Predict Disease Severity Research Articles

Monomeric C-reactive protein is associated with severity and prognosis of decompensated hepatitis B cirrhosis.

C-reactive protein (CRP) is an acute-phase protein produced by the liver in response to infection and during chronic inflammatory disorders. Systemic inflammation is a major driver of cirrhosis progression from the compensated to the decompensated stage. Previous studies have shown that pentameric CRP (pCRP) to be a weak predictor of disease severity and prognosis in patients with decompensated hepatitis B cirrhosis, with it being only helpful for identifying patients with a higher short-term risk of death under certain conditions. Accumulating evidence indicates that pCRP dissociates to and acts primarily as the monomeric conformation (mCRP) at inflammatory loci, suggesting that mCRP may be a potentially superior disease marker with higher specificity and relevance to pathogenesis. However, it is unknown whether mCRP and anti-mCRP autoantibodies are associated with disease severity, or progression in decompensated hepatitis B cirrhosis. In this study, we evaluated the serum levels of mCRP and anti-mCRP autoantibodies in patients with decompensated cirrhosis of hepatitis B and their association with disease severity and theoretical prognosis. The results showed that patients with high mCRP and anti-mCRP autoantibody levels had more severe liver damage and that coagulation function was worse in patients with high anti-mCRP autoantibodies. Analysis of the correlation between pCRP, mCRP and anti-mCRP autoantibody levels with Model for End-Stage Liver Disease (MELD), Albumin-Bilirubin (ALBI), and Child-Turcotte-Pugh (CTP) prognostic scores showed that mCRP was the most strongly correlated with MELD score, followed by anti-mCRP autoantibodies; conversely, pCRP was not significantly correlated with prognostic score. Therefore, mCRP and anti-mCRP autoantibodies may be more advantageous clinical indicators than pCRP for evaluating the pathological state of decompensated hepatitis B cirrhosis.

TM9SF1 offers utility as an efficient predictor of clinical severity and mortality among acute respiratory distress syndrome patients.

Acute respiratory distress syndrome (ARDS) is a major cause of death among critically ill patients in intensive care settings, underscoring the need to identify biomarkers capable of predicting ARDS patient clinical status and prognosis at an early time point. This study specifically sought to explore the utility and clinical relevance of TM9SF1 as a biomarker for the early prediction of disease severity and prognostic outcomes in patients with ARDS. This study enrolled 123 patients with severe ARDS and 116 patients with non-severe ARDS for whom follow-up information was available. The mRNA levels of TM9SF1 and cytokines in peripheral blood mononuclear cells from these patients were evaluated by qPCR. The predictive performance of TM9SF1 and other clinical indicators was evaluated using received operating characteristic (ROC) curves. A predictive nomogram was developed based on TM9SF1 expression and evaluated for its ability in the early prediction of severe disease and mortality in patients with ARDS. TM9SF1 mRNA expression was found to be significantly increased in patients with severe ARDS relative to those with non-severe disease or healthy controls. ARDS severity increased in correspondence with the level of TM9SF1 expression (odds ratio [OR] = 2.43, 95% confidence interval [CI] = 2.15-3.72, P = 0.005), and high TM9SF1 levels were associated with a greater risk of mortality (hazard ratio [HR] = 2.27, 95% CI = 2.20-4.39, P = 0.001). ROC curves demonstrated that relative to other clinical indicators, TM9SF1 offered superior performance in the prediction of ARDS severity and mortality. A novel nomogram incorporating TM9SF1 expression together with age, D-dimer levels, and C-reactive protein (CRP) levels was developed and was used to predict ARDS severity (AUC = 0.887, 95% CI = 0.715-0.943). A separate model incorporating TM9SF1 expression, age, neutrophil-lymphocyte ratio (NLR), and D-dimer levels (C-index = 0.890, 95% CI = 0.627-0.957) was also developed for predicting mortality. Increases in ARDS severity and patient mortality were observed with rising levels of TM9SF1 expression. TM9SF1 may thus offer utility as a novel biomarker for the early prediction of ARDS patient disease status and clinical outcomes.

Role of biomarkers in community-acquired pneumonia management

Community-acquired pneumonia (CAP) poses a significant global health threat, particularly affecting vulnerable populations. Biomarkers and scoring systems play a crucial role in diagnosing, assessing severity, and guiding treatment decisions for CAP patients. Biomarkers like C reactive protein, procalcitonin, and the neutrophil-to-lymphocyte ratio aid in diagnosis and severity assessment, while scoring systems such as CURB-65 and Pneumonia Severity Index classify patients into risk categories. Emerging biomarkers (uremia, elevated respiratory rate, hypotension, and age ≥ 65) like serum amyloid A and S100 proteins show promise in predicting disease severity and prognosis. However, further research is needed to determine their precise roles and clinical utility in CAP management.

An efficient synthetic minority oversampling technique-based ensemble learning model to detect COVID-19 severity

The COVID-19 pandemic has highlighted the importance of accurately predicting disease severity to ensure timely intervention and effective allocation of healthcare resources, which can ultimately improve patient outcomes. This study aims to develop an efficient machine learning (ML) model based on patient demographic and clinical data. It utilizes advanced feature engineering techniques to reduce the dimensionality of dataset and address the issue of highly imbalanced data using synthetic minority oversampling technique (SMOTE). The study employs several ensemble learning models, including XGBoost, Random Forest, AdaBoost, voting ensemble, enhanced-weighted voting ensemble, and stack-based ensembles with support vector machine (SVM) and Gaussian Naïve Bayes as meta-learners, to develop the proposed model. The results indicate that the proposed model outperformed the top-performing models reported in previous studies. It achieved an accuracy of 0.978, sensitivity of 1.0, precision of 0.875, F1-score of 0.934, and receiver operating characteristic area under the curve (ROC-AUC) of 0.965. The study identified several features that significantly correlated with COVID-19 severity, which included respiratory rate (breaths per minute), c-reactive proteins, age, and total leukocyte count (TLC) count. The proposed approach presents a promising method for accurate COVID-19 severity prediction, which may prove valuable in assisting healthcare providers in making informed decisions about patient care.

Identification of CXCL9 chemokine as a potential biomarker for assessing clinical severity in COVID-19 patients.

The severity and clinical outcome of COVID-19 depend on virus-specific factors and the host's inflammatory response. Identifying biomarkers of severe COVID-19 is a crucial condition and predicts disease severity. This study enrolled a total of 167 patients with COVID-19. These patients were categorized into three groups based on the severity of the disease: moderate course - 78 individuals, severe course - 52 individuals, and extremely severe course - 37 individuals. We analyzed chemokines (IP-10, CXCL9, CCL17) and cytokine IL28B levels using the enzyme immunoassay (EIA) method. CXCL9 levels were increased in severe and extremely severe cases compared to moderate ones. The CCL17 chemokine demonstrated significant elevation in severe cases. However, there was no significant difference in the level of IP-10, and IL28B in the compared groups. Our findings suggest that CXCL9 and CCL17 chemokines could be used as biomarkers to assess the clinical status of patients with COVID-19 and can relate to disease severity. These biomarkers could aid in identifying patients at high risk for severe disease and help guide clinical decision-making for the effective management of COVID-19.

Highly diverse sputum microbiota correlates with the disease severity in patients with community-acquired pneumonia: a longitudinal cohort study

BackgroundCommunity-acquired pneumonia (CAP) is a common and serious condition that can be caused by a variety of pathogens. However, much remains unknown about how these pathogens interact with the lower respiratory commensals, and whether any correlation exists between the dysbiosis of the lower respiratory microbiota and disease severity and prognosis.MethodsWe conducted a retrospective cohort study to investigate the composition and dynamics of sputum microbiota in patients diagnosed with CAP. In total, 917 sputum specimens were collected consecutively from 350 CAP inpatients enrolled in six hospitals following admission. The V3-V4 region of the 16 S rRNA gene was then sequenced.ResultsThe sputum microbiota in 71% of the samples were predominately composed of respiratory commensals. Conversely, 15% of the samples demonstrated dominance by five opportunistic pathogens. Additionally, 5% of the samples exhibited sterility, resembling the composition of negative controls. Compared to non-severe CAP patients, severe cases exhibited a more disrupted sputum microbiota, characterized by the highly dominant presence of potential pathogens, greater deviation from a healthy state, more significant alterations during hospitalization, and sparser bacterial interactions. The sputum microbiota on admission demonstrated a moderate prediction of disease severity (AUC = 0.74). Furthermore, different pathogenic infections were associated with specific microbiota alterations. Acinetobacter and Pseudomonas were more abundant in influenza A infections, with Acinetobacter was also enriched in Klebsiella pneumoniae infections.ConclusionCollectively, our study demonstrated that pneumonia may not consistently correlate with severe dysbiosis of the respiratory microbiota. Instead, the degree of microbiota dysbiosis was correlated with disease severity in CAP patients.

MUC5AC: A potential biomarker of severity in pediatric patients infected with influenza.

Numerous factors can increase the risk of severe influenza; however, a majority of severe cases occur in previously healthy children. Identification of high-risk children is important for targeted preventive interventions and prompt treatment. The aim of this study was to evaluate MUC5AC as a biomarker for influenza disease severity in children. For this, aprospective cohort study was conducted in 2019. Children hospitalized with acute respiratory infection (ARI) with confirmed positive influenza infection were enrolled. Influenza cases were identified by reverse transcriptase-polymerase chain reaction. Life-threatening disease (LTD) was defined by the need for intensive care and ventilatory support. MUC5AC, epidemiologic, and clinical risk factors were assessed. Three hundred and forty-two patients were hospitalized with ARI, of which 49 (14%) had confirmed influenza infection and 6 (12%) of them developed LTD. MUC5AC levels were higher in those patients with mild diseasecompared to cases with poorer outcomes. Our results show that the severity of influenza infection in children is significantly associated with low levels of MUC5AC. These findings suggest its potential as a suitable biomarker for predicting disease severity.

Predictive biomarkers of preeclampsia severity in a low resource setting: Role of red blood cell indices, NLR, and albumin-to-creatinine ratio.

Preeclampsia (PE), a serious medical condition with substantial maternal and perinatal implications, poses a significant challenge, particularly in high-incidence countries like Indonesia. Red blood cell (RBC) indices, neutrophil-to-lymphocyte ratio (NLR), and microalbuminuria (albumin-to-creatinine ratio (ACR)) may signal systemic inflammation and endothelial dysfunction, recently recognized as potential indicators for diagnosing and predicting disease severity. The aim of this study was to analyze RBC indices, NLR, and ACR changes in women with PE and their potential for predicting disease severity. A cross-sectional study was conducted at multi-center hospitals across Medan, Indonesia, from June 2022 to June 2023. The patients were grouped into PE cases with and without severe features. Demographic characteristics and complications were recorded while blood and urine were tested. The Chi-squared test, Fisher's exact test and Mann-Whitney test were used to determine biomarkers associated with severe PE. A total of 208 PE patients were included in the study (104 patients for each PE with and without severe features). Our data indicated that PE patients with severe features had higher red cell distribution width (18.5% vs 13.7%; p<0.001), NLR (5.66% vs 4.1%; p<0.001), and ACR (755.97 mg/dL vs 468.63 mg/dL; p<0.001) compared to those without severe features. In contrast, the platelet count was lower in severe features than those without (21.9 × 106/μL vs 27.0 × 106/μL; p=0.002). This study highlighted that PE patients with severe features predominantly had higher levels of RDW, NLR, and ACR and lower platelet counts compared to those without severe features. Therefore, basic tests such as complete blood count and urinalysis, which are inexpensive and feasible in primary care settings with limited resources, offer hope as valuable diagnostic biomarkers for pregnant women diagnosed with PE in a low resource setting.

Genetic determinants of renal scarring in children with febrile UTI

BackgroundFebrile urinary tract infections (UTIs) are among the most severe bacterial infections in infants, in which a subset of patients develops complications. Identifying infants at risk of recurrent infections or kidney damage based on clinical signs is challenging. Previous observations suggest that genetic factors influence UTI outcomes and could serve as predictors of disease severity. In this study, we conducted a nationwide survey of infant genotypes to develop a strategy for infection management based on individual genetic risk. Our aims were to identify genetic susceptibility variants for renal scarring (RS) and genetic host factors predisposing to dilating vesicoureteral reflux (VUR) and recurrent UTIs.MethodsTo assess genetic susceptibility, we collected and analyzed DNA from blood using exome genotyping. Disease-associated genetic variants were identified through bioinformatics analysis, including allelic frequency tests and odds ratio calculations. Kidney involvement was defined using dimercaptosuccinic acid (DMSA) scintigraphy.ResultsIn this investigation, a cohort comprising 1087 infants presenting with their first episode of febrile UTI was included. Among this cohort, a subset of 137 infants who underwent DMSA scanning was subjected to gene association analysis. Remarkable genetic distinctions were observed between patients with RS and those exhibiting resolved kidney involvement. Notably, the genetic signature indicative of renal scarring prominently featured mitochondrial genes.ConclusionsIn this nationwide study of genetic susceptibility to RS after febrile UTIs in infancy, we identified a profile dominated by mitochondrial polymorphisms. This profile can serve as a predictor of future complications, including RS and recurrent UTIs.Graphical abstractA higher resolution version of the Graphical abstract is available as Supplementary information

The Role of the Tissue Perfusion Index in Predicting Disease Severity and Prognosis in Patients with Severe and Critical COVID-19.

The study investigated whether percutaneous partial pressure of oxygen (PtcO2), percutaneous partial pressure of carbon dioxide (PtcCO2), and the derived tissue perfusion index (TPI) can predict the severity and short-term outcomes of severe and critical COVID-19. Prospective observational study conducted from January 1, 2023 to February 10, 2023. A teaching hospital specializing in tertiary care in Nanjing City, Jiangsu Province, China. Adults (≥18 years) with severe and critical COVID-19. Not applicable. The general information and vital signs of the patients were collected. The PtcO2 and PtcCO2 were monitored in the left dorsal volar. The ratio of TPI was defined as the ratio of PtcO2/fraction of inspired oxygen (FiO2) to PtcCO2. Mortality at 28 was recorded. The ability of the TPI to assess disease severity and predict prognosis was determined. Severity of the disease on the enrollment and mortality at 28. A total of 71 patients with severe and critical COVID-19, including 40 severe and 31 critical cases, according to the COVID-19 treatment guidelines published by WHO, were recruited. Their median age was 70 years, with 56 (79%) males. The median SpO2/FiO2, PtcO2, PtcCO2, PtcO2/ FiO2, and TPI values were 237, 61, 42, 143, and 3.6 mm Hg, respectively. Compared with those for severe COVID-19, the TPI, PtcO2/ FiO2, SpO2/FiO2, and PtcO2 were significantly lower in critical COVID-19, while the PtcCO2 was significantly higher. After 28 days, 26 (37%) patients had died. TPI values < 3.5 were correlated with more severe disease status (AUC 0.914; 95% CI: 0.847-0.981, P < 0.001), and TPI < 3.3 was associated with poor outcomes (AUC 0.937; 95% CI 0.880-0.994, P < 0.001). The tissue perfusion index (TPI), PtcCO2, and PtcO2/ FiO2 can predict the severity and outcome of severe and critical COVID-19.

Correlating Reiff scores with clinical, functional, and prognostic factors: characterizing noncystic fibrosis bronchiectasis severity: validation from a nationwide multicenter study in Taiwan

BackgroundOur study aimed to confirm a simplified radiological scoring system, derived from a modified Reiff score, to evaluate its relationship with clinical symptoms and predictive outcomes in Taiwanese patients with noncystic fibrosis bronchiectasis (NCFB).MethodsThis extensive multicenter retrospective study, performed in Taiwan, concentrated on patients diagnosed with NCFB verified through high-resolution computed tomography (HRCT) scans. We not only compared the clinical features of various types of bronchiectasis (cylindrical, varicose, and cystic). Furthermore, we established relationships between the severity of clinical factors, including symptom scores, pulmonary function, pseudomonas aeruginosa colonization, exacerbation and admission rates, and HRCT parameters using modified Reiff scores.ResultsData from 2,753 patients were classified based on HRCT patterns (cylindrical, varicose, and cystic) and severity, assessed by modified Reiff scores (mild, moderate, and severe). With increasing HRCT severity, a significant correlation was found with decreased forced expiratory volume in the first second (FEV1) (p < 0.001), heightened clinical symptoms (p < 0.001), elevated pathogen colonization (pseudomonas aeruginosa) (p < 0.001), and an increased annual hospitalization rate (p < 0.001). In the following multivariate analysis, elderly age, pseudomonas aeruginosa pneumonia, and hospitalizations per year emerged as the only independent predictors of mortality.ConclusionBased on our large cohort study, the simplified CT scoring system (Reiff score) can serve as a useful adjunct to clinical factors in predicting disease severity and prognosis among Taiwanese patients with NCFB.

Progress in novel biomarkers of anti-tuberculosis drug-induced liver injury

Anti-tuberculosis drug-induced liver injury(ATB-DILI) is the most common adverse reaction during anti-tuberculosis therapy in tuberculosis patients. At present, the diagnosis of ATB-DILI is mainly based on traditional biomarkers such as transaminases, but these indicators have low specificity for liver toxicity, they cannot explain the mechanism of liver injury and the early onset of ATB-DILI. Based on the prediction of disease severity, treatment and prevention, this paper described the current potential biomarkers of ATB-DILI.

CNS involvement in myotonic dystrophy type 1: does sex play a role?

Myotonic dystrophy type 1 (DM1) is a hereditary neuromuscular disorder affecting the central nervous system (CNS). Although sex differences have been explored in other neuromuscular disorders, research on this topic in DM1 remains limited. The present study aims to analyze sex differences (both the patient's and disease-transmitting parent's sex) with a focus on CNS outcomes. Retrospective data from 146 non-congenital DM1 patients were analyzed, including clinical, molecular, neuropsychological, and neuroradiological data. Sex and inheritance pattern differences were analyzed using t-tests, and ANOVA analyses were conducted to address the interactions. Overall, no significant sex differences were observed except in certain cognitive domains. However, individuals with maternal inheritance showed larger CTG expansion size, lower estimated IQs, and poorer performance on visual memory, executive functions, and language domains than those with paternal inheritance. Notably, IQ performance was independently influenced by inheritance pattern and CTG expansion. This study is the first to delve into sex differences in DM1 with a focus on CNS outcomes. While the results revealed the absence of a sex-specific clinic-molecular profile, more substantial CNS differences were observed between patients with maternal and paternal inheritance patterns. The hypothetical existence of genomic imprinting and its potential mechanism are discussed. These findings hold potential implications for aiding clinical management by improving genetic counseling and predicting disease severity and prognosis.

Clinical and laboratory findings characterizing the need for systemic corticosteroids and nonsteroidal systemic therapies and the predicted outcomes in cutaneous polyarteritis nodosa: a single-centre retrospective analysis.

Cutaneous polyarteritis nodosa (cPN) is a necrotizing arteritis of medium-sized vessels limited to the skin. Because of its rarity and the diversity of its clinical manifestations, there is no consensus treatment. Moreover, there are no established indicators that predict disease severity or its outcome. To investigate clinicolaboratory features that predict patients requiring systemic therapy, including corticosteroids, to control disease activity. Thirty-six patients with cPN who had not received systemic corticosteroids at their initial visit were retrospectively analysed by correlating the treatment and its response with clinicolaboratory findings. The major medications administered were antiplatelet agents [64% (23/36)], vasodilators [39% (14/36)] and prednisolone (PSL) [36% (13/36)]. In total, 23 patients achieved remission without PSL, 5 were managed with compression therapy alone or even observation and 18 received antiplatelet monotherapy or combined with vasodilator/dapsone whereas 13 required PSL. Of the 13 who required PSL, 10 achieved remission with PSL monotherapy or PSL and single/multiple medications and 3 with PSL and multiple drugs then failed to achieve remission and underwent limb amputation. There were more skin ulcers and an elevated peripheral white blood cell (WBC) count and erythrocyte sedimentation rate (ESR) before corticosteroid induction in patients requiring PSL. Three patients with treatment failure had a markedly elevated ESR (> 50 mm h-1). More than half of patients with cPN can achieve remission without corticosteroids. An elevated WBC, an elevated ESR and the presence of skin ulcers predict the need for PSL. A high ESR before corticosteroid induction predicts treatment resistance, even with PSL.

The cortical neurophysiological signature of amyotrophic lateral sclerosis.

The progressive loss of motor function characteristic of amyotrophic lateral sclerosis is associated with widespread cortical pathology extending beyond primary motor regions. Increasing muscle weakness reflects a dynamic, variably compensated brain network disorder. In the quest for biomarkers to accelerate therapeutic assessment, the high temporal resolution of magnetoencephalography is uniquely able to non-invasively capture micro-magnetic fields generated by neuronal activity across the entire cortex simultaneously. This study examined task-free magnetoencephalography to characterize the cortical oscillatory signature of amyotrophic lateral sclerosis for having potential as a pharmacodynamic biomarker. Eight to ten minutes of magnetoencephalography in the task-free, eyes-open state was recorded in amyotrophic lateral sclerosis (n = 36) and healthy age-matched controls (n = 51), followed by a structural MRI scan for co-registration. Extracted magnetoencephalography metrics from the delta, theta, alpha, beta, low-gamma, high-gamma frequency bands included oscillatory power (regional activity), 1/f exponent (complexity) and amplitude envelope correlation (connectivity). Groups were compared using a permutation-based general linear model with correction for multiple comparisons and confounders. To test whether the extracted metrics could predict disease severity, a random forest regression model was trained and evaluated using nested leave-one-out cross-validation. Amyotrophic lateral sclerosis was characterized by reduced sensorimotor beta band and increased high-gamma band power. Within the premotor cortex, increased disability was associated with a reduced 1/f exponent. Increased disability was more widely associated with increased global connectivity in the delta, theta and high-gamma bands. Intra-hemispherically, increased disability scores were particularly associated with increases in temporal connectivity and inter-hemispherically with increases in frontal and occipital connectivity. The random forest model achieved a coefficient of determination (R2) of 0.24. The combined reduction in cortical sensorimotor beta and rise in gamma power is compatible with the established hypothesis of loss of inhibitory, GABAergic interneuronal circuits in pathogenesis. A lower 1/f exponent potentially reflects a more excitable cortex and a pathology unique to amyotrophic lateral sclerosis when considered with the findings published in other neurodegenerative disorders. Power and complexity changes corroborate with the results from paired-pulse transcranial magnetic stimulation. Increased magnetoencephalography connectivity in worsening disability is thought to represent compensatory responses to a failing motor system. Restoration of cortical beta and gamma band power has significant potential to be tested in an experimental medicine setting. Magnetoencephalography-based measures have potential as sensitive outcome measures of therapeutic benefit in drug trials and may have a wider diagnostic value with further study, including as predictive markers in asymptomatic carriers of disease-causing genetic variants.

An assessment of severity of acute bronchiolitis using bronchiolitis severity score and its relation to serum sodium level in children attending Alexandria University Hospital

Background Acute viral bronchiolitis is a significant cause of respiratory morbidity globally. Acute bronchiolitis is a clinical diagnosis based on the clinical judgment of the treating physician. Consequently, management strategies for acute bronchiolitis have great variability. Therefore, valid objective, evidence-based assessment tools were needed to help assess the severity of the illness, therefore reducing variation in management plans and standardizing care. Aim The present work aims to assess the validity of the use of bronchiolitis severity score (BSS) and serum sodium level in predicting the severity of acute bronchiolitis and the relation between them in children attending Alexandria University Children’s Hospital. Patients and methods The study was a comparative cross-sectional study of 131 children clinically diagnosed with acute bronchiolitis, from 1 month to 2 years of age, who presented to the Emergency Department of Alexandria University Children’s Hospital. Measurement of each patient’s BSS and serum sodium level was done on presentation in triage. Admitted and nonadmitted patients were followed up. Longer length of hospital stay and Pediatric Intensive Care Unit (PICU) admission were considered indicators of increased severity of the disease and worse outcomes. Results There was a male predominance and the median age of the studied patients was 3 months. On the basis of BSS, acute bronchiolitis was classified as mild in 19 (14.5%) cases, moderate in 79 (60.3%), and severe in 33 (25.2%). Hyponatremia at presentation was present in 20 (15.2%) cases. Increased severity, as determined by BSS, was statistically significantly associated with higher rates of admissions, longer hospital stays, and increased incidence of PICU hospitalization. There was no statistically significant difference between the hyponatremic status and increased hospital stay or the incidence of PICU admission. By univariate analysis, length of hospital stay and incidence of PICU admission was significantly affected by BSS and by hyponatremia. By multivariate analysis, the only parameter that was significant was BSS. In predicting a longer hospital stay in admitted patients, BSS showed a sensitivity (Se)=77.78%, specificity (Sp)=100%, positive predictive value (PPV)=100%, and negative predictive value (NPV)=42.9 while hyponatremia showed a Se=20.83%, Sp=91.67%, PPV=93.75%, and NPV=16.18. In predicting the need for PICU admission in studied cases, BSS showed a Se=69.23%, Sp=94.92%, PPV=60%, and NPV=96.6 and Se=38.46%, while hyponatremia showed Sp=87.29%, PPV=25%, and NPV=92.79. Conclusion BSS could be used as a valuable tool for assessing the severity of acute bronchiolitis. The presence of hyponatremia on initial presentation, although occasionally observed, cannot be used as a predictor of disease severity, but it could be used as a prognostic factor of a more severe disease course.

Canine Cognitive Dysfunction Is Associated with Alzheimer’s Disease-Related Changes in the Brain Transcriptome and RNA Changes in Plasma Extracellular Vesicles

Chronic, age-related diseases, such as Alzheimer’s disease (AD), can be diffcult to study longitudinally because humans have long lifespans and are highly heterogeneous. Recently, companion dogs have emerged as a promising model of AD because dogs: a) have a shorter lifespan than humans; b) are heterogeneous like humans; c) exposed to diverse human environments; and d) naturally develop canine cognitive dysfunction (CCD), similar to AD. However, the transcriptomic similarities between AD and CCD have not been evaluated, and emerging mechanisms of AD have not been explored in dogs. One such mechanism involves extracellular vesicles (EVs), ~100nm lipid bilayer particles that can package neurodegeneration-relevant cargo (e.g., RNAs, cytokines), export it to other cells, and contribute to aging/AD-relevant processes like inflammation. To better understand CCD and determine if EVs may play a role in it, we generated total transcriptome (RNA-seq) on cortex tissue and EVs isolated from plasma of young, old, and CCD dogs, and we evaluated cytokine expression in corresponding plasma samples via ELISAs. In the animals we studied, we observed functional differences between old healthy and CCD animals, reflected by Canine Dementia Scale scores (CADES; 6 and 57, respectively). In our RNA-seq analyses, we found marked age- and CCD-related transcriptome differences in the cortex (328 and 2673 differentially expressed genes, respectively), which mostly reflected changes in immune activation and neuronal health (similar to what has been observed in AD). Moreover, when we overlapped transcriptome data on the cortex and plasma EVs, we found a significant overlap in genes that were either up- or down-regulated in both samples (344 and 515, respectively). The processes related to these genes reflected changes in regulation of immune responses, as well as synaptic signaling. We also found evidence of CCL5 (RANTES, increased in AD) RNA in plasma EVs only in CCD samples, which corresponded with increased CCL5 expression in the brains of the same animals, although no differences were observed in plasma concentrations. While preliminary in nature, these results suggest that CCD is associated with AD-like transcriptomic changes in the brain, and with AD-relevant changes in EV cargo. Future studies are needed to determine the functional relevance of these data, but our results suggest the possibility of finding specific EV/RNA markers that could predict disease severity in CCD, and perhaps eventually in AD. NIA R01AG078859; CSU Catalyst for Innovative Partnership Award. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Application of machine learning approaches for predicting hemophilia A severity

BackgroundHemophilia A (HA) is an X-linked congenital bleeding disorder, which leads to deficiency of clotting factor (F) VIII. It mostly affects males, and females are considered carriers. However, it is now recognized that variants of F8 in females can result in HA. Nonetheless, most females go undiagnosed and untreated for HA, and their bleeding complications are attributed to other causes. Predicting the severity of HA for female patients can provide valuable insights for treating the conditions associated with the disease, such as heavy bleeding. ObjectivesTo predict the severity of HA based on F8 genotype using a machine learning (ML) approach. MethodsUsing multiple datasets of variants in the F8 and disease severity from various repositories, we derived the sequence for the FVIII protein. Using the derived sequences, we used ML models to predict the severity of HA in female patients. ResultsUtilizing different classification models, we highlight the validity of the datasets and our approach with predictive F1 scores of 0.88, 0.99, 0.93, 0.99, and 0.90 for all the validation sets. ConclusionAlthough with some limitations, ML-based approaches demonstrated the successful prediction of disease severity in female HA patients based on variants in the F8. This study confirms previous research findings that ML can help predict the severity of hemophilia. These results can be valuable for future studies in achieving better treatment and clinical outcomes for female patients with HA, which is an urgent unmet need.

Cómo calificar el índice de gravedad en la apnea obstructiva del sueño

Currently, obstructive sleep apnea (OSA) is defined as having an apnea-hypopnea index (AHI) of 5 events per hour. The AHI is based on the frequency of respiratory events over time and is used to predict disease severity and guide therapeutic interventions. However, the AHI fails to capture the substantial heterogeneity present in OSA, including patterns of hypoxemia, sympathetic response, and gender differences. In recent years, multiple metrics derived from pulse oximeter signals, heart rate, electroencephalogram, and ventilation signals have been described. This article will focus on those metrics that have been validated through external studies and possess greater clinical relevance.

Chemokine CCL19 and Its Receptors CCR7 and CCRL1 in Chronic Rhinosinusitis.

CCL19 has been shown to predict disease severity in COVID-19 and treatment response in rheumatoid arthritis. CCL19 can exert both pro- and anti-inflammatory effects and is elevated in chronic rhinosinusitis (CRS). However, its role in CRS remains unknown. This study sought to determine the transcriptional changes in CCL19, its receptors, and associated cytokines and their association with disease severity in CRS. A clinical database of control subjects and patients with CRS was examined. Lund-Kennedy, Lund-Mackay, Sinonasal Outcomes Test 22 (SNOT-22), and rhinosinusitis disability index (RSDI) scores were collected at enrollment. mRNA was extracted from sinonasal tissues and subjected to multiplex gene expression analysis. Gene transcript differences between patients with CRS and controls were compared and correlated with disease severity metrics. Immunohistochemical analyses of CCL19, CCR7, and CCRL1 were conducted to compare differences in protein expression between cohorts. A subgroup analysis was performed to compare transcriptional and protein expression difference between patients with (CRSwNP) and without (CRSsNP) nasal polyps and controls. Thirty-eight subjects (control group, n=7; CRS group, n=31) were included in this study. CCRL1 (p=0.0093) and CCR7 (p=0.017) levels were significantly elevated in CRS compared to those in controls. CCL19 (p=0.038) and CCR7 (p=0.0097) levels were elevated in CRSwNP and CCRL1 was elevated in CRSsNP (p=0.0004). CCR7 expression was significantly elevated in sinonasal epithelial cells in CRSwNP (p=0.04). CCL19 expression was positively correlated with TNFA expression (p<0.0002). CCL19 and CCR7 expression was positively correlated with SNOT-22 and RSDI scores (p<0.05). CCL19 and CCR7 may modulate TNF-α-driven pro-inflammatory signaling and contribute to increased disease severity in CRS. Mechanistic studies are required to further elucidate the role of CCRL1 in CRS.