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PubMed2026

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (ΔAUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

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PubMed2026

Nourishing collaboration: interdisciplinary nutrition education for health care professionals.

Nutrition education remains insufficient in many health care professional training programs despite the central role of diet in the prevention and management of chronic disease. Contemporary nutrition science increasingly recognizes that dietary behaviors and health outcomes are shaped by complex interactions among biological, behavioral, environmental, and food system factors. This perspective proposes an interdisciplinary framework for nutrition education that integrates the complementary expertise of physicians, dietitians, chefs, and farmers. By bridging clinical care, nutrition science, culinary practice, and agricultural systems, such an approach may strengthen the translation of evidence into practice, improve nutrition-related competencies among health care professionals, and ultimately enhance population health outcomes.

Humans↗

PubMed2026

Targeting TP53 in triple-negative breast cancer: Molecular pathogenesis, therapeutic implications, and emerging pharmacological strategies.

Triple-negative breast cancer (TNBC) remains a highly aggressive and therapeutically challenging subtype, defined by the absence of oestrogen, progesterone, and HER2 expression. Tumour Protein 53 (TP53) mutations represent the most frequent genetic alteration, occurring in over 80% of cases and driving tumour initiation, progression, and therapeutic resistance. Mutant p53 proteins not only lose canonical tumour-suppressive functions but also often acquire gain-of-function (GOF) oncogenic properties that promote metastasis, genomic instability, and resistance to mechanisms like ferroptosis. This review examines the biological role of TP53 in TNBC pathogenesis and evaluates emerging pharmacological strategies aimed at targeting these vulnerabilities. Key approaches include the pharmacological reactivation of mutant p53 using small molecules such as APR-246, COTI-2, and the mutation-specific reactivator rezatapopt (PC14586), which has shown significant clinical tumour reduction in Y220C-mutant patients. Other strategies involve targeted protein degradation, the exploitation of synthetic lethal interactions (e.g., Chk1 or Aurora kinase B inhibition), and the use of natural products like cryptolepine or piperine derivatives. Recent clinical evidence further highlights the potential of combining epigenetic agents like decitabine with chemotherapy in TP53-mutant populations. Integrating TP53 mutation status into biomarker-driven treatment paradigms is a pivotal step toward achieving precision oncology and improving clinical outcomes for patients with TNBC.

Precision oncology↗

PubMed2026

Functional neuroimaging subtypes of obsessive-compulsive disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.

Humans↗

PubMed2026

Family-Wise Error Rate Control in Clinical Trials With Overlapping Populations.

We consider clinical trials with multiple, overlapping patient populations that test multiple treatment policies specifically tailored to these populations. Such designs may lead to multiplicity issues, as false statements will affect several populations. For type I error control, often the family-wise error rate (FWER) is controlled, which is the probability to reject at least one true null hypothesis. If the joint distribution of the test statistics is known, the FWER level can be exhausted by determining critical values or adjusted-levels. The adjustment is typically done under the common ANOVA assumptions. However, the performed tests are then only valid under the rather strong assumption of homogeneous null effects, that is, when the null hypothesis applies to all subpopulations and their intersections. We show that under cancelling null effects, when heterogeneous effects cancel out in some or all subpopulations, this procedure does not provide FWER control. We also suggest different alternatives and compare them in terms of FWER control and their power.

Humans↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Multi‑omics approaches to decipher the molecular mechanisms of exercise‑mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi‑omics technologies, including transcriptomics, proteomics, metabolomics and single‑cell spatial approaches, have revolutionized the capacity to decode exercise‑mediated bone adaptation at the systems level. The present review synthesizes current single‑omics landscapes and integrative multi‑omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi‑omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans↗

PubMed2026

Early infantile developmental and epileptic encephalopathy: clinical spectrum, diagnosis, outcomes, and evolving treatment strategies.

Early infantile developmental and epileptic encephalopathy (EIDEE) is among the most severe epilepsy syndromes, with onset before three months of age and an estimated incidence of approximately 10 per 100,000 live births. The 2022 International League Against Epilepsy classification unified the historically distinct Ohtahara syndrome and early myoclonic encephalopathy under a single diagnostic framework defined by frequent drug-resistant tonic and/or myoclonic seizures, an abnormal neurological examination, and an abnormal interictal electroencephalogram-most characteristically a burst-suppression pattern. This narrative review synthesizes the clinical, electrophysiological, neuroimaging, genetic, and therapeutic literature within the EIDEE framework. The clinical phenotype is characterized by central hypotonia, postnatal microcephaly, cortical visual impairment, and age-dependent syndromic evolution toward infantile epileptic spasms syndrome or Lennox-Gastaut syndrome in the majority of patients. Electroencephalography remains essential for syndromic classification, while systematic metabolic screening and early trio whole-exome or whole-genome sequencing are central to the etiologic workup, achieving diagnostic yields of 60-65%. The most commonly identified genetic causes include STXBP1, KCNQ2, and SCN2A variants. Outcomes are poor overall and strongly etiology-dependent: vitamin-responsive disorders carry a substantially more favorable prognosis, whereas mortality reaches 25% in genetic cohorts. Genotype-guided pharmacotherapy is now applicable to a clinically meaningful subset of patients, with sodium channel blockers, potassium channel openers, and emerging antisense oligonucleotide therapies representing important therapeutic advances. Gene therapy trials are underway but have encountered early safety signals, underscoring the vulnerability of this population. Critical unmet needs include earlier molecular diagnosis, precision therapies targeting developmental outcomes beyond seizure control, and prospective international registries to characterize the long-term natural history of EIDEE.

Humans↗

PubMed2026

A therapeutic atlas of monogenic inflammatory bowel disease.

BACKGROUND AND AIMS: Evidence-based, mechanism-guided therapies are urgently needed for treating monogenic inflammatory bowel disease (mIBD). For such rare diseases, mechanistic insight is essential to guide treatment when conventional clinical trials are often not feasible. We aimed to summarize literature-based evidence and to identify knowledge gaps. METHODS: We conducted a systematic review of published manuscripts evaluating the therapeutic efficacy in mIBD. We quantified and compared the global therapeutic response score across treatments and conditions. In a subset of conditions, biomarkers of longitudinal therapeutic response were evaluated in comparison to non-monogenic pediatric IBD cohorts. RESULTS: Responses to 35 therapeutics across the 102 known genetic causes of mIBD were evaluated in 241 articles and 669 patients, summarizing 302 gene-drug responses. The efficacy of at least one pharmacological intervention was identified in 61% (n = 62/102) of the mIBD conditions, highlighting a major unmet need for effective medications in many others. Gene- and pathway-specific responses were demonstrated for several therapies, including allogeneic hematopoietic stem cell transplantation, gene therapy, and advanced therapies such as anti-TNF agents, IL-1 inhibitors, mTOR inhibitors, as well as eculizumab in CD55 deficiency, abatacept in CTLA4 deficiency, and the immunometabolic agent empagliflozin in glycogen storage disease type 1b. CONCLUSIONS: This study highlights the potential of precision medicine approaches tailored to genetic and pathway-specific mechanisms, while underscoring the urgent need for effective therapies in many monogenic conditions that remain without established treatment options.

Humans↗

PubMed2026

Time-varying hazard rates reveal patterns of progression in HR+/HER2- metastatic breast cancer: Towards risk-adapted monitoring.

BACKGROUND: optimal imaging intervals for patients with hormone receptor-positive/HER2-negative metastatic breast cancer (MBC) remains undefined. Aim of this study was to analyze the temporal patterns of disease progression to identify high risk subgroups that may benefit from intensified monitoring. METHODS: we analyzed 149 hormone receptor-positive/HER2-negative MBC patients prospectively enrolled in the MAGNETIC.1 trial (NCT05814224) and treated with first line endocrine therapy. Hazard rates (HR) for disease progression were determined according to clinico-pathological and liquid biopsy features. RESULTS: in the overall population, two distinct progression-risk peaks emerged at 2-3 months (32.9/1000 person-months) and at 24 months (28.0/1000). Higher risk of progression was observed in lobular carcinoma (61.1) [HR 61.12 per 1000 person month (pm)], progesterone receptor-negative status (HR 39.07), fulvestrant-based treatment (HR 46.88), liver metastases (HR 59.00), and presence of ≥ 3 metastatic sites (HR 40.10). CONCLUSIONS: Hazard distribution in hormone receptor-positive/HER2-negative MBC is biphasic and modulated by readily available clinical variables. High-risk subgroups may benefit from intensified radiologic and liquid-biopsy surveillance during the first three months and around two years after treatment start.

Breast cancer↗

PubMed2026

A User-Friendly Protocol for Microinjection into Teleost Embryos to Study Gene Function.

Zebrafish (Danio rerio) and medaka (Oryzias latipes) are popular teleost models used in developmental biology and functional genomics. To achieve high-quality and reproducible microinjections, it is essential to have robust protocols for breeding, egg collection, and the precise delivery of genetic material. In this protocol, we present a comprehensive and optimized methodology for setting up breeding tanks under controlled photoperiod conditions to maximize egg yield while minimizing contamination. We provide detailed procedures for sex identification, pair selection, the use of grated breeding inserts, and methods to increase egg collection efficiency. We outline procedures for making injection gel beds, pulling needles, and calibration using one-microliter microcapillaries to achieve consistent nanoliter-scale injections. Our protocol outlines settings for the pico-liter injector that are optimized to deliver a precise amount per pulse with minimal variability. Finally, we demonstrate the application of these methods for gene knockdown using morpholino antisense oligonucleotides, gene knockout using CRISPR-Cas9, and gain-of-function mRNA overexpression experiments. Phenotypic assessments conducted at various developmental stages to evaluate gene-specific effects reveal consistent phenotypic outcomes between the morpholino and CRISPR-Cas9 approaches. This easy and comprehensive protocol enables efficient, precise, and scalable genetic manipulation of zebrafish and medaka embryos, thereby supporting advanced functional studies in developmental biology and disease modeling. To our knowledge, this is the first unified protocol for both zebrafish and medaka microinjection systems achieving 97.7% phenotype penetrance in CRISPR-Cas9 knockouts with precision together with a triple validation approach that confirms gene function across multiple techniques.

Animals↗

PubMed2026

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

Humans↗

PubMed2026

Meniscal preservation in the age of biologics: toward a quantitative decision algorithm for personalized repair.

BACKGROUND: Despite advances in arthroscopic repair and biologic augmentation, surgical indication for meniscal tears remains heterogeneous. No standardized framework currently integrates biomechanical, clinical, and biological determinants to guide repair versus resection. PURPOSE: To develop a quantitative decision model-the Meniscal Preservation Score (MPS)-that unifies biomechanical and biological evidence to stratify reparability potential and standardize treatment selection in meniscal surgery. METHODS: A systematic evidence synthesis conducted in accordance with PRISMA 2020 reporting standards of studies published from 2000 to 2025 in PubMed, Embase, and Scopus identified key determinants of meniscal healing. Five consistent predictors-patient age, vascularity, tear morphology, associated pathology, and activity profile-were weighted through a two-round modified Delphi consensus among ten experienced knee surgeons. The resulting 0-9-point MPS was incorporated into a stepwise decision tree linking lesion morphology, biological context, and surgical strategy. Conceptual validation used 50 simulated cases and a retrospective cohort of 45 patients to test agreement between algorithm recommendations and expert surgical decisions. RESULTS: The MPS achieved 86% concordance with expert judgment in simulation and 84% agreement in clinical validation. In this retrospective exploratory cohort, cases in which surgical management was concordant with MPS recommendations demonstrated higher mean IKDC scores at 24 months and lower observed reoperation rates. These findings should be interpreted as associative rather than causal, as treatment allocation was not controlled and discordant cases may have represented inherently more complex pathology. CONCLUSION: The MPS represents an evidence-informed decision-support framework designed to systematize reparability assessment. While exploratory analyses suggest structural coherence with expert reasoning, prospective implementation and external validation are required before clinical adoption as a predictive tool. LEVEL OF EVIDENCE: conceptual model with exploratory validation.

Humans↗

PubMed2026

Intramuscular patient-derived xenografts achieve high engraftment rates in gastric cancer: implications for pharmacodynamic testing and genomic biomarker discovery.

BACKGROUND: Gastric cancer (GC) exhibits marked inter-patient heterogeneity, limiting empirical chemotherapy efficacy. Patient-derived xenograft (PDX) models preserve the molecular features of parental tumors and can serve as pharmacodynamic surrogates, but conventional subcutaneous PDX suffers from low engraftment rates. This study evaluated an optimized intramuscular PDX platform for individualized drug testing in GC and applied whole exome sequencing (WES) for biomarker identification (Clinical trial registry: ChiCTR-OOC-17012731). MATERIALS AND METHODS: Ninety-eight treatment-naive GC patients were enrolled between April 2018 and December 2020. Fresh tumor tissues were engrafted into NCG mice by intramuscular transplantation. Drug efficacy was evaluated using tumor cell necrosis rate and Ki-67 expression. WES was performed on 32 engrafted tumorgrafts to characterize driver mutations in fast- and slow-growing subgroups. RESULTS: An engraftment rate of 71.7% (43/60) was achieved, substantially exceeding rates reported in prior studies. Clinical characteristics were independent of engraftment success and outgrowth time (all p > 0.05). Fast- and slow-growing tumorgrafts diverged in frequently altered genes: KMT2C, APOB, CDK12 and MSH2 predominated in fast-growing grafts, whereas TP53, CHD3 and TET2 were enriched in slow-growing grafts. Slow-growing tumorgrafts correlated with longer progression-free survival (p = 0.02). PDX-guided treatment was associated with improved prognosis. CONCLUSIONS: Intramuscular transplantation into NCG mice yields high engraftment rates for GC PDX. PDX-guided chemotherapy selection is associated with favorable outcomes. Driver mutation divergence between fast- and slow-growing tumorgrafts provides candidate prognostic biomarkers.

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PubMed2026

The potential of clustering methods for pre-test triage in sleep medicine: A systematic review.

Sleep disorders exhibit substantial heterogeneity, and traditional classifications may not fully capture clinically relevant subtypes. Clustering techniques can identify patient subgroups that improve phenotypic characterization and may support personalized management. This systematic review evaluated the application of clustering in sleep medicine, with particular focus on its potential use as a pre-test triage tool prior to formal sleep testing. PubMed/MEDLINE, Embase, Web of Science, and Scopus were searched to February 2025. Eligible studies applied clustering to classify sleep disorders in adults. Two reviewers independently conducted screening, data extraction, and risk-of-bias assessment using QUADAS-2. The protocol was registered on PROSPERO. Fifty-one studies (1983-2025) were included, predominantly focused on obstructive sleep apnea (OSA) (n = 38, 74%). Hierarchical clustering (n = 20) and K-means clustering (n = 14) were the most frequently used techniques. Internal validation was reported in only 18% of studies, and external validation was reported in only 1 study. Seven studies relied exclusively on baseline clinical, demographic, or questionnaire data, representing pre-test scenarios, whereas most incorporated polysomnography-derived variables, limiting their applicability to early clinical stratification. Hierarchical clustering was the most commonly applied method; however, the overall lack of validation limits confidence in the robustness and clinical applicability of identified phenotypes. The potential role of clustering as a pre-test triage strategy remains largely unexplored, as most studies focused on post-diagnostic phenotyping and were affected by incorporation bias. Future research should prioritize pre-test clinical variables, rigorously validate internally and externally, and adopt standardized methodological and reporting practices to facilitate clinical translation.

Humans↗

PubMed2026

An Assessment of Reliability Estimation Methods for Binomial Health Care Quality Measures.

We evaluated the performance of commonly used methods for estimating the reliability of binomial health care quality measures using simulated datasets spanning a range of performance score means and variances, numbers of entities, and patient sample sizes. For each simulation, reliability was estimated for all selected methods and compared with the known true reliability derived from the simulation parameters, with methods assessed on their accuracy and precision. Logistic regression with reliability estimated on the outcome scale demonstrated the highest accuracy and precision among all methods evaluated. The widely used Adams beta-binomial method performed poorly, although a modification recommended by Nieser and Harris substantially improved its performance. These approaches are applicable only to binomial measures. Among methods that can be applied to both binomial and continuous measures, permutation resampling of the Spearman rank correlation coefficient was the most accurate and precise, outperforming other commonly used approaches. Overall, for binomial quality measures, logistic regression on the outcome scale is the preferred method for reliability estimation, followed closely by the modified beta-binomial approach, while for non-binomial measures, permutation-based Spearman rank correlation appears to be the most suitable method.

Reproducibility of Results↗

PubMed2026

Timing of carbetocin administration in vaginal deliveries: a double-blind, randomized controlled trial.

OBJECTIVES: This study aimed to compare the efficacy of administering carbetocin before vs. after placental delivery in preventing postpartum hemorrhage (PPH) in low-risk vaginal deliveries. METHODS: The randomized controlled trial was conducted at Kartal City Hospital, Istanbul, Turkey. A total of 160 primiparous women with uncomplicated pregnancies who underwent vaginal delivery were enrolled. Participants were randomly assigned to receive 100 μg of carbetocin either before or after placental delivery. The primary outcome was the incidence of PPH. Secondary outcomes included the need for additional uterotonics, manual removal of the placenta with consequent antibiotic administration, blood transfusions, maternal adverse events, and changes in hemoglobin levels at baseline and 24 h postpartum. RESULTS: The incidence of PPH was significantly lower in the carbetocin-before group than in the carbetocin-after group (p=0.015). The carbetocin-before group had a significantly lower mean hemoglobin drop compared to the carbetocin-after group (p<0.001). The need for additional uterotonics was significantly higher in the carbetocin-after group (p<0.001). Manual placenta removal and the need for antibiotics were more frequent in the carbetocin-before group (p=0.017). No significant differences in adverse maternal events were observed between the groups. CONCLUSIONS: Administering carbetocin before placental delivery significantly reduces the incidence of PPH, blood loss, and the need for additional uterotonics. However, the increased rate of manual placenta removal necessitates individualized risk-benefit assessment; pre-placental administration may be most advantageous in women at elevated risk for PPH, in whom the hemorrhagic benefit outweighs the risks associated with manual extraction.

Humans↗

PubMed2026

Complication rates of 16- and 18-gauge needles for native kidney biopsies: a systematic review and proportional meta-analysis.

This systematic review and meta-analysis evaluated complication rates and diagnostic yield reported in studies of adult native kidney biopsy using 16-gauge (16 G) or 18-gauge (18 G) needles. We included randomized trials and cohort studies of real-time ultrasound-guided biopsies, including case series. MEDLINE, Embase, and CENTRAL were searched through October 2024. Two reviewers independently performed study selection, data extraction, and risk of bias assessment using Joanna Briggs Institute tools. Random-effects meta-analyses estimated pooled proportions with 95% confidence intervals (CI), and univariable random-effects meta-regression explored study-level associations with major complications, transfusion, or gross hematuria. We screened 4,499 titles and abstracts and reviewed 319 full-text articles; 62 studies comprising 68 biopsy series were included. The pooled major complication rate in studies using 16 G needles was 1.83% (95% CI: 1.20-2.79) and 1.29% (95% CI: 0.78-2.13) in studies using 18 G needles, with no statistically significant difference. Mean glomerular yield was 18.8 with 16 G and 17.5 with 18 G needles. In study-level meta-regression, studies with higher prevalence of acute kidney injury, lower mean estimated glomerular filtration rate, or lower mean hemoglobin reported higher pooled complication rates. Most studies were single-arm cohorts; between-needle differences therefore reflect indirect study-level contrasts. Interpretation is limited by retrospective design and heterogeneity across studies. Overall, studies using both needle sizes reported low complication rates and similar diagnostic yield, although definitions and reporting varied. Direct comparative studies are needed to determine whether meaningful differences exist.

Humans↗