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Results for “Varus deformity”

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3 recordsLinked to original sources
PubMed2026

The knee-ankle link: impact of knee varus severity on distal joint malalignment and concomitant pathologies.

BACKGROUND: Knee varus deformity is traditionally managed as an isolated joint pathology; however, persistent distal symptoms following proximal realignment suggest a more extensive kinetic chain dysfunction. The degree to which knee varus severity dictates distal malalignment and secondary pathologies remains poorly quantified in the current literature. METHODS: This systematic review and meta-analysis were conducted in accordance with PRISMA 2020 guidelines (PROSPERO: CRD420261363327). A comprehensive search of PubMed, Embase, Web of Science, and the Cochrane Library was performed from inception to April 2026. Studies examining the relationship between knee varus (HKA angle) and radiographic distal alignment or pathologies were included. Data synthesis utilized random-effects models, with prevalence analyzed via generalized linear mixed models (GLMM). RESULTS: Fourteen studies were included in the final synthesis. While pooling of continuous radiographic parameters was limited by high statistical heterogeneity in Talar Tilt (I2 = 96.5%), individual large-cohort data (Huang et al.) indicated that severe knee varus (HKA > 10°) was associated with increased odds of concomitant ankle osteoarthritis (OR 2.29; 95% CI 1.28-4.11) and a specific cohort prevalence of 37.1%. Furthermore, single-arm prevalence data revealed divergent trends across different study populations, with compensatory hindfoot valgus reaching 69.9% in some cohorts and rigid varus up to 63.9% in others. CONCLUSIONS: Severe genu varum is associated with distal kinetic chain alterations and concomitant ankle pathologies. However, due to the extreme heterogeneity and divergent distal adaptations observed across different cohorts, standardized knee-centric protocols may be insufficient. Further longitudinal and interventional studies are required to establish phenotype-specific rehabilitation guidelines.

Humans↗
PubMed2026

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans↗
PubMed2026

Studies on functional differentiation of xpr1a and xpr1b genes in zebrafish.

Xenotropic and polytropic retrovirus receptor 1 (XPR1) is known to be involved in various biological processes, including phosphate homeostasis, cellular signaling, brain and vascular mineralization, whereas its specific contribution to bone development remains incompletely characterized. Due to genome duplication in teleosts, zebrafish Danio rerio possess two paralogous genes of XPR1 namely xpr1a and xpr1b, whose functional divergence remains unclear. The amino acid sequence similarity between zebrafish xpr1a and xpr1b was 83.26%. In situ hybridization demonstrated overlapping localization in the head and spinal cord at 24-48 hpf, while diverged by 72 hpf, with xpr1a becoming restricted to the head while xpr1b persisted in both regions. CRISPR/Cas9 was used to generate xpr1a and xpr1b mutants. The xpr1a mutants are comparatively healthy, viable but with mild growth reduction, whereas the xpr1b mutants display high mortality, reduced body length and severe vertebral deformities. Interestingly, all the double mutants died at the embryonic stage. Moreover, to further investigate the molecular and regulatory mechanisms, we conducted comparative transcriptome analysis on bone and brain tissues from xpr1b+/+ and xpr1b-/- zebrafish. In bone tissue, 6749 DEGs were identified, comprising 3846 upregulated and 2903 downregulated genes. These DEGs were mainly enriched in the MAPK signaling pathway, Wnt signaling pathway, cysteine and methionine metabolism, and ECM-receptor interaction. RT-qPCR validated results showed that seven osteogenesis-related genes (col1a1a, sp7, runx2b, col1a2, col1a1b, alp1 and entpd5), and two phosphate homeostasis related genes (slc20a2 and pdgfba), which are essential for skeletal mineralization and phosphate homeostasis, exhibited significantly downregulated expression in bone tissue of xpr1b mutant zebrafish. These results highlight the pivotal role of xpr1b in regulating skeletal mineralization and phosphate metabolism, thereby elucidating the functional specialization of XPR1 paralogs while providing a theoretical basis for understanding bone developmental mechanism in teleost vertebrates.

Animals↗