Valuable Index Research Articles

Prognostic Value of Shock Index, Modified Shock Index, and Age Shock Index in Patients with Sepsis in the Intensive Care Unit

Objective: We aimed to evaluate the usability of the Shock Index (SI), Modified Shock Index (MSI), and Age Shock Index (ASI) in predicting clinical outcomes and mortality in sepsis patients followed in the intensive care unit. Methods: Records of patients admitted to the intensive care unit of Muş State Hospital between January 2022, and April 2024, who developed sepsis were retrospectively recorded from the hospital data system. Results: A total of 127 patients were included in the study. The average age of these patients was found to be 50.83±12.01 years. The average age of discharged patients was 46.14±10.12 years, while the average age of deceased patients was 58.54±10.89 years. In the gender distribution, 63.78% of all patients were male and 36.22% were female (p=0.028). SI was determined as 0.88±0.33 in discharged patients and 1.11±0.32 in deceased patients (p=0.0002). MSI was found to be 1.45±0.33 in discharged patients and 1.68±0.32 in deceased patients (p=0.00001). ASI was determined as 40.73±18.41 in discharged patients and 64.94±22.85 in deceased patients (p=0.0001). The cut-off value for SI was found to be 0.76, with an AUC value of 0.69. The cut-off value for the MSI was determined to be 1.35, with an AUC value of 0.72. The cut-off value for the ASI was found to be 38.76, with an AUC value of 0.85. Conclusion: All three shock indices were statistically significant in predicting mortality in sepsis patients. We believe they are valuable indices that can be used bedside and non-invasively in intensive care units.

Hydrochemical Characteristics and Spatial Variability in Coastal Aquifers Southern IraqUtilizing a GIS Technique

The present study investigates water quality regarding drinking and irrigation supplies by gathering and analyzing twelve groundwater samples south of Basrah, south Iraq. Many wells in the area concerned are exploited mainly for various industrial and agricultural activities, impacting the ground water quality. The standard guidelines recommended by the Iraqi Quality Standard limits and the World Health Organization have been used to determine the suitability of drinking. The physicochemica analyses showed that all sampled waters are unsuitable for the drinking supply due to high total dissolved solids (TDS) levels reaching 12925 mg/L. Four valuable indices have been applied for estimating the irrigated water quality, namely, the sodium adsorption ratio (SAR), the soluble sodium percentage (SSP%), the magnesium hazard (MH%), and Kelly’s ratio (KR%). The results of water class as regards the percent of samples showed: SAR results, 25% excellent water, 41.7% good water, and 33.3% doubtful water; SSP% results, 16.7 % good water, 75% permissible water, and 8.3 % doubtful water; MH% results, 100% suitable irrigated water; and KR% results show 41.7% suitable water and 58.3 % unsuitable water. The USSL salinity diagram (Wilcox) result revealed 83.3 % of samples fall in very high salinity-very high sodium hazard class C4S4, and 16.7 % of samples fall in very high salinity-high sodium hazard class C4S3 and very high salinity-medium sodium hazard class C4S2, respectively. Increasing salinity of coastal aquifers has impacted sources such as seawater intrusion and intensive irrigation, and usages of excessive fertilizers and herbicides can largely pollute the groundwater quality.

Correlation of serum homocysteine and cystatin C levels with prognosis in heart failure with preserved ejection fraction patients

ObjectiveThis study investigated the relationship of serum homocysteine (Hcy) and cystatin C (Cys C) levels with the prognosis of patients with heart failure with preserved ejection fraction (HFpEF).MethodsA total of 178 patients with HFpEF who were admitted to our hospital between December 2019 and November 2020 were included. Patients were grouped based on their serum Hcy and Cys C levels: high Hcy level, normal Hcy level, high Cys C level, and normal Cys C level. Cardiac function, ventricular remodeling indices, and prognosis were compared among patients in these groups. Additionally, the predictive value of serum Hcy and Cys C levels for adverse cardiovascular events in HFpEF patients was analyzed.ResultsPatients’ mean age in the high Hcy level, normal Hcy level, high Cys C level, and normal Cys C level groups was 69.21 ± 4.17,67.74 ± 4.28,69.95 ± 4.98, and 67.06 ± 4.13 years old, respectively. The high Hcy level group exhibited a lower proportion of class II cardiac function according to the New York Heart Association (NYHA) classification and a higher proportion of class IV cardiac function than the normal Hcy level group, with statistically significant differences. Similarly, the high Cys C level group had a lower proportion of class II cardiac function and a higher proportion of class IV cardiac function compared with the normal Cys C level group, with statistically significant differences. Left ventricular end-diastolic internal diameter (LVEDD), left ventricular end-systolic internal diameter (LVESD), and left ventricular mass index (LVMI) were significantly higher in both the high Hcy level and high Cys C level groups compared with the normal group, with statistically significant differences. The rates of all-cause mortality and class I endpoint events were significantly higher in the high Hcy level and high Cys C level groups than in the normal group. Multifactorial logistic regression analysis demonstrated that adverse cardiovascular events were significantly associated with cardiac function class, LVEDD, LVESD, LVMI, Hcy, and Cys C in patients with HFpEF. The area under the curve (AUC) values for Hcy and Cys C, determined using receiver operating characteristic (ROC) curve analysis, were 0.778 (optimal critical value, 25.38) and 0.681 (optimal critical value, 1.56), respectively, for predicting adverse cardiovascular events. Both Hcy and Cys C serum levels were positively correlated with LVEDD, LVESD, LVMI, and NYHA classification.ConclusionSerum levels of Hcy and Cys C were closely associated with cardiac function, ventricular remodeling indices, and prognosis in patients with HFpEF. These levels may serve as valuable indices for assessing HFpEF patients’ health status and prognosis, providing important insights into their potential role as biomarkers for HFpEF management and prognosis.

Influence of sex and functional status on the value of serum steroid profiling in discriminating adrenocortical carcinoma from adrenocortical adenoma.

It is challenging for clinicians to distinguish adrenocortical carcinoma (ACC) from benign adrenocortical adenomas (ACA) in their early stages. This study explored the value of serum steroid profiling as a complementary biomarker for malignancy diagnosis of ACC other than diameter and explored the influence of sex and functional status. In this retrospective study, a matched cohort of patients diagnosed with either ACC or ACA based on histopathology was meticulously paired in a 1:1 ratio according to sex, age, and functional status. Eight serum steroids including 11-deoxycortisol, 11-deoxycorticosterone, progesterone, androstenedione, dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS), 17-hydroxyprogesterone, and estradiol, were quantified by liquid chromatography tandem mass spectrometry. We conducted a comparative analysis of the clinical characteristics and serum steroid profiles of patients with ACC and ACA, with further subgroup analysis. The study included 31 patients with ACC and 31 matched patients with ACA. Patients with ACC exhibited significantly larger tumor diameters, lower body mass index (BMI), and higher levels of 11-deoxycortisol, progesterone, and androstenedione than those with ACA. 11-deoxycortisol was the only valuable index for discriminating ACC from ACA, regardless of functional status and sex. Progesterone, DHEA, and DHEAS levels were higher in the functional ACC group than in the non-functional ACC group. Female ACC patients, especially in postmenopausal female exhibited higher levels of androstenedione than male patients. The area under the curve of tumor diameter, 11-deoxycortisol, and BMI was 0.947 (95% CI 0.889-1.000), with a sensitivity of 96.8% and specificity of 90.3%. Serum steroid profiling serves as a helpful discriminative marker for ACC and ACA, with 11-deoxycortisol being the most valuable marker. For other steroid hormones, consideration of sex differences and functional status is crucial.

T2 mapping post acute myocardial infarction: a novel technique in assessing myocardial edema

ObjectiveCardiovascular magnetic resonance (CMR) is considered the gold standard imaging modality for assessing myocardial infarction lesions, offering precise myocardial tissue characterization. Elevated transverse relaxation time (T2) serves as a specific indicator of increased myocardial water content, thus becoming a valuable index for myocardial edema. However, conventional T2-weighted CMR sequence exhibits several limitations, primarily providing qualitative information. In contrast, recently developed quantitative T2 mapping techniques overcome these limitations, enabling a more reliable assessment of myocardial edema. These techniques offer the advantage of diagnosing and monitoring myocardial injury without the necessity of contrast agents. Our study aims to add to a growing literature demonstrating the efficacy of quantitative T2 mapping technique to detect and quantify regions of myocardial edema post-myocardial infarction.ResultNative T1 and T2 mapping accurately identified myocardial edema in all patients enrolled in the study. Notably, native T1 and T2 values exhibited a significant elevation in the infarcted myocardium compared to the remote myocardium (for T1: 1295.50 ± 87.65 vs. 1074.95 ± 92.86 ms, respectively; and for T2: 74.63 ± 6.51 vs. 52.53 ± 6.26 ms, respectively; p < 0.0001 for both). Microvascular obstruction was observed in 12 out of 20 patients, affecting one or more myocardial segments within the infarct areas. Among this subgroup, regions with a microvascular obstruction within the infarct zone displayed lower T1 and T2 values compared to areas of infarction without microvascular obstruction (for T1: 1115.05 ± 64.70 vs. 1295.50 ± 87.65 ms, respectively; and for T2: 53.65 ± 3.56 vs. 74.63 ± 6.51 ms, respectively; p < 0.0001 for both). Additionally, we provided reference values for myocardial T1 and T2 specific to our facility’s 1.5 Tesla CMR system, applicable to both infarct and remote myocardium.ConclusionParametric T1 and T2 mapping techniques can detect and quantify myocardial edema resulting from myocardial infarction. The presence of microvascular obstruction that results from revascularization injury affects both T1 and T2 values. This information can be used and has broad clinical implications for diagnosis and guiding or monitoring the treatment of myocardial infarction.

The value of phenylalanine in predicting atrial fibrillation risk in chronic heart failure.

Atrial fibrillation (AF) is a common complication of chronic heart failure (HF). Serum phenylalanine (Phe) levels are related to inflammation disorder. It is meaningful to study the circulating Phe with AF occurrence in HF. The cross-sectional study recruited 300 patients (78.0% male; mean age, 65 ± 13 years) with HF (left ventricular ejection fraction of ≤50%, containing 70 AF patients) and 100 normal controls. Serum Phe value was measured by liquid chromatography-tandem mass spectrometry. Logistic regression analysis was conducted to measure the association between Phe and AF risk in HF. The association between Phe and high-sensitivity C-reactive protein (hsCRP) was assessed by simple correlation analysis. In the prospective study, the 274 HF subjects (76.6% male; mean age, 65 ± 13 years) were followed up for a mean year (10.99 ± 3.00 months). Serum Phe levels increased across the control, the HF without AF, and the HF with AF groups (77.60 ± 8.67 umol/L vs. 95.24 ± 28.58 umol/L vs. 102.90 ± 30.43 umol/L, ANOVA P < 0.001). Serum Phe value was the independent risk factor for predicting AF in HF [odds ratio (OR), 1.640; 95% CI: 1.150-2.339; P = 0.006]. Phe levels were correlated positively with hsCRP value in HF patients with AF (r = 0.577, P < 0.001). The elevated Phe levels were associated with a higher risk of HF endpoint events in HF patients with AF (log-rank P = 0.005). In HF with AF subjects, elevated Phe value confers an increased risk for prediction AF and was more related to poor HF endpoint events. Phe can be a valuable index of AF in HF.

A radiomics approach for predicting gait freezing in Parkinson's disease based on resting-state functional magnetic resonance imaging indices: a cross-sectional study.

Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease. Resting-state functional magnetic resonance imaging, along with its multi-level feature indices, has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease. It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity. However, the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge. Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases, a knowledge gap still exists in the field of freezing of gait in Parkinson's disease. This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging, along with clinical features, to distinguish between Parkinson's disease patients with and without freezing of gait. We recruited 28 patients with Parkinson's disease who had freezing of gait (15 men and 13 women, average age 63 years) and 30 patients with Parkinson's disease who had no freezing of gait (16 men and 14 women, average age 64 years). Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations, mean regional homogeneity, and degree centrality. Neurological and clinical characteristics were also evaluated. We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators. We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features. Subsequently, we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve. The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait, or from healthy controls, the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750 (with an accuracy of 70.9%) and 0.759 (with an accuracy of 65.3%), respectively. When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait, the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847 (with an accuracy of 74.3%). The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics: Montreal Cognitive Assessment and Hamilton Depression Scale scores. Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.

The implicated role of GDF15 in gastrointestinal cancer.

Growth differentiation factor 15 (GDF15), a stress-responsive cytokine from transforming growth factor superfamily, is highly expressed in mammalian tissues, including pancreas, stomach and intestine under pathological conditions. In particular, elevated levels of GDF15 might play an important role in the development and progression of various gastrointestinal cancers (GCs), suggesting its potential as a promising target for disease prediction and treatment. In this review, systematic reviews addressing the role of GDF15 in GCs were updated, along with the latest clinical trials focussing on the GDF15-associated digestive malignancies. The multiple cellular pathways through which GDF15 is involved in the regulation of physiological and pathological conditions were first summarized. Then, GDF15 was also established as a valuable clinical index, functioning as a predictive marker in diverse GCs. Notably, latest clinical treatments targeting GDF15 were also highlighted, demonstrating its promising potential in mitigating and curing digestive malignancies. This review unveils the pivotal roles of GDF15 and its potential as a promising target in the pathogenesis of GCs, which may provide insightful directions for future investigations.

Deep learning based automated estimation of urban green space index from satellite image: A case study

The green area factor model is a crucial tool for conserving and creating urban greenery and ecosystem services within neighborhood land. This model serves as a valuable index, streamlining the planning, assessment, and comparison of local-scale green infrastructures. However, conventional on-site measurements of the green area factor are resource intensive. In response, this study pioneers a computational approach that integrates ecological and social dimensions to estimate the green area factor. Employing satellite remote sensing and advanced deep learning techniques, the methodology utilizes satellite orthophotos of urban areas subjected to semantic segmentation, identifying and categorizing diverse green elements. Ground truths are established through on-site measurements of green area factors and satellite orthophotos from benchmarking sites in Örebro, Sweden. Results reveal an 82.0% average F1-score for semantic segmentations, signifying a favourable correlation between computationally estimated and measured green area factors. The proposed methodology is potential for adapting to various urban settings. In essence, this research introduces a promising, cost-effective solution for assessing urban greenness, particularly beneficial for urban administrators and planners aiming for insightful and comprehensive green strategies in city planning.

Potential clinical value of fibrinogen-like protein 1 as a serum biomarker for the identification of diabetic cardiomyopathy

Diabetic individuals with diabetic cardiomyopathy (DbCM) present with abnormal myocardial structure and function. DbCM cannot be accurately diagnosed due to the lack of suitable diagnostic biomarkers. In this study, 171 eligible participants were divided into a healthy control (HC), type 2 diabetes mellitus (T2DM) patients without DbCM (T2DM), or DbCM group. Serum fibrinogen-like protein 1 (FGL-1) and other biochemical parameters were determined for all participants. Serum FGL-1 levels were significantly higher in patients with DbCM compared with those in the T2DM group and HCs. Serum FGL-1 levels were negatively correlated with left ventricular fractional shortening and left ventricular ejection fraction (LVEF) and positively correlated with left ventricular mass index in patients with DbCM after adjusting for age, sex and body mass index. Interaction of serum FGL-1 and triglyceride levels on LVEF was noted in patients with DbCM. A composite marker including serum FGL-1 and triglycerides could differentiate patients with DbCM from those with T2DM and HCs with an area under the curve of 0.773 and 0.789, respectively. Composite marker levels were negatively correlated with N-terminal B-type natriuretic peptide levels in patients with DbCM. Circulating FGL-1 may therefore be a valuable index reflecting cardiac functions in DbCM and to diagnose DbCM.

Potential for in vivo visualization of intracellular pH gradient in the brain using PET imaging.

Intracellular pH is a valuable index for predicting neuronal damage and injury. However, no PET probe is currently available for monitoring intracellular pH in vivo. In this study, we developed a new approach for visualizing the hydrolysis rate of monoacylglycerol lipase, which is widely distributed in neurons and astrocytes throughout the brain. This approach uses PET with the new radioprobe [11C]QST-0837 (1,1,1,3,3,3-hexafluoropropan-2-yl-3-(1-phenyl-1H-pyrazol-3-yl)azetidine-1-[11C]carboxylate), a covalent inhibitor containing an azetidine carbamate skeleton for monoacylglycerol lipase. The uptake and residence of this new radioprobe depends on the intracellular pH gradient, and we evaluated this with in silico, in vitro and in vivo assessments. Molecular dynamics simulations predicted that because the azetidine carbamate moiety is close to that of water molecules, the compound containing azetidine carbamate would be more easily hydrolyzed following binding to monoacylglycerol lipase than would its analogue containing a piperidine carbamate skeleton. Interestingly, it was difficult for monoacylglycerol lipase to hydrolyze the azetidine carbamate compound under weakly acidic (pH 6) conditions because of a change in the interactions with water molecules on the carbamate moiety of their complex. Subsequently, an in vitro assessment using rat brain homogenate to confirm the molecular dynamics simulation-predicted behaviour of the azetidine carbamate compound showed that [11C]QST-0837 reacted with monoacylglycerol lipase to yield an [11C]complex, which was hydrolyzed to liberate 11CO2 as a final product. Additionally, the 11CO2 liberation rate was slower at lower pH. Finally, to indicate the feasibility of estimating how the hydrolysis rate depends on intracellular pH in vivo, we performed a PET study with [11C]QST-0837 using ischaemic rats. In our proposed in vivo compartment model, the clearance rate of radioactivity from the brain reflected the rate of [11C]QST-0837 hydrolysis (clearance through the production of 11CO2) in the brain, which was lower in a remarkably hypoxic area than in the contralateral region. In conclusion, we indicated the potential for visualization of the intracellular pH gradient in the brain using PET imaging, although some limitations remain. This approach should permit further elucidation of the pathological mechanisms involved under acidic conditions in multiple CNS disorders.

Correlation of Prognostic Nutritional Index and Systemic Immune-Inflammation Index with the Recurrence and Prognosis in Oral Squamous Cell Carcinoma with the Stage of III/IV.

This study aimed to explore the correlation of systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) with the recurrence and prognosis in patients with advanced oral squamous cell carcinoma (OSCC). A total of 298 OSCC patients with the stage of III/IV were finally included in the study. SII = neutrophil count (109/L) × platelet count (109/L)/lymphocyte count (109/L). PNI = serum albumin (g/L) + 5 × total lymphocyte count (109/L). High preoperative SII and low preoperative PNI were independent risk factors for tumor recurrence in OSCC patients of the stage of III/IV. The area under the curves (AUC) for SII was 0.69 (0.63 to 0.76), for PNI was 0.72 (0.67 to 0.78), and for joint model was 0.81 (0.76 to 0.85). Patients with low level of joint model had significantly higher overall survival rate for 5 years follow-up than those with high level. Both preoperative SII and PNI are valuable independent tumor recurrence prediction index in patients with advanced OSCC. Meanwhile, the combination of preoperative SII and PNI is also valuable on OSCC recurrence and prognosis prediction.

Electroencephalography Spectral-power Volatility Predicts Problem-solving Outcomes.

Temporal variability is a fundamental property of brain processes and is functionally important to human cognition. This study examined how fluctuations in neural oscillatory activity are related to problem-solving performance as one example of how temporal variability affects high-level cognition. We used volatility to assess step-by-step fluctuations of EEG spectral power while individuals attempted to solve word-association puzzles. Inspired by recent results with hidden-state modeling, we tested the hypothesis that spectral-power volatility is directly associated with problem-solving outcomes. As predicted, volatility was lower during trials solved with insight compared with those solved analytically. Moreover, volatility during prestimulus preparation for problem-solving predicted solving outcomes, including solving success and solving time. These novel findings were replicated in a separate data set from an anagram-solving task, suggesting that less-rapid transitions between neural oscillatory synchronization and desynchronization predict better solving performance and are conducive to solving with insight for these types of problems. Thus, volatility can be a valuable index of cognition-related brain dynamics.

Patterns and drivers of plant carbon, nitrogen, and phosphorus stoichiometry in a novel riparian ecosystem.

Carbon (C), nitrogen (N), and phosphorus (P) stoichiometry serve as valuable indices for plant nutrient utilization and biogeochemical cycling within ecosystems. However, the allocation of these nutrients among different plant organs and the underlying drivers in dynamic riparian ecosystems remain inadequately understood. In this study, we gathered plant samples from diverse life forms (annuals and perennials) and organs (leaves, stems, and roots) in the riparian zone of the Three Gorges Reservoir Region (TGRR) in China-a novel ecosystem subject to winter flooding. We used random forest analysis and structural equation modeling to find out how flooding, life forms, plant communities, and soil variables affect organs C, N, and P levels. Results showed that the mean concentrations of plant C, N, and P in the riparian zone of the TGRR were 386.65, 19.31, and 5.27 mg/g for leaves respectively, 404.02, 11.23, and 4.81 mg/g for stems respectively, and 388.22, 9.32, and 3.27 mg/g for roots respectively. The C:N, C:P and N:P ratios were 16.15, 191.7 and 5.56 for leaves respectively; 26.98, 273.72 and 4.6 for stems respectively; and 16.63, 223.06 and 4.77 for roots respectively. Riparian plants exhibited nitrogen limitation, with weak carbon sequestration, low nutrient utilization efficiency, and a high capacity for nutrient uptake. Plant C:N:P stoichiometry was significantly different across life forms and organs, with higher N and P concentrations in leaves than stems and roots, and higher in annuals than perennials. While flooding stress triggered distinct responses in the C, N, and P concentrations among annual and perennial plants, they maintained similar stoichiometric ratios along flooding gradients. Furthermore, our investigation identified soil properties and life forms as more influential factors than plant communities in shaping variations in C:N:P stoichiometry in organs. Flooding indirectly impacts plant C:N:P stoichiometry primarily through alterations in plant community composition and soil factors. This study underscores the potential for hydrologic changes to influence plant community composition and soil nutrient dynamics, and further alter plant ecological strategies and biogeochemical cycling in riparian ecosystems.

Prediction of Intracranial Pressure in Patients with an Aneurysmal Subarachnoid Hemorrhage Using Optic Nerve Sheath Diameter via Explainable Predictive Modeling.

Background: The objective of this investigation was to formulate a model for predicting intracranial pressure (ICP) by utilizing optic nerve sheath diameter (ONSD) during endovascular treatment for an aneurysmal subarachnoid hemorrhage (aSAH), incorporating explainable predictive modeling. Methods: ONSD measurements were conducted using a handheld ultrasonography device during the course of endovascular treatment (n = 126, mean age 58.82 ± 14.86 years, and female ratio 67.46%). The optimal ONSD threshold associated with an increased ICP was determined. Additionally, the association between ONSD and ICP was validated through the application of a linear regression machine learning model. The correlation between ICP and various factors was explored through the modeling. Results: With an ICP threshold set at 20 cmH2O, 82 patients manifested an increased ICP, with a corresponding ONSD of 0.545 ± 0.08 cm. Similarly, with an ICP threshold set at 25 cmH2O, 44 patients demonstrated an increased ICP, with a cutoff ONSD of 0.553 cm. Conclusions: We revealed a robust correlation between ICP and ONSD. ONSD exhibited a significant association and demonstrated potential as a predictor of ICP in patients with an ICP ≥ 25 cmH2O. The findings suggest its potential as a valuable index in clinical practice, proposing a reference value of ONSD for increased ICP in the institution.

The 13C glucose breath test accurately identifies insulin resistance in people with type 1 diabetes.

This study investigated whether the delta-over-baseline of exhaled 13CO2 (Δ13CO2), generated from a 13C glucose breath test (13C-GBT), measured insulin resistance (IR) in people with type 1 diabetes, using the hyperinsulinemic-euglycemic clamp (HEC) as reference method. Secondary objective was to compare the 13C-GBT with the estimated glucose disposal rate (eGDR). A 40 mU/m2/min HEC and two separate 13C-GBTs (euglycemic with insulin bolus and hyperglycemic without bolus) were consecutively performed in 44 adults with type 1 diabetes with varying body compositions. eGDR was calculated based on HbA1c, presence of hypertension and waist circumference. Mean M-value was 5.9 ± 3.1 mg/kg/min, mean euglycemic Δ13CO2 was 6.4 ± 2.1 δ‰, while median eGDR was 5.9 [4.3 - 9.8] mg/kg/min. The hyperglycemic Δ13CO2 did not correlate with the M-value, while the euglycemic Δ13CO2 and the M-value correlated strongly (r = 0.74, p < 0.001). Correlation between M-value and eGDR was more moderate (Spearman's rho = 0.63, p < 0.001). Linear regression showed an association between Δ13CO2 and M-value, adjusted for age, sex and HbA1c (adjusted R² = 0.52, B = 1.16, 95% CI 0.80 - 1.52, p < 0.001). The AUROC for Δ13CO2 to identify subjects with IR (M-value < 4.9 mg/kg/min) was 0.81 (95% CI 0.68 - 0.94, p < 0.001). The optimal cut-off for Δ13CO2 to identify subjects with IR was ≤ 5.8 δ‰. Under euglycemic conditions, the 13C-GBT accurately identified individuals with type 1 diabetes and concurrent IR, suggesting its potential as a valuable non-invasive index.

The mean reticulocyte volume is a valuable index in early diagnosis of cancer-related anemia.

Cancer-related anemia (CRA) is a functional iron deficient anemia, and the early diagnosis will improve the prognosis of the patients. This prospective study aimed to investigate the utility of mean reticulocyte volume (MRV) in the early diagnosis of CRA. A total of 284 first-diagnosed cancer patients were enrolled, and the subjects were assigned anemia and non-anemia groups by hemoglobin (Hb) concentrations. The mature RBC and reticulocyte indices were detected with BC-7500 blood analyzer, and the MRV, reticulocyte hemoglobin (RHE) content, and reticulocyte production index (RPI) were obtained. ROC curves were constructed in identifying anemia diagnosed by the combination of RHE and RPI. An adjusted multivariate analyse and quartiles were used to assess the associations of MRV with early CRA diagnosed by combining RBC indices (MCV, MCH and MCHC), respectively. No statistical differences were observed in MCV, RHE and MRV levels between anemia and non-anemia subjects (p>0.05). MRV exhibited a complete or high correlation with the RHE levels (r=1.000, p<0.001), or MCV, MCH, and MCHC in anemia patients (R: 0.575-0.820, p<0.001). ROC curves analyse indicated a highest area under curve of 0.829 (95% CI [0.762-0.895]) and 0.884 (95% CI [0.831-0.936]) for MRV in identifying anemia in male and female patients, respectively (p<0.001). When the optimal cutoff values of MRV were set at 100.95 fl in males and 98.35 fl in females, the sensitivity and specificity were 1.00 and 0.68, and 1.00 and 0.73, respectively. The regression analyse showed that, when being as a categorical variable, MRV showed an odds ratio of 19.111 (95% CI [6.985-52.288]; p<0.001) for the incidence of CRA. The incidence of overall anemia demonstrated a more significant decrease trend along with the increase of MRV quartiles (p-trend < 0.001). This study revealed that the MRV can be used as a convenient and sensitive index in early diagnosis of cancer-related anemia, and decreased MRV level may be the powerful predictor of overt anemia in cancer patients.

Long-term findings on working memory neural dynamics in healthcare workers after mild COVID-19

ObjectiveUnderstanding the long-term impact of Coronavirus Disease 2019 (COVID-19) on cognitive function, even in mild cases, is critical to the well-being of individuals, especially for healthcare workers who are at increased risk of exposure to the virus. To the best of our knowledge, the electrophysiological activity underlying cognitive functioning has not yet been explored. MethodsSeventy-seven healthcare workers took part in the study (43 with mild infection about one year before the study and 34 uninfected). To assess cognitive status, event-related potentials (ERPs) and behavioural responses were recorded while participants performed a working memory task. ResultsCOVID-19 participants exhibited a distinct neural pattern with lower parieto-occipital N1 amplitudes and higher frontal P2 amplitudes as compared to non-infected healthcare workers. We found no behavioural differences (reaction times and error rates) in working memory functioning between groups. ConclusionsThis neural pattern suggests the presence of a decrement of processing resources linked to the encoding of sensory information (N1), followed by the enhanced of the P2 response which could be interpreted as the activation of compensation mechanism in COVID-19 participants. SignificanceThe current findings point out that ERPs could serve as valuable neural indices for detecting distinctive patterns in working memory functioning of COVID-19 participants, even in mild cases. However, further research is required to precisely ascertain the long-term cognitive effects of COVID-19 beyond one-year post-infection.

An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks.

Automated recognition of heart shunts using saline contrast transthoracic echocardiography (SC-TTE) has the potential to transform clinical practice, enabling non-experts to assess heart shunt lesions. This study aims to develop a fully automated and scalable analysis pipeline for distinguishing heart shunts, utilizing a deep neural network-based framework. The pipeline consists of three steps: (1) chamber segmentation, (2) ultrasound microbubble localization, and (3) disease classification model establishment. The study's normal control group included 91 patients with intracardiac shunts, 61 patients with extracardiac shunts, and 84 asymptomatic individuals. Participants' SC-TTE images were segmented using the U-Net model to obtain cardiac chambers. The segmentation results were combined with ultrasound microbubble localization to generate multivariate time series data on microbubble counts in each chamber. A classification model was then trained using this data to distinguish between intracardiac and extracardiac shunts. The proposed framework accurately segmented heart chambers (dice coefficient = 0.92 ± 0.1) and localized microbubbles. The disease classification model achieved high accuracy, sensitivity, specificity, F1 score, kappa value, and AUC value for both intracardiac and extracardiac shunts. For intracardiac shunts, accuracy was 0.875 ± 0.008, sensitivity was 0.891 ± 0.002, specificity was 0.865 ± 0.012, F1 score was 0.836 ± 0.011, kappa value was 0.735 ± 0.017, and AUC value was 0.942 ± 0.014. For extracardiac shunts, accuracy was 0.902 ± 0.007, sensitivity was 0.763 ± 0.014, specificity was 0.966 ± 0.008, F1 score was 0.830 ± 0.012, kappa value was 0.762 ± 0.017, and AUC value was 0.916 ± 0.006. The proposed framework utilizing deep neural networks offers a fast, convenient, and accurate method for identifying intracardiac and extracardiac shunts. It aids in shunt recognition and generates valuable quantitative indices, assisting clinicians in diagnosing these conditions.

Research on feature extraction method for different levels of cracks and pitting in spur gear based on dynamic characteristic templates

Health monitoring and fault diagnosis play a pivotal role in ensuring the safety of helicopter flights. Dynamic analysis has proven to be effective in accurately capturing the characteristics of crack and pitting signals. However, its application in fault diagnosis has limitations. This study introduces a feature extraction method based on the dynamic characteristic templates (DCTs) for different levels of cracks and pitting in spur gears. This method serves as a bridge between dynamic analysis and fault diagnosis, facilitating a comprehensive assessment of gear health. The integration of improved sparrow search algorithm (ISSA) and variational mode decomposition matching (VMDM) techniques enhances the search and matching capabilities of target signal based on DCTs. Based on above research, this study reveals distinctive morphological characteristics in the signals associated with crack and pitting under different levels and these characteristics serve as valuable index for fault diagnosis.