress, etc.). The issues of VEDLL require practicing dermatovenereologists not only to conduct clinical and differential diagnosis of wart-like dermatoses but also to carry out laboratory tests to identify dermatosis (biopsy, cytology, PCR), which will allow for more frequent detection of VDLL. Since the rarity of VEDLL does not contribute to the accumulation of a sufficient amount of results on the detection of pathogenetic factors of dermatosis, particularly immunological ones, the treatment problem remains relevant. It is necessary to conduct permanent monitoring of the development of VEDLL to identify early signs of neoplastic transformation and determine predictors, that is, prognostic parameters, and introduce methods for their determination.

Construction and Validation of a Novel Forecasting Nomogram to the Risk of Colorectal Adenomas: Preventing Colorectal Cancer at Its Origin.

Colorectal adenomas are responsible for the origin of most colorectal cancers. Early detection together with active intervention of colorectal adenomas plays a crucial role in the prevention of colorectal cancer. This study aimed to construct and validate a new nomogram for the forecasting of the risk of colorectal adenomas based on lifestyle risk factors that could offer potential benefits for colorectal cancer prevention. Colonoscopy reports, pathology reports, physical factors, family history, personal history of disease, diet, and lifestyle habits were collected from 1,133 subjects who underwent complete colonoscopy. All subjects were divided into the training cohort (n = 792) and the validation cohort (n = 341). A nomogram predicting the risk of colorectal adenoma development was constructed using the training cohort, and the C-index was calculated. The predictive accuracy and clinical applicability of the nomogram were verified in the validation cohort. The nomogram was constructed by six statistically significant variables selected from 18 health factors, including advanced age, male, smoking, drinking, pickles, and irregular defecation. The C-index of the training cohort was 0.778, and the C-index of the validation cohort was 0.754. The calibration curve and decision curve analysis also confirmed that the model has good predictive ability and high profit. The nomogram constructed in this study was validated and can be applied to predicting the occurrence risk of colorectal adenoma. The model can guide the identification of patients with nonsymptomatic colorectal adenomas and the recognition of high-risk individuals for whom colonoscopy is advisable. Prevention Relevance: Colorectal adenomas are the origin of most colorectal cancers. In this research, we explored the risk factors of colorectal adenomas and constructed a colorectal adenoma risk prediction nomogram in the expectation of early detection of patients with nonsymptomatic colorectal adenoma and advocated for their aggressive treatment to achieve colorectal cancer prevention.

A Lightweight Multi-Mental Disorders Detection Method Using Entropy-Based Matrix from Single-Channel EEG Signals.

Background: Mental health issues are increasingly prominent worldwide, posing significant threats to patients and deeply affecting their families and social relationships. Traditional diagnostic methods are subjective and delayed, indicating the need for an objective and effective early diagnosis method. Methods: To this end, this paper proposes a lightweight detection method for multi-mental disorders with fewer data sources, aiming to improve diagnostic procedures and enable early patient detection. First, the proposed method takes Electroencephalography (EEG) signals as sources, acquires brain rhythms through Discrete Wavelet Decomposition (DWT), and extracts their approximate entropy, fuzzy entropy, permutation entropy, and sample entropy to establish the entropy-based matrix. Then, six kinds of conventional machine learning classifiers, including Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Naive Bayes (NB), Generalized Additive Model (GAM), Linear Discriminant Analysis (LDA), and Decision Tree (DT), are adopted for the entropy-based matrix to achieve the detection task. Their performances are assessed by accuracy, sensitivity, specificity, and F1-score. Concerning these experiments, three public datasets of schizophrenia, epilepsy, and depression are utilized for method validation. Results: The analysis of the results from these datasets identifies the representative single-channel signals (schizophrenia: O1, epilepsy: F3, depression: O2), satisfying classification accuracies (88.10%, 75.47%, and 89.92%, respectively) with minimal input. Conclusions: Such performances are impressive when considering fewer data sources as a concern, which also improves the interpretability of the entropy features in EEG, providing a reliable detection approach for multi-mental disorders and advancing insights into their underlying mechanisms and pathological states.

The Molecular Mechanisms of Portal Vein Thrombosis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) represents the sixth most diagnosed cancer worldwide and is the second leading cause of cancer-related death in the world. The association of HCC and portal vein thrombosis (PVT) represents an advanced stage of the tumor. PVT has a prevalence of about 25–50% in HCC, determining poor prognosis and a remarkable reduction in therapeutic perspectives in these patients, leading to severe complications such as ascites, metastasis, an increase in portal hypertension and potentially fatal gastrointestinal bleeding. The aim of this review is to evaluate the molecular mechanisms that are at the basis of PVT development, trying to evaluate possible strategies in the early detection of patients at high risk of PVT.

The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports.

Early detection of patients with impending bone metastasis is crucial for prognosis improvement. This study aimed to investigate the feasibility of a fine-tuned, locally run large language model (LLM) in extracting patients with bone metastasis in unstructured Japanese radiology report and to compare its performance with manual annotation. This retrospective study included patients with "metastasis" in radiological reports (April 2018-January 2019, August-May 2022, and April-December 2023 for training, validation, and test datasets of 9559, 1498, and 7399 patients, respectively). Radiologists reviewed the clinical indication and diagnosis sections of the radiological report (used as input data) and classified them into groups 0 (no bone metastasis), 1 (progressive bone metastasis), and 2 (stable or decreased bone metastasis). The data for group 0 was under-sampled in training and test datasets due to group imbalance. The best-performing model from the validation set was subsequently tested using the testing dataset. Two additional radiologists (readers 1 and 2) were involved in classifying radiological reports within the test dataset for testing purposes. The fine-tuned LLM, reader 1, and reader 2 demonstrated an accuracy of 0.979, 0.996, and 0.993, sensitivity for groups 0/1/2 of 0.988/0.947/0.943, 1.000/1.000/0.966, and 1.000/0.982/0.954, and time required for classification (s) of 105, 2312, and 3094 in under-sampled test dataset (n = 711), respectively. Fine-tuned LLM extracted patients with bone metastasis, demonstrating satisfactory performance that was comparable to or slightly lower than manual annotation by radiologists in a noticeably shorter time.