Diagnostic Accuracy of Transient Elastography in Hepatosteatosis in Youth With Obesity.

Context: Steatotic liver disease is common but overlooked in childhood obesity; diagnostic methods are invasive or expensive. Objective: We sought to determine the diagnostic accuracy of vibration-controlled transient elastography (VCTE) compared with magnetic resonance imaging (MRI) in adolescents with obesity and high risk for hepatosteatosis. Methods: Baseline data in 3 clinical trials enrolling adolescents with obesity were included (NCT03919929, NCT03717935, NCT04342390). Liver fat was assessed using MRI fat fraction and VCTE-based controlled attenuation parameter (CAP). Hepatosteatosis was defined as MRI fat fraction ≥5.0%. The area under the receiver-operating characteristic curves (AUROCs) for CAP against MRI was calculated, and optimal CAP using the Youden index for hepatosteatosis diagnosis was determined. Results: Data from 82 adolescents (age 15.6 ± 1.4 years, body mass index 36.5 ± 5.9 kg/m2, 81% female) were included. Fifty youth had hepatosteatosis by MRI (fat fraction 9.3% ; 95% CI 6.7, 14.0), and 32 participants did not have hepatosteatosis (fat fraction 3.1%; 95% CI 2.2, 3.9; P < .001). The hepatosteatosis group had higher mean CAP compared with no hepatosteatosis (293 dB/m; 95% CI 267, 325 vs 267 dB/m; 95% CI 248, 282; P = .0120). A CAP of 281 dB/m had the highest sensitivity (60%) and specificity (74%) with AUROC of 0.649 (95% CI 0.51-0.79; P = .04) in the entire cohort. In a subset of participants with polycystic ovary syndrome (PCOS), a CAP of 306 dB/m had the highest sensitivity (78%) and specificity (52%) and AUROC of 0.678 (95% CI 0.45-0.90; P = .108). Conclusion: CAP of 281 dB/m has modest diagnostic performance for hepatosteatosis compared with MRI in youth with significant obesity. A higher CAP in youth with PCOS suggests that comorbidities might affect optimal CAP in hepatosteatosis diagnosis.

Diagnostic cut-off value of haemoglobin A1c for diabetes mellitus in Harare, Zimbabwe.

Very little is known about the diagnostic performance of the American Diabetes Association glycated haemoglobin (HbA1c) cut-off of 6.5% in resource-limited settings. This study, conducted between February 2023 and May 2023, aimed to determine the optimal HbA1c cut-off for the diagnosis of diabetes mellitus by measuring HbA1c and fasting plasma glucose levels in 120 adults attending care at a tertiary hospital in Harare, Zimbabwe. The optimal HbA1c cut-off was 6.1% and glucose levels were strongly correlated with HbA1c values. The prevalence of diabetes mellitus was higher (28.3%) at our derived HbA1c cut-off than with the American Diabetes Association criterion (21.6%). What this study adds: This study highlights the need for population-specific cut-off HbA1c values in the diagnosis of diabetes mellitus.

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The participants in this study consisted of 459 individuals who had undergone coronary angiography, contrast-enhanced ultrasonography, and focused carotid B-mode ultrasound. Each patient was tracked for thirty days. The measurements on these patients consisted of maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (cIMT), and intraplaque neovascularization (IPN). CAD risk and CV event stratification were performed by applying eight types of DL-based models. Univariate and multivariate analysis was also conducted to predict the most significant risk predictors. The DL's model effectiveness was evaluated by the area-under-the-curve measurement while the CV event prediction was evaluated using the Cox proportional hazard model (CPHM) and compared against the DL-based concordance index (c-index). IPN showed a substantial ability to predict CV events (p < 0.0001). The best DL system improved by 21% (0.929 vs. 0.762) over the best ML system. DL-based CV event prediction showed a ~ 17% increase in DL-based c-index compared to the CPHM (0.86 vs. 0.73). CAD and CV incidents were linked to IPN and carotid imaging characteristics. For survival analysis and CAD prediction, the DL-based system performs superior to ML-based models.

Development of an algorithm for identifying paraneoplastic ischemic stroke in association with lung, pancreatic, and colorectal cancer.

Background: Paraneoplastic ischemic stroke has a poor prognosis. We have recently reported an algorithm based on the number of ischemic territories, C-reactive protein (CRP), lactate dehydrogenase (LDH), and granulocytosis to predict the underlying active cancer in a case-control setting. However, co-occurrence of cancer and stroke might also be merely incidental. Objective: To detect cancer-associated ischemic stroke in a large, unselected cohort of consecutive stroke patients by detailed analysis of ischemic stroke associated with specific cancer subtypes and comparison to patients with bacterial endocarditis. Methods: Retrospective single-center cohort study of consecutive 1612 ischemic strokes with magnetic resonance imaging, CRP, LDH, and relative granulocytosis data was performed, including identification of active cancers, history of now inactive cancers, and the diagnosis of endocarditis. The previously developed algorithm to detect paraneoplastic cancer was applied. Tumor types associated with paraneoplastic stroke were used to optimize the diagnostic algorithm. Results: Ischemic strokes associated with active cancer, but also endocarditis, were associated with more ischemic territories as well as higher CRP and LDH levels. Our previous algorithm identified active cancer-associated strokes with a specificity of 83% and sensitivity of 52%. Ischemic strokes associated with lung, pancreatic, and colorectal (LPC) cancers but not with breast and prostate cancers showed more frequent and prominent characteristics of paraneoplastic stroke. A multiple logistic regression model optimized to identify LPC cancers detected active cancer with a sensitivity of 77.8% and specificity of 81.4%. The positive predictive value (PPV) for all active cancers was 13.1%. Conclusion: Standard clinical examinations can be employed to identify suspect paraneoplastic stroke with an adequate sensitivity, specificity, and PPV when it is considered that the association of ischemic stroke with breast and prostate cancers in the stroke-prone elderly population might be largely incidental.

Exploring the Role of Serum Hydrogen Sulphide (H2S) Levels in Manic Depressive Psychosis in Terms of Its Association, Diagnostic Ability, and Severity Prediction: Findings From a Tertiary Care Center in North Bengal.

INTRODUCTION: Manic depressive psychosis (MDP) or bipolar disorder, a prevalent psychiatric condition globally and in the Indian population, has been attributed to various pathological mechanisms. Hydrogen sulphide (H2S), a member of the gasotransmitter family, may be linked to the development of bipolar disorder because it plays a crucial role in maintaining proper neuronal function in terms of excitability, plasticity, and homeostatic functions. There is very little data regarding the role of the gasotransmitter H2S in MDP in terms of its association, diagnostic ability, and severity prediction, which led us to conduct this study among MDP patients in the Sub-Himalayan region of West Bengal. METHODS: This was an observational case-control study performed in the Department of Biochemistry, North Bengal Medical College and Hospital, Siliguri, West Bengal, India, from January 2022 to December 2022. Fifty diagnosed MDP patients and 50 healthy age- and sex-matched control subjects satisfying the inclusion and exclusion criteria were studied. The H2S level in the blood was assayed using the standardised spectrophotometric methylene blue method. The severity of depression was assessed by Hamilton Depression Rating Scale (HAM-D) scoring. RESULTS: Of the 50 MDP patients, 45 (90%) were in the depressive phase, and five (10%) were in the manic phase. Of the 45 depressive patients, eight (17.8%) had mild depression, 12 (26.7%) had moderate depression, 19 (42.2%) had severe depression, and six (13.3%) had very severe depression. The mean H2S level in MDP patients (41.98±18.88 µmol/l) was significantly (P<0.05) lower than that in control subjects (99.20± 15.20 µmol/l). It was also observed that the mean H2S level in MDP patients decreased with the duration of the disease but was not statistically significant. The mean H2S levels in the different depression severity groups were found to be significantly different (P<0.001). Receiver operating characteristic (ROC) curve analysis revealed that a cut-off value of H2S <78.5 µmol/l was associated with MDP, with a sensitivity of 96% and a specificity of 88%, and a cut-off value of H2S < 53 µmol/l predicted the severity of depression with a sensitivity of 89.3% and a specificity of 76.5%. CONCLUSION: The significant association of the gasotransmitter H2S in MDP patients and its role as a diagnostic and severity predictive marker can help us to employ proper measures for better management of MDP and improving quality of life.

Plasma levels of Sirtuin 7 are decreased in patients with essential hypertension.

BACKGROUND: Sirtuin 7 (SIRT7), as a nicotinamide adenine dinucleotide-dependent protein/histone deacetylase, has been implicated in the pathogenesis of cardiovascular diseases. However, whether SIRT7 is related to hypertension remains largely unclear. Thus, this study aims to explore the effects and correlation between SIRT7 and hypertension. METHODS: A total of 72 patients with essential hypertension and 82 controls with non-hypertension were recruited at Beijing Tongren Hospital Affiliated with Capital Medical University from July 2022 to June 2023. Plasma SIRT7 expression was measured using enzyme-linked immunosorbent assay analysis. Clinical baseline characteristics, laboratory measurements, echocardiographic data, and medical therapy were collected. RESULTS: Plasma levels of SIRT7 were lower in hypertensive patients compared with non-hypertensive patients [0.97 (0.58-1.30) vs. 1.24 (0.99-1.46) ng/mL, P < 0.001, respectively]. Furthermore, compared with the low SIRT7 group, there were lower levels of systolic blood pressure, hyperlipidemia, and the ultrasonic electrocardiogram parameters left ventricular end-diastolic diameter and left atrial in diastole in the high SIRT7 group (P < 0.05, respectively). More importantly, multivariate logistic regression analyses indicated that plasma SIRT7 was a predictor of hypertension [OR: 0.06, 95 % CI (0.02-0.19), P < 0.001]. Receiver operating characteristics curve analysis revealed that the optimal cutoff value for plasma SIRT7 levels in detecting hypertension was determined as 0.85 ng/mL with a sensitivity of 73.6 % and a specificity of 89.0 %. The area under the curve for SIRT7 was 0.821 (95 % CI, 0.751-0.878; P < 0.001). CONCLUSION: Plasma levels of SIRT7 are decreased in patients with essential hypertension, implying its potential as a biomarker for diagnosing essential hypertension..

Exploring machine learning and statistical approach techniques for landslide susceptibility mapping in Siwalik Himalayan Region using geospatial technology.

Landslides are a natural threat that poses a severe risk to human life and the environment. In the Kumaon mountains region in Uttarakhand (India), Nainital is among the most vulnerable areas prone to landslides inflicting harm to livelihood and civilization due to frequent landslides. Developing a landslide susceptibility map (LSM) in this Nainital area will help alleviate the probability of landslide occurrence. GIS and statistical-based approaches like the certainty factor (CF), information value (IV), frequency ratio (FR) and logistic regression (LR) are used for the assessment of LSM. The landslide inventories were prepared using topography, satellite imagery, lithology, slope, aspect, curvature, soil, land use and land cover, geomorphology, drainage density and lineament density to construct the geodatabase of the elements affecting landslides. Furthermore, the receiver operating characteristic (ROC) curve was used to check the accuracy of the predicting model. The results for the area under the curves (AUCs) were 87.8% for logistic regression, 87.6% for certainty factor, 87.4% for information value and 84.8% for frequency ratio, which indicates satisfactory accuracy in landslide susceptibility mapping. The present study perfectly combines GIS and statistical approaches for mapping landslide susceptibility zonation. Regional land use planners and natural disaster management will benefit from the proposed framework for landslide susceptibility maps.

Favorable factors for the survival of ST-segment elevation myocardial infarction patients with medium- and high-risk thrombolysis in myocardial infarction scores.

OBJECTIVE: ST-segment myocardial infarction (STEMI) is a time-sensitive emergency. This study screened the favorable factors for the survival of STEMI patients with medium- and high-risk thrombolysis in myocardial infarction (TIMI) scores. METHODS: According to the TIMI scores at admission, 433 STEMI patients were retrospectively and consecutively selected and allocated into low-/medium-/high-risk groups, with their general information/blood routine/biochemical indicators/coagulation indicators documented. The factors influencing the in-hospital survival of STEMI patients were analyzed using univariate and multivariate logistic regression analyses. Moreover, the predictive value of favorable factors was analyzed by receiver operating characteristics (ROC) curve, and patients were assigned into high/low level groups based on the cut-off value of these factors, with their in-hospital survival rates compared. RESULTS: The in-hospital survival rate of the medium-/high-risk groups was lower than that of the low-risk group. Emergency percutaneous coronary intervention (PCI), lymphocyte (LYM), total protein (TP), albumin (ALB), and sodium (Na) were independent favorable factors for in-hospital survival in the medium-/high-risk groups. Besides, LYM > 1.275 × 109/L, TP > 60.25 g/L, ALB > 34.55 g/L, and Na > 137.9 mmo1/L had auxiliary predictive value for the survival of STEMI patients with medium-/high-risk TIMI scores. Patients with high levels of LYM, TP, ALB, and Na exhibited higher in-hospital survival rates than patients with low levels. CONCLUSION: For STEMI patients with medium- and high-risk TIMI scores, accepting emergency PCI and normal levels of LYM, TP, ALB, and Na were more conducive to in-hospital survival.

Corrigendum: Systematic review and meta-analysis of screening tools for language disorder.

[This corrects the article DOI: 10.3389/fped.2022.801220.].

Inference for covariate-adjusted time-dependent prognostic accuracy measures.

Evaluating the prognostic performance of candidate markers for future disease onset or progression is one of the major goals in medical research. A marker's prognostic performance refers to how well it separates patients at the high or low risk of a future disease state. Often the discriminative performance of a marker is affected by the patient characteristics (covariates). Time-dependent receiver operating characteristic (ROC) curves that ignore the informativeness of the covariates will lead to biased estimates of the accuracy parameters. We propose a time-dependent ROC curve that accounts for the informativeness of the covariates in the case of censored data. We propose inverse probability weighted (IPW) estimators for estimating the proposed accuracy parameters. We investigate the performance of the IPW estimators through simulation studies and real-life data analysis.

The Leucine-Rich α2-Glycoprotein-1 Levels in Patients with Multiple Myeloma.

INTRODUCTION: Angiogenesis is considered important in the pathogenesis of multiple myeloma (MM), as well as in the targeted treatment of the disease. Leucine-rich α2-glycoprotein 1 (LRG1) is a protein that participates in angiogenesis and its effect on solid organ tumors has been investigated recently. This study aimed to investigate the relationship between MM and LRG1. METHODS: The MM patients who admitted to Hatay Mustafa Kemal University Hematology Clinic between September 2021 and October 2022 were included in the study. The study consists of a total of 4 groups: newly diagnosed MM (NDMM), relapsed refractory MM (RRMM), MM in remission (Rem-MM), and control group. Demographic data were retrieved from hospital records. Blood samples of our study groups were centrifuged at 1,500 × g for 10 min and serum was collected. LRG1, IL-6, IL-8, TGF-ß1, HIF-1α, FGF-2, and VEGF levels were analyzed in all groups by ELISA method, and statistical analysis was performed. RESULTS: A total of 112 individuals, including NDMM (n: 27), RRMM (n: 18), Rem-MM (n: 42), and control group (n: 25), were enrolled in the study. Based on the analyses, the NDMM group exhibited significantly elevated levels of LRG1 (p < 0.001), TGF-1 (p < 0.001), and HIF-1α (p = 0.046, p < 0.001, and p = 0.003 compared to the RRMM, Rem-MM, and control groups, respectively) compared to the other groups. LRG1 levels were positively correlated with creatinine (r: 0.363, p = 0.001), calcium (r: 0.344, p = 0.001), total protein (r: 0.473, p < 0.001), erythrocyte sedimentation rate (r: 0.547, p < 0.001), lactate dehydrogenase (r: 0.321, p = 0.003), beta-2-microglobulin (r: 0.312, p = 0.017), IL-6 (r: 0.478, p < 0.001), IL-8 (r: 0.240, p = 0.03), TGF-ß1 (r: 0.521, p < 0.001), and HIF-1α (r: 0.321, p = 0.003) levels and were negatively correlated with hemoglobin (r: -0.512, p < 0.001) and albumin (r: -0.549, p < 0.001) levels. Receiver operating characteristics (ROC) analysis revealed the association of LRG1 with the highest AUC value of 0.959 (95% CI: 0.904-1, p < 0.001) and the optimal cut-off value of 534.95 ng/mL (sensitivity: 93% and specificity: 99%) in the NDMM group compared to the control group. CONCLUSION: In this study, providing data for the first time on LRG1 levels in the setting of MM. LRG1 levels were found to be significantly higher in NDMM patients and in our study discriminate this patient population from RRMM, Rem-MM, and normal controls. Therefore, LRG1 seems to a potential biomarker that should be evaluated in future studies addressing the diagnosis, staging, follow-up, prognosis, and treatment target of MM.

Clinical application of serum NLRP3 on the diagnosis and prognosis of sepsis patients complicated with acute respiratory distress syndrome.

Introduction: Acute respiratory distress syndrome (ARDS) is a common complication of sepsis, which significantly increases the mortality rate. This work explored the diagnostic value of serum NOD-like receptor family pyrin domain containing 3 (NLRP3) concentration in patients with sepsis for ARDS, and the predictive value of serum NLRP3 concentration at the time of diagnosis for death 28 days after treatment. Methods: A total of 150 sepsis patients were included in this study, including age-matched two groups of patients, 75 patients with ARDS and 75 patients without ARDS. In addition, 60 age-matched healthy patients with physical examination were recruited in this study. Serum NLRP3 concentration was determined by enzyme-linked immunosorbent assay (ELISA). The diagnostic values of serum NLRP3 concentration for ARDS in sepsis patients were evaluated by receiver operating characteristics (ROC) analysis. Correlation of serum NLRP3 with APACHE II score and SOFA were performed by Spearman correlation analysis. Results: Pulmonary infection, APACHE II score and serum NLRP3 concentration were risk factors for patients with sepsis complicated with ARDS. ROC curve results showed that the specificity of serum NLRP3 concentration was 74.67%, the sensitivity was 76.00%, and the area under the curve (AUC) was 0.82 (p<0.001). APACHE II score and SOFA were significantly positively correlated with serum NLRP3 concentration. Baseline serum NLRP3 levels had significant predictive value for 28-day mortality in sepsis patients complicated with ARDS. Conclusion: Serum NLRP3 concentration has clinical value in the diagnosis of sepsis complicated with ARDS.

Evaluation and Determination of Quantitative Hepatitis B Surface Antigen Diagnostic Performance in Chronic Hepatitis B Virus-Infected Patients.

Background Hepatitis B virus DNA (HBV-DNA) assessment is recommended for diagnosing and monitoring chronic hepatitis B (CHB) patients. Quantitative hepatitis B surface antigen (qHBsAg) estimation adjunct to HBV-DNA is vital for assessing HBV chronicity and therapeutic prognosis. This study aimed to estimate the qHBsAg and compare its diagnostic performance with that of the HBV-DNA levels in CHB patients from Bangladesh. Methodology A total of 148 CHB patients were enrolled in this study. qHBsAg and hepatitis B e-antigen (HBeAg) were estimated using chemiluminescent and enzyme immunoassays, respectively, and HBV-DNA was quantified using real-time polymerase chain reaction. The parameters and diagnostic performances were analyzed by receiver operating characteristic (ROC) curve analysis. Results The overall levels (mean ± SD) of qHBsAg, HBV-DNA, and alanine aminotransferase (ALT) among the total population (n = 148) were 3.45 ± 0.80 log10 IU/mL, 4.40 ± 2.44 log10 IU/mL, and 86.17 ± 39.06 IU/L, respectively. Significant differences were observed in the levels of both qHBsAg (p = 0.004) and HBV-DNA (p < 0.0001) in cases with HBeAg positivity. qHBsAg levels showed a weak positive correlation with the levels of HBV-DNA and ALT in HBeAg-positive CHB patients, but no such relationship was observed in HBeAg-negative CHB patients. ROC curve analysis showed that the area under the curve for the qHBsAg level to distinguish high HBV-DNA levels (>5 log10 IU/mL) was 0.653 (p = 0.002), which indicated an acceptable diagnostic performance. The best cut-off of qHBsAg for predicting high HBV-DNA levels was 3.469 log10 IU/mL. Conclusions Our results indicated that qHBsAg might be a useful marker for monitoring HBV-DNA in CHB patients throughout treatment and follow-up.

EMD-Based Energy Spectrum Entropy Distribution Signal Detection Methods for Marine Mammal Vocalizations.

To develop a passive acoustic monitoring system for diversity detection and thereby adapt to the challenges of a complex marine environment, this study harnesses the advantages of empirical mode decomposition in analyzing nonstationary signals and introduces energy characteristics analysis and entropy of information theory to detect marine mammal vocalizations. The proposed detection algorithm has five main steps: sampling, energy characteristics analysis, marginal frequency distribution, feature extraction, and detection, which involve four signal feature extraction and analysis algorithms: energy ratio distribution (ERD), energy spectrum distribution (ESD), energy spectrum entropy distribution (ESED), and concentrated energy spectrum entropy distribution (CESED). In an experiment on 500 sampled signals (blue whale vocalizations), in the competent intrinsic mode function (IMF2) signal feature extraction function distribution of ERD, ESD, ESED, and CESED, the areas under the curves (AUCs) of the receiver operating characteristic (ROC) curves were 0.4621, 0.6162, 0.3894, and 0.8979, respectively; the Accuracy scores were 49.90%, 60.40%, 47.50%, and 80.84%, respectively; the Precision scores were 31.19%, 44.89%, 29.44%, and 68.20%, respectively; the Recall scores were 42.83%, 57.71%, 36.00%, and 84.57%, respectively; and the F1 scores were 37.41%, 50.50%, 32.39%, and 75.51%, respectively, based on the threshold of the optimal estimated results. It is clear that the CESED detector outperforms the other three detectors in signal detection and achieves efficient sound detection of marine mammals.

Relationship between miRNA-21, miRNA-155, and miRNA-182 expression and inflammatory factors in cerebrospinal fluid from patients with multiple sclerosis.

BACKGROUND: The impact of microRNAs (miRNAs) on the differentiation and function of inflammatory cells is well-established. MiRNAs play a crucial role in modulating the expression of pro-inflammatory genes in neuronal cells as well. With this knowledge in mind, our study aimed to explore the relationship between the expression of miRNAs and inflammatory markers in the cerebrospinal fluid (CSF) of patients diagnosed with multiple sclerosis (MS). By investigating this relationship, we aimed to gain insights into the potential involvement of miRNAs in the regulation of inflammation in the context of MS. MATERIALS AND METHODS: The expression levels of miRNA-21, miRNA-155, and miRNA-182 in cerebrospinal fluid (CSF) samples from multiple sclerosis (MS) patients and controls were determined by RT-PCR. CSF levels of the inflammatory cytokines IL-1ß, IL-6, and TNF-α were measured by enzyme-linked immunosorbent assay (ELISA). In addition, high-sensitivity C-reactive protein (hs-CRP) levels were measured by quantitative turbidimetry. RESULTS: The expression levels of microRNAs and inflammatory factors were found to be significantly higher in the CSF of MS patients compared to controls (P < 0.05). Receiver operating characteristics (ROC) analysis revealed that miRNA-21, miRNA-182, and miRNA-155 had a high area under the curve (AUC) in discriminating MS patients, with AUC values of 0.97 (P < 0.0001) for miRNA-21, 0.97 (P < 0.0001) for miRNA-182, and 0.96 (P < 0.0001) for miRNA-155. Notably, CSF miRNA-155 showed the highest accuracy in correctly diagnosing MS. Furthermore, a statistically significant relationship was observed between inflammatory cytokines and miRNA-21, miRNA-155 and miRNA-182. CONCLUSION: Our results demonstrated that cerebrospinal fluid (CSF) levels of IL-1ß, IL-6, TNF-α, hs-CRP and specific miRNAs serve as biomarkers for assessing central nervous system (CNS) inflammation and neurodegenerative processes in patients with multiple sclerosis (MS).

Characterizing ability of serum potassium (K) and the serum K reference interval to flag hypokalemia or hyperkalemia as observed in plasma: A simulation study.

OBJECTIVES: Serum potassium (K) exhibits a positive shift relative to plasma K due to a variable amount of K release associated with clotting. Because of this variation, plasma K results outside of the reference interval (RI) for plasma (hypokalemia or hyperkalemia) in individual samples may not produce classification-concordant results in serum according to the serum RI. We examined this premise from a theoretical standpoint by simulation. DESIGN & METHODS: We used textbook K reference intervals for plasma (PRI = 3.4-4.5 mmol/L) and serum (SRI = 3.5-5.1 mmol/L). The difference between PRI and SRI is characterized by a normal distribution: serum K = plasma K + 0.35 ± 0.308 mmol/L. This transformation was applied by simulation to an observed patient data distribution for plasma K to generate a corresponding theoretical serum K distribution. Individual samples were tracked for comparison with respect to classification (below, within, above RI) for plasma and serum. RESULTS: Primary data were an all-comers plasma K patient distribution (n = 41,768; median = 4.1 mmol/L; 7.1% below PRI (hypokalemia); 15.5% above PRI (hyperkalemia)). Simulation to obtain the associated serum K yielded a right-shifted distribution (median = 4.4 mmol/L; 4.8% below SRI; 10.8% above SRI). Sensitivity for detection in serum (flagged below SRI) for samples originating as hypokalemic in plasma was 45.7% (specificity = 98.3%). Sensitivity for detection in serum (flagged above SRI) for samples originating as hyperkalemic in plasma was 56.6% (specificity = 97.6%). CONCLUSIONS: Simulation results indicate that serum K should best be thought of as an inferior substitute marker for plasma K. These results follow simply from the variable component of serum K compared to plasma K. Plasma should be the preferred specimen type for K assessment.

Low LncRNA LUCAT1 Expression Assists in the Diagnosis of Chronic Heart Failure and Predicts Poor Prognosis.

Chronic heart failure (CHF) is a complicated syndrome caused by structural and functional abnormalities. Long noncoding RNA (LncRNA) lung cancer-associated transcript 1 (LUCAT1) downregulation inhibits cardiomyocyte apoptosis. This study aimed to measure LUCAT1 expression in patients with CHF and to explore its clinical value on CHF diagnosis and prognosis. A total of 94 patients with CHF and 90 participants without CHF were registered, followed by recording of their clinical characteristics and grading of their cardiac function. LUCAT1 expression in sera of patients with CHF and participants without CHF was detected. The correlation of LUCAT1 with brain natriuretic peptide (BNP) and left ventricular ejection fraction (LVEF) in patients with CHF and the diagnostic efficiency of LUCAT1, BNP, and LUCAT1 combined with BNP on patients with CHF were analyzed. Patients with CHF were treated with conventional drugs and followed up. The LUCAT1 expression in patients with CHF was lower than that in participants without CHF and was downregulated with the increase of New York Heart Association stage. LUCAT1 expression was negatively associated with BNP but positively associated with LVEF in the sera of patients with CHF. The receiver operating characteristic curve of LUCAT1 combined with BNP had better result than that of LUCAT1 and BNP alone. Low LUCAT1 expression indicated poor prognosis of patients with CHF and was an independent prognostic factor for the survival of patients with CHF. To summarize, low lncRNA LUCAT1 expression might help diagnose and predict the poor prognosis of CHF.

Utility of urinary presepsin in the diagnosis of pyelonephritis: a cross-sectional study.

BACKGROUND: Presepsin is produced during the phagocytosis of bacteria by granulocytes. Presepsin increases at the site of infection; however, the significance of urinary presepsin in pyelonephritis is unknown. This study aimed to evaluate whether measuring urinary presepsin can distinguish between pyelonephritis and nonpyelonephritis. METHODS: A cross-sectional study of patients with suspected pyelonephritis was conducted. Urinary presepsin at admission was compared between the pyelonephritis and nonpyelonephritis groups using the Mann-Whitney test. The predictive accuracy of urinary presepsin for diagnosing pyelonephritis was evaluated by the area under the receiver operating characteristics (ROC) analysis curve. RESULTS: A total of 35 eligible participants were included in the pyelonephritis group and 25 in the nonpyelonephritis group. The median urinary presepsin level was 2232.0 (interquartile range [IQR], 1029.0-3907.0) pg/mL in the pyelonephritis group and 1348.0 (IQR, 614.5-2304.8) pg/mL in the nonpyelonephritis group. Urinary presepsin concentrations were significantly higher in the pyelonephritis group than in the nonpyelonephritis group (P = 0.023). ROC analysis of urinary presepsin revealed a cutoff value of 3650 pg/mL to distinguish between the pyelonephritis and nonpyelonephritis groups. Sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio for the diagnosis of pyelonephritis were 0.40 (95% confidence interval [CI], 0.24-0.58), 0.96 (95% CI, 0.79-1.00), 0.93 (95% CI, 0.68-1.00), 0.52 (95% CI, 0.37-0.68), 9.60 (95% CI, 1.35-68.23), and 0.62 (95% CI, 0.47-0.83), respectively. CONCLUSIONS: The measurement of urinary presepsin is useful in differentiating pyelonephritis from other diseases.

Crosswalk between Charlson Comorbidity Index and the American Society of Anesthesiologists Physical Status Score for Geriatric Trauma Assessment.

The American Society of Anesthesiologists Physical Status (ASA-PS) grade better risk stratifies geriatric trauma patients, but it is only reported in patients scheduled for surgery. The Charlson Comorbidity Index (CCI), however, is available for all patients. This study aims to create a crosswalk from the CCI to ASA-PS. Geriatric trauma cases, aged 55 years and older with both ASA-PS and CCI values (N = 4223), were used for the analysis. We assessed the relationship between CCI and ASA-PS, adjusting for age, sex, marital status, and body mass index. We reported the predicted probabilities and the receiver operating characteristics. A CCI of zero was highly predictive of ASA-PS grade 1 or 2, and a CCI of 1 or higher was highly predictive of ASA-PS grade 3 or 4. Additionally, while a CCI of 3 predicted ASA-PS grade 4, a CCI of 4 and higher exhibited greater accuracy in predicting ASA-PS grade 4. We created a formula that may accurately situate a geriatric trauma patient in the appropriate ASA-PS grade after adjusting for age, sex, marital status, and body mass index. In conclusion, ASA-PS grades can be predicted from CCI, and this may aid in generating more predictive trauma models.

Identification of anthropometric surrogate measurements and their cut-off points for the detection of low birth weight and premature newborn babies using ROC Analysis.

Despite the fact that health facilities in Ethiopia are being built closer to communities in all regions, the proportion of home deliveries remains high, and there are no studies being conducted to identify low birth weight (LBW) and premature newborn babies using simple, best, alternative, and appropriate anthropometric measurement in the study area. The objective of the present study was to find the simple, best, and alternative anthropometric measurement and identified its cut-off points for detecting LBW and premature newborn babies. A health facility-based cross-sectional study was conducted in the Dire Dawa city administration, Eastern Ethiopia. The study included 385 women who gave birth in health facility. To evaluate the overall accuracy of the anthropometric measurements, a non-parametric receiver operating characteristic curve was used. Chest circumference (AUC = 0⋅95) with 29⋅4 cm and mean upper arm circumference (AUC = 0⋅93) with 7⋅9 cm proved to be the best anthropometric diagnostic measure for LBW and gestational age, respectively. Also, both anthropometric measuring tools are achieved the highest correlation (r = 0⋅62) for LBW and gestational age. Foot length had a higher sensitivity (94⋅8 %) in detecting LBW than other measurements, with a higher negative predictive value (NPV) (98⋅4 %) and a higher positive predictive value (PPV) (54⋅8 %). Chest circumference and mid-upper arm circumference were found to be better surrogate measurements for identifying LBW and premature babies in need of special care. More research is needed to identify better diagnostic interventions in situations like the study area, which has limited resources and a high proportion of home deliveries.