OBJECTIVES: To prospectively validate the diagnostic performance of a non-invasive point-of-care tool (Rapid IAI System), including vaginal alpha-fetoprotein and interleukin-6, to predict the occurrence of intra-amniotic inflammation in a Spanish cohort of patients admitted with a diagnosis of preterm labor and intact membranes. METHODS: From 2017 to 2022, we prospectively evaluated a cohort of pregnant women diagnosed with preterm labor and intact membranes admitted below 34+0 weeks who underwent amniocentesis to rule-in/out intra-amniotic infection and/or inflammation. Vaginal sampling was performed at the time of amniocentesis or within 24-48 h. Amniotic fluid IL-6, vaginal alpha-fetoprotein and vaginal IL-6 concentrations were measured using a point-of-care tool provided by Hologic Inc., "Rapid IAI System". We defined intra-amniotic inflammation when amniotic fluid IL-6 values were greater than 11.3 ng/mL. During recruitment, clinicians were blinded to the results of the point-of-care tool. The original prediction model proposed by Hologic Inc. to predict intra-amniotic inflammation was validated in this cohort of patients. RESULTS: We included 151 patients diagnosed with preterm labor and intact membranes. Among these, 29 (19.2 %) had intra-amniotic inflammation. The algorithm including vaginal IL-6 and alpha-fetoprotein showed an area under curve to predict intra-amniotic inflammation of 80.3 % (±5.3 %) with a sensitivity of 72.4 %, specificity of 84.6 %, positive predictive valuve (PPV) of 52.5 %, negative predictive value (NPV) of 92.9 %, and a positive likelihood ratio (LR+) of 4.6 and negative likelihood ratio (LR-) of 0.33. CONCLUSIONS: External validation of a non-invasive rapid point-of-care tool, including vaginal alpha-fetoprotein and IL-6, showed very good diagnostic performance for predicting the absence of intra-amniotic inflammation in women with preterm labor and intact membranes.
- MeSH
- alpha-Fetoproteins * analysis metabolism MeSH
- Amniocentesis methods MeSH
- Chorioamnionitis * diagnosis MeSH
- Adult MeSH
- Risk Assessment methods MeSH
- Interleukin-6 * analysis blood metabolism MeSH
- Humans MeSH
- Amniotic Fluid * metabolism chemistry MeSH
- Point-of-Care Testing MeSH
- Obstetric Labor, Premature * diagnosis MeSH
- Predictive Value of Tests MeSH
- Prospective Studies MeSH
- Pregnancy MeSH
- Vagina metabolism MeSH
- Point-of-Care Systems MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Validation Study MeSH
INTRODUCTION: The objective of this study was to assess the relationship between longitudinal changes in the uterine Doppler velocimetry and the maternal profile of angiogenic factors in the third trimester and to assess their ability to predict term preeclampsia (PE). METHODS: A cohort of low-risk pregnant women was scheduled for a uterine Doppler evaluation and measurement of the circulating levels of angiogenic factors at ∼30 and ∼36 weeks. The performance of both parameters and their change over time in predicting term PE was evaluated. RESULTS: A total of 1,191 women were analyzed, of which 28 (2.4%) women developed term PE. At ∼30 weeks, a model including the sFlt-1/PlGF (fms-like tyrosine kinase-1/placental growth factor) ratio and the uterine Doppler explained 16.2% of the uncertainty of developing term PE, while at ∼36 weeks, the same variables explained 25.2% [p < 0.001]. The longitudinal changes of both predictors had an R2 of 26.8%, which was not different from that of the ∼36 weeks evaluation [p = 0.45]. The area under the curve (AUC) of the ∼36 weeks ratio was significantly higher than at ∼30 weeks (0.86 [0.77-0.94] vs. 0.81 [0.73-0.9]; p = 0.043). The AUC of the longitudinal change of the ratio (0.85 [0.77-0.94]) did not differ from that of at ∼36 weeks (p = 0.82). At ∼36 weeks, for a 10% of false positives, the ratio had a detection rate of 71.4%. CONCLUSION: A cross-sectional measurement of the sFlt-1/PlGF ratio outperforms uterine Doppler in predicting term PE. The combination of both markers does not improve such prediction, nor the evaluation of the longitudinal changes between weeks.
- MeSH
- Adult MeSH
- Humans MeSH
- Placental Circulation physiology MeSH
- Placenta Growth Factor * blood MeSH
- Area Under Curve MeSH
- Predictive Value of Tests MeSH
- Pre-Eclampsia * blood diagnostic imaging MeSH
- Vascular Endothelial Growth Factor Receptor-1 * blood MeSH
- Rheology * methods statistics & numerical data MeSH
- Reproducibility of Results MeSH
- Blood Flow Velocity physiology MeSH
- Pregnancy MeSH
- Pregnancy Trimester, Third * blood physiology MeSH
- Ultrasonography, Doppler methods statistics & numerical data MeSH
- Ultrasonography, Prenatal * methods statistics & numerical data MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Randomized Controlled Trial MeSH
- Comparative Study MeSH
PURPOSE: The aim of this study was to develop a simple, robust, and easy-to-use calibration procedure for correcting misalignments in rosette MRI k-space sampling, with the objective of producing images with minimal artifacts. METHODS: Quick automatic calibration scans were proposed for the beginning of the measurement to collect information on the time course of the rosette acquisition trajectory. A two-parameter model was devised to match the measured time-varying readout gradient delays and approximate the actual rosette sampling trajectory. The proposed calibration approach was implemented, and performance assessment was conducted on both phantoms and human subjects. RESULTS: The fidelity of phantom and in vivo images exhibited significant improvement compared with uncorrected rosette data. The two-parameter calibration approach also demonstrated enhanced precision and reliability, as evidenced by quantitative T2*$$ {\mathrm{T}}_2^{\ast } $$ relaxometry analyses. CONCLUSION: Adequate correction of data sampling is a crucial step in rosette MRI. The presented experimental results underscore the robustness, ease of implementation, and suitability for routine experimental use of the proposed two-parameter rosette trajectory calibration approach.
- MeSH
- Algorithms * MeSH
- Artifacts * MeSH
- Phantoms, Imaging * MeSH
- Calibration MeSH
- Humans MeSH
- Magnetic Resonance Imaging * methods MeSH
- Brain diagnostic imaging MeSH
- Image Processing, Computer-Assisted * methods MeSH
- Reproducibility of Results MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
OBJECTIVES: To develop a gadolinium-free MRI-based diagnosis prediction decision tree (DPDT) for adult-type diffuse gliomas and to assess the added value of gadolinium-based contrast agent (GBCA) enhanced images. MATERIALS AND METHODS: This study included preoperative grade 2-4 adult-type diffuse gliomas (World Health Organization 2021) scanned between 2010 and 2021. The DPDT, incorporating eleven GBCA-free MRI features, was developed using 18% of the dataset based on consensus readings. Diagnosis predictions involved grade (grade 2 vs. grade 3/4) and molecular status (isocitrate dehydrogenase (IDH) and 1p/19q). GBCA-free diagnosis was predicted using DPDT, while GBCA-enhanced diagnosis included post-contrast images. The accuracy of these predictions was assessed by three raters with varying experience levels in neuroradiology using the test dataset. Agreement analyses were applied to evaluate the prediction performance/reproducibility. RESULTS: The test dataset included 303 patients (age (SD): 56.7 (14.2) years, female/male: 114/189, low-grade/high-grade: 54/249, IDH-mutant/wildtype: 82/221, 1p/19q-codeleted/intact: 34/269). Per-rater GBCA-free predictions achieved ≥ 0.85 (95%-CI: 0.80-0.88) accuracy for grade and ≥ 0.75 (95%-CI: 0.70-0.80) for molecular status, while GBCA-enhanced predictions reached ≥ 0.87 (95%-CI: 0.82-0.90) and ≥ 0.77 (95%-CI: 0.71-0.81), respectively. No accuracy difference was observed between GBCA-free and GBCA-enhanced predictions. Group inter-rater agreement was moderate for GBCA-free (0.56 (95%-CI: 0.46-0.66)) and substantial for GBCA-enhanced grade prediction (0.68 (95%-CI: 0.58-0.78), p = 0.008), while substantial for both GBCA-free (0.75 (95%-CI: 0.69-0.80) and GBCA-enhanced (0.77 (95%-CI: 0.71-0.82), p = 0.51) molecular status predictions. CONCLUSION: The proposed GBCA-free diagnosis prediction decision tree performed well, with GBCA-enhanced images adding little to the preoperative diagnostic accuracy of adult-type diffuse gliomas. KEY POINTS: Question Given health and environmental concerns, is there a gadolinium-free imaging protocol to preoperatively evaluate gliomas comparable to the gadolinium-enhanced standard practice? Findings The proposed gadolinium-free diagnosis prediction decision tree for adult-type diffuse gliomas performed well, and gadolinium-enhanced MRI demonstrated only limited improvement in diagnostic accuracy. Clinical relevance Even inexperienced raters effectively classified adult-type diffuse gliomas using the gadolinium-free diagnosis prediction decision tree, which, until further validation, can be used alongside gadolinium-enhanced images to respect standard practice, despite this study showing that gadolinium-enhanced images hardly improved diagnostic accuracy.
- MeSH
- Adult MeSH
- Gadolinium MeSH
- Glioma * diagnostic imaging MeSH
- Contrast Media * MeSH
- Middle Aged MeSH
- Humans MeSH
- Magnetic Resonance Imaging * methods MeSH
- Brain Neoplasms * diagnostic imaging MeSH
- Predictive Value of Tests MeSH
- Reproducibility of Results MeSH
- Decision Trees * MeSH
- Aged MeSH
- Neoplasm Grading * MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
In this study, lactic acid bacteria (LAB) isolation from fermented foods and molecular identification using magnetic bead technology were performed. And then exopolysaccharide (EPS) production possibility was tested in agar medium, and the positive ones were selected for the next step. The bacteria that could produce higher carbohydrate level were grown in MRS medium fortified with whey and pumpkin waste. In our study, 19 different LAB species were identified from fermented products collected from different places in Hatay (Türkiye) province. In molecular identification, universal primer pairs, p806R/p8FPL, and PEU7/DG74 were used for PCR amplification. After that, PCR products purified using paramagnetic bead technology were sequenced by the Sanger sequencing method. The dominant species, 23.8% of the isolates, were identified as Lactiplantibacillus plantarum. As a technological property of LAB, exopolysaccharide production capability of forty-two LAB isolate was tested in agar medium, and after eleven isolates were selected as positive. Two LAB (Latilactobacillus curvatus SHA2-3B and Loigolactobacillus coryniformis SHA6-3B) had higher EPS production capability when they were grown in MRS broth fortified with pumpkin waste and whey. The highest EPS content (1750 mg/L glucose equivalent) was determined in Loigolactobacillus coryniformis SHA6-3B grown in MRS broth fortified with 10% pumpkin waste. Besides the produced EPS samples were validated with FTIR and SEM methods.
- MeSH
- Polysaccharides, Bacterial * biosynthesis metabolism MeSH
- Cucurbita microbiology MeSH
- Fermentation MeSH
- Fermented Foods * microbiology MeSH
- Phylogeny MeSH
- Culture Media chemistry MeSH
- Lactobacillales * isolation & purification classification genetics metabolism MeSH
- Waste Products * analysis MeSH
- Food Microbiology * MeSH
- RNA, Ribosomal, 16S genetics MeSH
- Whey MeSH
- Publication type
- Journal Article MeSH
The UPPS-P Impulsive Behavior Model and the various psychometric instruments developed and validated based on this model are well established in clinical and research settings. However, evidence regarding the psychometric validity, reliability, and equivalence across multiple countries of residence, languages, or gender identities, including gender-diverse individuals, is lacking to date. Using data from the International Sex Survey (N = 82,243), confirmatory factor analyses and measurement invariance analyses were performed on the preestablished five-factor structure of the 20-item short version of the UPPS-P Impulsive Behavior Scale to examine whether (a) psychometric validity and reliability and (b) psychometric equivalence hold across 34 country-of-residence-related, 22 language-related, and three gender-identity-related groups. The results of the present study extend the latter psychometric instrument's well-established relevance to 26 countries, 13 languages, and three gender identities. Most notably, psychometric validity and reliability were evidenced across nine novel translations included in the present study (i.e., Croatian, English, German, Hebrew, Korean, Macedonian, Polish, Portuguese-Portugal, and Spanish-Latin American) and psychometric equivalence was evidenced across all three gender identities included in the present study (i.e., women, men, and gender-diverse individuals).
- MeSH
- Adult MeSH
- Factor Analysis, Statistical MeSH
- Gender Identity * MeSH
- Impulsive Behavior * MeSH
- Language MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Surveys and Questionnaires MeSH
- Psychometrics MeSH
- Reproducibility of Results MeSH
- Cross-Cultural Comparison MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Validation Study MeSH
Cognitive flexibility (CF) is the ability to adapt cognitive strategies according to the changing environment. The deficit in CF has often been linked to various neurological and psychiatric disorders including schizophrenia. However, the operationalization and assessment of CF have not been unified and the current research suggests that the available instruments measure different aspects of CF. The main objective of the present study was to compare three frequently used neuropsychological measures of CF-Wisconsin Card Sorting Test (WCST), Trail Making Test (TMT) and Stroop Color and Word Test (SCWT) in a population of patients (N = 220) with first-episode schizophrenia spectrum disorders in order to evaluate their convergent validity. The hypothesis of an underlying latent construct was tested via a confirmatory factor analysis. We used a one-factor CF model with scores from WCST, SCWT and TMT as observed variables. The established model showed a good fit to the data (χ2 = 1.67, p = 0.43, SRMR = 0.02, RMSEA = 0.0, CFI = 1.00). The highest factor loading was found in WCST as CF explained most of the variance in this neuropsychological measure compared to the other instruments. On the other hand, a TMT ratio index and a SCWT interference demonstrated lowest loadings in the model. The findings suggest that not all the frequently used measures share an underlying factor of CF or may capture different aspects of this construct.
- MeSH
- Adult MeSH
- Executive Function * physiology MeSH
- Factor Analysis, Statistical MeSH
- Cognitive Dysfunction * etiology diagnosis physiopathology MeSH
- Cognitive Flexibility MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Neuropsychological Tests * standards MeSH
- Psychometrics MeSH
- Schizophrenic Psychology * MeSH
- Schizophrenia * complications physiopathology MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
In vitro dissolution testing is commonly performed to ensure that oral solid dosage medicines are of high quality and will achieve their targeted in vivo performance. However, this testing is time and material consuming. Therefore, pharmaceutical companies have been developing predictive dissolution models (PDMs) for drug product release based on fast at- and/or on-line measurements, including real-time release testing of dissolution (RTRT-D). Recently, PDMs have seen acceptance by major regulatory bodies as release tests for the dissolution critical quality attribute. In this paper, several methodologies are described to develop and validate a fit-for-purpose model, then to implement it as a surrogate release test for dissolution. These approaches are further exemplified by real-life case studies, which demonstrate that PDMs for release are not only viable but more sustainable than in vitro dissolution testing and can significantly accelerate drug product release. The rise of continuous manufacturing within the pharmaceutical industry further favors the implementation of real-time release testing. Therefore, a steep uptake of PDMs for release is expected once this methodology is globally accepted. To that end, it is advantageous for global regulators and pharmaceutical innovators to coalesce around a harmonized set of expectations for development, validation, implementation, and lifecycle of PDMs as part of drug product release testing.
With the incorporation of effective therapies for myelofibrosis (MF), accurately predicting outcomes after allogeneic hematopoietic cell transplantation (allo-HCT) is crucial for determining the optimal timing for this procedure. Using data from 5183 patients with MF who underwent first allo-HCT between 2005 and 2020 at European Society for Blood and Marrow Transplantation centers, we examined different machine learning (ML) models to predict overall survival after transplant. The cohort was divided into a training set (75%) and a test set (25%) for model validation. A random survival forests (RSF) model was developed based on 10 variables: patient age, comorbidity index, performance status, blood blasts, hemoglobin, leukocytes, platelets, donor type, conditioning intensity, and graft-versus-host disease prophylaxis. Its performance was compared with a 4-level Cox regression-based score and other ML-based models derived from the same data set, and with the Center for International Blood and Marrow Transplant Research score. The RSF outperformed all comparators, achieving better concordance indices across both primary and postessential thrombocythemia/polycythemia vera MF subgroups. The robustness and generalizability of the RSF model was confirmed by Akaike information criterion and time-dependent receiver operating characteristic area under the curve metrics in both sets. Although all models were prognostic for nonrelapse mortality, the RSF provided better curve separation, effectively identifying a high-risk group comprising 25% of patients. In conclusion, ML enhances risk stratification in patients with MF undergoing allo-HCT, paving the way for personalized medicine. A web application (https://gemfin.click/ebmt) based on the RSF model offers a practical tool to identify patients at high risk for poor transplantation outcomes, supporting informed treatment decisions and advancing individualized care.
- MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Survival Rate MeSH
- Primary Myelofibrosis * therapy mortality MeSH
- Prognosis MeSH
- Aged MeSH
- Machine Learning * MeSH
- Hematopoietic Stem Cell Transplantation * mortality MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Background: Malnutrition is a lack of proper nutrition associated with different chronic diseases, comorbidities, frailty, and a higher prevalence of morbidity and mortality. Aim: The aim of the study was to determine the most appropriate items that reflect nutrition status in this population group and incorporate them into the nutrition risk screening and malnutrition assessment tool. Methods: A cross-sectional validation study was conducted in Bosnia and Herzegovina among 300 individuals older than 65 years. An eight-step approach that included correspondence analysis, generation of the pool item, content validity, internal consistency, construct validity, criterion validity, face validity, and reliability was performed. Results: Correspondence analyses were performed using the contingency table's low-dimensional graphical representation of the rows and columns. After identifying nutrition status assessment-related topics via correspondence analyses, a literature review was performed to determine additional items. The assessment tool's accuracy was measured against clinical judgement as a reference standard. To test face validity of the tool, cognitive interviewing was used. Responses were analyzed and necessary changes were made. The final version of the tool included 14 items. Possible range score on the assessment tool was 0-21. Lower scores indicated nutrition risk. The screening and assessment tool showed acceptable validity and internal consistency.
- MeSH
- Risk Assessment methods MeSH
- Nutrition Assessment * MeSH
- Humans MeSH
- Nutritional Status MeSH
- Malnutrition prevention & control MeSH
- Cross-Sectional Studies MeSH
- Aged * MeSH
- Statistics as Topic MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Aged * MeSH
- Female MeSH
- Publication type
- Validation Study MeSH
- Geographicals
- Bosnia and Herzegovina MeSH
