Diagnostics最新文献

{"title":"Improving Automatic Coronary Stenosis Classification Using a Hybrid Metaheuristic with Diversity Control.","authors":"Miguel-Angel Gil-Rios, Ivan Cruz-Aceves, Arturo Hernandez-Aguirre, Martha-Alicia Hernandez-Gonzalez, Sergio-Eduardo Solorio-Meza","doi":"10.3390/diagnostics14212372","DOIUrl":"10.3390/diagnostics14212372","url":null,"abstract":"<p><p>This study proposes a novel Hybrid Metaheuristic with explicit diversity control, aimed at finding an optimal feature subset by thoroughly exploring the search space to prevent premature convergence. <b>Background/Objectives</b>: Unlike traditional evolutionary computing techniques, which only consider the best individuals in a population, the proposed strategy also considers the worst individuals under certain conditions. In consequence, feature selection frequencies tend to be more uniform, decreasing the probability of premature convergent results and local-optima solutions. <b>Methods</b>: An image database containing 608 images, evenly balanced between positive and negative coronary stenosis cases, was used for experiments. A total of 473 features, including intensity, texture, and morphological types, were extracted from the image bank. A Support Vector Machine was employed to classify positive and negative stenosis cases, with Accuracy and the Jaccard Coefficient used as performance metrics. <b>Results</b>: The proposed strategy achieved a classification rate of 0.92 for Accuracy and 0.85 for the Jaccard Coefficient, obtaining a subset of 16 features, which represents a discrimination rate of 0.97 from the 473 initial features. <b>Conclusions</b>: The Hybrid Metaheuristic with explicit diversity control improved the classification performance of coronary stenosis cases compared to previous literature. Based on the achieved results, the identified feature subset demonstrates potential for use in clinical practice, particularly in decision-support information systems.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545375/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Tube Type, Centrifugation Conditions, and Hemolysis on Plasma Circulating MicroRNAs.","authors":"Belén Pastor-Navarro, Marta Ramírez-Calvo, Isabel Gil-Aldea, Isabel Cortell-Granero, José A López-Guerrero","doi":"10.3390/diagnostics14212369","DOIUrl":"10.3390/diagnostics14212369","url":null,"abstract":"<p><strong>Background: </strong>In recent years, liquid biopsy has emerged as a promising tool for the diagnosis and prognosis of numerous diseases, including cancer. Among the biomolecules analyzed in liquid biopsies are plasma circulating microRNAs (miRNAs), small non-coding RNAs that have proven to be crucial in the regulation of gene expression and the pathobiology of different health conditions, making them useful as biomarkers. However, variations in preanalytical conditions during biospecimen collection and processing can affect the analytical results.</p><p><strong>Objectives: </strong>Herein, we determined how the type of collection tube, the number of centrifugations, and the degree of hemolysis can affect plasma circulating miRNA levels.</p><p><strong>Methods: </strong>A cohort of 11 healthy donors was included. Whole blood was collected and handled in three different conditions, and miRNAs levels were analyzed using quantitative RT-PCR.</p><p><strong>Results: </strong>Our results show that the differences in the type of preservative tubes influence hemolysis, measured as OD at 414 nm. Moreover, the number of centrifugations performed also altered miRNAs levels, increasing or decreasing them depending on the miRNA analyzed. Hence, our study shows that alterations in preanalytical conditions affect miRNAs levels, particularly the number of centrifugations and the type of collection tubes.</p><p><strong>Conclusions: </strong>In our work, we highlight the importance of registering the preanalytical conditions in a standardized way that might be considered when analytical results are obtained.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545111/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fetal Cortical Abnormalities Identified on Ultrasound.","authors":"Mara Rosner, Casey Reed, Aylin Tekes, Lindsey N Goodman, Angie C Jelin, Jena L Miller, Michelle L Kush, Ahmet A Baschat, Lisa R Sun, Jessica M DeMay, Kristin Baranano","doi":"10.3390/diagnostics14212371","DOIUrl":"10.3390/diagnostics14212371","url":null,"abstract":"<p><p>Normal neuronal cell differentiation and migration is critical to brain formation, is rapidly occurring as the fetal brain develops, and peaks at the time of the routine ultrasound anatomic survey. Abnormalities in cortical migration can signify an underlying genetic abnormality or other fetal injury that can have a profound impact on future development. Although cortical migration peaks at 20-22 weeks, cortical migration abnormalities are rarely diagnosed at the time of the anatomic survey. We describe three cases of fetal cortical abnormalities in which prenatal ultrasound imaging was instrumental to making a prompt and accurate diagnosis in the mid-trimester and for guiding clinical counseling.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545029/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Pneumoperitoneum on Mean Expiratory Flow Rate: Observational Insights from Patients with Healthy Lungs.","authors":"Lajos Bogár, Kamilla Domokos, Csaba Csontos, Balázs Sütő","doi":"10.3390/diagnostics14212375","DOIUrl":"10.3390/diagnostics14212375","url":null,"abstract":"<p><strong>Background/objectives: </strong>Surgical pneumoperitoneum (PP) significantly impacts volume-controlled ventilation, characterized by reduced respiratory compliance, elevated peak inspiratory pressure, and an accelerated expiratory phase due to an earlier onset of the airway pressure gradient. We hypothesized that this would shorten expiratory time, potentially increasing expiratory flow rate compared to pneumoperitoneum conditions. Calculations were performed to establish correlations between respiratory parameters and the mean increase in expiratory flow rate relative to baseline.</p><p><strong>Methods: </strong>Mechanical ventilation parameters were recorded for 67 patients both pre- and post-PP. Ventilator settings were standardized with a tidal volume of 6 mL/kg, a respiratory rate of 12 breaths per minute, a PEEP of 3 cmH₂O, an inspiratory time of 2 s, and an inspiratory-to-expiratory ratio of 1:1.5 (I:E).</p><p><strong>Results: </strong>The application of PP increased both peak inspiratory pressure and mean expiratory flow rate by 28% compared to baseline levels. The elevated intra-abdominal pressure of 20 cmH₂O resulted in a 34% reduction in dynamic chest compliance, a 50% increase in elastance, and a 20% increase in airway resistance. The mean expiratory flow rate increments relative to baseline showed a significant negative correlation with elastance (<i>p</i> = 0.0119) and a positive correlation with dynamic compliance (<i>p</i> = 0.0028) and resistance (<i>p</i> = 0.0240).</p><p><strong>Conclusions: </strong>A PP of 20 cmH₂O resulted in an increase in the mean expiratory flow rate in the conventional I:E ratio in the volume-ventilated mode. PP reduces lung and chest wall compliance by elevating the diaphragm, compressing the thoracic cavity, and increasing airway pressures. Consequently, the lungs and chest wall stiffen, requiring greater ventilatory effort and accelerating expiratory flow due to increased airway resistance and altered pulmonary mechanics. Prolonging the inspiratory phase through I:E ratio adjustment helps maintain peak inspiratory pressures closer to baseline levels, and this method enhances the safety and efficacy of mechanical ventilation in maintaining optimal respiratory function during laparoscopic surgery.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11544817/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abbreviated Multiparametric MR Solution (the \"Liver Triple Screen\"), the Future of Non-Invasive MR Quantification of Liver Fat, Iron, and Fibrosis.","authors":"Gavin Low, Ryan K W Chee, Yu Jun Wong, Puneeta Tandon, Florin Manolea, Stephanie Locas, Craig Ferguson, Wendy Tu, Mitchell P Wilson","doi":"10.3390/diagnostics14212373","DOIUrl":"10.3390/diagnostics14212373","url":null,"abstract":"<p><p><b>Background/Objectives:</b> To review the findings of a multiparametric MRI (the \"liver triple screen\") solution for the non-invasive assessment of liver fat, iron, and fibrosis in patients with chronic liver disease (CLD). <b>Methods:</b> A retrospective evaluation of all consecutive triple screen MRI cases was performed at our institution over the last 32 months. Relevant clinical, laboratory, and radiologic data were analyzed using descriptive statistics. <b>Results:</b> There were 268 patients, including 162 (60.4%) males and 106 (39.6%) females. The mean age was 54 ± 15.2 years (range 16 to 71 years). The most common cause of CLD was metabolic dysfunction-associated steatotic liver disease (MASLD) at 45.5%. The most common referring physician group was Gastroenterology at 62.7%. In 23.9% of cases, the reason for ordering the MRI was a pre-existing failed or unreliable US elastography. There were 17 cases (6.3%) of MRI technical failure. Our analysis revealed liver fibrosis in 66% of patients, steatosis in 68.3%, and iron overload in 22.1%. Combined fibrosis and steatosis were seen in 28.7%, steatosis and iron overload in 16.8%, fibrosis and iron overload in 6%, and combined fibrosis, steatosis, and iron overload in 4.1%. A positive MEFIB index, a predictor of liver-related outcomes, was found in 57 (27.5%) of 207 patients. Incidental findings were found in 14.9% of all MRIs. <b>Conclusions:</b> The liver triple screen MRI is an effective tool for evaluating liver fat, iron, and fibrosis in patients with CLD. It provides essential clinical information and can help identify MASLD patients at risk for liver-related outcomes.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545674/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142615226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Histopathological Evaluation of Somatostatin Receptor 2 Expression in Myocarditis-Rationale for the Diagnostic Use of Somatostatin Receptor Imaging.","authors":"Christian L Polte, Kittichate Visuttijai, Kristina Vukusic, Joakim Sandstedt, Mikael Sandstedt, Emanuele Bobbio, Marie Björkenstam, Kristjan Karason, Niklas Bergh, Entela Bollano, Anders Oldfors","doi":"10.3390/diagnostics14212374","DOIUrl":"10.3390/diagnostics14212374","url":null,"abstract":"<p><strong>Background/objectives: </strong>Myocarditis is an inflammatory disease of the myocardium and remains to this day a challenging diagnosis. A promising novel imaging method uses the expression of somatostatin receptors (SSTRs) on inflammatory cells to visualize myocardial inflammation. However, little is known about the histopathological correlate of SSTR imaging in different forms of myocarditis.</p><p><strong>Methods: </strong>In the present retrospective histopathological study, we systematically analysed the expression of SSTR subtype 2 (SSTR2) on inflammatory cells of 33 patients with biopsy- or explant-proven myocarditis (lymphocytic myocarditis (<i>n</i> = 5), giant-cell myocarditis (<i>n</i> = 11), and cardiac sarcoidosis (<i>n</i> = 17)), and in eight controls (multi-organ donors) without signs of myocardial inflammation and/or scars.</p><p><strong>Results: </strong>In all patients, immunohistochemical staining for SSTR2 was positive in areas with CD68-positive macrophages and multinucleated giant cells. Staining for SSTR2 was most prominent in the presence of multinucleated giant cells. The colocalization of both SSTR2 and CD68 on the same cell could be confirmed using immunofluorescence microscopy. Western blotting confirmed the upregulated expression of SSTR2 in cases of granulomatous inflammation (sarcoidosis) of the skeletal and heart muscle, in comparison with controls.</p><p><strong>Conclusions: </strong>In conclusion, our findings demonstrate the expression of SSTR2 on the protein level on CD68-positive macrophages and multinucleated giant cells in various forms of myocarditis, which provides a clear rationale for the diagnostic use of SSTR imaging in this patient group.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545006/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Feature-Fusion Technique-Based Alzheimer's Disease Classification Using Magnetic Resonance Imaging.","authors":"Abdul Rahaman Wahab Sait, Ramprasad Nagaraj","doi":"10.3390/diagnostics14212363","DOIUrl":"10.3390/diagnostics14212363","url":null,"abstract":"<p><strong>Background: </strong>Early identification of Alzheimer's disease (AD) is essential for optimal treatment and management. Deep learning (DL) technologies, including convolutional neural networks (CNNs) and vision transformers (ViTs) can provide promising outcomes in AD diagnosis. However, these technologies lack model interpretability and demand substantial computational resources, causing challenges in the resource-constrained environment. Hybrid ViTs can outperform individual ViTs by visualizing key features with limited computational power. This synergy enhances feature extraction and promotes model interpretability.</p><p><strong>Objectives: </strong>Thus, the authors present an innovative model for classifying AD using MRI images with limited computational resources.</p><p><strong>Methods: </strong>The authors improved the AD feature-extraction process by modifying the existing ViTs. A CatBoost-based classifier was used to classify the extracted features into multiple classes.</p><p><strong>Results: </strong>The proposed model was generalized using the OASIS dataset. The model obtained an exceptional classification accuracy of 98.8% with a minimal loss of 0.12.</p><p><strong>Conclusions: </strong>The findings highlight the potential of the proposed AD classification model in providing an interpretable and resource-efficient solution for healthcare centers. To improve model robustness and applicability, subsequent research can include genetic and clinical data.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545033/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association Between Obesity, Chronic Inflammation, Metabolic Disorders and Mood Disorders Among Patients up to 12 Months After Hospitalization for SARS-CoV-2.","authors":"Kamila Rachubińska, Alicja Mińko, Iwona Rotter, Joanna Sołek-Pastuszka, Przemysław Ustianowski, Karolina Skonieczna-Żydecka, Elżbieta Grochans","doi":"10.3390/diagnostics14212357","DOIUrl":"10.3390/diagnostics14212357","url":null,"abstract":"<p><strong>Background/objectives: </strong>The relationship between BMI, inflammation, and mental health is complex. A high BMI, especially obesity, is associated with chronic inflammation, which can lead to mental disorders such as depression. Inflammatory cytokines affect neurotransmitters and the stress axis, worsening mental health. Obesity and mental disorders can mutually reinforce each other. New findings show that inflammation can lead to neurobiological changes, and the gut microbiota may play a key role. Obesity has been implicated as a factor in the high mortality and duration of influenza-like illnesses, even in people who do not have other chronic diseases that may increase the risk of complications. The aim of this study was to determine the associations between BMI and chronic inflammation, metabolic disorders, depression, and anxiety in patients hospitalized with COVID-19 up to 12 months after hospitalization.</p><p><strong>Methods: </strong>The study included 248 participants previously hospitalized for SARS-CoV-2 infection up to 12 months after hospitalization. The study was conducted in a multistage design using a diagnostic survey, anthropometric measurements, and laboratory methods.</p><p><strong>Results: </strong>A statistically significantly higher BDI-II score was observed among women. Statistical analysis showed a statistically significant higher GAD-7 score among women and those over 75 years of age.</p><p><strong>Conclusions: </strong>Higher BMI among subjects is often associated with elevated values of inflammatory markers and immune cells, such as WBC, neutrophils, monocytes, and CRP, as well as higher blood glucose levels. These associations may be related to the chronic inflammation and metabolic disorders that often accompany obesity. Lymphocytes and eosinophils may show more varied relationships depending on individual factors and specific health conditions. It is therefore important to continue research in this area.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11544786/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning Models for Anatomical Location Classification in Esophagogastroduodenoscopy Images and Videos: A Quantitative Evaluation with Clinical Data.","authors":"Seong Min Kang, Gi Pyo Lee, Young Jae Kim, Kyoung Oh Kim, Kwang Gi Kim","doi":"10.3390/diagnostics14212360","DOIUrl":"10.3390/diagnostics14212360","url":null,"abstract":"<p><strong>Background/objectives: </strong>During gastroscopy, accurately identifying the anatomical locations of the gastrointestinal tract is crucial for developing diagnostic aids, such as lesion localization and blind spot alerts.</p><p><strong>Methods: </strong>This study utilized a dataset of 31,403 still images from 1000 patients with normal findings to annotate the anatomical locations within the images and develop a classification model. The model was then applied to videos of 20 esophagogastroduodenoscopy procedures, where it was validated for real-time location prediction. To address instability of predictions caused by independent frame-by-frame assessment, we implemented a hard-voting-based post-processing algorithm that aggregates results from seven consecutive frames, improving the overall accuracy.</p><p><strong>Results: </strong>Among the tested models, InceptionV3 demonstrated superior performance for still images, achieving an F1 score of 79.79%, precision of 80.57%, and recall of 80.08%. For video data, the InceptionResNetV2 model performed best, achieving an F1 score of 61.37%, precision of 73.08%, and recall of 57.21%. These results indicate that the deep learning models not only achieved high accuracy in position recognition for still images but also performed well on video data. Additionally, the post-processing algorithm effectively stabilized the predictions, highlighting its potential for real-time endoscopic applications.</p><p><strong>Conclusions: </strong>This study demonstrates the feasibility of predicting the gastrointestinal tract locations during gastroscopy and suggests a promising path for the development of advanced diagnostic aids to assist clinicians. Furthermore, the location information generated by this model can be leveraged in future technologies, such as automated report generation and supporting follow-up examinations for patients.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545494/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proenkephalin A 119-159 in Perioperative and Intensive Care-A Promising Biomarker or Merely Another Option?","authors":"Paulina Walczak-Wieteska, Konrad Zuzda, Jolanta Małyszko, Paweł Andruszkiewicz","doi":"10.3390/diagnostics14212364","DOIUrl":"10.3390/diagnostics14212364","url":null,"abstract":"<p><p>Acute kidney injury (AKI) is a severe and prevalent syndrome, primarily observed in intensive care units (ICUs) and perioperative settings. The discovery of a new biomarker for kidney function and injury, capable of overcoming the limitations of traditional markers, has the potential to improve the diagnosis and management of AKI. Proenkephalin A 119-159 (PENK) has emerged as a novel biomarker for AKI and has been validated in various clinical settings. It has demonstrated a faster response to AKI compared to creatinine and has been shown to predict successful weaning from renal replacement therapy in the ICU. PENK has also shown promise as an AKI biomarker in perioperative patients. Additionally, PENK has been proven to be effective in estimating mortality and morbidity in patients undergoing cardiac surgery, and those with traumatic brain injury or ischemic stroke. Incorporating PENK into a novel estimation of the glomerular filtration rate, referred to as the PENK-Crea equation, has yielded promising results.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"14 21","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545452/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142615914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}