Search Results (1,247)

Background/Objectives: Herein, we report the clinical cases of two affected first-degree relatives from a family with highly variable macular dystrophy, expanding the known phenotype spectrum with mutations in the thyroid hormone receptor beta gene (THRB). Methods: Multimodal retinal imaging included wide-field fundus photography, fundus autofluorescence (FAF), spectral domain optical coherence tomography (SD-OCT) imaging, performed alongside functional testing (visual fields, electroretinogram (ERG)), metabolic blood analyses, and genetic testing of both cases. Results: A 67-year-old female patient presenting with reading difficulties and visual impairment since childhood was referred for evaluation and counseling for potential treatment options. Extensive ophthalmologic examination, including multimodal retinal imaging and functional testing, revealed an occult macular dystrophy. Her 39-year-old son reported similar visual symptoms in combination with mild photophobia. In multimodal retinal imaging, he also showed a macular dystrophy but with a vitelliform phenotype. Genetic testing identified the heterozygous pathogenic variant c.283+1G>A in the thyroid hormone receptor beta gene (THRB) in both patients. Conclusions: This report shows a high intrafamilial variability of macular dystrophy caused by a heterozygous THRB mutation, which has only recently been recognized as a cause of macular dystrophy. Here, we describe a novel clinical presentation characterized by a vitelliform lesion, expanding the phenotypic spectrum of THRB-associated macular dystrophy. Full article

Early diagnosis of pancreatic cancer, particularly in intraductal papillary mucinous neoplasm (IPMN), remains challenging despite advances in imaging and biomarkers. Pancreatic adenocarcinoma (PDAC) has a high mortality rate; therefore, its early detection and adequate interventions are necessary to improve the disease outcome. Most IPMNs are asymptomatic and discovered incidentally. Magnetic resonance imaging (MRI) is a preferred tool for diagnosing malignant IPMNs, with a sensitivity of 90.7–94.1% and a specificity of 84.7–87.2% in detecting mural nodules > 5 mm, a strong predictor of high-risk lesions. Radiomics further enhances diagnostic accuracy (sensitivity 91–96%, specificity 78–81%), especially when combined with CA 19-9, which has lower sensitivity (73–90%) but higher specificity (79–95%). Computed tomography (CT), though less effective for small mural nodules, remains widely used; its accuracy improves with radiomics and clinical variables (sensitivity 90.4%, specificity 74%). Conventional endoscopic ultrasonography (EUS) shows lower performance (sensitivity 60%, specificity 80%), but its advanced variations have improved outcomes. Contrast-enhanced EUS (CE-EUS) visualizes mural nodules with more than 90% sensitivity and involvement of the main pancreatic duct, with a sensitivity of 83.5% and a specificity of 87%. EUS–fine-needle aspiration (EUS-FNA) allows cyst fluid analysis; however, CEA, glucose, and KRAS/GNAS mutations show poor value for malignancy risk. Cytology has low sensitivity (28.7–64.8%) but high specificity (84–94%) in diagnostic malignant changes and strongly affects further management. EUS–through-the-needle biopsy (EUS-TTNB) yields high diagnostic accuracy (sensitivity 90%, specificity 95%) but carries a range of 2–23% adverse events, which limits its wide use. EUS–confocal laser endomicroscopy (EUS-nCLE) provides real-time microscopic evaluation, detecting malignant IPMN with a sensitivity of 90% and a specificity of 73%, though its availability is limited. New emerging biomarkers available in cyst fluid or blood include mucins, miRNA panels (sensitivity 66.7–89%, specificity 89.7–100%), lipidomics, and cancer metabolite profiling, with diagnostic accuracy approaching 89–91%. Pancreatoscopy (POP) enables direct main pancreatic duct (MPD) visualization and biopsy with a sensitivity of 64–100% and a specificity of 75–100%, though adverse events occur in around 12% cases. Combining advanced imaging, EUS-based tissue acquisition, and novel biomarkers holds promise for earlier and more accurate detection of malignant IPMN, potentially improving PDAC outcomes. Full article

Background: The present study aimed to clarify the neurocognitive processes through which blood levels of omega-3 LCPUFAs affect reading and writing abilities. Methods: A total of 74 school-age children whose reading and writing skills varied from normal to largely below normal underwent an assessment of reading and writing abilities, auditory and visual processing, phonological awareness, attention, and executive functions. Exploratory factor analysis extracted three neuropsychological factors whose roles as mediators between omega-3 LCPUFAs and reading/writing abilities were tested in GLM mediation models. The possible interactions with other PUFAs were further investigated. Results (on 73 participants): Omega-3 LCPUFA levels (EPA and DHA) correlated with reading and writing abilities and with the three extracted factors. Auditory–phonological processing skills were found to be significant mediators of the effect of PUFAs (especially EPA) on reading and writing abilities, whereas DHA and AA/ALA significantly moderated some of these effects. Conclusions: The link between omega-3 LCPUFAs and reading and writing abilities seems to be mediated mainly by the effects of LCPUFAs on auditory–phonological processing skills. These effects are especially linked to EPA, but they are modulated by DHA and AA/ALA levels. Hypotheses about possible molecular mechanisms at the basis of these effects are discussed. Full article

Background: Idiopathic epiretinal membrane (iERM) is a common retinal pathology in elderly patients, thought to originate primarily from an anomalous process of posterior vitreous detachment. The standard treatment is pars plana vitrectomy (PPV) with membrane peeling. No consensus exists regarding the optimal timing of surgery, nor is it clear which patients are most likely to benefit. Given that iERM profoundly affects retinal vascular morphology and function, optical coherence tomography angiography (OCTA) has emerged as a valuable tool for identifying potential biomarkers. This systematic review aimed to synthesize the available evidence on OCTA-derived biomarkers and their correlations with visual function before and/or after surgical intervention in iERM, with a particular focus on their prognostic value for postoperative outcomes. Methods: A systematic search of PubMed/MEDLINE and Scopus was conducted on the 20th of May 2025 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligible studies included patients with iERM undergoing vitreoretinal surgery, used OCTA for pre- and/or postoperative assessment, investigated structure–function correlations, and were designed as clinical trials, observational studies, or case series with more than 10 patients. Exclusion criteria were studies with ≤10 cases, absence of separate iERM analysis, lack of surgical intervention, or non-English language. Data extraction covered study design, demographics, surgical approach, OCTA device, follow-up, OCTA biomarkers, and structure–function outcomes. Risk of bias in observational studies was assessed using the National Institute of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results: The search yielded 1053 records, of which 71 underwent full-text review and 43 met eligibility criteria. All included studies were observational, encompassing 1958 eyes from 1953 patients. The most frequently investigated biomarkers were the foveal avascular zone (FAZ) area and related parameters, vessel density (VD), and foveal density 300 (FD-300). Additional studies evaluated average vessel length (VL), blood flow area, vessel length density (VLD), vessel tortuosity (VT), fractal dimension (FD), and perfusion capacity (PC). Conclusions: By consolidating current evidence, this systematic review provides a comprehensive overview of structure–function correlations in iERM and highlights the potential of OCTA-derived metrics as biomarkers of disease severity and surgical prognosis. These findings help clarify underlying mechanisms of visual decline and establish the context for further research. Nonetheless, interpretation is limited by the observational design of all included studies and by heterogeneity in OCTA methodology and nomenclature, underscoring the need for standardization to improve comparability and foster greater coherence across studies. No funding was provided for this review. Full article

Cholesterol, triglycerides, high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), and very-low-density lipoproteins (VLDLs) were evaluated in chimpanzees at Tacugama Chimpanzee Sanctuary, Sierra Leone. Blood from 75 visually healthy chimpanzees was collected, centrifuged within one hour of collection, and analyzed at Choithram Hospital within 24 h. Statistical analyses assessed differences and interactions based on age, body condition score (BCS), housing group, and sex. HDLs varied widely by housing group; HDLs and LDLs were higher in males than in females. Cholesterol and LDLs were higher in prepubertal individuals while VLDLs and triglycerides were higher in postpubertal individuals. Lipid biomarker differences by age and age ∗ sex statistical interactions were not observed. These data represent a novel compilation of serum lipid biomarkers from a large population of sanctuary-housed Western chimpanzees (Pan troglodytes verus) within a range country, a population not previously studied with regard to serum lipid biomarkers. This study has documented significant differences compared to known values from managed chimpanzees and human reference ranges. The relationship of serum lipid biomarkers with health and disease in great apes remains understudied, but the present data set provides a basis for future studies to ascertain whether these differences are healthy biomarker variations or represent an elevated risk factor for disease. Full article

The term heart disease refers to a wide range of conditions that impact the heart and blood vessels. It continues to be a major global cause of morbidity and mortality. The narrowing or blockage of blood vessels, which can result in major medical events like heart attacks, angina (chest pain) or strokes, is a common issue linked to heart disease. In order to lower the risk of serious complications and facilitate prompt medical intervention, early diagnosis and prediction are essential. This study developed predictive models that can precisely identify people at risk by applying a variety of machine learning algorithms to a structured dataset on heart disease. Blood pressure, cholesterol, age, gender, and other health-related indicators are among the 13 essential characteristics that make up the dataset. Numerous machine learning models such as Naïve Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, Random Forest, and others were trained using these features. Using the RapidMiner platform, which offered a visual environment for data preprocessing, model training, and performance analysis, all models were created and assessed. The best-performing model was the Naïve Bayes classifier which achieved an impressive accuracy rate of 90% after extensive testing and comparison of performance metrics like accuracy precision and recall. This outcome shows how well the model can predict heart disease in actual clinical settings. By supporting individualized health recommendations, enabling early diagnosis, and facilitating timely treatment, the effective application of such models can significantly benefit patients and healthcare professionals. Furthermore, heart disease incidence can be considerably decreased by identifying and addressing modifiable risk factors such as high blood pressure, elevated cholesterol, smoking, diabetes, and physical inactivity. In summary, machine learning has the potential to improve the identification and treatment of heart-related disorders. This study highlights the value of data-driven methods in healthcare and indicates that incorporating predictive models into standard medical procedures may enhance patient outcomes, lower healthcare expenses, and improve public health administration. Full article

To date, visual analysis is mainly used to evaluate images of dehydrated films (facies) of biological fluids—microscopy at various magnifications, illumination with white or polarized light, as well as using a dark field. At the same time, important information on the architectonics of optically anisotropic supramolecular networks of facies is unknown (inaccessible). In our work, a model of optical anisotropy of the architectonics of supramolecular networks of blood facies is proposed. Algorithms and a methodology for a new multifunctional method of polarization-interference visualization of the Jones matrix and digital layer-by-layer phase reconstruction of optical anisotropy maps (theziograms) have been developed. As a result, statistically significant markers of oncological changes in the polycrystalline architectonics of supramolecular networks of blood facies samples from healthy donors and patients with papillary thyroid cancer at different stages of the oncological process have been determined and physically analyzed. A comparative study of the diagnostic efficiency of Jones matrix theziography (JT) and Mueller matrix diffusion tomography (MDT) of blood facies samples was conducted within the framework of evidence-based medicine. The main advantages of the Jones matrix method are shown: its multifunctionality (complex detection of birefringence and dichroism), high accuracy of early (stage 1: JM—90.4% and MDT—78.8%) and current (stage 2: JM—96.2% and MDT—88.5%) cancer diagnostics and an excellent level (JM—94.2% and MDT—84.6%) of differentiation of papillary thyroid cancer stages. Full article

Atrial fibrillation (AF) is a prevalent heart arrhythmia, characterized by an irregularly irregular rhythm and the absence of identifiable P waves on ECG. Given the loss of effective atrial contraction, AF carries a risk of serious complications. If untreated, AF can promote thrombogenesis, leading to stroke, systemic embolism (e.g., limb or organ ischemia), and myocardial infarction. These serious complications highlight the importance of understanding AF and assessing stroke risk to guide optimal management of this chronic arrhythmia. Congruent with recent technological developments, advanced imaging has emerged as a modality to better understand AF. This review highlights advanced imaging techniques and their advantages, with a focus on 4D flow MRI, a novel modality that enables visualization of blood flow patterns in three dimensions and provides unique insights into cardiac hemodynamics. It also synthesizes the current literature on key hemodynamic markers identified by 4D flow MRI, including blood flow stasis, wall shear stress, and vorticity. Quantifying these markers has improved predictive accuracy of future stroke risk in AF patients, allowing clinicians to risk stratifying their patients and optimize management. Finally, the review discusses potential future markers that may further refine our understanding of AF and inform patient care. Full article

COVID-19 infection is often accompanied by psychological symptoms, which may persist long after the end of the infection (long COVID). The symptoms include fatigue, cognitive impairment, and anxiety. The reason for these long-term effects is currently unclear. Therapeutic approaches have included cognitive rehabilitation therapy, physical activity, and serotonin reuptake inhibitors (SSRIs) if depression co-exists. The neuropsychological evaluation of subjects with suspected cognitive issues is essential for the correct diagnosis. Most of the COVID-19 studies used the Montreal Cognitive Assessment (MoCA) or the Mini Mental State Examination (MMSE). However, MoCA scores can be confusing if not interpreted correctly. For this reason, we have developed an original technique to map cognitive domains and motor performance on various brain areas in COVID-19 patients aiming at improving the follow-up of long-COVID-19 symptoms. To this end, we retrospectively reanalyzed data from a cohort of 40 patients hospitalized for COVID-19 without requiring intubation or hemodialysis. Cognitive function was tested during hospitalization and six months after. Global cognitive function and cognitive domains were retrieved using MoCA tests. Laboratory data were retrieved regarding kidney function, electrolytes, acid–base, blood pressure, TC score, and P/F ratio. The dimensionality of cognitive functions was represented over cortical brain structures using a transformation matrix derived from fMRI data from the literature and the Cerebroviz mapping tool. Memory function was linearly dependent on the P/F ratio. We also used the UMAP method to reduce the dimensionality of the data and represent them in low-dimensional space. Six months after hospitalization, no cases of severe cognitive deficit persisted, and the number of moderate cognitive deficits reduced from 14% to 4%. Most cognitive domains (visuospatial abilities, executive functions, attention, working memory, spatial–temporal orientation) improved over time, except for long-term memory and language skills, which remained reduced or slightly decreased. The Cerebroviz algorithm helps to visualize which brain regions might be involved in the process. Many patients with COVID-19 continue to suffer from a subclinical cognitive deficit, particularly in the memory and language domains. Cerebroviz’s representation of the results provides a new tool for visually representing the data. Full article

Background/Objectives: Behavioral variant frontotemporal dementia (bvFTD), the most prevalent clinical subtype within the frontotemporal lobar degeneration spectrum disorders, is characterized by early and prominent changes that significantly disrupt everyday functioning. This study aims to identify the key correlates of functional status in bvFTD by investigating the relative contributions of cognitive deficits, behavioral disturbances, personality changes, and brain perfusion abnormalities. Additionally, it seeks to develop a theoretical framework to elucidate how these factors may interconnect and shape unique functional profiles. Methods: A total of 26 individuals diagnosed with bvFTD were recruited from the 2nd Neurology Clinic of “AHEPA” University Hospital in Thessaloniki, Greece, and underwent a comprehensive neuropsychological assessment to evaluate their cognitive functions. Behavioral disturbances, personality traits, and functional status were rated using informant-based measures. Regional cerebral blood flow was assessed using Single Photon Emission Computed Tomography (SPECT) imaging to evaluate brain perfusion patterns. Penalized Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to identify the most robust correlates of functional impairment, followed by path analyses using structural equation modeling to explore how these factors may interrelate and contribute to functional disability. Results: The severity of negative behavioral symptoms (e.g., apathy), conscientiousness levels, and performance on neuropsychological measures of semantic verbal fluency, visual attention, visuomotor speed, and global cognition were identified as the strongest correlates of performance in activities of daily living. Neuroimaging analysis revealed hypoperfusion in the right prefrontal (Brodmann area 8) and inferior parietal (Brodmann area 40) cortices as statistically significant neural correlates of functional impairment in bvFTD. Path analyses indicated that reduced brain perfusion was associated with attentional and processing speed deficits, which were further linked to more severe negative behavioral symptoms. These behavioral disturbances were subsequently correlated with declines in global cognition and conscientiousness, which were ultimately associated with poorer daily functioning. Conclusions: Hypoperfusion in key prefrontal and parietal regions, along with the subsequent cognitive and neuropsychiatric manifestations, appears to be associated with the pronounced functional limitations observed in individuals with bvFTD, even in early stages. Understanding the key determinants of the disease can inform the development of more targeted, personalized treatment strategies aimed at mitigating functional deterioration and enhancing the quality of life for affected individuals. Full article

Cells of the innate immune system, particularly natural killer (NK) cells, serve as the first line of defense against tumor development and play a critical role in antitumor immunity. Characterizing the immune cell pool and its functional state is essential for understanding immunotherapy mechanisms and identifying key cellular players. However, defining NK cell populations in mice, the primary model for cancer immunotherapy, is challenging due to strain-specific marker variability and the absence of a universal NK cell marker, such as human CD56. This study evaluates surface markers of NK and other peripheral blood immune cells in both humans and mice, associating these markers with specific functional profiles. Bioinformatic approaches are employed to visualize these markers, enabling rapid immunoprofiling. We explore the translational relevance of these markers in assessing immunotherapy efficacy, including their gene associations, ligand interactions, and interspecies variations. Markers compatible with rapid flow-cytometry-based detection are prioritized to streamline experimental workflows. We propose a standardized immunoprofiling strategy for monitoring systemic immune status and evaluating the effectiveness of immunotherapy in preclinical and clinical settings. This approach facilitates the design of preclinical studies that aim to identify predictive biomarkers for immunotherapy outcomes by monitoring immune status. Full article

Objective: Vitamin D deficiency (VDD) is common in pregnancy and may affect lipid metabolism. The underlying mechanisms are multifactorial, but most evidence so far comes from non-pregnant populations. This study aims to identify metabolites and metabolic patterns associated with VDD in early pregnancy and to evaluate their relationships with maternal lipid profiles. Methods: A nested case–control research was carried out in the Zhoushan Pregnant Women Cohort (ZPWC). Cases were defined as women with VDD (25(OH)D < 20 ng/mL), and controls (≥20 ng/mL) were matched 1:1 using propensity scores based on age, pre-pregnancy BMI, gestational week, and calendar year at blood sampling. The untargeted metabolomics of first-trimester maternal plasma were measured. Metabolic profiles were analyzed using partial least squares-discriminant analysis (PLS-DA). Principal component analysis (PCA) was applied to visualize group separation, and metabolite set enrichment analysis (MSEA) was performed to reveal biologically relevant metabolic patterns. Associations between VDD-related metabolite components in early pregnancy and lipid levels in mid-pregnancy were assessed using linear regression models. Results: 44 cases and 44 controls were selected for the study. There were 60 metabolites identified as being connected to VDD. Among these, 26 metabolites, primarily glycerophospholipids and fatty acyls, exhibited decreased levels in the VDD group. In contrast, 34 metabolites showed increased levels, mainly comprising benzene derivatives, carboxylic acids, and organooxygen compounds. PCA based on these metabolites explained 52.8% of the total variance (R²X = 0.528) across the first six principal components (PC1: 16.4%, PC2: 10.6%, PC3: 9.2%, PC4: 6.3%, PC5: 5.7%, PC6: 4.6%). PC2, dominated by lineolic acids and derivatives, was negatively associated with total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) (all p < 0.01). PC3, dominated by glycerophosphocholines, was negatively associated with TC, TG, and high-density lipoprotein cholesterol (HDL-C) (all p < 0.05). MSEA revealed significant enrichment of the pantothenate and CoA biosynthesis pathway after multiple testing correction (FDR < 0.05). Conclusions: This study reveals distinct metabolic alterations linked to VDD and suggests potential mechanisms underlying its association with maternal lipid metabolism in early pregnancy. Full article

Mesenchymal stem cells (MSCs) are known to assist liver regeneration. In this study, we show a dose-dependent mode of recovery from liver fibrosis after intravenous injections of MSCs. Male Wistar rats experienced a 42-day-long modeling of liver fibrosis via CCl₄ poisoning and received either a single injection of 2.5 × 10⁶ MSCs on Day 3 after the last CCl₄ dose or two MSC injections on Days 3 and 10. We dynamically monitored levels of liver cytolysis markers and cytokines in the venous blood and performed a histological study of Mallory-stained liver sections. All experimental groups experienced a nearly complete recovery of biochemical markers up to 4 weeks after the end of CCl₄ administration, although we observed anti-inflammatory changes in the cytokine levels only in animals treated by two MSC injections. Histological study revealed minor signs of liver damage up to Day 90 in animals receiving two MSC doses with worse pathology in those who received a single MSC dose. Morphometric values stayed consistent with visual data, demonstrating a significantly larger number of binuclear hepatocytes, a smaller number of false lobules, and a lesser area of connective tissue proper in animals treated by two MSC injections. Our results reflect MSC grafting in applied doses to affect liver fibrosis in a dose-dependent mode. These findings provide a deeper understanding of MSC action in liver fibrosis, and the doses applied may serve as a milestone for further studies in humans. Full article

Extracellular vesicles are critical mediators of intercellular signaling. Recent studies have revealed that, in addition to vesicular structures, smaller non-vesicular nanoparticles—termed exomeres and supermeres—also participate in intercellular communication. Detailed characterization of these nanoscale entities within biological systems is essential for elucidating their structural and functional roles. Due to their sub-50 nm dimensions, high-resolution imaging modalities such as atomic force microscopy and electron microscopy are currently the primary techniques available for their visualization. In the present study, we employed low-voltage scanning electron microscopy to investigate the size of exomeres and supermeres isolated from human blood plasma via high-speed ultracentrifugation. Platelet-poor plasma was obtained from the blood of six healthy donors (two women and four men, aged 21–46 years). By ultracentrifugation (170,000× g for 4 h), the plasma was purified of extracellular vesicles. Two fractions were sequentially isolated: one containing exomeres (170,000× g for 20 h) and one containing supermeres (370,000× g for 20 h). The particles were examined using a Zeiss Auriga microscope with no sputter coating at an accelerating voltage of 0.4–0.5 kV. The images obtained from the fractions showed particles 10–50 nm in diameter, both individual particles and aggregated structures. The fractions were also slightly contaminated with larger particles, supposedly extracellular vesicles. Examining the fractions using a dynamic light scattering device additionally revealed the presence of particles 10–18 nm in size. It should be noted that the fractions obtained did indeed contain particles measuring 10–50 nm, which corresponds to the size of exomeres and supermeres. Low-voltage scanning electron microscopy allows for examination of the structure of exomeres and supermeres in blood plasma fractions. However, it should be noted that without the use of immunological identification, this method does not allow exomeres and supermeres to be distinguished from accompanying particles. It should also be noted that because the size of exomeres and supermeres is close to the detection threshold of low-voltage scanning electron microscopy, in such studies it is generally only possible to detect the size of these particles. Full article

Background/Objectives: Cervical spine disease requiring surgical intervention is a major cause of disability. Anterior cervical discectomy and fusion (ACDF) is a well-established procedure for treating cervical pathology; however, there remains no consensus on whether 1-level versus 2-level ACDF yields comparable outcomes. This study compares 1-level versus 2-level ACDF by evaluating surgery-related and postoperative outcomes, radiographic parameters, and patient-reported outcome measures (PROMs). Methods: PubMed, Embase, Scopus, and Cochrane Library were searched through 10 July 2024. Studies comparing 1-level with 2-level ACDF were included. Data on operating room (OR) time, estimated blood loss (EBL), length of hospital stay (LOS), complications, and PROMs, including Neck Disability Index (NDI) and Visual Analogue Scale (VAS) for neck and arm pain, were extracted. Results: Thirteen studies met our inclusion criteria, comprising 2091 patients (1078 undergoing 1-level and 1013 2-level ACDF). No statistically significant differences were observed in EBL or LOS between the cohorts. However, the 2-level ACDF group showed significantly longer OR times (p-value < 0.001) and higher odds of developing dysphagia (p-value = 0.05). Patients undergoing 2-level ACDF showed greater correction in cervical lordosis. Both cohorts reported similar statistically and clinically significant improvements in VAS neck and NDI scores at final follow-up. There was no difference in adjacent segment disease or revision surgery at final follow-up. Conclusions: Both 1-level and 2-level ACDF improve clinical and radiographic outcomes. The choice should be tailored to the patient’s pathology and anatomy while considering the higher dysphagia risk with additional fusion levels. This study highlights the importance of individualized surgical planning to optimize postoperative outcomes while minimizing complications. Full article