Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Background: We investigated osteoporosis management strategies and clinical outcomes following the occurrence of medicationrelated osteonecrosis of the jaw (MRONJ). Methods: We retrospectively studied individuals diagnosed with MRONJ during osteoporosis treatment who were managed in the Osteoporosis Center or the Oral Maxillofacial Surgery & Dental Unit at Queen Mary Hospital in Hong Kong between 2010 and 2022. We examined subsequent osteoporosis management plans, fracture events, and bone mineral density (BMD). Results: Thirty-six individuals were included (mean age, 78.5 years; 94.4% women). The estimated prevalence of MRONJ was 0.26%. All patients had been exposed to bisphosphonates, and seven had also received denosumab before MRONJ. Following MRONJ, only 14 individuals continued anti-osteoporosis treatment, a decision influenced by a higher fracture probability at MRONJ onset. The most common regimen was a teriparatide-raloxifene sequence (n=8): three patients achieved stable BMD, four achieved improving BMD, and one exhibited a mixed response. The patient with a mixed BMD response had also been treated with denosumab. Six patients sustained incident fractures after MRONJ, and these patients had lower BMD T-scores than their counterparts. Two patients experienced MRONJ recurrence, which was associated with the resumption of bisphosphonate or denosumab therapy after MRONJ. These patients had higher BMD T-scores than those who did not experience MRONJ recurrence. Conclusion MRONJ is challenging because high fracture risk necessitates discontinuation of antiresorptive agents. Teriparatide followed by raloxifene may be a reasonable regimen. Individualised decisions in osteoporosis management after MRONJ are required to balance fracture risk reduction with minimising MRONJ recurrence.

Objective To explore the accumulated effects of physical activity,sedentary behavior,and sleep on cardiorespiratory fitness(CRF)among college students and provide effective measures for enhancing their CRF. Methods From May to June in 2023,223 college students aged 18 to 24 years old were recruited from Tianjin University of Science and Technology for a 24 hours activity behavior survey and CRF testing.Compositional analysis was employed to investigate the relationships of physical activity,sedentary behavior,and sleep with CRF.Isotemporal substitution models were established to predict the effects of substituting various activity behaviors on CRF.Results The proportion of time spent on moderate-to-vigorous physical activity(MVPA)was positively correlated with CRF of college students(β=6.40,P=0.002),while the proportion of time spent on sedentary behavior was negatively correlated with CRF(β=-3.02,P=0.004).Light physical activity(LPA)and sleep were not correlated with CRF(β=-1.06,P=0.504).Isotemporal substitution results for 15-min increments showed that replacing other activity behaviors with MVPA significantly increased the CRF of college students[SB:1.72 mL/(kg·min),95% CI=0.94-2.51;LPA:1.82 mL/(kg·min),95% CI=0.95-2.68;sleep:1.64 mL/(kg·min),95% CI=0.84-2.45].In the dose-response relationship from -30 min to 30 min,reallocating time from other behaviors to MVPA had greater adverse effect on CRF than reallocating time from MVPA to other behaviors.Among all the substitutions,replacing LPA with MVPA had the most beneficial effect on improving CRF.Additionally,a 5-min increment was considered the optimal tipping point for MVPA replacing other activities.Conclusions This study underscores the importance of participating in MVPA for improving the CRF of college students.The isotemporal substitution model provides clear goals for the allocation of time for these behaviors,aiding in future intervention measure development and policy-making.
Humans ; Sedentary Behavior ; Sleep ; Students ; Cardiorespiratory Fitness ; Exercise ; Young Adult ; Adolescent ; Universities ; Male ; Female

Objective To explore the effects of time reallocation among moderate-to-vigorous physical activity(MVPA),light physical activity(LPA),sedentary behavior(SB),and sleep on a body shape index(ABSI),body roundness index(BRI),conicity index(CI),and relative fat mass(RFM)of college students by the compositional isotemporal substitution method,thus providing measures for alleviating the obesity problem of college students. Methods Two hundred and ten college students(111 males and 99 females)aged 18-22 years old were recruited from Tianjin University of Science and Technology from April to June in 2023.Three-dimensional acceleration sensors were used to collect data of MVPA,LPA,SB,and sleep of college students.The body height,body weight,and waist circumference were measured,and four novel obesity indicators(ABSI,BRI,CI,and RFM)were calculated.The effects of substituting each activity behavior for 15 min on the obesity indicators were predicted,and the dose-effect relationship was explored at intervals of 5 min from -30 to 30 min.Results MVPA was negatively correlated with ABSI(β=-0.03,P=0.001),BRI(β=-0.27,P=0.049),CI(β=-0.10,P=0.001),and RFM(β=-9.95,P=0.004).LPA was negatively correlated with CI(β=-0.05,P=0.011)and RFM(β=-8.74,P=0.007).Neither SB nor sleep had correlations with ABSI,BRI,CI,and RFM.The results of 15 min isotemporal substitutions showed that increasing the MVPA time decreased the ABSI,BRI,CI,and RFM by 0.006-0.008,0.306-0.393,0.162-0.205,and 2.468-2.897,respectively.Decreasing the MVPA time increased the ABSI,BRI,CI,and RFM by 0.012-0.014,0.548-0.632,0.286-0.328,and 4.358-4.748,respectively.In the dose-effect relationship from -30 min to 30 min,MVPA was irreplaceable,and the negative benefits from substituting MVPA for other activity behaviors were much greater than the positive benefits from substituting MVPA for other activity behaviors.Conclusions Future research should take 24 hours activity behaviors as a whole.Increasing the time spent on MVPA and LPA and decreasing the time spent on SB is one of the effective ways to alleviate the obesity problem among college students.
Humans ; Male ; Students ; Female ; Young Adult ; Obesity ; Sleep ; Adolescent ; Exercise ; Universities ; Sedentary Behavior ; Body Mass Index ; Body Weight

Background/Aims: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups. Methods: The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort. Results: In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores. Conclusions Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.

Background: We evaluated changes in glycemic status, over 1 year, of coronavirus disease 2019 (COVID-19) survivors with dysglycemia in acute COVID-19. Methods: COVID-19 survivors who had dysglycemia (defined by glycosylated hemoglobin [HbA1c] 5.7% to 6.4% or random glucose ≥10.0 mmol/L) in acute COVID-19 were recruited from a major COVID-19 treatment center from September to October 2020. Matched non-COVID controls were recruited from community. The 75-g oral glucose tolerance test (OGTT) were performed at baseline (6 weeks after acute COVID-19) and 1 year after acute COVID-19, with HbA1c, insulin and C-peptide measurements. Progression in glycemic status was defined by progression from normoglycemia to prediabetes/diabetes, or prediabetes to diabetes. Results: Fifty-two COVID-19 survivors were recruited. Compared with non-COVID controls, they had higher C-peptide (P< 0.001) and trend towards higher homeostasis model assessment of insulin resistance (P=0.065). Forty-three COVID-19 survivors attended 1-year reassessment. HbA1c increased from 5.5%±0.3% to 5.7%±0.2% (P<0.001), with increases in glucose on OGTT at fasting (P=0.089), 30-minute (P=0.126), 1-hour (P=0.014), and 2-hour (P=0.165). At baseline, 19 subjects had normoglycemia, 23 had prediabetes, and one had diabetes. Over 1 year, 10 subjects (23.8%; of 42 non-diabetes subjects at baseline) had progression in glycemic status. C-peptide levels remained unchanged (P=0.835). Matsuda index decreased (P=0.007) and there was a trend of body mass index increase from 24.4±2.7 kg/m2 to 25.6±5.2 (P=0.083). Subjects with progression in glycemic status had more severe COVID-19 illness than non-progressors (P=0.030). Reassessment was not performed in the control group. Conclusion Subjects who had dysglycemia in acute COVID-19 were characterized by insulin resistance. Over 1 year, a quarter had progression in glycemic status, especially those with more severe COVID-19. Importantly, there was no significant deterioration in insulin secretory capacity.

Background::Life’s Simple 7, the former construct of cardiovascular health (CVH) has been used to evaluate adverse non-communicable chronic diseases (NCDs). However, some flaws have been recognized in recent years and Life’s Essential 8 has been established. In this study, we aimed to analyze the association between CVH defined by Life’s Essential 8 and risk of 44 common NCDs and further estimate the population attributable fractions (PAFs) of low-moderate CVH scores in the 44 NCDs.Methods::In the UK Biobank, 170,726 participants free of 44 common NCDs at baseline were included. The Life’s Essential 8 composite measure consists of four health behaviours (diet, physical activity, nicotine exposure, and sleep) and four health factors (body mass index, non-high density lipoprotein cholesterol, blood glucose, and blood pressure), and the maximum CVH score was 100 points. CVH score was categorized into low, moderate, and high groups. Participants were followed up for 44 NCDs diagnosis across 10 human system disorders according to the International Classification of Diseases 10th edition (ICD-10) code using linkage to national health records until 2022. Cox proportional hazard models were used in this study. The hazard ratios (HRs) and PAFs of 44 NCDs associated with CVH score were examined.Results::During the median follow-up of 10.85 years, 58, 889 incident NCD cases were documented. Significant linear dose-response associations were found between higher CVH score and lower risk of 25 (56.8%) of 44 NCDs. Low-moderate CVH (<80 points) score accounted for the largest proportion of incident cases in diabetes (PAF: 80.3%), followed by gout (59.6%), sleep disorder (55.6%), chronic liver disease (45.9%), chronic kidney disease (40.9%), ischemic heart disease (40.8%), chronic obstructive pulmonary disease (40.0%), endometrium cancer (35.8%), lung cancer (34.0%), and heart failure (34.0%) as the top 10. Among the eight modifiable factors, overweight/obesity explained the largest number of cases of incident NCDs in endocrine, nutritional, and metabolic diseases (35.4%), digestive system disorders (21.4%), mental and behavioral disorders (12.6%), and cancer (10.3%); however, the PAF of ideal sleep duration ranked first in nervous system (27.5%) and neuropsychiatric disorders (9.9%).Conclusions::Improving CVH score based on Life’s Essential 8 may lower risk of 25 common NCDs. Among CVH metrics, avoiding overweight/obesity may be especially important to prevent new cases of metabolic diseases, NCDs in digestive system, mental and behavioral disorders, and cancer.

Background: Insulin-treated patients with long duration of type 2 diabetes mellitus (T2DM) are at increased risk of ketoacidosis related to sodium-glucose co-transporter 2 inhibitor (SGLT2i). The extent of circulating ketone elevation in these patients remains unknown. We conducted this study to compare the serum ketone response between dapagliflozin, an SGLT2i, and sitagliptin, a dipeptidyl peptidase-4 inhibitor, among insulin-treated T2DM patients. Methods: This was a randomized, open-label, active comparator-controlled study involving 60 insulin-treated T2DM patients. Participants were randomized 1:1 for 24-week of dapagliflozin 10 mg daily or sitagliptin 100 mg daily. Serum β-hydroxybutyrate (BHB) levels were measured at baseline, 12 and 24 weeks after intervention. Comprehensive cardiometabolic assessments were performed with measurements of high-density lipoprotein cholesterol (HDL-C) cholesterol efflux capacity (CEC), vibration-controlled transient elastography and echocardiography. Results: Among these 60 insulin-treated participants (mean age 58.8 years, diabetes duration 18.2 years, glycosylated hemoglobin 8.87%), as compared with sitagliptin, serum BHB levels increased significantly after 24 weeks of dapagliflozin (P=0.045), with a median of 27% increase from baseline. Change in serum BHB levels correlated significantly with change in free fatty acid levels. Despite similar glucose lowering, dapagliflozin led to significant improvements in body weight (P=0.006), waist circumference (P=0.028), HDL-C (P=0.041), CEC (P=0.045), controlled attenuation parameter (P=0.007), and liver stiffness (P=0.022). Average E/e’, an echocardiographic index of left ventricular diastolic dysfunction, was also significantly lower at 24 weeks in participants treated with dapagliflozin (P=0.037). Conclusion Among insulin-treated T2DM patients with long diabetes duration, compared to sitagliptin, dapagliflozin modestly increased ketone levels and was associated with cardiometabolic benefits.

INTRODUCTION: Idiopathic granulomatous mastitis (IGM) is a rare, benign, chronic breast condition that can cause repeated abscesses or mass formation in bilateral breasts. The condition can severely impact the quality of life of affected women. This study aims to evaluate effective treatment modalities, as well as understand the demographics and clinical presentation of patients with IGM. METHODS: An 11-year retrospective review was performed of patients diagnosed with IGM from 1 January 2008 to 31 December 2018 at a tertiary breast unit. RESULTS: A total of 77 patients were included in the study. The median age at presentation was 36 years old. IGM presented most commonly as a breast lump (98.1%). The median number of flares was 2 (1-12). Of the 77 patients, 68.8% (53) were treated with antibiotics, 50.6% (39) with steroids, and 44.2% (34) underwent surgery, in the course of their IGM treatment. Forty-five (59.2%) of the 76 patients with IGM required a multimodal treatment approach to achieve remission. There was no significant difference in the number of flares no matter the initial treatment ( CONCLUSION IGM is a clinical diagnosis. It is a rare, relapsing breast inflammatory condition that affects young females with no superior treatment modality. Smoking is associated with higher number of flares of IGM and should be discouraged in IGM patients.
Adult ; Anti-Bacterial Agents/therapeutic use* ; Female ; Granulomatous Mastitis/therapy* ; Humans ; Quality of Life ; Retrospective Studies ; Treatment Outcome

Background: The occurrence of Graves’ disease and Hashimoto thyroiditis after coronavirus disease 2019 (COVID-19) raised concerns that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may trigger thyroid autoimmunity. We aimed to address the current uncertainties regarding incident thyroid dysfunction and autoimmunity among COVID-19 survivors. Methods: We included consecutive adult COVID-19 patients without known thyroid disorders, who were admitted to Queen Mary Hospital from July 21 to September 21, 2020 and had serum levels of thyroid-stimulating hormone, free thyroxine, free triiodothyronine (fT3), and anti-thyroid antibodies measured both on admission and at 3 months. Results: In total, 122 patients were included. Among 20 patients with abnormal thyroid function tests (TFTs) on admission (mostly low fT3), 15 recovered. Among 102 patients with initial normal TFTs, two had new-onset abnormalities that could represent different phases of thyroiditis. Among 104 patients whose anti-thyroid antibody titers were reassessed, we observed increases in anti-thyroid peroxidase (TPO) (P<0.001) and anti-thyroglobulin (P<0.001), but not anti-thyroid stimulating hormone receptor titers (P=0.486). Of 82 patients with negative anti-TPO findings at baseline, 16 had a significant interval increase in anti-TPO titer by >12 U, and four became anti-TPO-positive. Worse baseline clinical severity (P=0.018), elevated C-reactive protein during hospitalization (P=0.033), and higher baseline anti-TPO titer (P=0.005) were associated with a significant increase in anti-TPO titer. Conclusion Most patients with thyroid dysfunction on admission recovered during convalescence. Abnormal TFTs suggestive of thyroiditis occurred during convalescence, but infrequently. Importantly, our novel observation of an increase in anti-thyroid antibody titers post-COVID-19 warrants further follow-up for incident thyroid dysfunction among COVID-19 survivors.