Search Results (615)

Background and Objectives: General-purpose multimodal large language models (LLMs) are increasingly used for medical image interpretation despite lacking clinical validation. This study evaluates the diagnostic reliability of ChatGPT-4o and Claude 2 in photographic assessment of adolescent idiopathic scoliosis (AIS) against radiological standards. This study examines two critical questions: whether families can derive reliable preliminary assessments from LLMs through analysis of clinical photographs and whether LLMs exhibit cognitive fidelity in their visuospatial reasoning capabilities for AIS assessment. Materials and Methods: A prospective diagnostic accuracy study (STARD-compliant) analyzed 97 adolescents (74 with AIS and 23 with postural asymmetry). Standardized clinical photographs (nine views/patient) were assessed by two LLMs and two orthopedic residents against reference radiological measurements. Primary outcomes included diagnostic accuracy (sensitivity/specificity), Cobb angle concordance (Lin’s CCC), inter-rater reliability (Cohen’s κ), and measurement agreement (Bland–Altman LoA). Results: The LLMs exhibited hazardous diagnostic inaccuracy: ChatGPT misclassified all non-AIS cases (specificity 0% [95% CI: 0.0–14.8]), while Claude 2 generated 78.3% false positives. Systematic measurement errors exceeded clinical tolerance: ChatGPT overestimated thoracic curves by +10.74° (LoA: −21.45° to +42.92°), exceeding tolerance by >800%. Both LLMs showed inverse biomechanical concordance in thoracolumbar curves (CCC ≤ −0.106). Inter-rater reliability fell below random chance (ChatGPT κ = −0.039). Universal proportional bias (slopes ≈ −1.0) caused severe curve underestimation (e.g., 10–15° error for 50° deformities). Human evaluators demonstrated superior bias control (0.3–2.8° vs. 2.6–10.7°) but suboptimal specificity (21.7–26.1%) and hazardous lumbar concordance (CCC: −0.123). Conclusions: General-purpose LLMs demonstrate clinically unacceptable inaccuracy in photographic AIS assessment, contraindicating clinical deployment. Catastrophic false positives, systematic measurement errors exceeding tolerance by 480–1074%, and inverse diagnostic concordance necessitate urgent regulatory safeguards under frameworks like the EU AI Act. Neither LLMs nor photographic human assessment achieve reliability thresholds for standalone screening, mandating domain-specific algorithm development and integration of 3D modalities. Full article

Background: Interprofessional collaboration (IPC) is considered fundamental for integrated, high-quality woman-centered care. This study analyzes concordance/differences in the perspectives of midwives and physicians on IPC and Equitable Communication (EC) in prenatal/postpartum (PPC) and birth care (BC). Methods: The short form of the ICS Scale (ICS-R with eight items) adapted for the midwifery context, and the EC scale (three items) were completed by 293 midwives and 215 physicians in Germany. Profession- and the setting-specific differences were analyzed using t-tests and ANOVA with repeated measurements. Confirmatory factor analysis with nested model comparisons test the fairness of the scales. Results: Midwives’ ratings of all IPC aspects were systematically lower than physicians’ in both care settings (variance component professional group: η²_p = 0.227/ 0.318), esp. for EC (d = 1.22–1.41). Both groups rated EC higher in BC. The setting effect was less pronounced among physicians for the ICS-R items than among midwives. Violations of test fairness reveal validity deficiencies when using the aggregated EC sum score for group comparisons. Conclusions: Fundamental professional differences were found in the IPC assessment between physicians and midwives. The results enhance the understanding of IPC dynamics and provide starting points for action to leverage IPC’s potential for woman-centered care. Full article

Background and Objective: Large language model (LLM)–based chatbots are increasingly utilized by postpartum individuals seeking guidance on breastfeeding. However, the chatbots’ content quality, readability, and alignment with clinical guidelines remain uncertain. This study was conducted to evaluate and compare the quality, readability, and factual accuracy of responses generated by three publicly accessible AI chatbots—ChatGPT-4o Pro, Gemini 2.5 Pro, and Copilot Pro—when prompted with common maternal questions related to breast-milk supply. Methods: Twenty frequently asked breastfeeding-related questions were submitted to each chatbot in separate sessions. The responses were paraphrased to enable standardized scoring and were then evaluated using three validated tools: ensuring quality information for patients (EQIP), the simple measure of gobbledygook (SMOG), and the global quality scale (GQS). Factual accuracy was benchmarked against WHO, ACOG, CDC, and NICE guidelines using a three-point rubric. Additional user experience metrics included response time, character count, content density, and structural formatting. Statistical comparisons were performed using the Kruskal–Wallis and Wilcoxon rank-sum tests with Bonferroni correction. Results: ChatGPT-4o Pro achieved the highest overall performance across all primary outcomes: EQIP score (85.7 ± 2.4%), SMOG score (9.78 ± 0.22), and GQS rating (4.55 ± 0.50), followed by Gemini 2.5 Pro and Copilot Pro (p < 0.001 for all comparisons). ChatGPT-4o Pro also demonstrated the highest factual alignment with clinical guidelines (95%), while Copilot showed more frequent omissions or simplifications. Differences in response time and formatting quality were statistically significant, although not always clinically meaningful. Conclusions: ChatGPT-4o Pro outperforms other chatbots in delivering structured, readable, and guideline-concordant breastfeeding information. However, substantial variability persists across the platforms, and none should be considered a substitute for professional guidance. Importantly, the phenomenon of AI hallucinations—where chatbots may generate factually incorrect or fabricated information—remains a critical risk that must be addressed to ensure safe integration into maternal health communication. Future efforts should focus on improving the transparency, accuracy, and multilingual reliability of AI chatbots to ensure their safe integration into maternal health communications. Full article

Recent studies have demonstrated the high analytical and diagnostic performance of plasma p-tau217 using well-defined cohorts. We aimed to assess the analytical, diagnostic, and prognostic utility of plasma p-tau217 as a routine biomarker in symptomatic patients attending our memory clinic. We also sought to identify optimal cutoff points that align with cerebrospinal fluid (CSF) amyloid beta (Aβ) status. A total of 276 cognitively impaired patients were included, with 81 mild cognitive impairment (MCI) patients followed for a mean of 56 (±15.8) months to evaluate progression to Alzheimer’s disease (AD). CSF and blood biomarkers of AD were quantified using the Lumipulse G platform. Plasma p-tau217 levels showed strong correlations with CSF Aβ42/Aβ40 (r = −0.707), p-tau181/Aβ42 (r = 0.842), and p-tau181 (r = 0.728). Plasma p-tau217 levels were significantly higher in the A + T + group than in A − T +/− (p < 0.001) and outperformed other plasma markers in detecting CSF Aβ pathology (AUC 0.924).Additionally, p-tau217 moderated cognitive changes over time as measured by the Mini-mental state examination (MMSE) (F(2, 70) = 13.995, p < 0.001) and outperformed other plasma biomarkers in predicting progression from MCI to AD (AUC 0.876). Using a dual cutoff strategy, 72% of patients were classified with 94.9% concordance with CSF Aβ status. Plasma p-tau217 shows strong potential as a non-invasive, cost-effective diagnostic and prognostic tool in clinical settings. Full article

Background and Objectives: Pediatric pulmonary medicine relies heavily on accurate lung function assessment, yet conventional spirometry presents challenges in children due to cooperation requirements. In this context, the interrupter resistance technique (Rint), a method used in pediatric pulmonology, offers a potentially more feasible alternative for evaluating airway resistance in younger populations. This study aimed to assess the feasibility and clinical concordance between expiratory interrupter resistance (Rint(e)) and standard spirometry in healthy children under 8 years, thus contributing to the development of age-appropriate pulmonary function testing in pediatric medicine. Materials and Methods: A cross-sectional study was conducted on 200 healthy children (aged 2–8 years) in Tunisia. Pulmonary measurements were taken using a handheld device for both Rint(e) and spirometry. Feasibility rates were calculated, and correlations between the techniques were statistically analyzed. Results: Rint(e) showed significantly higher feasibility than spirometry (82.5% vs. 34.5%, p < 0.05). While older children had higher success rates with both techniques, feasibility was independent of sex, BMI, and passive smoking exposure. Moderate negative correlations were found between log Rint(e) and FEV1/FVC indices. Conclusions: In pediatric pulmonary assessment, Rint(e) demonstrated higher feasibility than spirometry among young children, making it a practical complementary method in clinical settings. However, due to only moderate correlation with spirometric indices, Rint(e) cannot yet replace spirometry in diagnostic use. Its integration into pediatric medicine may help address the gap in functional respiratory evaluation for children under the age of 8. Full article

The existence of echoes in an acoustic event can ruin the capture of a spoken message and the perception of a piece of music. Likewise, in the performers’ area, clear hearing is essential for the coordination and execution of the ensemble. Bullrings are buildings with a circular plan in which echo-encouraging focalisations can occur. Since bullrings lack a roof, the density of reflections is lower than that in a closed area, and therefore strong isolated reflections perceived by the audience as an echo can be created. In this work, calculations of the echo parameter (Echo Criterion EK) and inspection of impulse responses and energy decay curves are obtained in an on-site measurement campaign in the audience zones and in arena areas where the EK parameter exceeds the thresholds. To this end, four bullrings very emblematic of the Iberian Peninsula together with a very prominent Roman amphitheatre in a relatively good state of conservation in the Roman province of Hispania comprise the study cases. Experimental results of the EK parameter and from acoustic simulation in two of the bullrings present good concordance and show that there is no echo for music in any of the venues in the spectator zones and that the most critical area is when source and receiver are both in the arena, where even double and triple echoes appear. Full article

Background: The Korean Pediatric Emergency Tape (KPET), developed using 2005 anthropometric data, aims to improve weight estimation in Korean children. However, its validity has not been evaluated using recent large-scale data. This study evaluates the accuracy of the KPET compared with the latest version of the Broselow Tape (BT) using contemporary national anthropometric datasets. Methods: A cross-sectional analysis was conducted using pooled data from the 2019 National Health Screening Program for Infants and Children (NHSPIC, age 0–5) and the 2018–2019 Student Health Examination Sample Survey in Korea (SHESS, age 6–12). Accuracy was assessed by the proportion of estimates within 10% (PW10) and 20% (PW20) of measured weight, and by concordance between estimated and measured weight color zones. Results: Data from 1,992,646 (KPET) and 1,987,504 (BT) children were analyzed. In NHSPIC, the KPET showed slightly lower overall accuracy than the BT (PW10: 72.7% vs. 74.0%) but outperformed the BT in infants (PW10: 72.1% vs. 67.4%). In SHESS, the KPET consistently underperformed compared with the BT (PW10: 49.5% vs. 52.9%). The KPET showed higher concordance only in infants. Both tapes showed a trend of underestimation with increasing age, more pronounced in the KPET. Conclusion: The KPET showed lower overall performance than the BT but outperformed the BT in infants. Its accuracy declines in older children and tends to underestimate weight. Regular updates using recent anthropometric data are necessary to ensure accurate weight estimation and reflect current growth trends in Korean children. Full article

Background/Objectives: The clinically validated multiplex Oncuria bladder cancer (BC) assay quickly and noninvasively identifies disease risk and tracks treatment success by simultaneously profiling 10 protein biomarkers in voided urine samples. Oncuria uses paramagnetic bead-based fluorescence multiplex technology (xMAP^®; Luminex, Austin, TX, USA) to simultaneously measure 10 protein analytes in urine [angiogenin, apolipoprotein E, carbonic anhydrase IX (CA9), interleukin-8, matrix metalloproteinase-9 and -10, alpha-1 anti-trypsin, plasminogen activator inhibitor-1, syndecan-1, and vascular endothelial growth factor]. Methods: In a pilot study (N = 36 subjects; 18 with BC), Oncuria performed essentially identically across three different common analyzers (the laser/flow-based FlexMap 3D and 200 systems, and the LED/image-based MagPix system; Luminex). The current study compared Oncuria performance across instrumentation platforms using a larger study population (N = 181 subjects; 51 with BC). Results: All three analyzers assessed all 10 analytes in identical samples with excellent concordance. The percent coefficient of variation (%CV) in protein concentrations across systems was ≤2.3% for 9/10 analytes, with only CA9 having %CVs > 2.3%. In pairwise correlation plot comparisons between instruments for all 10 biomarkers, R² values were 0.999 for 15/30 comparisons and R² ≥ 0.995 for 27/30 comparisons; CA9 showed the greatest variability (R² = 0.948–0.970). Standard curve slopes were statistically indistinguishable for all 10 biomarkers across analyzers. Conclusions: The Oncuria BC assay generates comprehensive urinary protein signatures useful for assisting BC diagnosis, predicting treatment response, and tracking disease progression and recurrence. The equivalent performance of the multiplex BC assay using three popular analyzers rationalizes test adoption by CLIA (Clinical Laboratory Improvement Amendments) clinical and research laboratories. Full article

Background: Osteotomies around the knee aim to correct varus or valgus malalignment and improve biomechanics. However, little is known about their effect on knee phenotypes, as defined by the Coronal-Plane-Alignment-of-the-Knee (CPAK) and Hirschmann’s functional classification. This study evaluated pre- and postoperative phenotypes in patients undergoing high-tibial-osteotomy (HTO) or distal-femoral-osteotomy (DFO). Methods: We retrospectively analysed 214 osteotomies around the knee (HTO: 145; DFO: 69) of 188 patients from our institutional registry. Radiographic parameters were measured using a validated artificial intelligence software, with phenotypes classified by CPAK and Hirschmann classification. Preoperative osteotomy planning was compared to postoperative alignment. Regression was used to assess the influence of demographic and radiographic factors. Results: CPAK types changed in 95.3% of cases. Medial opening HTOs most frequently shifted from CPAK type I (73.8%) to VI (42.3%), while medial closing DFOs transitioned from type III (81.5%) to V (24.1%). Concordance between planned and achieved CPAK types was highest for types III, IV, and V. Postoperative angles were generally smaller than planned for joint-line-obliquity (JLO), lateral-distal-femur-angle, and medial-proximal-tibial-angle (p < 0.001). Neutral JLO was restored in only 48.1%. Preoperative phenotypes NEUmLDFA0° (40.1%) and VARmMPTA3° (32.3%) were most common, while postoperative phenotypes included VALmLDFA3° (52.4%) and VALmMPTA3° (37.7%). Age, sex, and BMI significantly influenced alignment outcomes. Conclusions: Postoperative CPAK classifications shifted significantly across all osteotomy types, with minimal retention of preoperative types. Although most procedures achieved correction within the target HKA range, restoration of a neutral JLO was observed in only half of the cases, emphasizing the importance of phenotype-specific planning and highlight potential limitations of CPAK classification. Full article

Background/Objectives: It remains unclear whether certain areas of the prostate are more difficult to accurately sample using MRI/US-fusion-guided freehand single-access transperineal prostate biopsy (FSA-TP). The aim of this study was to evaluate the detection rates of clinically significant (cs) and clinically insignificant (ci) prostate cancer (PCa) in each prostate zone during FSA-TP MRI-target biopsies (MRI-TBs) and systematic biopsies (SB). Methods: This monocentric observational study included a cohort of 277 patients with no prior history of PCa who underwent 3 MRI-TB cores and 14 SB cores with an FSA-TP from January to December 2023. The intraclass correlation coefficient (ICC) was assessed to evaluate the correlation between the Prostate Imaging–Reporting and Data System (PI-RADS) of the index lesion and the International Society of Urological Pathology (ISUP) grade stratified according to prostate zone and region of index lesion at MRI. Multivariate logistic regression analysis was conducted to identify factors associated with PCa and csPCa in patients with discordant results between MRI-TB and SB. Results: FSA-TP-MRI-TB demonstrated higher detection rates of both ciPCa and csPCa in the anterior, apical, and intermediate zones when each of the three MRI-TB cores was analysed separately (p < 0.01). However, when all MRI-TB cores were combined, no significant differences were observed in detection rates across prostate zones (apex, mid, base; p = 0.57) or regions (anterior vs. posterior; p = 0.34). Concordance between radiologic and histopathologic findings, as measured by the intraclass correlation coefficient (ICC), was similar across all zones (apex ICC: 0.33; mid ICC: 0.34; base ICC: 0.38) and regions (anterior ICC: 0.42; posterior ICC: 0.26). Univariate analysis showed that in patients with PCa detected on SB but with negative MRI-TB, older age was the only significant predictor (p = 0.04). Multivariate analysis revealed that patients with PCa detected on MRI-TB but with negative SB, only PSA remained a significant predictor (OR 1.2, 95% CI 1.1–1.4; p = 0.01). In cases with csPCa detected on MRI-TB but with negative SB, age (OR: 1.0, 95% CI 1.0–1.1; p = 0.02), positive digital rectal examination (OR: 2.0, 95% CI 1.1–3.8; p = 0.03), PI-RADS score >3 (OR: 4.5, 95% CI 1.7–12.1; p < 0.01), and larger lesion size (OR: 1.1, 95% CI 1.1–1.2; p < 0.01) were significant predictors. Conclusions: FSA-TP using 14 SB cores and 3 MRI-TB cores ensures comprehensive sampling of all prostate regions, including anterior and apical zones, without significant differences in detection rates between nodules across different zones. Only in a small percentage of patients was csPCa detected exclusively by SB, highlighting the small but important complementary value of combining SB and MRI-TB. Full article

Temperature forecasting is critical for public safety, environmental risk management, and energy conservation. However, reliable forecasting becomes challenging in regions where governmental institutions lack adequate measurement infrastructure. To address this limitation, the present study aims to improve temperature forecasting by collecting temperature, pressure, and humidity data through IoT sensor networks. The study further seeks to identify the most effective method for the real-time processing of large-scale datasets generated by sensor measurements and to ensure data reliability. The collected data were pre-processed using Discrete Wavelet Transform (DWT) to extract essential features and reduce noise. Subsequently, three wavelet-processed deep-learning models were employed: Wavelet-processed Artificial Neural Networks (W-ANN), Wavelet-processed Long Short-Term Memory Networks (W-LSTM), and Wavelet-processed Bidirectional Long Short-Term Memory Networks (W-BiLSTM). Among these, the W-BiLSTM model yielded the highest performance, achieving a test accuracy of 97% and a Mean Absolute Percentage Error (MAPE) of 2%. It significantly outperformed the W-LSTM and W-ANN models in predictive accuracy. Forecasts were validated using data obtained from the Turkish State Meteorological Service (TSMS), yielding a 94% concordance, thereby confirming the robustness of the proposed approach. The findings demonstrate that the W-BiLSTM-based model enables reliable temperature forecasting, even in regions with insufficient governmental measurement infrastructure. Accordingly, this approach holds considerable potential for supporting data-driven decision-making in environmental risk management and energy conservation. Full article

Soil organic carbon (SOC) monitoring is central to carbon farming Monitoring, Reporting, and Verification (MRV), yet high laboratory costs and sparse sampling limit its scalability. We present the first independent field validation of the Stenon FarmLab multi-sensor probe across 100 temperate European arable-soil samples, benchmarking its default outputs and a simple pH-corrected model against three laboratory reference methods: acid-treated TOC, temperature-differentiated TOC (SoliTOC), and total carbon dry combustion. Uncorrected FarmLab algorithms systematically overestimated SOC by +0.20% to +0.27% (SD = 0.25–0.28%), while pH adjustment reduced bias to +0.11% and tightened precision to SD = 0.23%. Volumetric moisture had no significant effect on measurement error (r = −0.14, p = 0.16). Bland–Altman and Deming regression demonstrated improved agreement after pH correction, but formal equivalence testing (accuracy, precision, concordance) showed that no in-field model fully matched laboratory standards—the pH-corrected variant passed accuracy and concordance evaluation yet failed the precision criterion (p = 0.0087). At ~EUR 3–4 per measurement versus ~EUR 44 for lab analysis, FarmLab facilitates dense spatial sampling. We recommend a hybrid monitoring strategy combining routine, pH-corrected in-field mapping with laboratory-based recalibrations alongside expanded calibration libraries, integrated bulk density measurement, and adaptive machine learning to achieve both high-resolution and certification-grade rigor. Full article

Background: The reduced Gross Motor Function Measure-66 (rGMFM-66) has already demonstrated its validity compared to the standard GMFM-66 using the Gross Motor Ability Estimator-2 (GMAE-2). This study aimed to evaluate its validity using the updated Gross Motor Ability Estimator-3 (GMAE-3) and to compare agreement between GMFM-66v2 and GMFM-66v3. Methods: A retrospective analysis was conducted on 250 children with cerebral palsy (CP) enrolled in a rehabilitation program between 2015 and 2024. All GMFCS levels (I–V) were represented. The sample included 107 females and 143 males, with a mean age of 6.9 years (SD 3.4). Agreement between scoring methods was assessed using intraclass correlation coefficients (ICCs) and Bland–Altman analyses. Results: The rGMFM-66 showed excellent agreement with GMFM-66v3 (ICC = 0.994; 95% CI 0.992–0.996). Similar agreement was found between GMFM-66v2 andGMFM-66v3 (ICC = 0.994; 95% CI 0.991–0.996). Bland–Altman plots confirmed close agreement across all comparisons. The rGMFM-66 reduces administration time from 45 to 26 min, offering a 42% time saving in clinical use. Conclusions: The rGMFM-66 demonstrates very high agreement with GMFM-66v3 and appears to be a valid alternative. Its strong concordance supports its applicability in both clinical and research settings. Although agreement was high, minor differences between scoring methods indicate that results should be interpreted in light of the scoring algorithm applied. Full article

Objectives: To evaluate the agreement between AI-CAD-guided mammographic and MRI measurements of tumor size and T stage in breast cancer patients being considered for neoadjuvant chemotherapy (NAC). Methods: This retrospective study included 144 women (mean age, 52 ± 11 years) with invasive breast cancer who subsequently received NAC and underwent both AI-CAD mammography (score ≥ 10) and pre-treatment MRI. Tumor sizes from AI-CAD contours were compared with MRI using Pearson correlation, intraclass correlation coefficients (ICCs), and Bland–Altman analysis. Concordance was defined as a ±0.5 cm difference. The contour showing the highest agreement was used to compare T stage with MRI using weighted kappa. Results: The mean AI-CAD abnormality score was 86.3 ± 22.2. Tumor sizes on mammography were 3.0 ± 1.2 cm (inner), 3.8 ± 1.5 cm (middle), and 4.8 ± 2.2 cm (outer), while the MRI-measured tumor size was 4.0 ± 1.9 cm. The middle contour showed the strongest correlation with MRI (r = 0.897; ICC = 0.866), the smallest mean difference (–0.19 cm; limits of agreement, –1.87 to 1.49), and the highest concordance (61.1%). Agreement was higher in mass-only lesions than in NME-involved lesions (ICC = 0.883 vs. 0.775; concordance, 70.9% vs. 46.6%). T stage comparison using the middle contour showed substantial agreement with MRI (κ = 0.743 [95% CI, 0.634–0.852]; agreement, 88.2%), with higher concordance in mass-only lesions (93.0%) than NME-involved lesions (81.0%) and more frequent understaging in the latter (17.2% vs. 2.3%). Conclusions: AI-CAD-guided mammographic assessment using the middle contour demonstrated good agreement with MRI for tumor size and T stage, indicating its value as a supportive tool for clinical staging in MRI-limited settings. Full article

This study presents a mobile-based sperm analysis system featuring a user-friendly, droplet-loaded microfluidic chip that enables non-specialist users to perform the rapid and accurate quantitative evaluation of boar semen directly on the farm. The iSperm system integrates a tablet, optical module, heater, and real-time image analysis app to deliver automated measurements of sperm concentration, motility, and progressive motility in under one minute. Precision and user variability tests demonstrated high concordance with CASA and the hemocytometer, with minimal differences between trained and untrained users. A method comparison using 77 farm-collected samples confirmed agreement through Passing–Bablok regression and Bland–Altman analysis. ROC curve analyses further validated diagnostic accuracy for all parameters, with AUC values exceeding 0.95. The iSperm platform offers a reliable, user-friendly, and field-deployable solution for on-site semen quality assessment, improving decision-making in swine artificial insemination. Full article