China Medical University Hospital Research Articles

Relationship between family support, serum lipid knowledge and quality of life in Chinese breast cancer women with adjuvant endocrine therapy.

Serum lipid management is an important health management goal for breast cancer patients with endocrine therapy, and serum lipid knowledge is a substantial factor influencing patients' serum lipid management behavior. The aim of this study was to explore the relationship between family support, serum lipid knowledge and quality of life in breast cancer women with endocrine therapy. Through convenience sampling, 301 women who had been treated in the First Affiliated Hospital of China Medical University and Liaoning Cancer Hospital were selected to fill in the questionnaire of knowledge-attitude-practice (KAP) on serum lipids, family support questionnaire (FSQ), and the functional assessment of cancer therapy-breast cancer (FACT-B). Pearson correlation coefficient was used to analyze the correlation between the three. Multiple linear regression model was used to analyze the influencing factors of quality of life in breast cancer patients with endocrine therapy. The average score of KAP on serum lipids was 42.62 ± 7.333, the average score of family support was 12.55 ± 2.390, and the average score of quality of life was 97.13 ± 21.347, all above the medium level. Family support of breast cancer women with endocrine therapy was positively correlated with serum lipid knowledge and quality of life. Disease stage, family support, and serum lipid knowledge were the influencing factors of quality of life of breast cancer women with endocrine therapy. Good family support is associated with better serum lipid knowledge in breast cancer women with endocrine therapy. Therefore, interventions that aim to improve the level of family support may be one way to improve the knowledge level of serum lipid, prevent cardiovascular and cerebrovascular diseases, and improve the quality of life.

Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care.

ObjectiveTo implement an all-day online artificial intelligence (AI)-assisted detection of ST-elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) to facilitate patient triage for timely reperfusion therapy.MethodsThe proposed AI model combines a convolutional neural network and long short-term memory (CNN-LSTM) to predict STEMI on prehospital 12-lead ECGs obtained from mini-12-lead ECG devices equipped in ambulance vehicles in Central Taiwan. Emergency medical technicians (EMTs) from the 14 AI-implemented fire stations performed the on-site 12-lead ECG examinations using the mini portable device. The 12-lead ECG signals were transmitted to the AI center of China Medical University Hospital to classify the recordings as “STEMI” or “Not STEMI”. In 11 non-AI fire stations, the ECG data were transmitted to a secure network and read by available on-line emergency physicians. The response time was defined as the time interval between the ECG transmission and ECG interpretation feedback.ResultsBetween July 17, 2021, and March 26, 2022, the AI model classified 362 prehospital 12-lead ECGs obtained from 275 consecutive patients who had called the 119 dispatch centers of fire stations in Central Taiwan for symptoms of chest pain or shortness of breath. The AI's response time to the EMTs in ambulance vehicles was 37.2 ± 11.3 s, which was shorter than the online physicians' response time from 11 other fire stations with no AI implementation (113.2 ± 369.4 s, P < 0.001) after analyzing another set of 335 prehospital 12-lead ECGs. The evaluation metrics including accuracy, precision, specificity, recall, area under the receiver operating characteristic curve, and F1 score to assess the overall AI performance in the remote detection of STEMI were 0.992, 0.889, 0.994, 0.941, 0.997, and 0.914, respectively. During the study period, the AI model promptly identified 10 STEMI patients who underwent primary percutaneous coronary intervention (PPCI) with a median contact-to-door time of 18.5 (IQR: 16–20.8) minutes.ConclusionImplementation of an all-day real-time AI-assisted remote detection of STEMI on prehospital 12-lead ECGs in the field is feasible with a high diagnostic accuracy rate. This approach may help minimize preventable delays in contact-to-treatment times for STEMI patients who require PPCI.

Enterotypes in asthenospermia patients with obesity

The essence of enterotypes is stratifying the entire human gut microbiome, which modulates the association between diet and disease risk. A study was designed at the Center of Reproductive Medicine, Shengjing Hospital of China Medical University and Jinghua Hospital of Shenyang. Prevotella and Bacteroides were analyzed in 407 samples of stool, including 178 men with enterotype B (61 normal, 117 overweight/obese) and 229 men with enterotype P (74 normal, 155 overweight/obese). The ratio between Prevotella and Bacteroides abundance, P/B, was used as a simplified way to distinguish the predominant enterotype. In enterotype P group (P/B ≥ 0.01), obesity was a risk factor for a reduced rate of forward progressive sperm motility (odds ratio [OR] 3.350; 95% confidence interval [CI] 1.881–5.966; P < 0.001), and a reduced rate of total sperm motility (OR 4.298; 95% CI 2.365–7.809; P < 0.001). Obesity was also an independent risk factor (OR 3.131; 95% CI 1.749–5.607; P < 0.001) after adjusting follicle-stimulating hormone. In enterotype P, body mass index, as a diagnostic indicator of a reduced rate of forward progressive sperm motility and a decreased rate of decreased total sperm motility, had AUC values of 0.627 (P = 0.001) and 0.675 (P < 0.0001), respectively, which were significantly higher than the predicted values in all patients. However, in enterotype B group (P < 0.01), obesity was not a risk factor for asthenospermia, where no significant difference between obesity and sperm quality parameters was observed. This study is tried to introduce enterotypes as a population-based individualized classification index to investigate the correlation between BMI and asthenospermia. In our study, overweight/obese men with enterotype P were found to have poorer sperm quality. however, sperm quality was not associated with overweight/obese in men with enterotype B. Thereof, BMI is a risk factor for asthenospermia only in men with enterotype P, but not in men with enterotype B.

Establishment and validation of nomogram for predicting immuno checkpoint inhibitor related pneumonia

ObjectiveCancer is one of the main causes of death worldwide. Although immunotherapy brings hope for cancer treatment, it is also accompanied by immune checkpoint inhibitor-related adverse events (irAEs). Immune checkpoint inhibitor pneumonia (CIP) is a potentially fatal adverse event, but there is still a lack of effective markers and prediction models to identify patients at increased risk of CIP.MethodsA total of 369 cancer patients treated between 2017 and 2022 with immune checkpoint inhibitors at Shengjing Hospital of China Medical University and Liaoning People's Hospital were recruited for this study. Independent variables were selected by differences and binary logistic regression analysis, and a risk assessment nomogram was constructed for CIP risk. The accuracy and discriminative abilities of the nomogram were evaluated by calibration plots, receiver operating characteristic curves (ROCs) and decision curve analyses (DCAs).ResultsBinary logistic regression analysis showed that smoking history, acute phase proteins [interleukin (IL-6) and C-reactive protein (CRP)], CD8 + T lymphocyte count and serum alveolar protein [surface protein-A (SP-A) and Krebs Von den Lungen-6 (KL-6)] were significantly associated with CIP risk. A nomogram consisting of these variables was established and validated by different analyses.ConclusionsWe developed an effective risk nomogram for CIP prediction in immune-checkpoint inhibitor administrated cancer patients, which will further assist early detection of immunotherapy-related adverse events.

Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan

BackgroundBreast cancer is an umbrella term referring to a group of biologically and molecularly heterogeneous diseases originating from the breast. Globally, incidences of breast cancer has been increasing dramatically over the past decades. Analyses of multiple clinical “big data” can aid us in clarifying the means of preventing the disease. In addition, predisposing risk factors will be the most important issues if we can confirm their relevance. This study aims to provide an overview of the predisposing factors that contribute to a higher possibility of developing breast cancer and emphasize the signs that we ought to pay more attention to.MethodsThis is a matched nested case-control study. The cohort focused on identifying the eligible risk factors in breast cancer development by data screening (2000-2013) from the Taiwan National Health Insurance Research Database (NHIRD) under approved protocol. A total of 486,069 females were enrolled from a nationwide sampled database, and 3281 females was elligible as breast cancer cohort, 478,574 females who had never diagnosed with breast cancer from 2000 to 2013 were eligible as non-breast cancer controls, and matched to breast cancer cases according to age using a 1:6 ratio.ResultsWe analyzed 3281 breast cancer cases and 19,686 non-breast cancer controls after an age-matched procedure. The significant predisposing factors associated with breast cancer development including obesity, hyperlipidemia, thyroid cancer and liver cancer. As for patients under the age of 55, gastric cancer does seem to have an impact on the development of breast cancer; compared with their counterparts over the age of 55, endometrial cancer appears to exhibit an evocative effect.ConclusionsIn this nationwide matched nested case-control study, we identified obesity, hyperlipidemia, previous cancers of the thyroid, stomach and liver as risk factors associated with breast cancer. However, the retrospective nature and limited case numbers of certain cancers still difficult to provide robust evidence. Further prospective studies are necessitated to corroborate this finding in order to nip the disease in the bud.Trial registrationThe studies involving human participants were reviewed and approved by the China Medical University Hospital [CMUH104-REC2-115(AR-4)].

A novel diagnostic tool for hyaline vascular Castleman disease versus lymphoma based on contrast-enhanced computed tomography in neck mass.

Castleman disease and lymphoma each have a distinct treatment plan; however, they share the same features on contrast-enhanced computed tomography. To assess the quantitative outcomes of Castleman disease versus lymphoma using contrast-enhanced computed tomography based on Hounsfield units (HU). We retrospectively reviewed eight patients with unicentric Castleman disease and 30 patients with lymphoma based on pathological diagnosis at China Medical University Hospital between 2015 and 2020. Preoperative computed tomography with contrast scans was reviewed, and the HU of each tumor were measured. This study included eight patients with unicentric Castleman disease (four men and four women; mean age, 33 years) and 25 patients with lymphoma (11 men and 14 women; mean age, 53 years). There was no significant difference in heterogeneity between the two diseases (0.161 ± 0.052 vs 0.239 ± 0.063, p = 0.22); however, enhancement in Castleman disease was higher than that in lymphoma (126.40 ± 31.90 vs 74.19 ± 7.11, p < 0.001), providing a very good diagnostic tool (cutoff point at 88.5-91.3, sensitivity 0.86/specificity 0.88). Furthermore, we found a highly linear relationship in Castleman disease, which was not noted in lymphoma. The value of HU provides a good diagnostic tool for the differential diagnosis of Castleman disease versus lymphoma in the neck lymph nodes. Considering the linear relationship in Castleman disease, an increasingly accurate differential diagnosis can be made.

Prediction of all-cause and cardiovascular mortality using ankle-brachial index and brachial-ankle pulse wave velocity in patients with type 2 diabetes

Ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV) are used as non-invasive indicators for detecting atherosclerosis and arterial stiffness, two well-known predictors of mortality in patients with type 2 diabetes mellitus (T2DM). ABI and baPWV have independent associations with mortality; however, their joint and interactive effects on mortality have not been assessed in patients with T2DM. This work aims to evaluate the independent, joint, and interactive associations of ABI and baPWV with all-cause and expanded cardiovascular disease (CVD) mortality in patients with T2DM. This observational study included 2160 patients with T2DM enlisted in the Diabetes Care Management Program database of China Medical University Hospital from 2001 to 2016 and then followed their death status until August 2021. Cox proportional hazard models were used to evaluate the independent, joint, and interactive effects of ABI and baPWV on the risk of all-cause and expanded CVD mortality. A total of 474 patient deaths occurred after a mean follow-up of 8.4 years, and 268 of which were attributed to cardiovascular events. Abnormal ABI (≤ 0.9) and highest baPWV quartile were independently associated with increased risks of all-cause [ABI: hazard ratio (HR) 1.67, 95% confidence interval (CI) 1.30–2.11; baPWV: 1.63, 1.16–2.27] and expanded CVD mortality (ABI: 2.21, 1.62–3.02; baPWV: 1.75, 1.09–2.83). The combination of abnormal ABI (≤ 0.9) and highest baPWV quartile was associated with a significantly higher risk of all-cause (4.51, 2.50–8.11) and expanded CVD mortality (9.74, 4.21–22.51) compared with that of the combination of normal ABI and lowest baPWV quartile. Significant interactions were observed between ABI and baPWV in relation to all-cause and expand CVD mortality (both p for interaction < 0.001). Through their independent, joint, and interactive effects, ABI and baPWV are significant parameters that can improve the prediction of all-cause and expanded CVD mortality in patients with T2DM and help identify high-risk patients who may benefit from diabetes care.

Genetic contributions to female gout and hyperuricaemia using genome-wide association study and polygenic risk score analyses.

To identify genetic variants and polygenic risk score (PRS) relating to female gout and asymptomatic hyperuricaemia (AH) in a genome-wide association study (GWAS). Gout, AH and normouricemia controls were included from Taiwan biobank and China Medical University Hospital. All participants were divided into discovery and replication cohorts for GWAS. PRS was estimated according to whether the variant exhibited a protective effect on the phenotypes or not. Each cohort was separated into two groups by the age of 50 years old. A total of 59 472 females were enrolled, and gout and AH occupied 1.60% and 19.59%, respectively. Six variants located in genes SLC2A9, C5orf22, CNTNAP2 and GLRX5 were significantly predictors of female gout in those aged ≥50. For those aged <50 years old, only the variant rs147750368 (SPANXN1) on chromosome X was found. Most variants located in genes SLC2A9, ZNF518B, PKD2 and ABCG2 were found to be significantly related to AH in both age groups. The PRS could explain ∼0.59% to 0.89% of variance of gout in variants with protective effects, which showed 6.2 times of mean PRS in the risk variants, but only 1.2 times in the AH phenotype. Moreover, the PRS also revealed a dose-response trend between AH rates and quartile scores. The variants in gene SLC2A9 are the major genetic factors for females associated with gout in those aged ≥50. PRS can provide a more robust prediction of the gout/AH under a homogeneous selection of variants that show effects on the traits.

Machine learning–based triage to identify low-severity patients with a short discharge length of stay in emergency department

BackgroundOvercrowding in emergency departments (ED) is a critical problem worldwide, and streaming can alleviate crowding to improve patient flows. Among triage scales, patients labeled as “triage level 3” or “urgent” generally comprise the majority, but there is no uniform criterion for classifying low-severity patients in this diverse population. Our aim is to establish a machine learning model for prediction of low-severity patients with short discharge length of stay (DLOS) in ED.MethodsThis was a retrospective study in the ED of China Medical University Hospital (CMUH) and Asia University Hospital (AUH) in Taiwan. Adult patients (aged over 20 years) with Taiwan Triage Acuity Scale level 3 were enrolled between 2018 and 2019. We used available information during triage to establish a machine learning model that can predict low-severity patients with short DLOS. To achieve this goal, we trained five models—CatBoost, XGBoost, decision tree, random forest, and logistic regression—by using large ED visit data and examined their performance in internal and external validation.ResultsFor internal validation in CMUH, 33,986 patients (75.9%) had a short DLOS (shorter than 4 h), and for external validation in AUH, there were 13,269 (82.7%) patients with short DLOS. The best prediction model was CatBoost in internal validation, and area under the receiver operating cha racteristic curve (AUC) was 0.755 (95% confidence interval (CI): 0.743–0.767). Under the same threshold, XGBoost yielded the best performance, with an AUC value of 0.761 (95% CI: 0.742- 0.765) in external validation.ConclusionsThis is the first study to establish a machine learning model by applying triage information alone for prediction of short DLOS in ED with both internal and external validation. In future work, the models could be developed as an assisting tool in real-time triage to identify low-severity patients as fast track candidates.

MO340: Acute Kidney Disease in the Outpatient Setting: From Big Data Phenotyping to Biomarker Validation Using the NGAL and DNLITE-IVD103 Tests

Abstract BACKGROUND AND AIMS Acute kidney injury (AKI) and acute kidney disease (AKD), a typical inpatient disease spectrum, pose an exceptional burden on the current healthcare system worldwide. By contrast, developing operative diagnostic criteria for AKD in the outpatient setting (AKDOPT) remains an unattained goal due to the data silos built around the disconnected healthcare systems. In 2017, Taiwan launched the National Cloud-based Health Information Exchange Platform and established the interoperability standard that makes the automated monitoring of change of serum creatinine (S-Cre) in the outpatient setting a possible practice. This study aims to verify our previously proposed AKDOPT diagnostic algorithms using both the conventional neutrophil gelatinase-associated lipocalin (NGAL) and DNlite-IVD103 tests, detecting a novel biomarker, a post-translational modified (PTM) fragment of Fetuin-A [1, 2]. METHOD The Big Data Center of China Medical University Hospital (CMUH) has launched the Acute Kidney Injury Detection System (AKIDS) in the outpatient setting since December 2017 based on our AKDOPT diagnostic algorithms (Fig. 1). In November 2020, we conducted a pragmatic randomized trial to evaluate the clinical effectiveness of AKIDS in reducing the risk of AKDOPT progression to dialysis. Among patients who participated in this trial, both urine and blood were obtained at the enrollment and the urine samples were sent for the quantification of NGAL and the unique PTM-Fetuin-A fragment, an ELISA test developed by Bio Preventive Medicine (BPM). The risk of S-Cre doubling was estimated by Firth's logistic regression. RESULTS A total of 56 patients who were captured by the AKIDS and with the last estimated glomerular filtration rate (eGFR) below 45 mL/min/1.73 m2 recruited in this trial with a median age of 73 years (IQR: 66.2–82.5) and a baseline eGFR of 36.4 (IQR: 21.0–46.3) mL/min/1.7 3 m2. During the follow-up, there were six participants reached the S-Cre double status. The median levels of NGAL and IVD103 were 1360 (IQR: 299–1827) ng/mg and 74.7 (IQR: 37.3–236) ng/mg, respectively, among patients experiencing the endpoint, and they were 187 (81.4–1152) ng/mg and 15.9 (6.16–67.3) ng/mg for patients free of the primary outcome. The odds ratios of the S-Cre doubling for each log unit increase in NGAL and IVD103 were 2.26 (95% confidence interval 0.73–6.98; p-value .16) and 3.48 (0.78–15.6; p-value .10), respectively. In the dose-response plot, we found only IVD103 showed a positive linear relationship with the risk of S-Cre doubling despite the two biomarkers showed comparable area under the receiver operating characteristic curve for predicting poor kidney outcome (NGAL 0.697 versus IVD103 0.723). CONCLUSION This is the first study to phenotypically validate the previously unrecognized phenotype, AKDOPT, by the AKIDS developed under the National Health Insurance (NHI) information technology infrastructure and molecularly validate its prognostic role using kidney injury biomarkers, NGAL and a novel eGFR decline prediction biomarker, a unique PTM-fragment of Fetuin-A (IVD103). The linear association between IVD103 and the risk of S-Cre doubling supports its prognostic value in the risk assessment of AKDOPT.

A specific 25-mer peptide from the cysteine protease of P. gingivalis is the epitope of humoral immune response in rheumatoid arthritis

Abstract Objective Several lines of evidence suggest that the pathobiont Porphyromonas gingivalis is involved in the development and/or progression of rheumatoid arthritis. This bacterium produces cysteine proteases, such as gingipain RgpA, endowed with the potential to induce significant inflammation in patients with periodontitis and rheumatoid arthritis. Both diseases involve chronic inflammation with the production of pro-inflammatory cytokines, connective tissue breakdown and bone erosion. Methods A 25-peptide named BR1 from Porphyromonas gingivalis was synthesized for the study. Serum samples from patients with RA, early arthritis, other rheumatic diseases, and normal controls were used in the study. A monoclonal antibody named BR2mAb was derived from BALB/c mice immunized with the 25-mer peptide was produced as the control. Anti-BR1, ACPA and RF were detected by ELISA. Results Anti-BR1 were detected in 56.0% (59/106) of RA patients and were found in 63.8% (23/36) of RA patients without both RF and/or ACPA. The serological positive rates with the two tests of RF and ACPA and with the three tests of anti-BR1, RF, and ACPA were 66% and 84.2%, respectively. Anti-BR1 were detected in 60.0% (9/15) of patients with early arthritis, but neither RF nor ACPA was detected in this group of patients. The sensitivity and specificity for RA were 60.1% and 95%, respectively. The BR2 mAb reacted to Porphyromonas gingivalis as well. Conclusions A specific 25-mer peptide from the cysteine protease of P. gingivalis is the epitope for humoral immune response in rheumatoid arthritis. The anti-25-mer peptide antibody test is an excellent new test for the diagnosis of patients with RA and early arthritis. This study was supported by grants from the Ministry of Science and Technology, Taiwan (MOST-104-2314-B-039-045, MOST-105-2911-I-039-504, MOST-105-2314-B-039-047, MOST-106-2911-I-039-501, MOST-107-2314-B-039-050, MOST-108-2314-B-039-019), and from China Medical University Hospital (DMR-106-188, DMR-108-183, DMR-109-206).

MP45-18 IDENTIFICATION OF DNA DAMAGE REPAIR-ASSOCIATED PROGNOSTIC BIOMARKERS FOR PROSTATE CANCER USING TRANSCRIPTOMIC DATA ANALYSIS

You have accessJournal of UrologyCME1 May 2022MP45-18 IDENTIFICATION OF DNA DAMAGE REPAIR-ASSOCIATED PROGNOSTIC BIOMARKERS FOR PROSTATE CANCER USING TRANSCRIPTOMIC DATA ANALYSIS Shu-Pin Huang, Pai-Chi Teng, Chia-Hsin Liu, Ting-Yi Lin, Yi-Chun Cho, Yo-Liang Lai, Shu-Chi Wang, Hsin-Chih Yeh, Chih-Pin Chuu, Deng-Neng Chen, Wei-Chung Cheng, and Chia-Yang Li Shu-Pin HuangShu-Pin Huang More articles by this author , Pai-Chi TengPai-Chi Teng More articles by this author , Chia-Hsin LiuChia-Hsin Liu More articles by this author , Ting-Yi LinTing-Yi Lin More articles by this author , Yi-Chun ChoYi-Chun Cho More articles by this author , Yo-Liang LaiYo-Liang Lai More articles by this author , Shu-Chi WangShu-Chi Wang More articles by this author , Hsin-Chih YehHsin-Chih Yeh More articles by this author , Chih-Pin ChuuChih-Pin Chuu More articles by this author , Deng-Neng ChenDeng-Neng Chen More articles by this author , Wei-Chung ChengWei-Chung Cheng More articles by this author , and Chia-Yang LiChia-Yang Li More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002611.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: In the recent decade, the importance of DNA damage repair (DDR) and its clinical appli- cation have been firmly recognized in prostate cancer (PC). For example, olaparib was just approved in May 2020 to treat metastatic castration-resistant PC with homologous recombination repair-mu- tated genes; however, not all patients can benefit from olaparib, and the treatment response de- pends on patient-specific mutations. This highlights the need to understand the detailed DDR biol- ogy further and develop DDR-based biomarkers. METHODS: In this study, we establish a four-gene panel of which the expression is significantly associated with overall survival (OS) and progression-free survival (PFS) in PC patients from the TCGA-PRAD database. RESULTS: The established panel includes DNTT, EXO1, NEIL3, and EME2 genes. Patients with higher expression of the four identified genes have signifi- cantly worse OS and PFS. This significance also exists in a multivariate Cox regression model ad- justing for age, PSA, TNM stages, and Gleason scores. Moreover, the expression of the four-gene panel is highly correlated with aggressiveness based on well-known PAM50 and PCS subtyping classifiers. CONCLUSIONS: Using publicly available databases, we successfully validate the four-gene panel as hav- ing the potential to serve as a prognostic and predictive biomarker for PC specifically based on DDR biology. Source of Funding: This study was supported by grants from the Ministry of Science and Technology, Taiwan, R.O.C. (grant No. MOST 108-2314-B-037-079-MY3, MOST 109-2622-E-039-004-CC2, MOST 109-2628- E-039-001-MY3, MOST 109-2327-B-039-002, MOST109-2314-B-037-106-MY3 and MOST 109-2320-B- 037-007-MY3), Kaohsiung Medical University Chung-Ho Memorial Hospital (grant No. KMUH105- 5M55), China Medical University Hospital (grant No. DMR-109-223, DMR-110-072 and DMR-110- 244), and China Medical University, Taiwan, R.O.C. (grant No. CMU107-S-24, CMU108-Z-02, CMU108-S-22, CMU109-MF-61 and CMU110-MF-64) © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e770 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Shu-Pin Huang More articles by this author Pai-Chi Teng More articles by this author Chia-Hsin Liu More articles by this author Ting-Yi Lin More articles by this author Yi-Chun Cho More articles by this author Yo-Liang Lai More articles by this author Shu-Chi Wang More articles by this author Hsin-Chih Yeh More articles by this author Chih-Pin Chuu More articles by this author Deng-Neng Chen More articles by this author Wei-Chung Cheng More articles by this author Chia-Yang Li More articles by this author Expand All Advertisement PDF DownloadLoading ...

A Study to Evaluate Accuracy and Validity of the EFAI Computer-Aided Bone Age Diagnosis System Compared With Qualified Physicians.

Study ObjectivesIn previous research, we built a deep neural network model based on Inception-Resnet-v2 to predict bone age (EFAI-BAA). The primary objective of the study was to determine if the EFAI-BAA was substantially concordant with the qualified physicians in assessing bone ages. The secondary objective of the study was to determine if the EFAI-BAA was no different in the clinical rating (advanced, normal, or delayed) with the qualified physicians.MethodThis was a retrospective study. The left-hand X-ray images of male subjects aged 3–16 years old and female subjects aged 2–15 years old were collected from China Medical University Hospital (CMUH) and Asia University Hospital (AUH) retrospectively since the trial began until the included image amount reached 368. This was a blinded study. The qualified physicians who ran, read, and interpreted the tests were blinded to the values assessed by the other qualified physicians and the EFAI-BAA.ResultsThe concordance correlation coefficient (CCC) between the EFAI-BAA (EFAI-BAA), the evaluation of bone age by physician in Kaohsiung Veterans General Hospital (KVGH), Taichung Veterans General Hospital (TVGH2), and in Taipei Tzu Chi Hospital (TZUCHI-TP) was 0.9828 (95% CI: 0.9790–0.9859, p-value = 0.6782), 0.9739 (95% CI: 0.9681–0.9786, p-value = 0.0202), and 0.9592 (95% CI: 0.9501–0.9666, p-value = 0.4855), respectively.ConclusionThere was a consistency of bone age assessment between the EFAI-BAA and each one of the three qualified physicians (CCC = 0.9). As the significant difference in the clinical rating was only found between the EFAI-BAA and the qualified physician in TVGH2, the performance of the EFAI-BAA was considered similar to the qualified physicians.

An observational study of acupuncture and complementary treatments for major depression: Case series from a preliminary study of proposed collaborative care model

BackgroundMajor depressive disorder is identified as a mood disorder characterized by episodically recurring and potentially life-threatening negative symptoms. It is currently important for study, as it involves high morbidity, mortality and prevalence, as well as unsatisfactory treatment results. AimEstablish an outpatient model from an integrative approach promoting the diversified development of traditional Chinese and Western medicine cooperation, leading to a holistic intervention for patients with depression. Experimental procedureFifteen participants with moderate to severe depression were followed up for eight weeks in the Acupuncture Department of the China Medical University Hospital in Taichung, Taiwan, under a collaborative outpatient model that combined Western psychiatry and traditional Chinese medicine (TCM). Interdisciplinary Intervention included manual acupuncture twice a week (16 sessions), tai chi, yoga meditation, and nutritional assessment. Symptomatology was measured with primary outcomes (self-reporting via questionnaires) and secondary outcomes (heart rate variability [HRV] and blood samples to measure inflammation via high-sensitivity C-reactive protein [hs-CRP]). ResultsThe response rate was 80% (12/15 participants), with a statistically and clinically significant decrease in depression severity according to the 21-question Hamilton depression rating scale (HDRS21) (p < 0.001), the Beck Depression Inventory (BDI) (p < 0.003), and quality of life (QoL) questionnaires (p < 0.002). We found body constitution heterogeneity in the participants with major depressive disorder (MDD), predominantly blood stagnation and Qi stagnation (in 70% of participants). ConclusionAn interdisciplinary outpatient treatment method of complementary therapies can be applied successfully with pharmacological treatment in clinical practice to reduce depression symptomatology. SectionPhysical/Mental practices. TaxonomyMajor Depressive Disorder, Collaborative healthcare Treatment, Observational study.

Analysis of HLA Variants and Graves' Disease and Its Comorbidities Using a High Resolution Imputation System to Examine Electronic Medical Health Records.

Hyperthyroidism is a prevalent endocrine disorder, and genetics play a major role in the development of thyroid-associated diseases. In particular, the inheritance of HLA has been demonstrated to induce the highest susceptibility to Graves’ disease (GD). However, thus far, no studies have reported the contribution of HLA to the development of GD and the complications that follow. Thus, in the present study, to the best of our knowledge, for the first time, a powerful imputation method, HIBAG, was used to predict the HLA subtypes among populations with available genome-wide SNP array data from the China Medical University Hospital (CMUH). The disease status was extracted from the CMUH electronic medical records; a total of 2,998 subjects with GD were identified as the cases to be tested and 29,083 subjects without any diagnosis of thyroid disorders were randomly selected as the controls. A total of 12 HLA class I genotypes (HLA-A*02:07-*11:01, HLA-B*40:01-*46:01 and *46:01-*46:01, and HLA-C*01:02-*01:02, *01:02-*03:04, and *01:02-*07:02) and 17 HLA class II genotypes (HLA-DPA1*02:02-*02:02, HLA-DPB1*02:01-*05:01, *02:02-*05:01, and *04:01-*05:01, HLA-DQA1*03:02, HLA-DRB1*09:01-*15:01, and *09:01-*09:01) were found to be associated with GD in the Taiwanese population. Moreover, the HLA subtypes HLA-A*11:01, HLA-B*46:01, HLA-DPA1*01:03, and HLA-DPB1*05:01 were found to be associated with heart disease, stroke, diabetes, and hypertension among subjects with GD. Our data suggest that several HLA alleles are markedly associated with GD and its comorbidities, including heart disease, hypertension, and diabetes.

Paradoxical mortality of high estimated glomerular filtration rate reversed by 24-h urine creatinine excretion rate adjustment: sarcopenia matters.

BackgroundMuscle wasting may explain the paradoxical mortality of patients with high estimated glomerular filtration rates (eGFRs) derived from equation methods. However, empirical evidence and solutions remain insufficient.MethodsIn this retrospective cohort study, we compared the performance of equation methods for predicting all‐cause mortality; we used 24‐h creatinine clearance (24‐h CrCl), equation‐based eGFRs, and a new eGFR estimating equation weighting for population 24‐h urine creatinine excretion rate (U‐CER). From 2003 to 2018, we identified 4986 patients whose data constituted the first 24‐h CrCl measurement data in the Clinical Research Data Repository of China Medical University Hospital and were followed up for at least 5 years after careful exclusion. Three GFR estimation equations [the Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI), Modification of Diet in Renal Disease (MDRD) Study, and Taiwanese MDRD], 24‐h CrCl, and 24‐h U‐CER–adjusted eGFR were used.ResultsA high correlation was observed among the eGFR levels derived from the equation methods (0.995–1.000); however, the correlation decreased to 0.895–0.914 when equation methods were compared with the 24‐h CrCl or 24‐h U‐CER–adjusted equation‐based eGFR. In the Bland–Altman plots, the average discrepancy between the equation methods and the 24‐h CrCl method was close to zero (maximal bias range: 5.12 for the Taiwanese MDRD equation vs. 24‐h CrCl), but the range in limit of agreement was wide, from ±43.7 mL/min/1.73 m2 for the CKD‐EPI equation to ±54.3 mL/min/1.73 m2 for the Taiwanese MDRD equation. A J‐shaped dose–response relationship was observed between all equation‐based eGFRs and all‐cause mortality. Only 24‐h CrCl exhibited a non‐linear negative dose–response relationship with all‐cause mortality. After adjustment for 24‐h U‐CER in the statistical model, the paradoxical increase in mortality risk for an eGFR of >90 mL/min/1.73 m2 returned to null. When 24‐h U‐CER was used directly to correct eGFR, the monotonic non‐linear negative relationship with all‐cause mortality was almost identical to that of 24‐h CrCl.ConclusionsThe 24‐h U‐CER–adjusted eGFR and 24‐h CrCl are viable options for informing mortality risk. The 24‐h U‐CER adjustment method can be practically implemented to eGFR‐based care and effectively mitigate the inherent confounding biases from individual's muscle mass amount due to both sex and racial differences.

Adjuvant Probiotics of Lactobacillus salivarius subsp. salicinius AP-32, L. johnsonii MH-68, and Bifidobacterium animalis subsp. lactis CP-9 Attenuate Glycemic Levels and Inflammatory Cytokines in Patients With Type 1 Diabetes Mellitus.

IntroductionType 1 diabetes mellitus (T1DM) is characterized by autoimmune destruction of pancreatic β cells. Previous study has discovered that probiotic strains residing in the gut play essential roles in host immune regulation. However, few clinical results demonstrated probiotic would actually benefit in attenuating glycated hemoglobin (HbA1c) along with inflammatory cytokine levels of the T1DM patients and analyzed their gut microbiota profile at the same time. In this clinical trial, we evaluated the therapeutic efficacy of probiotics on HbA1c along with inflammatory cytokine levels of T1DM patients to determine an alternative administration mode for T1DM medication. The probiotics changed T1DM gut microbiota profile will be measured by next-generation sequencing (NGS).Research Design and MethodsA randomized, double-blind, placebo-controlled trial was performed at China Medical University Hospital. T1DM patients between 6 and 18 years of age were enrolled. 27 patients were administered regular insulin therapy plus capsules containing probiotic strains Lactobacillus salivarius subsp. salicinius AP-32, L. johnsonii MH-68, and Bifidobacterium animalis subsp. lactis CP-9 daily for 6 months, and 29 patients were administered insulin therapy without extra probiotic supplement as placebo group. The variations of fasting blood glucose and HbA1c in these patients were analyzed. In addition, serum levels of inflammatory cytokines and anti-inflammatory cytokine were assessed using enzyme-linked immunosorbent assay. Patients’ stool microbiota were all subjects to NGS analysis.ResultsNGS data showed elevated populations of Bifidobacterium animalis, Akkermansia muciniphila and Lactobacillus salivarius in the gut of patients with T1DM who were taking probiotics. Patients with T1DM who were administered probiotics showed significantly reduced fasting blood glucose levels compared with the before-intervention levels. The HbA1c levels of the patients also improved after administration of probiotics. The concentrations of IL-8, IL-17, MIP-1β, RANTES, and TNF-α were significantly reduced and were associated with an increased TGF-β1 expression after probiotic intervention. The persistence effect of glycemic control and immunomodulation were observed even 3 months after discontinuation of the probiotics.ConclusionsHere, we found that conventional insulin therapy plus probiotics supplementation attenuated T1DM symptoms than receiving insulin treatment only. Probiotics supplementation with insulin treatment changed gut microbiota and revealed better outcome in stabilizing glycemic levels and reducing HbA1c levels in patients with T1DM through beneficial regulation of immune cytokines. Clinical Trial Registration ClinicalTrials.gov, identifier NCT03880760.

Effects of Vision Therapy on Bilateral Amblyopia Unresponsive to Conventional Treatment: A Retrospective Comparative Study

Background: In this study we aim to determines the effect of our vision therapy program for 7- to 10-year-old patients who exhibit bilateral amblyopia that is no longer responsive to conventional treatment. Methods: Children with bilateral amblyopia between the ages of 7 and 10 treated with vision therapy at the China Medical University Hospital between 2016 and 2019 were retrospectively reviewed. Age and visual acuity-matched bilateral amblyopes are included as a control group. The visual acuity for both groups showed no improvement for more than 3 months with part-time patching and full refraction correction. The initial and final visual acuity, stereopsis, and refractive status were analyzed. Results: Here, 15 cases were included as the treatment group and 16 cases as a control group. At the endpoint, the study group shows a significant improvement in BCVA, with a mean of 0.32 ± 0.15 logMAR (3 lines improvement) versus 0.003 ± 0.19 logMAR (nearly no improvement) for the control group (p < 0.001). The benefits of treatment are most obvious in the first 3 months after treatment (p < 0.001) and last until the end point. Stereoacuity also improves from 190.00 ± 163.34 to 85.00 ± 61.24 arc seconds, which is a 55.26% improvement. Conclusions: Vision therapy, comprising orthoptic therapy, perceptual learning and dichoptic training, is a successful program for increasing visual acuity and stereoacuity in 7- to 10-year-old children with bilateral amblyopia that is unresponsive to conventional treatment.

Applying Machine Learning to Carotid Sonographic Features for Recurrent Stroke in Patients With Acute Stroke.

BackgroundAlthough carotid sonographic features have been used as predictors of recurrent stroke, few large-scale studies have explored the use of machine learning analysis of carotid sonographic features for the prediction of recurrent stroke.MethodsWe retrospectively collected electronic medical records of enrolled patients from the data warehouse of China Medical University Hospital, a tertiary medical center in central Taiwan, from January 2012 to November 2018. We included patients who underwent a documented carotid ultrasound within 30 days of experiencing an acute first stroke during the study period. We classified these participants into two groups: those with non-recurrent stroke (those who has not been diagnosed with acute stroke again during the study period) and those with recurrent stoke (those who has been diagnosed with acute stroke during the study period). A total of 1,235 carotid sonographic parameters were analyzed. Data on the patients' demographic characteristics and comorbidities were also collected. Python 3.7 was used as the programming language, and the scikit-learn toolkit was used to complete the derivation and verification of the machine learning methods.ResultsIn total, 2,411 patients were enrolled in this study, of whom 1,896 and 515 had non-recurrent and recurrent stroke, respectively. After extraction, 43 features of carotid sonography (36 carotid sonographic parameters and seven transcranial color Doppler sonographic parameter) were analyzed. For predicting recurrent stroke, CatBoost achieved the highest area under the curve (0.844, CIs 95% 0.824–0.868), followed by the Light Gradient Boosting Machine (0.832, CIs 95% 0.813–0.851), random forest (0.819, CIs 95% 0.802–0.846), support-vector machine (0.759, CIs 95% 0.739–0.781), logistic regression (0.781, CIs 95% 0.764–0.800), and decision tree (0.735, CIs 95% 0.717–0.755) models.ConclusionWhen using the CatBoost model, the top three features for predicting recurrent stroke were determined to be the use of anticoagulation medications, the use of NSAID medications, and the resistive index of the left subclavian artery. The CatBoost model demonstrated efficiency and achieved optimal performance in the predictive classification of non-recurrent and recurrent stroke.

Perception of the threat, mental health burden, and healthcare-seeking behavior change among psoriasis patients during the COVID-19 pandemic.

This study aimed to investigate the perceived threat, mental health outcomes, behavior changes, and associated predictors among psoriasis patients during the COVID-19 pandemic. The COVID-19 has been known to increase the health risks of patients with psoriasis owing to patients' immune dysregulation, comorbidities, and immunosuppressive drug use. A total of 423 psoriasis patients not infected with COVID-19 was recruited from the Department of Dermatology, National Taiwan University Hospital Hsin-Chu Branch, Chang Gung Memorial Hospital, and China Medical University Hospital from May 2020 to July 2020. A self-administered questionnaire was used to evaluate the perceived threat, mental health, and psychological impact on psoriasis patients using the Perceived COVID-19-Related Risk Scale score for Psoriasis (PCRSP), depression, anxiety, insomnia, and stress-associated symptoms (DAISS) scales, and Impact of Event Scale-Revised (IES-R), respectively. Over 94% of 423 patients with psoriasis perceived threat to be ≥ 1 due to COVID-19; 18% of the patients experienced psychological symptoms more frequently ≥ 1, and 22% perceived psychological impact during the pandemic to be ≥ 1. Multivariable linear regression showed that the higher psoriasis severity and comorbidities were significantly associated with higher PCRSP, DAISS, and IES-R scores. The requirement for a prolonged prescription and canceling or deferring clinic visits for psoriasis treatment among patients are the two most common healthcare-seeking behavior changes during the COVID-19 pandemic. Psoriasis patients who perceived a higher COVID-19 threat were more likely to require a prolonged prescription and have their clinic visits canceled or deferred. Surveillance of the psychological consequences in psoriasis patients due to COVID-19 must be implemented to avoid psychological consequences and inappropriate treatment delays or withdrawal.