Association between Circadian Rhythm-Disturbing Factors and Metabolic Syndrome in Korean Adults: Korea National Health and Nutrition Examination Survey (2016-2020).

Background: Circadian misalignment is associated with metabolic syndrome. This study aimed to examine the association between circadian rhythm-disturbing factors and metabolic syndrome. Methods: We used data from the 7th and 8th Korea National Health and Nutrition Examination Survey conducted between 2016 and 2020, which surveyed 16,253 individuals. Circadian rhythm-disturbing factors were defined as follows: sleep duration outside the reference group (6-8 hours), irregular breakfast, shift work, and physical inactivity. The adjusted odds ratio (aOR) for metabolic syndrome was calculated based on the number of circadian rhythm-disturbing factors present in adults over the age of 19 years. Results: Among a total of 16,253 participants (mean age 48.2±15 years), metabolic syndrome was found in 5,237 participants (29.3 %). The participants were classified into three categories based on the number of circadian rhythm-disturbing factors as follows: 2,627 (15.6%) did not have any factors, 6,406 (38.13%) had one factor, and 7,220 (46.3%) had two or more factors. Participants with a single circadian rhythm-disturbing factor were 21% more likely to have metabolic syndrome (aOR, 1.21; 95% confidence interval [CI], 1.08-1.36), and participants with two or more factors were 27% more likely to have metabolic syndrome (aOR, 1.27; 95% CI, 1.12-1.43). Conclusion: Circadian rhythm-disturbing factors were significantly associated with the prevalence of metabolic syndrome in Korean adults. This finding has potential clinical implications for maintaining circadian rhythms by avoiding certain factors to prevent metabolic syndrome. Further studies are required to confirm these findings.

Posterior Approach and Inferior Capsulotomy in Bipolar Hemiarthroplasty for Femoral Neck Fractures: Comparison with Superior Capsulotomy.

Background: Hemiarthroplasty is frequently used to treat displaced femoral neck fractures in elderly patients, but it has a higher risk of postoperative dislocation. We introduced the posterior approach and inferior capsulotomy (PAICO) to enhance joint stability after bipolar hemiarthroplasty for femoral neck fracture. We evaluated whether the PAICO would have a lower dislocation rate than the conventional posterior approach with superior capsulotomy. Methods: From January 2021 to December 2021, we prospectively recruited 25 patients (25 hips) aged 50 years or older who underwent bipolar hemiarthroplasty for femoral neck fractures due to low-energy trauma as the PAICO group. We compared the PAICO group with a historical control group who had undergone hemiarthroplasty in 7 institutes between 2010 and 2020. The primary endpoint was dislocation within 1 year after the surgery. We compared data from the PAICO group with the data from the historical control group from the Korean Hip Fracture Registry which was carried out in South Korea. Results: A total of 25 patients (25 hips) were enrolled in the present study; 3,477 patients (3,571 hips) who underwent bipolar hemiarthroplasty were reviewed as the historical control group. In the PAICO group, we observed no dislocation, whereas the dislocation rate in the control group was 1.3%. Conclusions: In patients with displaced femoral neck fractures, the PAICO approach demonstrated comparable results in operation time and complication rates when compared to bipolar hemiarthroplasty using superior capsulotomy. Notably, there were no observed cases of dislocation among patients who underwent the PAICO approach. We recommend this PAICO approach to surgeons using the posterior approach, hoping to prevent dislocation in bipolar hemiarthroplasty.

Recent Update on the Prevalence of Sarcopenia in Koreans: Findings from the Korea National Health and Nutrition Examination Survey.

BACKGROUND: As recognized by the World Health Organization in 2016 with its inclusion in the International Classification of Diseases, Tenth Revision as M62.84, and by South Korea in 2021 as M62.5, the diagnostic guidelines for sarcopenia vary globally. Despite its prevalence in older populations, data on sarcopenia in Koreans aged 60 and above is scarce, highlighting the need for research on its prevalence in this demographic. METHODS: Utilizing the 2022 Korea National Health and Nutrition Examination Survey dataset, sarcopenia was assessed among 1,946 individuals aged 60 or older according to the Asian Working Group for Sarcopenia 2019 criteria, incorporating grip strength and bioelectrical impedance analysis measurements. Statistical analyses were performed to differentiate categorical and continuous variables using logistic regression and Student's t-tests, respectively. RESULTS: The prevalence of sarcopenia was found to increase with age, with the highest prevalence observed in the oldest age group (80 years and older). The overall prevalence of sarcopenia in our study population was 6.8%. Among men, the prevalence of sarcopenia was 5.5% in the 60 or older age group, 9.6% in the 70 or older age group, and 21.5% in the 80 or older age group. Among women, the prevalence of sarcopenia was 7.9%, 10.5%, and 25.9%, respectively. CONCLUSIONS: This study highlights the significant burden of sarcopenia in elderly Koreans, particularly among the oldest individuals. These findings call for targeted interventions to manage and prevent sarcopenia, along with further research on its risk factors, consequences, and effective mitigation strategies.

Family-based genome-wide association analysis of novelty seeking in a Korean schizophrenic population: A pilot study.

Schizophrenia (SPR) is the most devastating mental illness that causes severe deterioration in social and occupational functioning, but, the etiology remains unknown. The objective of this study is to explore the genetic underpinnings of novelty seeking behavior in schizophrenic family within the Korean population. By conducting a family-based genome-wide association study, we aim to identify potential genetic markers and variations associated with novelty seeking traits in the context of SPR. We have recruited 27 probands (with SPR) with their parents and siblings whenever possible. DNA was extracted from blood sampling of 58 individuals in 27 families and analyzed in an Illumina core exome single nucleotide polymorphism (SNP) array. A family-based association test (qFAM) was used to derive SNP association values across all chromosomes. Although none of the final 800,000 SNPs reached the genome-wide significant threshold of 8.45 × 10-7, the most significant 4 SNPs were within the 10-5 to 10-7. This study identifies genetic associations between novelty seeking behavior and SPR within families. RAPGEF5 emerges as a significant gene, along with other neuropsychiatric-related genes. Noteworthy genes like DRD4 and COMT did not show associations, possibly due to the focus on schizophrenic family. While shedding light on this complex relationship, larger studies are needed for robust conclusions and deeper mechanistic insights.

Comparison of the Surgical Outcome between the Multiple Screw Fixation and Fixed Angle Devices for the Basicervical Femoral Neck Fractures.

Introduction: Basicervical femoral neck fracture (FNF) is an uncommon type of femoral neck fracture and is associated with an increased risk of fixation failure due to its inherent instability. The purpose of this study was to compare the surgical parameters and reoperation rate between the use of a multiple cannulated screw (MCS) and fixed angle device (FAD) in treating basicervical FNFs. Methods: We retrospectively reviewed the records of 885 patients who underwent internal fixation between May 2004 and August 2019 to determine basicervical FNF with at least 12 months of follow-up. Among the identified 77 patients with basicervical FNF, 17 patients who underwent multiple cannulated screw (MCS) fixation and 36 patients who underwent fixed angle device (FAD) fixation were included. We compared the rates of fracture-site collapse and reoperations according to the fixation device. Results: Among the 53 patients with basicervical FNF, 13 patients (24.5%) sustained surgical complications (8 collapses of fracture site and 5 reoperations). The reoperation rate in the MCS group was significantly higher than that in the FAD group (23.5% vs. 2.8%, p = 0.016), without any significant difference in the collapse of the fracture site (11.8% vs. 16.7%, p = 0.642). Conclusions: Although basicervical FNF was rare among hip fractures, fracture site collapse was prevalent and prone to fixation failure. Surgeons should keep this in mind, and consider FAD for basicervical FNF.

Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques.

Background: As the population ages, the rates of hip diseases and fragility fractures are increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly patients. With the increasing number of THA surgeries and diverse surgical methods, there is a need for standard evaluation protocols. This study aimed to use deep learning algorithms to classify THA videos and evaluate the accuracy of the labelling of these videos. Methods: In our study, we manually annotated 7 phases in THA, including skin incision, broaching, exposure of acetabulum, acetabular reaming, acetabular cup positioning, femoral stem insertion, and skin closure. Within each phase, a second trained annotator marked the beginning and end of instrument usages, such as the skin blade, forceps, Bovie, suction device, suture material, retractor, rasp, femoral stem, acetabular reamer, head trial, and real head. Results: In our study, we utilized YOLOv3 to collect 540 operating images of THA procedures and create a scene annotation model. The results of our study showed relatively high accuracy in the clear classification of surgical techniques such as skin incision and closure, broaching, acetabular reaming, and femoral stem insertion, with a mean average precision (mAP) of 0.75 or higher. Most of the equipment showed good accuracy of mAP 0.7 or higher, except for the suction device, suture material, and retractor. Conclusions: Scene annotation for the instrument and phases in THA using deep learning techniques may provide potentially useful tools for subsequent documentation, assessment of skills, and feedback.

Digital Templating of Hip Arthroplasty Using Microsoft PowerPoint: A Pilot Study with Technical Details.

Templating is essential in hip arthroplasty preparation, facilitating implant size prediction and surgical rehearsal. It ensures the selection of suitable implants according to patient anatomy and disease, aiming to minimize post-operative complications. Various templating methods exist, including traditional acetate templating on both analog and digital images, alongside digital templating on digital images, which is categorized into 2D and 3D approaches. Despite the popularity of acetate templating on digital images, challenges such as the requirement for physical templates and result preservation persist. To address these limitations, digital templating with software like OrthoSize and Orthoview has been suggested, although not universally accessible. This technical note advocates for Microsoft PowerPoint as an effective alternative for 2D digital templating, highlighting its user-friendly features for image manipulation without needing specialized software. The described method involves scanning acetate templates, adjusting the images in PowerPoint 365 for size, position, and calibration on patient radiographs, and demonstrating reliability through preliminary assessments, with intraclass correlation coefficient (ICC) values indicating a high level of agreement for cup and stem size (ICC = 0.860, 0.841, respectively) but moderate for neck length (ICC = 0.592). We have introduced a method for performing 2D digital templating in the clinical field without the need for specialized software dedicated to digital templating. We believe this method significantly improves the accessibility to 2D digital templating, which was previously limited by the need for digital templating software. Additionally, it enables surgeons to easily establish arthroplasty plans and share them, overcoming the limitations of acetate templates.

RefQSR: Reference-Based Quantization for Image Super-Resolution Networks.

Single image super-resolution (SISR) aims to reconstruct a high-resolution image from its low-resolution observation. Recent deep learning-based SISR models show high performance at the expense of increased computational costs, limiting their use in resource-constrained environments. As a promising solution for computationally efficient network design, network quantization has been extensively studied. However, existing quantization methods developed for SISR have yet to effectively exploit image self-similarity, which is a new direction for exploration in this study. We introduce a novel method called reference-based quantization for image super-resolution (RefQSR) that applies high-bit quantization to several representative patches and uses them as references for low-bit quantization of the rest of the patches in an image. To this end, we design dedicated patch clustering and reference-based quantization modules and integrate them into existing SISR network quantization methods. The experimental results demonstrate the effectiveness of RefQSR on various SISR networks and quantization methods.

Application of clinical decision support tools for predicting outcomes with vedolizumab therapy in patients with inflammatory bowel disease: A KASID multicentre study.

BACKGROUND/AIM: We aimed to validate clinical decision support tools (CDSTs) to predict real-life effectiveness of vedolizumab (VDZ) in patients with inflammatory bowel disease. METHODS: We retrospectively enrolled patients with Crohn's disease (CD) or ulcerative colitis (UC) treated with VDZ at 10 tertiary referral centres in Korea between January 2017 and November 2021. We assessed clinical remission (CREM) and response (CRES), corticosteroid-free clinical remission (CSF-CREM) and response (CSF-CRES), biochemical response based on C-reactive protein (BioRES[CRP]) and faecal calprotectin (BioRES[FC]), endoscopic healing (EH), and the need to optimise or switch drugs based on CDST-defined response groups. Additionally, the area under the receiver operating characteristics curve (AUC) for the CDSTs was calculated. RESULTS: We included 143 patients with CD and 219 with UC. We observed incremental trends on CSF-CRES at week 14 (W14) (ptrend = 0.004) and decreasing trends for the need to optimise or switch drugs (ptrend = 0.016) in CD from the low to high probability groups. Except for CSF-CREM at W54, we noticed incremental trends for all clinical responses at W14, W26 and W54 (ptrend <0.001) in UC. W26 and W54 BioRES[CRP] and W14 EH also showed increasing trends (ptrend <0.05) in UC. With increasing probabilities of response, drug optimisation or switching was less frequently required in UC (ptrend = 0.013). With 26 points cut-off, CDSTs effectively identified W14 CSF-CRES, W26 BioRES[CRP], BioRES[FC] and W54 BioRES[CRP] in UC, all with AUCs >0.600, whereas CDSTs showed poor accuracy in CD. CONCLUSIONS: CDSTs for VDZ had acceptable accuracy in predicting effectiveness outcomes including clinical and biochemical outcomes in UC. However, their utility in CD was limited.

Human umbilical cord/placenta mesenchymal stem cell conditioned medium attenuates intestinal fibrosis in vivo and in vitro.

BACKGROUND: A significant unmet need in inflammatory bowel disease is the lack of anti-fibrotic agents targeting intestinal fibrosis. This study aimed to investigate the anti-fibrogenic properties and mechanisms of the conditioned medium (CM) from human umbilical cord/placenta-derived mesenchymal stem cells (UC/PL-MSC-CM) in a murine intestinal fibrosis model and human primary intestinal myofibroblasts (HIMFs). METHODS: UC/PL-MSC-CM was concentrated 15-fold using a 3 kDa cut-off filter. C57BL/6 mice aged 7 weeks old were randomly assigned to one of four groups: (1) control, (2) dextran sulfate sodium (DSS), (3) DSS + CM (late-phase treatment), and (4) DSS + CM (early-phase treatment). Chronic DSS colitis and intestinal fibrosis was induced by three cycles of DSS administration. One DSS cycle consisted of 7 days of oral DSS administration (1.75%, 2%, and 2.5% DSS), followed by 14 days of drinking water. UC/PL-MSC-CM was intraperitoneally administered in the late phase (from day 50, 10 times) or early phase (from day 29, 10 times) of DSS cycles. HIMFs were treated with TGF-ß1 and co-treated with UC/PL-MSC-CM (10% of culture media) in the cellular model. RESULTS: In the animal study, UC/PL-MSC-CM reduced submucosa/muscularis propria thickness and collagen deposition, which improved intestinal fibrosis in chronic DSS colitis. The UC/PL-MSC-CM significantly reduced the expressions of procollagen1A1 and α-smooth muscle actin, which DSS significantly elevated. The anti-fibrogenic effect was more apparent in the UC-MSC-CM or early-phase treatment model. The UC/PL-MSC-CM reduced procollagen1A1, fibronectin, and α-smooth muscle actin expression in HIMFs in the cellular model. The UC/PL-MSC-CM downregulated fibrogenesis by suppressing RhoA, MRTF-A, and SRF expression. CONCLUSIONS: Human UC/PL-MSC-CM inhibits TGF-ß1-induced fibrogenic activation in HIMFs by blocking the Rho/MRTF/SRF pathway and chronic DSS colitis-induced intestinal fibrosis. Thus, it may be regarded as a novel candidate for stem cell-based therapy of intestinal fibrosis.

Precise individual muscle segmentation in whole thigh CT scans for sarcopenia assessment using U-net transformer.

The study aims to develop a deep learning based automatic segmentation approach using the UNETR(U-net Transformer) architecture to quantify the volume of individual thigh muscles(27 muscles in 5 groups) for Sarcopenia assessment. By automating the segmentation process, this approach improves the efficiency and accuracy of muscle volume calculation, facilitating a comprehensive understanding of muscle composition and its relationship to Sarcopenia. The study utilized a dataset of 72 whole thigh CT scans from hip fracture patients, annotated by two radiologists. The UNETR model was trained to perform precise voxel-level segmentation and various metrics such as dice score, average symmetric surface distance, volume correlation, relative absolute volume difference and Hausdorff distance were employed to evaluate the model's performance. Additionally, the correlation between Sarcopenia and individual thigh muscle volumes was examined. The proposed model demonstrated superior segmentation performance compared to the baseline model, achieving higher dice scores (DC = 0.84) and lower average symmetric surface distances (ASSD = 1.4191 ± 0.91). The volume correlation between Sarcopenia and individual thigh muscles in the male group. Furthermore, the correlation analysis of grouped thigh muscles also showed negative associations with Sarcopenia in the male participants. This thesis presents a deep learning based automatic segmentation approach for quantifying individual thigh muscle volume in sarcopenia assessment. The results highlights the associations between Sarcopenia and specific individual muscles as well as grouped thigh muscle regions, particularly in males. The proposed method improves the efficiency and accuracy of muscle volume calculation, contributing to a comprehensive evaluation of Sarcopenia. This research enhances our understanding of muscle composition and performance, providing valuable insights for effective interventions in Sarcopenia management.

A machine learning model for prediction of sarcopenia in patients with Parkinson's Disease.

OBJECTIVE: Patients with Parkinson's disease (PD) have an increased risk of sarcopenia which is expected to negatively affect gait, leading to poor clinical outcomes including falls. In this study, we investigated the gait patterns of patients with PD with and without sarcopenia (sarcopenia and non-sarcopenia groups, respectively) using an app-derived program and explored if gait parameters could be utilized to predict sarcopenia based on machine learning. METHODS: Clinical and sarcopenia profiles were collected from patients with PD at Hoehn and Yahr (HY) stage ≤ 2. Sarcopenia was defined based on the updated criteria of the Asian Working Group for Sarcopenia. The gait patterns of the patients with and without sarcopenia were recorded and analyzed using a smartphone application. The random forest model was applied to predict sarcopenia in patients with PD. RESULTS: Data from 38 patients with PD were obtained, among which 9 (23.7%) were with sarcopenia. Clinical parameters were comparable between the sarcopenia and non-sarcopenia groups. Among various clinical and gait parameters, the average range of motion of the hip joint showed the highest association with sarcopenia. Based on the random forest algorithm, the combined difference in knee and ankle angles from standing still before walking to the maximum angle during walking (Kneeankle_diff), the difference between the angle when standing still before walking and the maximum angle during walking for the ankle (Ankle_dif), and the min angle of the hip joint (Hip_min) were the top three features that best predict sarcopenia. The accuracy of this model was 0.949. CONCLUSIONS: Using smartphone app and machine learning technique, our study revealed gait parameters that are associated with sarcopenia and that help predict sarcopenia in PD. Our study showed potential application of advanced technology in clinical research.

Quality of life in sarcopenia measured with the SarQoL questionnaire: A meta-analysis of individual patient data.

Age-related sarcopenia, resulting from a gradual loss in skeletal muscle mass and strength, is pivotal to the increased prevalence of functional limitation among the older adult community. The purpose of this meta-analysis of individual patient data is to investigate the difference in health-related quality of life between sarcopenic individuals and those without the condition using the Sarcopenia Quality of Life (SarQoL) questionnaire. A protocol was published on PROSPERO. Multiple databases and the grey literature were searched until March 2023 for studies reporting quality of life assessed with the SarQoL for patients with and without sarcopenia. Two researchers conducted the systematic review independently. A two-stage meta-analysis was performed. First, crude (mean difference) and adjusted (beta coefficient) effect sizes were calculated within each database; then, a random effect meta-analysis was applied to pool them. Heterogeneity was measured using the Q-test and I2 value. Subgroup analyses were performed to investigate the source of potential heterogeneity. The strength of evidence of this association was assessed using GRADE. From the 413 studies identified, 32 were eventually included, of which 10 were unpublished data studies. Sarcopenic participants displayed significantly reduced health-related quality of life compared with non-sarcopenic individuals (mean difference = -12.32; 95 % CI = [-15.27; -9.37]). The model revealed significant heterogeneity. Subgroup analyses revealed a substantial impact of regions, clinical settings, and diagnostic criteria on the difference in health-related quality of life between sarcopenic and non-sarcopenic individuals. The level of evidence was moderate. This meta-analysis of individual patient data suggested that sarcopenia is associated with lower health-related quality of life measured with SarQoL.

Hip Fractures in Centenarians: Functional Outcomes, Mortality, and Risk Factors from a Multicenter Cohort Study.

Background: Increasing longevity has caused the very old population to become the fastest-growing segment. The number of centenarians (over 100 years old) is increasing rapidly. Fractures in the elderly lead to excessive medical costs and decreased quality of life with socioeconomic burdens. However, little research has thoroughly examined the functional outcomes and mortality of hip fractures in centenarians. Methods: This is a retrospective observational study. Sixty-eight centenarian hip fracture patients were admitted to the 10 institutions from February 2004 to December 2019. Fifty-six patients with 1-year follow-up were finally included. The following data were obtained: sex, age, body mass index, Charlson comorbidity index value on the operation day, Koval's classification for ambulatory ability, type of fracture, the time interval from trauma to surgery, American Society of Anesthesiologists grade, surgery-related complications, and duration of hospital stay. Postoperative Koval's classification (at 1 year after surgery) and information about death were also collected. Multivariate analysis was performed to analyze the risk factors affecting mortality 1 year after surgery. Results: Mortality rates were 26.8% at 6 months and 39.3% at 1 year. The 90-day mortality was 19.6%, and one of them (2.1%) died in the hospital. The 1-year mortality rates for the community ambulatory and non-community ambulatory groups were 29% and 52%, respectively. Only 9 (16.1%) were able to walk outdoors 1 year after surgery. The remaining 47 patients (83.9%) had to stay indoors after surgery. Multivariate analysis demonstrated that the pre-injury ambulatory level (adjusted hazard ratio, 2.884; p = 0.034) was associated with the risk of mortality. Conclusions: We report a 1-year mortality rate of 39.3% in centenarian patients with hip fractures. The risk factor for mortality was the pre-injury ambulatory status. This could be an important consideration in the planning of treatment for centenarian hip fracture patients.

Effectiveness and Usefulness of Bone Turnover Marker in Osteoporosis Patients: A Multicenter Study in Korea.

BACKGROUND: This study aimed to investigate real-world data of C-terminal telopeptide (CTX), propeptide of type I collagen (P1NP), and osteocalcin through present multicenter clinical study, and retrospectively analyze the usefulness of bone turnover markers (BTMs) in Koreans. METHODS: The study focused on pre- and post-menopausal patients diagnosed with osteoporosis and excluded patients without certain test results or with test intervals of over 1 year. The demographic data and 3 BTMs (CTX, P1NP, and osteocalcin) were collected. The patients were classified by demographic characteristics and the BTM concentrations were analyzed by the group. RESULTS: Among women with no history of fractures, the levels of P1NP (N=2,100) were 43.544±36.902, CTX (N=1,855) were 0.373 ±0.927, and osteocalcin (N=219) were 10.81 ±20.631. Among men with no history of fractures, the levels of P1NP (N=221) were 48.498±52.892, CTX (N=201) were 0.370±0.351, and osteocalcin (N=15) were 7.868 ±10.674. Treatment with teriparatide increased the P1NP levels after 3 months in both men and women, with a 50% increase observed in women. Similarly, treatment with denosumab decreased the CTX levels after 3 months in both men and women, with a reduction of 50% observed in women. CONCLUSIONS: The results of this study can contribute to the accurate assessment of bone replacement status in Koreans. We also provide the P1NP level in the Korean population for future comparative studies with other populations.

Analysis of Changes in Sleep Quality and Patterns after Hip Fracture Using Real Evidence of Artificial Intelligence Linked (REAL) Hip Cohort Data.

Background and Objectives: Hip fractures are commonly found in elderly patients, and often result in chronic pain and decreased physical function, as well as worsening of overall health. It is known that early surgical intervention during the acute phase and rehabilitation are important for improving clinical outcomes for these patients. However, the importance of management for improving the quality of life of these patients is becoming more emphasized. Studies on changes in sleep patterns after hip fractures are rare overseas. Therefore, the aim of this study is to investigate the prevalence of sleep disturbance in patients with hip fractures and to analyze the changes in sleep disturbance after surgery by comparing the preoperative and postoperative results. Materials and Methods: During the period from August 2022 to January 2023, patients who underwent surgical treatment for hip fractures and were recruited into the REAL Hip Cohort were selected as research subjects. The sleep survey was conducted using the Pittsburgh Sleep Quality Index (PSQI). The PSQI is composed of 18 questions, each divided into areas of sleep quality, sleep latency, duration, efficiency, disturbance, use of medication, and daytime dysfunction. Each area is scored 0-3 points and the total is 0-21. A score greater than five indicates sleep disorder. The PSQI was surveyed during hospitalization and three months after surgery for post-fracture sleep status. To analyze changes before and after the fracture, paired T-tests and chi-square tests were performed. Results: From August 2022 to January 2023, a total of 40 patients who were recruited into the REAL Hip Cohort responded to the PSQI survey. The average age was 77.4 years and 36 were female. Sleep quality worsened from 0.75 ± 1.0 before surgery to 1.4 ± 1.0 three months after surgery (p = 0.019), and sleep efficiency also worsened from 0.4 ± 0.6 to 1.4 ± 1.0 (p < 0.001). The PSQI increased from an average of 5.2 ± 2.8 before surgery to 8.2 ± 4.2 three months after surgery (p = 0.007), and the number of patients who could be diagnosed with sleep disorders also increased from 12 (40%) to 24 (60%) (p = 0.030). Conclusions: A decline in overall sleep status was observed in patients in a survey on sleep patterns three months after hip fracture. Additional management is needed to improve their sleep patterns.

Development of droplet digital PCR-based detection of bacterial pathogens in prosthetic joint infection: a preliminary study using a synthesized model plasmid.

Periprosthetic joint infection (PJI) can be diagnosed to characterize the microorganisms constituting a biofilm, which is an essential procedure for proper treatment. The gold standard method for detecting and identifying the causative microorganism is culture of microorganisms from patients-derived sample.; however, this method takes a long time and has low sensitivity. To compensate for these limitations, identification methods based on real-time PCR (RT-PCR) have been widely used. However, RT-PCR also has limitations, including low sensitivity and the requirement of a standard curve for quantification. Therefore, to prevent significant proliferation of pathogenic bacteria, it is important to detect a limited number of infectious bacteria during early stages of PJI. In the present study, we developed droplet digital PCR-based detection of bacterial pathogens in PJI. And we evaluated the analytical performance of the assay using a model plasmid, based on the 16S ribosomal DNA sequence of target bacteria commonly found in PJI. We also prepared genomic DNA extracted from E. coli, S. aureus, and S. epidermidis to test whether ddPCR provides better sensitivity and quantification of the target sequences. ddPCR detected 400 attograms of target DNA, which was more than 10 times less than that detected by real-time PCR using synthesized plasmid. In addition, ddPCR detected target regions from genomic DNA of 50 femtograms for E. coli, 70 femtograms for S. epidermidis, and 90 femtograms for S. aureus. The results indicate that ddPCR has the potential to decrease the microbial detection limit and provide precise detection, signifying its effectiveness for early PJI.

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis.

BACKGROUND: The relationship between physical function, musculoskeletal disorders and sarcopenia is intricate. Current physical function tests, such as the gait speed test and the chair stand test, have limitations in eliminating subjective influences. To overcome this, smart devices utilizing inertial measurement unit sensors and artificial intelligence (AI)-based methods are being developed. METHODS: We employed cutting-edge technologies, including the smart insole device and pose estimation based on AI, along with three classification models: random forest (RF), support vector machine and artificial neural network, to classify control and sarcopenia groups. Patient data of 83 individuals were divided into train and test sets, with approximately 67% allocated for training. Classification models were implemented using RStudio, considering individual and combined variables obtained through pose estimation and smart insole measurements. RESULTS: Performance evaluation of the classification models utilized accuracy, precision, recall and F1-score indicators. Using only pose estimation variables, accuracy ranged from 0.92 to 0.96, with F1-scores of 0.94-0.97. Key variables identified by the RF model were 'Hip_dif', 'Ankle_dif' and 'Hipankle_dif'. Combining variables from both methods increased accuracy to 0.80-1.00, with F1-scores of 0.73-1.00. CONCLUSIONS: In our study, a classification model that integrates smart insole and pose estimation technology was assessed. The RF model showed impressive results, particularly in the case of the Hip and Ankle variables. The growth of advanced measurement technologies suggests a promising avenue for identifying and utilizing additional digital biomarkers in the management of various disorders. The convergence of AI technologies with diagnostics and treatment approaches a promising future for enhanced interventions in conditions like sarcopenia.

The Influences of Macronutrients on Bone Mineral Density, Bone Turnover Markers, and Fracture Risk in Elderly People: A Review of Human Studies.

Osteoporosis is a health condition that involves weak bone mass and a deteriorated microstructure, which consequently lead to an increased risk of bone fractures with age. In elderly people, a fracture attributable to osteoporosis elevates mortality. The objective of this review was to examine the effects of macronutrients on bone mineral density (BMD), bone turnover markers (BTMs), and bone fracture in elderly people based on human studies. A systematic search was conducted in the PubMed®/MEDLINE® database. We included human studies published up to April 2023 that investigated the association between macronutrient intake and bone health outcomes. A total of 11 meta-analyses and 127 individual human studies were included after screening the records. Carbohydrate consumption seemed to have neutral effects on bone fracture in limited studies, but human studies on carbohydrates' effects on BMD or/and BTMs are needed. The human studies analyzed herein did not clearly show whether the intake of animal, vegetable, soy, or milk basic proteins has beneficial effects on bone health due to inconsistent results. Moreover, several individual human studies indicated an association between eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and osteocalcin. Further studies are required to draw a clear association between macronutrients and bone health in elderly people.