Early detection of malignant thyroid nodules is crucial for effective treatment, but traditional diagnostic methods face challenges such as variability in expert opinions and limited integration of advanced imaging techniques. This prospective cohort study investigates a novel multimodal approach, integrating traditional methods with advanced machine learning techniques. We studied 181 patients who underwent fine-needle aspiration (FNA) biopsy, each contributing one nodule, resulting in a total of 181 nodules for our analysis. Data collection included sex, age, and ultrasound imaging, which incorporated elastography. Features extracted from these images included Thyroid Imaging Reporting and Data System (TIRADS) scores, elastography parameters, and radiomic features. The pathological results based on the FNA biopsy, provided by the pathologists, served as our gold standard for nodule classification. Our methodology, termed ELTIRADS, combines these features with interpretable machine learning techniques. Performance evaluation showed that a Support Vector Machine (SVM) classifier using TIRADS, elastography data, and radiomic features achieved high accuracy (0.92), with sensitivity (0.89), specificity (0.94), precision (0.89), and F1 score (0.89). To enhance interpretability, we used hierarchical clustering, shapley additive explanations (SHAP), and partial dependence plots (PDP). This combined approach holds promise for enhancing the accuracy of thyroid nodule malignancy detection, thereby contributing to advancements in personalized and precision medicine in the field of thyroid cancer research.
- MeSH
- Adult MeSH
- Elasticity Imaging Techniques * methods MeSH
- Middle Aged MeSH
- Humans MeSH
- Thyroid Neoplasms diagnostic imaging classification pathology diagnosis MeSH
- Prospective Studies MeSH
- Radiomics MeSH
- Aged MeSH
- Thyroid Gland diagnostic imaging pathology MeSH
- Machine Learning * MeSH
- Support Vector Machine MeSH
- Biopsy, Fine-Needle MeSH
- Thyroid Nodule * diagnostic imaging pathology classification MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Glomerulonephritis (GN) encompasses a diverse group of immune-mediated diseases that damage the glomerular component of the nephron. While kidney biopsy remains the gold standard for diagnosis, it often fails to provide adequate insight into the underlying etiology of GN. Current classification systems have limited our understanding of the disease's pathophysiology and hinder the development of targeted therapies. Immunosuppressive treatments, such as glucocorticoids, calcineurin inhibitors, cyclophosphamide, and rituximab, remain the mainstay of therapy, though many patients fail to achieve remission or experience significant adverse effects. Moreover, the complex and multifactorial nature of GN pathogenesis calls for more refined therapeutic approaches. In recent years, multitarget therapies-combining different immunosuppressive agents targeting distinct immune pathways-have emerged as promising alternatives. Evidence suggests that multitarget therapy may offer superior outcomes compared to standard treatments. Despite early success, further studies are needed to optimize these regimens, reduce toxicity, and extend benefits to a broader range of GN patients. The development of personalized, biomarker-driven treatments, potentially leveraging innovative drug delivery systems and targeted biologics, holds promise for transforming GN care in the future.
- Publication type
- Journal Article MeSH
Chronická obstrukční plicní nemoc (CHOPN) je definována jako heterogenní onemocnění manifestující se respiračními příznaky. Podkladem jsou abnormality dýchacích cest a alveolů, které progredují a vedou k ireverzibilní obstrukční ventilační poruše. Léčba vychází z nové klasifikace CHOPN dle Globální iniciativy pro CHOPN 2023 (GOLD), kde jsou rozhodujícími kritérii symptomy onemocnění a exacerbace. Klíčovou léčbou jsou bronchodilatační léky v monoterapii, duální kombinaci či trojkombinaci. Kombinační bron- chodilatační léčba na základě rozdílných mechanismů zlepšuje stupeň dilatace bronchiálního stromu. Jedná se o kombinaci dlouhodobě působících β2-agonistů (LABA), dlouhodobě působících antagonistů muskarinových receptorů (LAMA) a případně inhalačního kortikosteroidu (IKS). Zařazení IKS směřuje především k snížení rizika a počtu exacerbací CHOPN.1 Trendem je kombinační léčba v jednom inhalačním systému, která zajišťuje lepší compliance pacien ta a i snazší inhalační techniku. Terapii je vhodné individualizovat podle konkrétních nálezů s cílem redukovat riziko exacerbací a zlepšit příznaky onemocnění s dopadem na zlepšení kvality života.
Chronic obstructive pulmonary disease (COPD) is defined as a heterogeneous disease manifesting with respiratory symptoms. Underlying abnormalities of the airways and alveoli progress and lead to irreversible obstructive ventilatory failure. Treatment is based on the new Global Initiative for COPD 2023 (GOLD) classification of COPD, where disease symptoms and exacerbations are the critical criteria. The key treatment is bronchodilators in monotherapy, dual combination or triple combination. Combination bronchodilator therapy improves the degree of bronchial tree dilatation based on different mechanisms. It is a combination of long-acting β2-agonists (LABAs), long- acting muscarinic receptor antagonists (LAMAs) and possibly an inhaled corticosteroid (ICS). The inclusion of ICS is primarily aimed at reducing the risk and number of COPD exacerbations. 1 The trend is towards combination therapy in a single inhalation system, which provides better patient compliance as well as easier inhalation technique. Therapy should be individualized according to specific findings in order to reduce the risk of exacerbations and improve disease symptoms with an impact on quality of life.
- MeSH
- Adrenergic beta-2 Receptor Agonists pharmacology therapeutic use MeSH
- Muscarinic Antagonists pharmacology therapeutic use MeSH
- Administration, Inhalation MeSH
- Bronchodilator Agents pharmacology therapeutic use MeSH
- Pulmonary Disease, Chronic Obstructive * diagnosis drug therapy classification physiopathology MeSH
- Eosinophils drug effects MeSH
- Adrenal Cortex Hormones therapeutic use MeSH
- Drug Therapy, Combination * MeSH
- Humans MeSH
- Disease Progression MeSH
- Respiratory Function Tests methods MeSH
- Risk Factors MeSH
- Practice Guidelines as Topic MeSH
- Check Tag
- Humans MeSH
Introduction: The deep inferior epigastric perforator (DIEP) flap is widely considered as the gold standard in breast reconstruction. The inset technique of the DIEP flap is crucial in determining the overall aesthetic outcome; however, to date no systematic review is available that comprehensively assesses the various techniques. Evaluation of topic: A systematic review was performed according to the PRISMA guidelines. The methodology is outlined within our published protocol (Prospero CRD42023449477). Included articles met a minimal criterion compromising of the intervention (DIEP free flap for breast reconstruction) and outcomes (aesthetic and clinical outcomes). Six articles were included in this review, with a total of 346 patients and a follow-up ranging from 6 months to 4 years. Four articles were of a prospective case series study design, one article was a randomized controlled trial, and one article was a case-control study. The risk of bias was assessed to be high in the case series, but low and moderate in the randomized controlled trial and case-control study respectively. Conclusion: Although limited by the quality of the evidence, the single aesthetic unit principle, dual-plane inset, elimination of the need for a skin paddle, appropriate flap positioning and rotation, and algorithmic in-setting may all improve the aesthetic outcome of DIEP free flaps.
- Keywords
- DIEP,
- MeSH
- Esthetics * MeSH
- Clinical Studies as Topic MeSH
- Humans MeSH
- Mammaplasty * methods adverse effects MeSH
- Statistics as Topic MeSH
- Check Tag
- Humans MeSH
- Publication type
- Systematic Review MeSH
Karcinom vaječníku je heterogenní onemocnění s celkově špatnou prognózou, jehož léčba by měla být nastavena s ohledem na kvalitu života a přežití pacientky. Základem správného nastavení léčebné strategie je kvalitní předoperační diagnostika a mezioborová spolupráce. V časném stadiu onemocnění představuje chirurgická léčba primárně léčebný a stagingový účel a v pokročilém stadiu onemocnění je chirurgická léčba primárně léčebnou modalitou se snahou dosáhnout optimální resekce. Chirurgická léčba by měla být koncentrována do onkogynekologických center se zkušenostmi s danou problematikou. U pacientek s pokročilým onemocněním je stále diskutováno provedení primární cytoredukční operace nebo intervalové cytoredukční operace, avšak stále platí, že cytoredukční chirurgická léčba je primární léčebná modalita, jejíž extenzi a radikalitu je vždy nutné zvážit individuálně.
Ovarian cancer is a heterogeneous group of diseases with an overall poor prognosis, whose treatment is necessary to manage well keeping in mind the quality of life and overall survival of the patient. Preoperative diagnosis and treatment in a multidisciplinary setting play an important role in setting the optimal treatment strategy. Surgical treatment in the early stages of ovarian cancer has a curative and staging purpose while in advanced stages it has primarily a goal of optimal resection of macroscopic tumors. Surgical treatment of ovarian cancer should be performed by experienced gynecological oncologists in centers with expertise. The discussion between primary cytoreductive surgery versus interval cytoreductive surgery in advanced ovarian cancer remains very active and alive, however surgical treatment remains the gold standard of treatment in ovarian cancer, the extension and radicality of which needs to be always individualized.
- MeSH
- Gynecologic Surgical Procedures methods MeSH
- Humans MeSH
- Ovarian Neoplasms * surgery MeSH
- Neoplasm Staging MeSH
- Fertility Preservation MeSH
- Check Tag
- Humans MeSH
- Female MeSH
- Publication type
- Review MeSH
Pathological pain subtypes can be classified as either neuropathic pain, caused by a somatosensory nervous system lesion or disease, or nociplastic pain, which develops without evidence of somatosensory system damage. Since there is no gold standard for the diagnosis of pathological pain subtypes, the proper classification of individual patients is currently an unmet challenge for clinicians. While the determination of specific biomarkers for each condition by current biochemical techniques is a complex task, the use of multimolecular techniques, such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), combined with artificial intelligence allows specific fingerprints for pathological pain-subtypes to be obtained, which may be useful for diagnosis. We analyzed whether the information provided by the mass spectra of serum samples of four experimental models of neuropathic and nociplastic pain combined with their functional pain outcomes could enable pathological pain subtype classification by artificial neural networks. As a result, a simple and innovative clinical decision support method has been developed that combines MALDI-TOF MS serum spectra and pain evaluation with its subsequent data analysis by artificial neural networks and allows the identification and classification of pathological pain subtypes in experimental models with a high level of specificity.
Chronická obstrukční plicní nemoc (CHOPN) se celosvětově dostává na třetí příčku úmrtnosti. Mezi rizikové faktory se řadí chronický nikotinismus, znečištěné životní či pracovní prostředí a genetická dispozice. Pro onemocnění je typická ireverzibilní obstrukční ventilační porucha, která je prokazatelná plicním funkčním vyšetřením. Typickými symptomy jsou progredující námahová dušnost a chronický kašel, které vedou k zhoršené kvalitě života. Časté jsou další komorbidity, které ovlivňují prognózu a průběh onemocnění. Léčba CHOPN je založena na aplikaci dlouhodobě působících bronchodilatačních přípravků. Závažným momentem jsou exacerbace CHOPN, které ovlivňují prognózu onemocnění. Nová doporučení GOLD 2023 přinášejí změnu v klasifikaci kategorií CHOPN s dopadem na optimální léčbu. Bronchodilatační kombinační léčba se doporučuje již v časných stadiích CHOPN, aby se zpomalil rychlý pokles ventilačních hodnot. Podstatné je i zvládnutí inhalační techniky. Komplexní přístup v managementu CHOPN je specifikován dle jednotlivých fenotypů onemocnění a zahrnuje i nefarmakologické přístupy.
Chronic obstructive pulmonary disease (COPD) ranks third in mortality worldwide. Risk factors include chronic nicotinism, polluted living or working environment and genetic disposition. The disease is characterised by irreversible obstructive ventilatory disorder, which is demonstrable by pulmonary function tests. Typical symptoms are progressive exertional dyspnoea and chronic cough, leading to impaired quality of life. Other comorbidities are common and affect the prognosis and course of the disease. Treatment of COPD is based on the application of long-acting bronchodilators. Exacerbations of COPD are an important factor affecting the prognosis of the disease. The new GOLD 2023 recommendations bring a change in the classification of COPD categories with implications for optimal treatment. Bronchodilator combination therapy is recommended already in the early stages of COPD to slow the rapid decline in ventilatory values. Mastery of inhalation technique is also essential. A comprehensive approach to COPD management is specified according to the individual disease phenotypes and includes also non-pharmacological approaches.
Ťažkou akcidentálnou hypotermiou sa označuje pokles telesnej teploty jadra ľudského tela pod 28 °C. Je charakterizovaná poruchou vedomia a malígnymi poruchami rytmu často vedúcimi k zastaveniu obehu. Avšak pre nízku využiteľnosť klasifikácie akcidentálnej hypotermie podľa telesnej teploty jadra v prednemocničnej starostlivosti je dnes revidovanou Švajčiarskou klasifikáciou hypotermie, stupnica AVPU, ktorá prioritizuje klinický stav pacienta. Ťažká hypotermia spadá do stavu „painful“ so zachovanými známkami života, alebo „unresponsive“ so zastavením obehu. Mimotelový obeh je dnes zlatým štandardom pri liečbe pacientov s ťažkou hypotermiou a prípadným zastavením obehu. Prezentujeme prípad pacienta s ťažkou hypotermiou (úvodná telesná teplota 22 °C v jadre) a zastavením obehu pri malígnom rytme jemnovlnej komorovej fibrilácie. Štandardne prebiahujúcim protokolom ALS (Advance Life Support) do napojenia na mimotelový obeh s ohrevom. Následným obnovením činnosti srdca po dosiahnutí telesnej teploty jadra pacienta reagujúcej na podaný defibrilačný výboj a kardiopulmonálnym zotavením pacienta bez neurologického deficitu. Cieľom článku je oboznámiť odbornú spoločnosť s protokolizovaným, integrovaným konceptom mimotelového ohrevu pacienta pomocou ECMO metodiky a poukázať na príležitosti a výzvy implementácie ECPR na Slovensku.
Severe accidental hypothermia refers to a drop in the core body temperature of the human body below 28 °C. It is characterized by impaired consciousness and malignant rhythm disorders often leading to circulatory arrest. However, due to the low applicability of the classification of accidental hypothermia according to core body temperature in pre-hospital health care, today the revised Swiss classification of hypothermia is the AVPU scale, which prioritizes the patient‘s clinical condition. Severe hypothermia falls into the state of „painful“ with preserved signs of life and or „unresponsive“ with cessation of circulation. Extracorporeal circulation is today the gold standard in the treatment of patients with severe hypothermia and possible circulatory arrest. The article presents the case of a patient with severe hypothermia (initial body temperature 22 °C in the core) and circulatory arrest in a malignant rhythm of ventricular fibrillation. By standard ALS protocol (Advance Life Support) until the connection to extracorporeal circulation with heating. By subsequent restoration of heart activity after reaching the patient‘s core body temperature responding to the delivered defibrillation shock and cardiopulmonary recovery of the patient without neurological deficit. The published article aim is to familiarize the professional society with the protocolized, integrated concept of extracorporeal heating of the patient using the ECMO methodology and to point out the opportunities and challenges of ECPR implementation in Slovakia.
INTRODUCTION: Recently, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) has published an update on the Global Strategy for Prevention, Diagnosis and Management of COPD, introducing a new classification of chronic obstructive pulmonary disease (COPD). Our aim was to assess the prognostic value of the new GOLD classification system in comparison with the previous GOLD classification systems (GOLD stages I-IV and GOLD groups A-D) and the BODE index. METHODS: We used the data of 784 patients with COPD from the Czech Multicenter Research Database of COPD. Patient survival was analyzed with the use of Kaplan-Meier estimate and Cox model of proportional risks. ROC analysis and area under curve (AUC) were used for comparison of GOLD classifications and BODE index. The analyses were performed with the use of software R (version 4.2.0). RESULTS: We analyzed data of 782 patients with complete data on GOLD classifications. The study population comprised 72.9% of men, 89.1% current or former smokers, with a mean age of 66.6 years, a mean BMI of 27.4 and a mean FEV1 44.9% of predicted. Probability of 5-year survival differed by GOLD classification. Application of the 2023 GOLD classification showed increased risk of death in group B (HR 1.82, 95% CI 1.14-2.92; p = 0.013) and in group E (HR 2.48, 95% CI 1.54-3.99; p˂0.001). The ROC analysis showed that the overall prognostic value of the 2023 GOLD classification was similarly weak to previous A-D GOLD classification schemes (AUCs 0.557-0.576) and was lower compared to the GOLD 1-4 system (AUC 0.614) and even lower when compared to the BODE index (AUC 0.715). CONCLUSION: We concluded that the new GOLD classification system has poor prognostic properties and that specific prediction tools (eg, the BODE index) should be used for mortality risk assessment.
- MeSH
- Pulmonary Disease, Chronic Obstructive * diagnosis therapy MeSH
- Risk Assessment MeSH
- Humans MeSH
- Prognosis MeSH
- Disease Progression MeSH
- Proportional Hazards Models MeSH
- Aged MeSH
- Severity of Illness Index MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Aged MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
Manual visual review, annotation and categorization of electroencephalography (EEG) is a time-consuming task that is often associated with human bias and requires trained electrophysiology experts with specific domain knowledge. This challenge is now compounded by development of measurement technologies and devices allowing large-scale heterogeneous, multi-channel recordings spanning multiple brain regions over days, weeks. Currently, supervised deep-learning techniques were shown to be an effective tool for analyzing big data sets, including EEG. However, the most significant caveat in training the supervised deep-learning models in a clinical research setting is the lack of adequate gold-standard annotations created by electrophysiology experts. Here, we propose a semi-supervised machine learning technique that utilizes deep-learning methods with a minimal amount of gold-standard labels. The method utilizes a temporal autoencoder for dimensionality reduction and a small number of the expert-provided gold-standard labels used for kernel density estimating (KDE) maps. We used data from electrophysiological intracranial EEG (iEEG) recordings acquired in two hospitals with different recording systems across 39 patients to validate the method. The method achieved iEEG classification (Pathologic vs. Normal vs. Artifacts) results with an area under the receiver operating characteristic (AUROC) scores of 0.862 ± 0.037, 0.879 ± 0.042, and area under the precision-recall curve (AUPRC) scores of 0.740 ± 0.740, 0.714 ± 0.042. This demonstrates that semi-supervised methods can provide acceptable results while requiring only 100 gold-standard data samples in each classification category. Subsequently, we deployed the technique to 12 novel patients in a pseudo-prospective framework for detecting Interictal epileptiform discharges (IEDs). We show that the proposed temporal autoencoder was able to generalize to novel patients while achieving AUROC of 0.877 ± 0.067 and AUPRC of 0.705 ± 0.154.
