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Extent of Digital Health Fragmentation and Potential Implications for Antimicrobial Prescribing: Rapid Evidence Review

Background: Prior microbiology results, resistance patterns, and antimicrobial exposure are central to safe and effective antimicrobial prescribing. Digital health fragmentation refers to the dispersal of patient data across multiple electronic systems and the associated challenge of accessing complete information at the point of care. Antimicrobial prescribing for infections represents a critical use case to investigate the impact of digital health fragmentation on patient care. While interoperability has been studied in the context of patient safety, no review has described digital health fragmentation within the United Kingdom and examined its impact on antimicrobial prescribing and antimicrobial stewardship (AMS). Objective: This study aimed to (1) characterize the extent of digital health fragmentation in the United Kingdom, (2) summarize the available evidence on its impact on AMS and prescribing practices in high-income countries, and (3) identify potential solutions. Methods: A rapid review of the peer-reviewed literature was conducted following published guidance for rapid reviews and the PRISMA (Preferred Reporting Items of Systematic Reviews and Meta-Analyses) statement. MEDLINE ALL and PsycInfo were searched on August 19, 2025, using search terms relating to digital health fragmentation or interoperability, patient safety, and antimicrobial use. Searches were limited to English-language publications from 2015 (for characterizing the recent trends or current state of digital health fragmentation in the United Kingdom) or 2010 onward (for AMS-related impacts and solutions). Screening was conducted by 4 researchers following predefined inclusion and exclusion criteria. Extracted data were synthesized narratively through framework analysis. Study quality was appraised using the Mixed Methods Appraisal Tool. Results: Fourteen studies met the inclusion criteria. Ten studies described the extent and nature of digital health fragmentation in the United Kingdom. Digital health fragmentation affects a large number of patients and is linked to clinical care efficiency, quality, and safety risks, including limited access to external clinical records, missing or incomplete information, duplicate investigations, delays in decision‑making, and substantial time spent searching for data. Evidence specific to antimicrobial prescribing was limited (4 studies) but indicated that AMS relies on information spread across multiple systems, with poor interoperability disrupting workflows, hindering communication, and undermining stewardship activities. Only 1 study reported the development of a digital tool designed to address digital health fragmentation and support AMS. Conclusions: Digital health fragmentation negatively affects patient care across the United Kingdom, yet evidence on how it impacts AMS remains scarce. Given the urgency of the global antimicrobial resistance crisis, future research should therefore quantify the scale and impact of digital health fragmentation for AMS to inform investment and innovation in digital infrastructure and clinical-supportive solutions. Trial Registration: PROSPERO CRD420251126067; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251126067

Development and Preliminary Evaluation of a Conversational Agent Delivering Problem-Solving Therapy for Family Caregivers of Children With a Chronic Health Condition: Multiphase Mixed Methods Study

Background: Family caregivers of children with chronic health conditions experience substantial physical and mental health burdens, including burnout, anxiety, depression, fatigue, and sleep disturbances. Despite this need, validated digital mental health tools tailored to family caregivers remain limited. AI-powered conversational agents offer a promising approach for delivering on-demand, personalized mental health support, yet development and evaluation frameworks for this population are lacking. Objective: This paper describes the iterative development and formative evaluation of COCO (Caring of Caregivers Online), a conversational agent designed for family caregivers of children with chronic health conditions. COCO integrates problem-solving therapy (PST) and motivational interviewing (MI) within a human-in-the-loop development framework that progressed from rule-based interactions to a large language model (LLM)–powered conversational agent. Methods: COCO was developed across four phases: (1) caregiver persona and dialogue development based on PST and MI; (2) usability testing of a low-fidelity prototype with standardized patients in a single session of PST; (3) usability testing of a high-fidelity prototype with caregivers in a single session of PST (n=38); (4) integration of an LLM into COCO. The Wizard-of-Oz method was used across phases 2 and 3 to collect naturalistic dialogues and refine COCO’s conversational design. In phase 3, usability of COCO was assessed using the System Usability Scale (SUS). Caregiver emotions were measured before and after the session using 6 subscales of the PANAS-X. In phase 4, GPT-4 was integrated into COCO with few-shot learning and evaluated by research team members using the caregiver personas. Descriptive statistics were used to summarize quantitative measures. The MI principles and techniques used by COCO across the 4 phases were coded using the . Results: In phase 1, 4 gold-standard dialogues were developed using caregiver personas. In phase 2, standardized patients described COCO as validating and identified its problem-solving and on-demand support as helpful for caregivers. In phase 3, COCO-Wizard-of-Oz achieved a mean SUS score of 75.6% (SD 12.9%), reflecting acceptable usability. Participants demonstrated significant improvement in negative affect, sadness, guilt, and fatigue following PST sessions (

Authors’ Reply: Clarifying the Comparative Interpretation and Clinical Implications of Radiomics-Based AI for Pathological Response Prediction

This author reply responds to a Letter to the Editor commenting on our systematic review and meta‑analysis evaluating radiomics‑based artificial intelligence for predicting pathological response following neoadjuvant immunochemotherapy in non‑small‑cell lung cancer. We clarify several methodological points raised in the comment, including patient versus assessment counts in a cited study, cross‑study versus within‑patient comparisons of diagnostic metrics, and the sensitivity‑specificity trade‑off between artificial‑intelligence models and conventional response criteria (RECIST 1.1, PERCIST). We acknowledge two textual errors in the original discussion and confirm they do not affect primary pooled analyses. We further elaborate on eligibility constraints, heterogeneity across prediction time points, definitions of pathological complete response, and reporting standards such as DECIDE‑AI. Our core conclusion remains unchanged: radiomics‑based artificial intelligence shows promising predictive performance with a potential sensitivity advantage over RECIST 1.1, though definitive evidence requires prospective same‑patient, same‑time‑point validation studies.

Same-Patient, Same–Time Point Evidence for Radiomics Benchmarking

This letter examines the interpretation and clinical translation of a meta-analysis of radiomics-based artificial intelligence (AI) for predicting pathological response after neoadjuvant immunochemotherapy in resectable non–small cell lung cancer. We highlight that the conventional-response comparator combines PERCIST and RECIST 1.1 assessments from the same 36-patient cohort, whereas the AI estimates arise from unmatched cohorts; consequently, the reported denominator and Z tests do not establish comparative superiority. We further consider how restriction to patients who reached resection and variation in imaging timepoints narrow the clinical estimand and limit inference about earlier treatment redirection. Clarification of the RECIST and error-direction examples is also warranted. We propose same-patient comparisons in treatment-initiation cohorts using fixed imaging times, locked thresholds, explicit primary-tumor and nodal labels, and calibration and net-benefit analyses at prespecified clinical thresholds.

Metal–organic framework nanovaccines for systemic tumour regression

Nature Biomedical Engineering, Published online: 06 October 2026; doi:10.1038/s41551-026-01786-5

A nanoscale metal–organic framework (MOF)-based cancer vaccine platform enables coordinated antigen presentation and innate immune activation, resulting in tumour regression, immune memory and protection against metastasis.

Realignment of representational drift in mouse visual cortex via flexible electrode arrays

Nature Biomedical Engineering, Published online: 06 October 2026; doi:10.1038/s41551-026-01780-x

A long-term flexible electrode array system stably tracks individual neurons for months, revealing intrinsic drift in visual evoked neural activity and potentiating durable cross-session and cross-animal decoding.

SPIRIT-CONSORT-ELM: element-level annotated dataset and large language model approach for assessing randomized controlled trial reporting

npj Digital Medicine, Published online: 06 October 2026; doi:10.1038/s41746-026-03318-6

SPIRIT-CONSORT-ELM: element-level annotated dataset and large language model approach for assessing randomized controlled trial reporting

Microphysiological models of human gastrointestinal diseases

Nature Biomedical Engineering, Published online: 05 October 2026; doi:10.1038/s41551-026-01805-5

This Review highlights how organoids and organ-on-a-chip technologies are transforming gastrointestinal disease research by providing clinically relevant models of inflammation, infection and cancer and discusses future opportunities for therapeutic developments.

Engineering human multi-organ tissue chip niches for drug absorption, distribution, metabolism, excretion and toxicity prediction

Nature Biomedical Engineering, Published online: 05 October 2026; doi:10.1038/s41551-026-01806-4

Multi-organ-on-a-chip systems aim to improve the prediction of human drug responses by replicating organ interactions in vitro. This Review discusses advances in niche-preserving engineering, scalable manufacturing and multimodal readouts needed to make these systems reliable tools.

Selective PET imaging of bacterial infection using a glycosylated <sup>18</sup>F-fluorodeoxyglucose-derived tracer

Nature Biomedical Engineering, Published online: 05 October 2026; doi:10.1038/s41551-026-01798-1

A positron emission tomography tracer that directly targets bacterial metabolism by exploiting the phosphotransferase system, a carbohydrate transport pathway absent in mammalian cells, enables selective detection of living bacteria in vivo.

Stereochemical origin of potential hysteresis in lithium metal batteries with lithium-rich cation-disordered rocksalt positive electrodes

Nature Nanotechnology, Published online: 05 October 2026; doi:10.1038/s41565-026-02301-2

Multiscale physicochemical and electrochemical characterizations demonstrate that atomic-scale structural distortion and nanoscale short-range ordering govern the thermodynamic and kinetic components of potential hysteresis in Li||DRX cells.

Telemedicine in surgical and anesthetic care in urban and rural settings across time: a scoping review

npj Digital Medicine, Published online: 05 October 2026; doi:10.1038/s41746-026-03340-8

Telemedicine in surgical and anesthetic care in urban and rural settings across time: a scoping review

Standardized pre-consultation by a large language model agent vs ophthalmology residents: a randomized clinical trial

npj Digital Medicine, Published online: 05 October 2026; doi:10.1038/s41746-026-03232-x

Standardized pre-consultation by a large language model agent vs ophthalmology residents: a randomized clinical trial

KDM4A drives TGCT metastasis by inducing focal adhesion disassembly via STAT1-mediated <i>CCL3</i> transcriptional activation

Oncogene, Published online: 04 October 2026; doi:10.1038/s41388-026-04002-5

KDM4A drives TGCT metastasis by inducing focal adhesion disassembly via STAT1-mediated CCL3 transcriptional activation

Minimal residual disease combined with radiological tumor volume as a tool for identification of resected NSCLC patients at high risk of recurrence

J Liq Biopsy. 2026 Sep 18;14:100501. doi: 10.1016/j.jlb.2026.100501. eCollection 2026 Dec.

ABSTRACT

INTRODUCTION: Circulating tumor DNA (ctDNA) is a valuable tool for assessing minimal residual disease (MRD) and predicting recurrence in resected non-small cell lung cancer (NSCLC) patients. Combining ctDNA-detection with radiological tumor volume may improve risk stratification.

METHODS: Patients with stage I-III resectable NSCLC were prospectively enrolled in the RESIDUAL study. Plasma samples were collected before surgery (T0), at landmark (10 days after surgery), during surveillance (T2, 20 days, T3, 1 months after surgery and every 3 months for the first year and then at the end of the second year after surgery), and at relapse. Samples were analyzed using Guardant Reveal, a tissue-free methylation-based ctDNA assay. Receiver operating characteristic analysis associated T1 ctDNA status with tumor volume; volume thresholds were calculated via Youden's J, and Cox regression analysis was performed.

RESULTS: Forty-eight patients were enrolled (median age 72 years; 64.6% male). Most had stage I disease (54.2%) and adenocarcinoma histology (79.2%). Median follow-up was 41.8 months, and 19 patients (39.6%) relapsed. Overall ctDNA detection rate was 15.2% across all timepoints. Pre-surgical ctDNA detection was higher in squamous histology and stage II-III disease and was associated with worse disease-free survival (DFS; p = 0.022). Landmark MRD detection was also associated with worse DFS (p = 0.024). Serial surveillance sampling anticipated radiologic recurrence by a median of 2.6 months (range 2.0-7.5). Patients with tumor volume >26,378 mm3 had a significantly higher relapse risk (p < 0.001).

CONCLUSIONS: MRD detection in NSCLC resected patients predicts relapse and poor outcome; integrating ctDNA with tumor volume enhances identification of high-risk patients.

PMID:42828040 | PMC:PMC13631347 | DOI:10.1016/j.jlb.2026.100501

Multi-omics-driven personalized management of advanced HCC

Cell Rep Med. 2026 Oct 2:103085. doi: 10.1016/j.xcrm.2026.103085. Online ahead of print.

ABSTRACT

Hepatocellular carcinoma (HCC) management is challenging due to its complex tumor microenvironment and poor treatment responses. Here, using tumor specimens from a prospective clinical trial of combined transarterial chemoembolization (TACE) with immune checkpoint blockade (ICB), we perform exhaustive multi-omics analysis including spatial proteomics and transcriptomics, single-cell RNA sequencing, and bulk transcriptomics. These analyses reveal that treatment response is associated with enrichment of anti-tumor T cell regions that are regulated by cGAS-STING activation within immune-suppressive epithelial cells. Conversely, fibrotic processes impede these pro-response processes. Based on these insights, we test triple combination therapy consisting of cGAS activation, immune checkpoint blockade, and anti-fibrosis strategies, which shows improved efficacy over dual therapy. To identify patients who would benefit, we construct a predictive model using a group sparse learning algorithm. Our findings provide a blueprint for crafting personalized HCC therapies using next-generation biomarkers.

PMID:42826719 | DOI:10.1016/j.xcrm.2026.103085

Urine cell-free RNA for bladder cancer detection and treatment response prediction

Nat Med. 2026 Oct 2. doi: 10.1038/s41591-026-04673-3. Online ahead of print.

ABSTRACT

Urine biomarkers promise to improve noninvasive detection and molecular characterization of genitourinary malignancies. Here we describe urine random priming and affinity capture of cell-free RNA (cfRNA) fragments for enrichment analysis by sequencing (uRARE-seq), a liquid biopsy method for urine cfRNA profiling, and apply it to 683 urine samples from patients with cancer and controls. Urine cfRNA contained transcripts from genitourinary tissues and, in patients with prostate, kidney or bladder cancer, tumor-derived transcripts. uRARE-seq demonstrated 95% sensitivity at 90% specificity for detecting localized bladder cancer. The method outperformed urine tumor DNA analysis and was unaffected by the presence of field-effect mutations. Urine cfRNA analysis also sensitively detected minimal residual disease and distinguished complete molecular responses after surgery from those after intravesical Bacillus Calmette-Guérin (BCG). Pretreatment urine from complete responders to BCG was enriched for T cell and other immune signatures, suggesting a preexisting antitumor immune response, whereas nonresponders showed higher expression of proliferation-related genes. In pretreatment urine from 114 patients, this biological difference enabled development of a biomarker predicting likelihood of response to BCG versus chemotherapy (area under the curve 0.93) that was strongly associated with risk of recurrence. Urine cfRNA analysis is therefore a promising biomarker approach for bladder cancer and potentially other urologic malignancies, although prospective studies are needed to assess its clinical utility.

PMID:42827132 | DOI:10.1038/s41591-026-04673-3

Liquid biopsy in head and neck tumors: novel approaches and clinical applications

Clin Chim Acta. 2026 Oct 2;594:122871. doi: 10.1016/j.cca.2026.122871. Online ahead of print.

ABSTRACT

Head and neck cancers (HNCs) represent one of the most prevalent and lethal types of cancer, accounting for 4.7% of annual cancer new cases and 4.9% of cancer-related mortalities. These high prevalence and mortality rates have positioned HNCs as a global health issue. Despite advances in disease treatment methods, the prognosis of patients with advanced or recurrent diseases remains poor. The difficulty of early-stage diagnosis of HNCs is one of the primary contributors to this reduced long-term survival. Currently available diagnostic and disease-monitoring tools, such as tissue biopsy and imaging techniques, are associated with several limitations, including invasiveness, limited repeatability, and limited sensitivity for detecting minimal residual disease (MRD) and microscopic metastases. In recent years, liquid biopsy has emerged as a promising approach, enabling minimally invasive detection of tumor-related biomarkers in body fluids. This review aims to provide a comprehensive overview of the progress and pitfalls of liquid biopsy in the context of HNCs. In this regard, we discuss the principles of liquid biopsy, applicable biomarker types, sample sources, and advanced detection methods. Furthermore, the current status of liquid biopsy in clinical trials of HNCs and the challenges of its clinical translation are also comprehensively explored.

PMID:42826825 | DOI:10.1016/j.cca.2026.122871

Minimal residual disease and relapse surveillance in osteosarcoma: an action-linked framework integrating liquid biopsy and imaging biomarkers

2 October 2026 at 18:00

J Bone Oncol. 2026 Sep 16;61:100803. doi: 10.1016/j.jbo.2026.100803. eCollection 2026 Dec.

ABSTRACT

Osteosarcoma relapse surveillance remains dominated by scheduled imaging because salvage treatment depends on anatomical confirmation of pulmonary, local or extrapulmonary recurrence. However, radiological recurrence may occur after a biologically active phase in which residual viable disease or micrometastatic progression is already present but not yet localizable. This clinical-translational review reframes postoperative osteosarcoma surveillance as an action-linked decision workflow rather than a comparison of isolated biomarker technologies. Current evidence suggests that tumor-informed circulating tumor DNA (ctDNA) sequencing provides the strongest osteosarcoma-specific minimal residual disease (MRD) signal, with postoperative positivity associated with inferior event-free survival and, in selected patients, molecular detection preceding imaging-confirmed relapse or progression. Cell-free DNA methylation may offer a mutation-independent adjunct, whereas circulating tumor cells, extracellular vesicles and circulating microRNAs remain exploratory signals without validated postoperative surveillance actions. Chest computed tomography (CT) and local magnetic resonance imaging (MRI) remain indispensable for disease localization and treatment planning, while diffusion-weighted imaging, dynamic contrast-enhanced MRI and radiomics currently provide mainly local viability or risk-enrichment information rather than proven surveillance-intervention evidence. The near-term role of integrated biomarkers is therefore not to replace guideline-based imaging, but to define protocolized pathways for molecular-positive/imaging-negative, imaging-positive/molecular-negative, concordant high-risk and concordant low-risk states. Future studies should test whether biomarker-triggered reassessment improves clinically meaningful outcomes, including resectability, second complete remission, clinical trial access, patient burden and survival, rather than simply documenting recurrence earlier.

PMID:42824543 | PMC:PMC13628598 | DOI:10.1016/j.jbo.2026.100803

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