OBJECTIVE: Epilepsy surgery needs predictive features that are easily implemented in clinical practice. Previous studies are limited by small sample sizes, lack of external validation, and complex computational approaches. We aimed to identify and validate visually stereo-electroencephalography (SEEG) features with the highest predictive value for surgical outcome, and assess the reliability of their visual extraction. METHODS: We included 177 patients with drug-resistant epilepsy who underwent SEEG-guided surgery at 4 epilepsy centers. We assessed the predictive performance of 10 SEEG features from various SEEG periods for surgical outcome, using the area under the receiver operating characteristic curve, and considering resected channels and surgical outcome as the gold standard. Findings were validated externally using balanced accuracy. Six experts, blinded to outcome, evaluated the visual reliability of the optimal feature using interrater reliability, percentage agreement (standard deviation ± SD) and Gwet's kappa (κ ± SD). RESULTS: The derivation cohort comprised 100 consecutive patients, each with at least 1-year of postoperative follow up (40% temporal lobe epilepsy; 42% Engel Ia). Spatial co-occurrence of gamma spikes and preictal spikes emerged as the optimal predictive feature of surgical outcome (area under the receiver operating characteristic curve 0.82). Applying the optimized threshold from the derivation cohort, external validation in 2 datasets showed similar performances (balanced accuracy 69.2% and 73.2%). Expert interrater reliability for gamma spikes (percentage agreement, 96% ± 2%; κ, 0.63 ± 0.16) and preictal spikes (percentage agreement, 92% ± 2%; κ, 0.65 ± 0.18) were substantial. INTERPRETATION: Spatial co-occurrence of gamma spikes and preictal spikes predicts surgical outcome. These visually identifiable features may reduce the burden of SEEG analysis by reducing analysis time, and improve outcome by guiding surgical resection margins. ANN NEUROL 2025;98:547-560.

• MeSH
• dospělí MeSH
• elektroencefalografie * metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• prediktivní hodnota testů MeSH
• refrakterní epilepsie * chirurgie   patofyziologie   MeSH
• reprodukovatelnost výsledků MeSH
• stereotaktické techniky MeSH
• výsledek terapie MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH

BACKGROUND & AIMS: Acute liver failure (ALF) is defined as rapid onset coagulopathy and encephalopathy in patients without a prior history of liver disease. We performed untargeted and targeted serum proteomics to delineate processes occurring in adult patients with ALF and to identify potential biomarkers. METHODS: Sera of 319 adult patients with ALF (∼50% acetaminophen [APAP]-related cases) were randomly selected from admission samples of the multicenter USA Acute Liver Failure Study Group consortium and subdivided into discovery/validation cohorts. They were analyzed using untargeted proteomics with mass spectroscopy and a serum cytokine profiling and compared with 30 healthy controls. The primary clinical outcome was 21-day transplant-free survival. Single-cell RNAseq data mapped biomarkers to cells of origin; functional enrichment analysis provided mechanistic insights. Novel prognostic scores were compared with the model for end-stage liver disease and ALFSG prognostic index scores. RESULTS: In the discovery cohort, 117 proteins differed between patients with ALF and healthy controls. There were 167 proteins associated with APAP-related ALF, with the majority being hepatocyte-derived. Three hepatocellular proteins (ALDOB, CAT, and PIGR) robustly and reproducibly discriminated APAP from non-APAP cases (AUROCs ∼0.9). In the discovery cohort, 37 proteins were related to 21-day outcome. The key processes associated with survival were acute-phase response and hepatocyte nuclear factor 1α signaling. SERPINA1 and LRG1 were the best individual discriminators of 21-day transplant-free survival in both cohorts. Two models of blood-based proteomic biomarkers outperformed the model for end-stage liver disease and ALFSG prognostic index and were reproduced in the validation cohort (AUROCs 0.83-0.86) for 21-day transplant-free survival. CONCLUSIONS: Proteomics and cytokine profiling identified new, reproducible biomarkers associated with APAP etiology and 21-day outcome. These biomarkers may improve prognostication and understanding of the etiopathogenesis of ALF but need to be independently validated. IMPACT AND IMPLICATIONS: Acute liver failure (ALF) is a sudden, and severe condition associated with high fatality. More sensitive and specific prognostic scores are urgently needed to facilitate decision-making regarding liver transplantation in patients with ALF. Our proteomic analysis uncovered marked differences between acetaminophen and non-acetaminophen-related ALF. The identification of routinely measurable biomarkers that are associated with 21-day transplant-free survival and the derivation of novel prognostic scores may facilitate clinical management as well as decisions for/against liver transplantation. Further studies are needed to quantify less abundant proteins. Although we used two cohorts, our findings still need to be independently and prospectively validated.

• Klíčová slova
• ALF subtyping, Acetaminophen, Acute liver injury, Proteomic profiling,
• Publikační typ
• časopisecké články MeSH

Preterm prelabour rupture of membranes (PPROM) complicated by intra-amniotic inflammation (IAI) represents a substantial proportion of preterm birth cases. Currently, IAI is frequently defined as amniotic fluid IL-6 concentration above 2,600 pg/mL. However, the amniotic fluid IL-6 concentration was never correlated with the global response of other proinflammatory proteins to the ongoing IAI. In this cross-sectional study, protein quantification was performed using mass spectrometry (MS) analysis followed by target quantification of selected proinflammatory proteins. Levels of amniotic fluid proteins determined by MS were put into the correlation with IL-6 concentration determined by electrochemiluminescence immunoassay method (ECLIA). In total, 925 proteins were efficiently quantified and differential expression analysis revealed 378 proteins upregulated towards IL-6 concentration above 10,000 pg/mL. Four proteins (LCN2, MMP8, MPO, and S100A12) were selected to verify the achieved results and IL-6 concentration of 10,000 pg/mL was determined as the cut-off value for global IAI response.

• MeSH
• biologické markery metabolismus   MeSH
• chorioamnionitida * metabolismus   MeSH
• dospělí MeSH
• interleukin-6 metabolismus   MeSH
• lidé MeSH
• plodová voda * metabolismus   MeSH
• předčasný odtok plodové vody * metabolismus   patologie   MeSH
• protein S100A12 metabolismus   MeSH
• průřezové studie MeSH
• těhotenství MeSH
• zánět * metabolismus   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• těhotenství MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• biologické markery MeSH
• IL6 protein, human MeSH Prohlížeč
• interleukin-6 MeSH
• protein S100A12 MeSH

Human nails have recently become a sample of interest for toxicological purposes. Multiple studies have proven the ability to detect various analytes within the keratin matrix of the nail. The analyte of interest in this study is fentanyl, a highly dangerous and abused drug in recent decades. In this proof-of-concept study, ATR-FTIR was combined with machine learning methods, which are effective in detecting and differentiating fentanyl in samples, to explore whether nail samples are distinguishable from individuals who have used fentanyl and those who have not. PLS-DA and SVM-DA prediction models were created for this study and had an overall accuracy rate of 84.8% and 81.4%, respectively. Notably, when classification was considered at the donor level-i.e., determining whether the donor of the nail sample was using fentanyl-all donors were correctly classified. These results show that ATR-FTIR spectroscopy in combination with machine learning can effectively differentiate donors who have used fentanyl and those who have not and that human nails are a viable sample matrix for toxicology.

• Klíčová slova
• ATR–FTIR, PLS-DA, SVM-DA, fentanyl, fingernails, machine learning, toenails,
• MeSH
• fentanyl * analýza   izolace a purifikace   MeSH
• lidé MeSH
• nehty * chemie   MeSH
• spektroskopie infračervená s Fourierovou transformací metody   MeSH
• strojové učení * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• fentanyl * MeSH

BACKGROUND AND AIMS: Circulating proenkephalin (PENK) is a stable endogenous polypeptide with fast response to glomerular dysfunction and tubular damage. This study examined the predictive value of PENK for renal outcomes and mortality in patients with acute coronary syndrome (ACS). METHODS: Proenkephalin was measured in plasma in a prospective multicentre ACS cohort from Switzerland (n = 4787) and in validation cohorts from the UK (n = 1141), Czechia (n = 927), and Germany (n = 220). A biomarker-enhanced risk score (KID-ACS score) for simultaneous prediction of in-hospital acute kidney injury (AKI) and 30-day mortality was derived and externally validated. RESULTS: On multivariable adjustment for established risk factors, circulating PENK remained associated with in-hospital AKI [per log2 increase: adjusted odds ratio 1.53, 95% confidence interval (CI) 1.13-2.09, P = .007] and 30-day mortality (adjusted hazard ratio 2.73, 95% CI 1.85-4.02, P < .001). The KID-ACS score integrates PENK and showed an area under the receiver operating characteristic curve (AUC) of .72 (95% CI .68-.76) for in-hospital AKI and .91 (95% CI .87-.95) for 30-day mortality in the derivation cohort. Upon external validation, KID-ACS achieved similarly high performance for in-hospital AKI (Zurich: AUC .73, 95% CI .70-.77; Czechia: AUC .75, 95% CI .68-.81; Germany: AUC .71, 95% CI .55-.87) and 30-day mortality (UK: AUC .87, 95% CI .83-.91; Czechia: AUC .91, 95% CI .87-.94; Germany: AUC .96, 95% CI .92-1.00), outperforming the contrast-associated AKI score and the Global Registry of Acute Coronary Events 2.0 score, respectively. CONCLUSIONS: Circulating PENK offers incremental value for predicting in-hospital AKI and mortality in ACS. The simple six-item KID-ACS risk score integrates PENK and provides a novel tool for simultaneous assessment of renal and mortality risk in patients with ACS.

• Klíčová slova
• Acute coronary syndromes, Acute kidney injury, Mortality risk, Proenkephalin, Risk prediction,
• MeSH
• akutní koronární syndrom * mortalita   krev   MeSH
• akutní poškození ledvin * MeSH
• biologické markery * krev   MeSH
• enkefaliny * krev   MeSH
• hodnocení rizik metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• prediktivní hodnota testů MeSH
• prospektivní studie MeSH
• proteinové prekurzory * krev   MeSH
• rizikové faktory MeSH
• senioři MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• Názvy látek
• biologické markery * MeSH
• enkefaliny * MeSH
• proenkephalin MeSH Prohlížeč
• proteinové prekurzory * MeSH

BACKGROUND AND OBJECTIVE: Stone size has traditionally been measured in one dimension. This is reflected in most of the literature and in the EAU guidelines. However, recent studies have shown that multidimensional measures provide better prediction of outcomes. METHODS: We performed a systematic review and meta-analysis of the prognostic accuracy of measures of stone size (PROSPERO reference CRD42022346967). We considered all studies reporting prognostic accuracy statistics on any intervention for kidney stones (extracorporeal shockwave lithotripsy [ESWL], ureterorenoscopy [URS], or percutaneous nephrolithotomy [PCNL]; Population) using multiplane measurements of stone burden (area in mm2 or volume in mm3; Intervention) in comparison to single-plane measurements of stone burden (size in mm; Intervention) for the study-defined stone-free rate (Outcome) in a PICO-framed question. We also assessed complication rates (overall and by Clavien-Dindo grade) and the operative time as secondary outcomes. Searches were made between 1970 and August 2023. We used the DeLong method to compare receiver operating characteristic (ROC) curves. KEY FINDINGS AND LIMITATIONS: Of 24 studies included in the review, 12 were eligible for comparative analysis with the DeLong test following meta-analysis of prognostic accuracy. For prediction of stone-free status, the area under the ROC curve (AUC) was significantly higher for stone volume than for stone size (0.71 vs 0.67; p < 0.001). Subanalyses confirmed this for ESWL and URS, but not for PCNL. For URS, the AUC was also significantly higher for stone area than for stone size (0.79 vs 0.77; p < 0.001). Throughout all analyses, there was no difference in AUC between stone area and stone volume. There was high risk of bias for all analyses apart from the URS subanalyses. CONCLUSIONS AND CLINICAL IMPLICATIONS: According to the limited data currently available, stone-free rates are predicted with significantly higher accuracy using multidimensional measures of stone burden in comparison to a single linear measurement. PATIENT SUMMARY: We reviewed different ways of measuring the size of stones in the kidney or urinary tract and compared their accuracy in predicting stone-free rates after treatment. We found that measurement of the stone area (2 dimensions) or stone volume (3 dimensions) is better than stone diameter (1 dimension) in predicting stone-free status after treatment.

• Klíčová slova
• Guidelines, Multidimensional measures, Predictor, Single linear measurement, Stone burden, Stone-free rate, Urolithiasis,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

PURPOSE: Incident delirium is a frequent complication among hospitalized older people with COVID-19, associated with increased length of hospital stay, higher morbidity and mortality rates. Although delirium is preventable with early detection, systematic assessment methods and predictive models are not universally defined, thus delirium is often underrated. In this study, we tested the role of the Multidimensional Prognostic Index (MPI), a prognostic tool based on Comprehensive Geriatric Assessment, to predict the risk of incident delirium. METHODS: Hospitalized older patients (≥ 65 years) with COVID-19 infection were enrolled (n = 502) from ten centers across Europe. At hospital admission, the MPI was administered to all the patients and two already validated delirium prediction models were computed (AWOL delirium risk-stratification score and Martinez model). Delirium occurrence during hospitalization was ascertained using the 4A's Test (4AT). Accuracy of the MPI and the other delirium predictive models was assessed through logistic regression models and the area under the curve (AUC). RESULTS: We analyzed 293 patients without delirium at hospital admission. Of them 33 (11.3%) developed delirium during hospitalization. Higher MPI score at admission (higher multidimensional frailty) was associated with higher risk of incident delirium also adjusting for the other delirium predictive models and COVID-19 severity (OR = 12.72, 95% CI = 2.11-76.86 for MPI-2 vs MPI-1, and OR = 33.44, 95% CI = 4.55-146.61 for MPI-3 vs MPI-1). The MPI showed good accuracy in predicting incident delirium (AUC = 0.71) also superior to AWOL tool, (AUC = 0.63) and Martinez model (AUC = 0.61) (p < 0.0001 for both comparisons). CONCLUSIONS: The MPI is a sensitive tool for early identification of older patients with incident delirium.

• Klíčová slova
• COVID-19, Comprehensive geriatric assessment, Delirium prediction, Multidimensional Prognostic Index, Older people,
• MeSH
• COVID-19 * komplikace   epidemiologie   diagnóza   MeSH
• delirium * diagnóza   epidemiologie   MeSH
• geriatrické hodnocení * metody   MeSH
• hodnocení rizik MeSH
• hospitalizace * statistika a číselné údaje   MeSH
• incidence MeSH
• lidé MeSH
• prognóza MeSH
• prospektivní studie MeSH
• rizikové faktory MeSH
• SARS-CoV-2 MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• Geografické názvy
• Evropa epidemiologie   MeSH

INTRODUCTION: The aim of the study was to identify predictive values of the soluble fms-like tyrosine kinase/placental growth factor (sFlt-1/PlGF) ratio and interleukin (IL)-6, assessed with a clinically available method in a large-volume biochemistry laboratory, in maternal blood, amniotic fluid, and umbilical cord blood for the presence of the placental lesions consistent with maternal vascular malperfusion (MVM) and acute histological chorioamnionitis (HCA), respectively. METHODS: This retrospective study included 92 women with preterm labor with intact membranes (PTL) delivered within 7 days of admission with gestational ages between 22+0 and 34+6 weeks. The sFlt-1/PlGF ratio and IL-6 were assessed in stored samples of maternal serum, amniotic fluid, and umbilical cord serum using Elecsys® sFlt-1, PlGF, and IL-6 immunoassays. RESULTS: Women with MVM had a higher sFlt-1/PlGF ratio in the maternal serum, compared to those without MVM (19.9 vs. 4.6; p < 0.0001), but not in the amniotic fluid or umbilical cord blood. A cut-off value of 8 for the sFlt-1/PlGF ratio in maternal serum was identified as optimal for predicting MVM in patients with PTL. Women with HCA had higher concentrations of IL-6 in maternal serum, compared to those without HCA (11.1 pg/mL vs. 8.4 pg/mL; p = 0.03), amniotic fluid (9,216 pg/mL vs. 1,423 pg/mL; p < 0.0001), and umbilical cord blood (20.7 pg/mL vs. 10.7 pg/mL, p = 0.002). Amniotic-fluid IL-6 showed the highest predictive value. A cut-off value of IL-6 concentration in the amniotic fluid of 5,000 pg/mL was found to be optimal for predicting HCA in PTL. CONCLUSION: Maternal serum sFlt-1/PlGF and amniotic fluid IL-6 concentrations can be used for liquid biopsy to predict placental lesions in women with PTL who deliver within 7 days.

• Klíčová slova
• Amniocentesis, Amniotic fluid, Angiogenic factors, Biomarker, Inflammation, Interleukin-6, PlGF, Preeclampsia, Pregnancy, Preterm birth, Preterm labor with intact membrane, Rapid point-of-care test, Receptor, VEGF, sFlt-1,
• MeSH
• biologické markery krev   MeSH
• chorioamnionitida krev   diagnóza   MeSH
• dospělí MeSH
• fetální krev metabolismus   MeSH
• interleukin-6 * krev   MeSH
• lidé MeSH
• placenta metabolismus   MeSH
• placentární růstový faktor * krev   MeSH
• plodová voda metabolismus   MeSH
• předčasná porodní činnost * krev   MeSH
• prediktivní hodnota testů * MeSH
• receptor 1 pro vaskulární endoteliální růstový faktor * krev   MeSH
• retrospektivní studie MeSH
• těhotenství MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• těhotenství MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• biologické markery MeSH
• FLT1 protein, human MeSH Prohlížeč
• IL6 protein, human MeSH Prohlížeč
• interleukin-6 * MeSH
• PGF protein, human MeSH Prohlížeč
• placentární růstový faktor * MeSH
• receptor 1 pro vaskulární endoteliální růstový faktor * MeSH

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder where pathophysiological changes begin decades before the onset of clinical symptoms. Analysis of brain atrophy patterns using structural MRI and multivariate data analysis are an effective tool in identifying patients with subjective cognitive decline (SCD) at higher risk of progression to AD dementia. Atrophy patterns obtained from models trained to classify advanced AD versus normal subjects, may not be optimal for subjects at an early stage, like SCD. In this study, we compared the accuracy of the SCD progression prediction using the 'severity index' generated using a standard classification model trained on patients with AD dementia versus a new model trained on β-amyloid (Aβ) positive patients with amnestic mild cognitive impairment (aMCI). METHODS: We used structural MRI data of 504 patients from the Swedish BioFINDER-1 study cohort (cognitively normal (CN), Aβ-negative = 220; SCD, Aβ positive and negative = 139; aMCI, Aβ-positive = 106; AD dementia = 39). We applied multivariate data analysis to create two predictive models trained to discriminate CN individuals from either individuals with Aβ positive aMCI or AD dementia. Models were applied to individuals with SCD to classify their atrophy patterns as either high-risk "disease-like" or low-risk "CN-like". Clinical trajectory and model accuracy were evaluated using 8 years of longitudinal data. RESULTS: In predicting progression from SCD to MCI or dementia, the standard, dementia-based model, reached 100% specificity but only 10.6% sensitivity, while the new, aMCI-based model, reached 72.3% sensitivity and 60.9% specificity. The aMCI-based model was superior in predicting progression from SCD to MCI or dementia, reaching a higher receiver operating characteristic area under curve (AUC = 0.72; P = 0.037) in comparison with the dementia-based model (AUC = 0.57). CONCLUSION: When predicting conversion from SCD to MCI or dementia using structural MRI data, prediction models based on individuals with milder levels of atrophy (i.e. aMCI) may offer superior clinical value compared to standard dementia-based models.

• Klíčová slova
• Alzheimer’s disease, Atrophy patterns, Multivariate analysis, Structural MRI, Subjective cognitive decline,
• MeSH
• Alzheimerova nemoc diagnostické zobrazování   patologie   MeSH
• atrofie * patologie   MeSH
• demence * diagnostické zobrazování   patologie   MeSH
• kognitivní dysfunkce * diagnostické zobrazování   patologie   diagnóza   MeSH
• kohortové studie MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie * metody   MeSH
• mozek * patologie   diagnostické zobrazování   MeSH
• neuropsychologické testy MeSH
• progrese nemoci * MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients' risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.

• Publikační typ
• časopisecké články MeSH