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PubMed2026

Application of Three-Dimensionally Printed Surgical Guides in Precise Sacral Tumor Excision and Defect Reconstruction.

OBJECTIVE: Precise resection of sacral tumors remains technically demanding due to their deep anatomical location and close proximity to critical neurovascular structures. Conventional freehand techniques often result in suboptimal resection margins, excessive blood loss, and compromised lumbopelvic stability. This study evaluated whether patient-specific three-dimensional (3D)-printed guiding templates improve surgical accuracy and perioperative outcomes in sacral tumor resection and reconstruction. METHODS: Nineteen patients undergoing en bloc sacral tumor resection (S1-S3 involvement) with spinopelvic reconstruction (2006-2020) were retrospectively analyzed. Patients were divided into a 3D-printing group (n = 10) and a conventional freehand group (n = 9). In the 3D-printing group, computer-aided design and 3D-printed templates were used for osteotomy, screw placement, and defect reconstruction. Perioperative metrics, surgical accuracy, and complications were compared between groups using Welch's t-test and the Hodges-Lehmann method; oncologic events during follow-up were recorded descriptively. RESULTS: The 3D-printing group demonstrated significantly shorter operative time (456.5 ± 62.36 vs. 574.44 ± 114.58 min, p = 0.012), reduced blood loss (4081.40 ± 838.99 vs. 5090.0 ± 1059.67 mL, p = 0.034), and fewer fluoroscopic exposures (4.2 ± 0.79 vs. 10.0 ± 1.58, p < 0.001) compared with the conventional group. Osteotomy accuracy was also superior in the 3D-printing group, with significantly lower angular deviation (3.33° ± 0.45° vs. 6.79° ± 2.16°, p = 0.0012). Postoperative complication rates were comparable (30% vs. 44.4%, p = 0.649), but hospital stay was significantly shorter in the 3D-printing group (10.7 ± 2.71 vs. 18.11 ± 4.01 days, p < 0.001). CONCLUSION: Patient-specific 3D-printed guiding templates enhance precision in sacral tumor excision and reconstruction, improving surgical efficiency and perioperative safety. This computer-assisted, template-guided approach represents a valuable advancement for complex sacral oncologic surgery.

Humans↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Fundamentals of pacemakers ECG interpretation - part 2.

BACKGROUND: Modern pacemakers incorporate arrhythmia-response algorithms, ventricular pacing minimization protocols, and safety mechanisms that generate ECG patterns indistinguishable from pathological AV block, sensing malfunction, or device-mediated tachycardia. Failure to recognize these algorithm-driven signatures leads to unnecessary interventions, misdiagnosis, and inappropriate device reprogramming. This manuscript is the second in a two-part series on pacemaker ECG interpretation. METHODS: We conducted a narrative review of peer-reviewed literature and device-specific documentation on algorithm-driven ECG behavior, synthesizing evidence across arrhythmia recognition, upper rate physiology, ventricular pacing minimization, mode switching, safety mechanisms, and hysteresis algorithms. RESULTS: Pacemaker-mediated tachycardia produces regular paced wide-complex tachycardia locked at the upper tracking rate, initiated by any event with retrograde VA conduction. Ventricular tachycardia is identified by QRS morphology diverging from the known paced pattern, absent pacing spikes, and AV dissociation. Upper rate Wenckebach behavior mimics Mobitz type I AV block; 2:1 upper rate response mimics second-degree AV block. Ventricular pacing minimization algorithms produce isolated nonconducted P waves and prolonged AV intervals that simulate pathological conduction disease. Mode switching causes abrupt rate drops misidentified as output failure. Ventricular safety pacing generates a conspicuously short, fixed AV interval. Three discrete pacing artifacts reflect AV-sequential cardiac resynchronization therapy (CRT), ventricular safety pacing in CRT, or His-bundle pacing with backup RV output. Rate and AV hysteresis produce pauses and wandering AV intervals mimicking oversensing or Wenckebach periodicity. CONCLUSIONS: Recognizing algorithm-driven ECG patterns requires knowledge of device timing intervals and refractory periods, which lets clinicians distinguish programmed behavior from true malfunction or cardiac arrhythmia.

Humans↗

PubMed2026

Evaluation of the difference between automated and measured QTc intervals in children.

BACKGROUND: The corrected QT interval (QTc) is obtained through automated ECG computations or manual physician measurements. We hypothesized that differences exist in children between the measured and automated QTc intervals within and between Healthy and hypertrophic cardiomyopathy (HCM) subjects with greater differences for HCM due to structural abnormalities. METHODS: QT measurements - Bazett correction- automated (aQTc) and measured (mQTc), were extracted from the GE MUSE database for 385 Healthy pediatric (single ECG) and 208 HCM subjects (2 ECGs), stratified by age < 12 and ≥ 12 yrs., sex, race, and ethnicity. QTc means (SD), automated and measured differences, and the difference of the differences of aQTc and mQTc were analyzed overall and by subgroups. All ECGs were read by one pediatric cardiologist with a second cardiologist reading a random subset of HCM ECGs to evaluate intraclass correlations and agreement. RESULTS: The mQTc intervals were shorter than aQTc intervals within Healthy (p < 0.001) and within first HCM ECGs (p < 0.001) with both aQTc and mQTc shorter in Healthy than HCM (p < 0.001). The difference in these differences was significant overall using HCM ECG 1 but not HCM ECG 2. Healthy subject aQTc and mQTc intervals differed by age, sex, and race (p < 0.002). HCM ECG 1 aQTc- mQTc intervals differed for age < 12 yrs., as well as by sex and race. HCM ECG 2 intervals differed only for age < 12 yrs. CONCLUSIONS: Compared to measured values, automated QTc values were significantly longer in both Healthy and HCM subjects. Automated measurements may overestimate the QTc.

Humans↗

PubMed2026

Initial 4-Year Experience With Microaxial Flow Pumps Within a Tertiary Centre in Regional Australia.

BACKGROUND & AIM: The Microaxial Flow Pump (MFP) is a miniaturised rotary pump that aspirates blood from the left ventricle and expels it into the ascending aorta. It unloads the left ventricle and increases mean arterial pressure and cardiac output. MFP is most commonly utilised in cardiogenic shock, for protected percutaneous coronary intervention (PCI), and for ventricular offloading in veno-arterial extracorporeal membrane oxygenation (VA-ECMO). METHOD: We conducted a retrospective review of all patients who underwent MFP insertion at John Hunter Hospital, Australia. Categorical data are represented as counts and percentages, with continuous variables described as means with standard deviations. RESULTS: Twenty-three MFP devices were inserted between September 2020 and May 2024. Five (22%) were for protected PCI, three (13%) for venting with VA-ECMO (ECPELLA), and 15 (65%) for acute coronary syndrome (ACS) and cardiogenic shock. The median age for the overall cohort was 62 years, with a 74% male predominance. Eighty percent of the protected PCI cohort were elective outpatient procedures, and there were no deaths in this cohort. The mortality in the ECPELLA group was 67%. Thirteen (87%) of the patients with cardiogenic shock presented with an anterior infarct, and 53% had cardiac arrest on admission. The overall morality in the cardiogenic shock cohort was 40%. Complications in this cohort included limb ischaemia in four patients (17%) and site bleeding in seven patients (30%). Four patients (17%) required vascular surgery intervention. CONCLUSION: Our initial experience showed the use of MFP in a tertiary centre was safe and feasible, allowing progression from protected percutaneous intervention to acute cardiogenic shock.

Humans↗

PubMed2026

RR-interval-based atrial fibrillation detection and burden estimation: cross-dataset validation and calibration-aware probability analysis.

Objective.Atrial fibrillation (AF) burden has become an increasingly important endpoint in long-duration rhythm monitoring, but reliable burden estimation requires more than accurate AF detection alone. In particular, when burden is derived by aggregating predicted AF probabilities over time, probability calibration may directly affect burden validity under external dataset shift.Approach.This study developed an interpretable-interval feature model for AF detection and evaluated it using record-wise cross-validation on a development cohort and independent cross-dataset external validation on public Holter electrocardiographic databases. Window-level performance was assessed using the area under the receiver operating characteristic curve (ROC-AUC), area under the precision-recall curve (PR-AUC), Brier score, expected calibration error (ECE), and calibration intercept and calibration slope. Recording-level AF burden was estimated using both probability-based and hard-label aggregation and evaluated using mean absolute error (MAE) and agreement analyses.Main results.The model showed high discrimination in both development and external evaluation, with external ROC-AUC ofand PR-AUC of. However, external calibration deteriorated despite preserved ranking performance, with Brier score of, ECE(15) of, calibration intercept of, and calibration slope of. In the external cohort, probability-based burden estimation preserved strong association with reference burden but showed weaker raw agreement than hard-label aggregation, with MAE ofversus, consistent with systematic probability underprediction. Repeated external recalibration across record-level splits substantially improved probability quality and probability-based burden estimation. Median probability-burden MAE decreased fromwithout recalibration toafter Platt recalibration andafter isotonic recalibration, while median ECE(15) decreased fromtoand, respectively.Significance.These findings indicate that-interval-based AF detection maintained strong ranking performance in the tested external cohort, but probability calibration should be evaluated explicitly when predicted probabilities are aggregated into AF-burden estimates.

Atrial Fibrillation↗

PubMed2026

How I do it: 3-Suture robotic pyeloplasty: Step-by-step technique.

Robot-assisted pyeloplasty is now a gold standard in the treatment of pediatric ureteropelvic junction obstruction. We describe a standardized "3-suture" technique designed to facilitate the pyelo-ureteral anastomosis. We used this technique in 65 paediatric patients aged 3-17 years. Early major complications (Clavien-Dindo grade III) occurred in 3 patients (4.6%). The median operative time was 150 min. Surgical success was achieved in 96% of cases at a median follow-up of 9.5 months. This 3-suture approach offers a highly reproducible method for robotic pyeloplasty, facilitating accurate anatomical reconstruction with excellent surgical outcomes.

Humans↗

PubMed2026

Efficacy and Safety of Mechanical Insufflation-Exsufflation in Invasively Ventilated Critically Ill Adults: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Mechanical insufflation-exsufflation (MI-E) is increasingly used in invasively ventilated adults in the intensive care unit (ICU), yet its therapeutic efficacy and safety remain uncertain due to inconsistent evidence. AIM: To synthesize evidence on the clinical efficacy and safety of MI-E in this population and to examine methodological and clinical heterogeneity underlying reported outcomes. STUDY DESIGN: A systematic review and meta-analysis of randomized studies (including RCTs and randomized crossover trials), conducted following PRISMA guidelines, with risk of bias assessed using the Cochrane risk-of-bias tool. RESULTS: Five randomized controlled trials involving 310 patients were included. Meta-analysis showed that mechanical insufflation-exsufflation (MI-E) significantly increased sputum clearance (SMD = 0.63, 95% CI, 0.32-0.93; p < 0.00011; I2 = 38%) without affecting oxygenation (MD = 0.28, 95% CI, -0.53 to 1.09; p = 0.50; I2 = 9%). Data on respiratory mechanics, ventilation duration and ICU stay could not be pooled. No serious adverse events were reported. CONCLUSIONS: MI-E significantly improves sputum clearance in invasively ventilated critically ill adults, with no severe adverse events reported in the included studies. Its effects on other outcomes remain inconclusive due to limited data and heterogeneity. Standardized protocols and larger trials are needed. RELEVANCE TO CLINICAL PRACTICE: Clinicians may consider MI-E as an adjunct for respiratory secretion management. Application should be guided by structured patient assessment and individualized parameter adjustment. Future research should standardize interventions and target well-defined patient subgroups to inform clear practice guidelines. TRIAL REGISTRATION: The review protocol was registered in the International Prospective Register of Systematic Reviews, with registration number CRD42023403299.

Humans↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

Effectiveness of a blended care intervention in physiotherapy with exercise and education for patients with hip or knee osteoarthritis (SmArt-E): A multicentre pragmatic randomized controlled trial.

OBJECTIVE: To evaluate the effectiveness of a twelve-month smartphone-assisted physiotherapy (SmArt-E) intervention versus usual care in hip and/or knee osteoarthritis (OA), and to assess usability and patient satisfaction with the digital support. METHOD: We conducted a multicentre, pragmatic, parallel-group randomized controlled trial in 27 physiotherapy practices in Germany. Patients with physician-diagnosed hip and/or knee OA aged ≥50 (hip) or ≥38 years (knee) were randomly allocated to SmArt-E (IG; n=166) or usual care (CG; n=164). The twelve-month intervention combined supervised and smartphone-assisted training and education (blended care). Primary outcomes were pain (NRS, 0-10) and physical function (HOOS/KOOS-ADL, 0-100) at twelve months. Secondary outcomes followed OARSI domains; usability and patient satisfaction were also assessed. RESULTS: Among 330 participants (mean age 64±8 years), baseline NRS was 3.2±2.3 in the CG and 3.5±2.4 in the IG; HOOS/KOOS-ADL was 71.6±17.7 and 69.4±17.5, respectively. No significant between-group differences were found for pain (-0.36; 95% CI: -0.84 to 0.12; p=0.14) or physical function (2.66; 95% CI: -0.46 to 5.77; p=0.09). Among 13 secondary outcomes, significant differences favouring the IG emerged at three and twelve months for several domains; however, effect sizes were small and unlikely to be clinically meaningful. CONCLUSION: SmArt-E did not demonstrate superior effectiveness over usual care in mild hip and/or knee OA. Both groups improved over time, with slightly more favourable but clinically inconclusive outcomes in the IG. Findings highlight the need to refine the intervention, better identify eligible patients, and optimize digital and in-person components.

Humans↗

PubMed2025

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

Humans↗

PubMed2026

Delphi study robot consenso: Strategies for the implementation of robotic surgery in general surgery in the Spanish hospital network.

INTRODUCTION: The implementation of robotic surgery in public hospitals presents multiple logistical, educational, and organizational challenges. In the absence of unified guidelines, a national consensus is required to optimize its safe and efficient adoption. This study aimed to establish a set of consensus-based and measurable recommendations for the implementation of robotic surgery programs in hospitals within the Spanish National Health System, based on the experience of centres with established robotic programs and intended to serve as guidance for hospitals that are initiating or planning their implementation. METHODS: A national Delphi study was conducted with the participation of robotic surgery experts from 26 public hospitals. The expert panel was composed exclusively of digestive surgeons with experience in robotic surgery. Three iterative rounds of expert panel evaluation were conducted between March 2024 and March 2025. The questions were grouped into five thematic blocks. Consensus was defined as an agreement level of ≥66.7%. Kendall's W coefficient was used to assess concordance. RESULTS: High levels of consensus were achieved on key aspects related to infrastructure, structured training, cost evaluation, and quality assurance mechanisms. Areas of disagreement were also identified, such as the need for a dedicated anaesthesiologist, purchase of accessory instruments during the initial phase, and official accreditation pathways. CONCLUSIONS: This study provides a guideline for developing a national robotic surgery strategy focused on patient safety, program sustainability, and standardized training of surgical teams. These recommendations can guide hospitals at different stages of robotic technology adoption. Given that the consensus was reached from an exclusively surgical perspective, the recommendations focus on patient safety, program sustainability, and standardized training of the surgical team, and should be interpreted in an adaptable manner according to each centre's context, case volume, and available resources.

Cirugía Asistida por Robot↗

PubMed2026

Effects of an actuated ankle exoskeleton on walking stability in healthy adults: a controlled laboratory study.

BACKGROUND: Ankle exoskeletons are widely used to reduce the metabolic cost of walking, yet their effects on walking stability during unperturbed gait remain insufficiently understood. Walking stability can be characterized using complementary measures that capture stride-to-stride variability, global temporal organization, and local dynamic stability. Understanding how walking with an actuated ankle exoskeleton system influences these different aspects of gait stability is essential for the safe design and control of wearable robotic devices. METHODS: Eighteen healthy adults walked on a treadmill at a constant speed (1.1 m/s) with and without an actuated bilateral ankle exoskeleton in a randomized crossover design. Spatiotemporal variability was quantified using coefficients of variation (CoV) of stride length, step width, and stance ratio. Global gait stability was assessed using detrended fluctuation analysis of stride time. Local dynamic stability was evaluated using maximum Lyapunov exponent calculated for the trunk, hip, upper leg, lower leg, and foot. Paired-samples two-sided t-tests were used to compare conditions. RESULTS: Walking with the ankle exoskeleton resulted in increased stride-to-stride spatiotemporal variability, reflected by higher CoV values for stride length (p < 0.001) and stance ratio (p = 0.005), while mean stride length and step width remained unchanged. Mean stance ratio was reduced in the exoskeleton condition (p < 0.001). Global gait stability did not differ between conditions, indicating preserved long-range temporal gait organization. Local dynamic stability increased at the lower leg (p < 0.001) and foot (p = 0.019) when walking with the exoskeleton. CONCLUSIONS: Walking with the actuated ankle exoskeleton alters gait control across multiple levels during steady walking. While stride-to-stride variability in stride length and stance ratio increased, global gait stability remained unchanged. Local dynamic stability was increased at the lower leg and foot, suggesting segment-specific effects of ankle-level assistance close to the assisted joint. However, these findings should be interpreted as the combined effect of wearing the exoskeleton and receiving active assistance, rather than the isolated effect of plantarflexion assistance. These results provide insight for the design and control of ankle exoskeletons with respect to stability-related effects during walking.

Humans↗

PubMed2026

Comparative evaluation of molecular technologies for the identification of prevalent non-tuberculous mycobacteria in pulmonary infections: a systematic review and meta-analysis.

BACKGROUND: The increasing prevalence of non-tuberculous mycobacteria pulmonary disease (NTM PD) is a burden to public health. Successful management of NTM PD critically depends on accurate species identification and reliable drug susceptibility testing to guide appropriate antibiotic therapy. Emerging molecular technologies offer rapid diagnostic solutions compared to conventional methods, but their performance varies. This study aims to provide a comprehensive evaluation of current molecular techniques for NTM identification and to present a global antibiotic resistance profile. METHODS: A systematic literature search was conducted in PubMed and Web of Science for studies published between 2005 and 2024. Studies applying molecular methods for NTM identification and resistance detection in humans were included. Data on study characteristics, diagnostic methods, sample types, sample sizes, identification sensitivity, and drug susceptibility results were extracted. Meta-analysis was performed using R with the meta4diag package. The quality of included studies was assessed using the QUADAS-2 tool. RESULTS: The analysis included 49 studies on NTM identification and 33 studies on antibiotic resistance. For species identification, all evaluated molecular technologies (MALDI-TOF MS, PCR-based methods, Sequencing, DNA chip, and DNA strip) demonstrated high pooled sensitivities (>0.92). Subgroup analysis revealed that sample type significantly affected performance for MALDI-TOF MS. Preliminary analysis of antibiotic resistance rates revealed varying patterns. For slowly growing mycobacteria, a significantly high Ethambutol resistance rate was observed in M. avium (69.20%). Among rapidly growing mycobacteria, resistance to Imipenem was notable (54.22%), and Clarithromycin resistance varied significantly within the Mycobacterium abscessus complex. CONCLUSION: Emerging molecular technologies have revolutionized the methodology for NTM identification with excellent performance. However, their performance can be influenced by sample type, particularly for MALDI-TOF MS. The alarming and heterogeneous antibiotic resistance patterns also highlight the critical need for rapid and accurate species identification and drug susceptibility testing to inform effective therapeutic strategies. Key messagesMolecular technologies demonstrate high accuracy for NTM identification.Antibiotic resistance is a serious concern with variations among NTM species and subspecies.Rapid and accurate species identification and drug susceptibility testing are crucial for guiding effective clinical management of NTM PD.

Humans↗

PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed2026

Changes in hippocampal functional connectivity and volume associated with cognitive improvement and decline in amnestic mild cognitive impairment following computerized cognitive training.

BACKGROUND: The hippocampus influences the outcomes of amnestic mild cognitive impairment (aMCI) and undergoes different changes during the cognitive decline or recovery of aMCI compared to elderly individuals with normal cognition, which may reveal disease-dependent neurodegeneration or plasticity. We first aimed to investigate the hippocampal changes associated with cognitive changes in aMCI using a combined case-control study design. METHODS: In total, 50 aMCI individuals and 50 healthy controls (HCs) were recruited in Shenyang, China, and separately randomized into training and control groups: aMCI training group, aMCI no training group, HC training group, and HC no training group. The aMCI and HC training groups received computerized cognitive training (CCT) thrice weekly for 12 weeks. Cognitive assessments and MRI data were collected at baseline and follow-up. RESULTS: The primary outcome was significant CCT×diagnosis interaction effect on the change in cognitive performance as measured by clock drawing test (CDT) scores (F = 4.322, P = 0.041); this interaction was driven by CCT specifically in aMCI (F = 4.465, P = 0.038). Significant CCT×diagnosis interaction effects of right-hippocampal FC changes were observed in the bilateral precuneus/cuneus (Pvoxel<0.05) driven by CCT in aMCI (F = 5.429, P = 0.023), and in the left superior temporal gyrus/middle temporal gyrus (STG/MTG, Pvoxel<0.05), driven by CCT of only in HCs (F = 6.587, P = 0.013). A significant interaction effect of left-hippocampal FC changes were observed in the right triangular part of the inferior frontal gyrus (IFGtriang, Pvoxel<0.05), driven by CCT in aMCI and HCs (F = 6.550, P = 0.013; F = 7.097, P = 0.010). No significant interaction effect on the change in hippocampal GMV was noted (P > 0.05). CONCLUSION: CCT can improve the visuospatial ability of aMCI, which is reflected by the CDT scores. CCT can alter hippocampal FC in the bilateral precuneus/cuneus, the right IFGtriang, and the left STG/MTG. The hippocampal GMV is difficult to change in both HCs and aMCI during the cognitive decline. REGISTRATION NUMBER: ChiCTR1900026849. DATE OF REGISTRATION: 24 October 2019 NAME OF TRIAL REGISTRY: Chinese Clinical Trial Registry (ChiCTR).

Humans↗

PubMed2026

Evaluation of a cornea-specialized large language model for diagnostic and management accuracy in complex corneal cases.

PURPOSE: To evaluate whether a cornea-specialized large language model (LLM) enhanced with retrieval-augmented generation (RAG) improves clinicians' diagnostic and management accuracy in complex corneal cases compared to a general-purpose GPT-4o model and unaided clinician performance. METHODS: This prospective, randomized, masked evaluation study involved three cornea trainees who each independently reviewed 39 real-world corneal cases under three experimental conditions: unaided, GPT-4o-assisted, and assisted by a cornea-specialized GPT-4o model. The cornea-specialized model was constructed by embedding over 200 publicly available Wikipedia articles into GPT-4o's RAG framework. Participants provided open-ended diagnoses and selected the next-step management options (multiple choice). They were allowed up to three GPT-4o queries per case, and the AI-assisted arms were randomized to minimize bias. Accuracy for both tasks was compared against expert reference standards using McNemar's test. RESULTS: Diagnostic accuracy was 48.7%, 20.5%, and 38.5% unaided, improving to 69.2%, 46.2%, and 59.0% with general GPT-4o (p<0.04). The cornea-specialized GPT-4o further improved accuracy to 71.8%, 48.7%, and 74.4%, with improvements over unaided performance for all clinicians (p<0.01). For next-step decisions, unaided accuracy was 76.9%, 87.2%, and 59.0%. With the specialized model, Ophthalmologist 3 improved to 71.8% (p<0.05), Ophthalmologist 1 remained high at 82.1%, and Ophthalmologist 2 declined to 64.1% (p<0.05). CONCLUSIONS: A cornea-specialized LLM enhanced with RAG improved diagnostic accuracy in complex corneal cases, particularly among clinicians with lower baseline performance. Effects on management accuracy were inconsistent. Future studies should explore the use of open-ended management tasks and examine whether smaller, curated retrieval corpora yield better model performance.

Humans↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗