Cardioprotective Effects of PARP Inhibitors: A Re-Analysis of a Meta-Analysis and a Real-Word Data Analysis Using the FAERS Database.

Objective: This study aimed to assess the potential of PARP inhibitors to prevent cardiotoxicity. Methods: First, a re-analysis and update of a previously published study was conducted. Additional searches were conducted of the PubMed and Cochrane Central Register of Controlled Trials databases on 2 June 2023. After the selection process, the pooled odds ratio (OR) for cardiac adverse events (AEs) was calculated. Second, the FAERS database was examined for 10 frequently co-administered anticancer agents. The reporting odds ratio (ROR) was calculated based on the occurrence of cardiac AEs depending on the co-administration of PARP inhibitors. Results: Seven studies were selected for the meta-analysis. Although not statistically significant, co-administration of PARP inhibitors with chemotherapy/bevacizumab decreased the risk of cardiac AEs (Peto OR = 0.61; p = 0.36), while co-administration with antiandrogens increased the risk of cardiac AEs (Peto OR = 1.83; p = 0.18). A total of 19 cases of cardiac AEs were reported with co-administration of PARP inhibitors in the FAERS database. Co-administration of PARP inhibitors with chemotherapy/bevacizumab significantly decreased the risk of cardiac AEs (ROR = 0.352; 95% confidence interval (CI), 0.194-0.637). On the other hand, for antiandrogens co-administered with PARP inhibitors, the ROR was 3.496 (95% CI, 1.539-7.942). The ROR for immune checkpoint inhibitors co-administered with PARP inhibitors was 0.606 (95% CI, 0.151-2.432), indicating a non-significant effect on cardiac AEs. Conclusion: This study reports that PARP inhibitors show cardioprotective effects when used with conventional anticancer agents.

Comparative effects of glucose-lowering agents on endothelial function and arterial stiffness in patients with type 2 diabetes: A network meta-analysis.

BACKGROUND AND AIMS: Despite accumulating evidence on the potential of glucose-lowering agents (GLAs) to prevent cardiovascular events, the comparative effects of GLAs on vascular function remain unclear. This study utilized validated indicators such as flow-mediated dilation (FMD; positive value favors) and pulse wave velocity (PWV; negative value favors) to uncover the comparative effects of GLAs on vascular function. METHODS: Randomized controlled trials (RCTs) comparing the effects of GLAs on FMD or PWV with placebo or other GLAs in patients with type 2 diabetes (T2DM) were searched through PubMed and Embase. The frequentist method of network meta-analysis (NMA) was conducted using a random effects model, and standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated. RESULTS: The NMA included 38 RCTs with 2,065 patients. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium glucose cotransporter-2 inhibitors (SGLT-2Is) had significantly more positive effects on FMD improvement and PWV reduction than placebo. Thiazolidinedione (TZD) treatment resulted in significantly improved FMD compared to other GLAs as well as placebo (SMD: 1.14; 95% CI: 0.84 to 1.43). Both pioglitazone and rosiglitazone were discovered to have considerably more favorable effects on improving FMD and reducing PWV compared to placebo and other GLAs, as a result of the analysis incorporating each drug in the TZD class. The sensitivity analysis results corroborated the main findings. CONCLUSIONS: This NMA showed more favorable effects of GLP-1RAs and SGLT-2Is than placebo in improving both arterial stiffness and endothelial function in patients with T2DM. In addition, TZDs showed superior effects in improving endothelial function as compared with the other GLAs and placebo.

Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers.

Natural language processing (NLP) technology has recently used to predict substance properties based on their Simplified Molecular-Input Line-Entry System (SMILES). We aimed to develop a model predicting human skin sensitizers by integrating text features derived from SMILES with in vitro test outcomes. The dataset on SMILES, physicochemical properties, in vitro tests (DPRA, KeratinoSensTM, h-CLAT, and SENS-IS assays), and human potency categories for 122 substances sourced from the Cosmetics Europe database. The ChemBERTa model was employed to analyze the SMILES of substances. The last hidden layer embedding of ChemBERTa was tested with other features. Given the modest dataset size, we trained five XGBoost models using subsets of the training data, and subsequently employed bagging to create the final model. Notably, the features computed from SMILES played a pivotal role in the model for distinguishing sensitizers and non-sensitizers. The final model demonstrated a classification accuracy of 80% and an AUC-ROC of 0.82, effectively discriminating sensitizers from non-sensitizers. Furthermore, the model exhibited an accuracy of 82% and an AUC-ROC of 0.82 in classifying strong and weak sensitizers. In summary, we demonstrated that the integration of NLP of SMILES with in vitro test results can enhance the prediction of health hazard associated with chemicals.

Enhancement of the therapeutic efficacy of the MAP regimen using thiamine pyrophosphate-decorated albumin nanoclusters in osteosarcoma treatment.

Recent studies on osteosarcoma regimens have mainly focused on modifying the combination of antineoplastic agents rather than enhancing the therapeutic efficacy of each component. Here, an albumin nanocluster (NC)-assisted methotrexate (MTX), doxorubicin (DOX), and cisplatin (MAP) regimen with improved antitumor efficacy is presented. Human serum albumin (HSA) is decorated with thiamine pyrophosphate (TPP) to increase the affinity to the bone tumor microenvironment (TME). MTX or DOX (hydrophobic MAP components) is adsorbed to HSA-TPP via hydrophobic interactions. MTX- or DOX-adsorbed HSA-TPP NCs exhibit 20.8- and 1.64-fold higher binding affinity to hydroxyapatite, respectively, than corresponding HSA NCs, suggesting improved targeting ability to the bone TME via TPP decoration. A modified MAP regimen consisting of MTX- or DOX-adsorbed HSA-TPP NCs and free cisplatin displays a higher synergistic anticancer effect in HOS/MNNG human osteosarcoma cells than conventional MAP. TPP-decorated NCs show 1.53-fold higher tumor accumulation than unmodified NCs in an orthotopic osteosarcoma mouse model, indicating increased bone tumor distribution. As a result, the modified regimen more significantly suppresses tumor growth in vivo than solution-based conventional MAP, suggesting that HSA-TPP NC-assisted MAP may be a promising strategy for osteosarcoma treatment.

Effects of Omega-3 Fatty Acids on Flow-mediated Dilatation and Carotid Intima Media Thickness: A Meta-analysis.

PURPOSE OF REVIEW: To investigate the effects of omega-3 fatty acids on flow-mediated dilatation (FMD) and carotid intima-media thickness (CIMT) and explore the factors influencing these effects. RECENT FINDINGS: FMD was significantly higher in the omega-3 fatty acid group compared to the control group (mean difference = 0.90%; p = 0.0003). In particular, the subgroup with CHD (both EPA + DHA < 1 g/day and ≥ 1 g/day) and the subgroup without CHD but with CHD risk factors (only EPA + DHA ≥ 1 g/day) showed significantly increased FMD after supplementation of omega-3 fatty acids. CIMT was not significantly different between the omega-3 fatty acid and control groups (standardized mean difference = -0.08; p = 0.26). Subgroup analysis of CHD patients was not conducted because of the limited number of studies. Intake of omega-3 fatty acids improved FMD in patients with CHD and patients with risk factors for CHD. Further research is needed on the effects of omega-3 fatty acids on CIMT.

Risk of type 2 diabetes mellitus in adult patients with atopic dermatitis.

AIMS: This study aimed to investigate the subsequent risk of type 2 diabetes mellitus (T2D) in adults newly diagnosed with atopic dermatitis (AD). METHODS: This propensity score-matching cohort study used data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC) 2.0 database in South Korea from 2002 to 2015. The adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using a Cox proportional hazards model, for the new onset of T2D (ICD-10 code, E11) in AD patients compared to the matched controls. Subgroup and sensitivity analyses were also conducted. RESULTS: Each of the 36,692 individuals in the AD group and matched control group was included in the analysis. The risk of T2D in the AD group was significantly higher than that of the matched controls in the adjusted model (adjusted HR 1.44; 95% CI 1.27-1.63, P <.001). The results of subgroup analysis by sex, age, and body mass index were consistent with the results of the primary analysis. Sensitivity analyses using different T2D and/or AD definitions also showed consistent results. CONCLUSIONS: The significant risk of subsequent T2D in adult AD patients suggested the necessity for efforts to prevent T2D in AD patients.

Novel innovative computer-based test (Inno-CBT) item types for national licensing examinations for health care professionals.

BACKGROUND: An effective test mechanism to evaluate clinical knowledge and skills of the entry-level healthcare professionals is important for providing clinical competency and improving patient care. This study aimed to develop novel, innovative computer-based test (Inno-CBT) item types for application in the national examination of Korean healthcare professionals. METHODS: This exploratory study was conducted from May 2021 to March 2022 by a team of faculty members from pharmacy schools in South Korea. A literature search using PubMed, Google Scholar, RISS, Web of Science, and KoreaMed was performed. Forum presentations, media articles, and previous reports by the Korea Health Personnel Licensing Examination Institute (KHPLEI) were included. Workshops were held, information and ideas were collected and conceptualized, and item types were designed, drafted, and refined. By repeating this process, the Inno-CBT item types were finalized. RESULTS: Forty-one Inno-CBT item types with 28 subtypes were developed. New digital technologies, such as a reactive responsive media interface, an animation insertion, multimedia embedding, and network surfing, were utilized in these novel types. It was anticipated that these Inno-CBT item types would effectively measure abilities in healthcare knowledge, problem-solving skills, and professional behaviors. Some potential barriers to implementing the Inno-CBT item types include item difficulty, operational unfamiliarity, complexity in scoring protocols, and network security. CONCLUSIONS: A variety of styles of novel Inno-CBT item types were developed to evaluate the multifaceted and in-depth professional abilities required for healthcare professionals. Prior to implementing these item types in the national examination, item validation and technical support should be conducted.

Machine-learning based prediction models for assessing skin irritation and corrosion potential of liquid chemicals using physicochemical properties by XGBoost.

Skin irritation test is an essential part of the safety assessment of chemicals. Recently, computational models to predict the skin irritation draw attention as alternatives to animal testing. We developed prediction models on skin irritation/corrosion of liquid chemicals using machine learning algorithms, with 34 physicochemical descriptors calculated from the structure. The training and test dataset of 545 liquid chemicals with reliable in vivo skin hazard classifications based on UN Globally Harmonized System [category 1 (corrosive, Cat 1), 2 (irritant, Cat 2), 3 (mild irritant, Cat 3), and no category (nonirritant, NC)] were collected from public databases. After the curation of input data through removal and correlation analysis, every model was constructed to predict skin hazard classification for liquid chemicals with 22 physicochemical descriptors. Seven machine learning algorithms [Logistic regression, Naïve Bayes, k-nearest neighbor, Support vector machine, Random Forest, Extreme gradient boosting (XGB), and Neural net] were applied to ternary and binary classification of skin hazard. XGB model demonstrated the highest accuracy (0.73-0.81), sensitivity (0.71-0.92), and positive predictive value (0.65-0.81). The contribution of physicochemical descriptors to the classification was analyzed using Shapley Additive exPlanations plot to provide an insight into the skin irritation of chemicals. Supplementary Information: The online version contains supplementary material available at 10.1007/s43188-022-00168-8.

Clinical impacts of the concomitant use of L-asparaginase and total parenteral nutrition containing L-aspartic acid in patients with acute lymphoblastic leukemia.

Introduction: L-asparaginase (ASNase) depletes L-asparagine and causes the death of leukemic cells, making it a mainstay for the treatment of acute lymphoblastic leukemia (ALL). However, ASNase's activity can be inhibited by L-aspartic acid (Asp), which competes for the same substrate and reduces the drug's efficacy. While many commercially used total parenteral nutrition (TPN) products contain Asp, it is unclear how the concomitant use of TPNs containing Asp (Asp-TPN) affects ALL patients treated with ASNase. This propensity-matched retrospective cohort study evaluated the clinical effects of the interaction between ASNase and Asp-TPN. Methods: The study population included newly diagnosed adult Korean ALL patients who received VPDL induction therapy consisting of vincristine, prednisolone, daunorubicin, and Escherichia coli L-asparaginase between 2004 and 2021. Patients were divided into two groups based on their exposure to Asp-TPN: (1) Asp-TPN group and (2) control group. Data, including baseline characteristics, disease information, medication information, and laboratory data, were collected retrospectively. The primary outcomes for the effectiveness were overall and complete response rates. Relapse-free survival at six months and one year of treatment were also evaluated. The safety of both TPN and ASNase was evaluated by comparing liver function test levels between groups. A 1:1 propensity score matching analysis was conducted to minimize potential selection bias. Results: The analysis included a total of 112 ALL patients, and 34 of whom received Asp-TPN and ASNase concomitantly. After propensity score matching, 30 patients remained in each group. The concomitant use of Asp-TPN and ASNase did not affect the overall response rate (odds ratio [OR] 0.53; 95% confidence interval [CI] = 0.17-1.62) or the complete response rate (OR 0.86; 95% CI = 0.29-2.59) of the ASNase-including induction therapy. The concomitant use of Asp-TPN and ASNase also did not impact relapse-free survival (RFS) at six months and one year of treatment (OR 1.00; 95% CI = 0.36-2.78 and OR 1.24; 95% CI, 0.50-3.12, respectively). The peak levels of each liver function test (LFT) and the frequency of LFT elevations were evaluated during induction therapy and showed no difference between the two groups. Conclusion: There is no clear rationale for avoiding Asp-TPN in ASNase-treated patients.

Comparison of glucagon-like peptide-1 receptor agonists and thiazolidinediones on treating nonalcoholic fatty liver disease: A network meta-analysis.

BACKGROUND/AIMS: Previous studies have revealed that glucagon-like peptide-1 receptor agonist (GLP-1RA) and thiazolidinedione (TZD) can improve nonalcoholic fatty liver disease (NAFLD) or nonalcoholic steatohepatitis (NASH). However, comprehensive research comparing the effects of GLP-1RA and TZD is limited. Thus, this study aimed to compare the effects of GLP-1RA and TZD on NAFLD or NASH through a network meta-analysis. METHODS: The PubMed, Embase, Web of Science, and Scopus databases were searched for randomized controlled trials (RCTs) that explored the efficacy of GLP-1RAs or TZDs in adult patients with NAFLD or NASH. The outcomes were liver biopsy-based (NAFLD activity score [NAS], fibrosis stage, and NASH resolution), noninvasive technique-based (liver fat content on proton magnetic resonance spectroscopy [1H-MRS] and controlled attenuation parameter [CAP]), biological, and anthropometric indicators. A random effects model was used to calculate the mean difference (MD) and relative risk with 95% confidence interval (CI). RESULTS: Twenty-five RCTs with 2,237 overweight or obese patients were included. GLP-1RA was significantly superior in reducing liver fat content evaluated using 1H-MRS (MD -2.42, 95% CI -3.84 to -1.00), body mass index (MD -1.60, 95% CI -2.41 to -0.80), and waist circumference (MD -4.89, 95% CI -8.17 to -1.61) than TZD. In liver biopsy-based evaluation and liver fat content assessment using CAP, GLP-1RA tended to surpass TZD, albeit not significantly. Sensitivity analysis showed consistent results with the main results. CONCLUSION: Compared with TZD, GLP-1RA had better effects on liver fat content, body mass index, and waist circumference in overweight or obese patients with NAFLD or NASH.

Electrocatalytic Properties of Co3O4 Prepared on Carbon Fibers by Thermal Metal-Organic Deposition for the Oxygen Evolution Reaction in Alkaline Water Electrolysis.

Cobalt oxide (Co3O4) serves as a promising electrocatalyst for oxygen evolution reactions (OER) in water-electrolytic hydrogen production. For more practical applications, advances in dry-deposition processes for the high-throughput fabrication of such Co3O4 electrocatalysts are needed. In this work, a thermal metal-organic deposition (MOD) technique is developed to form Co3O4 deposits on microscale-diameter carbon fibers constituting a carbon fiber paper (CFP) substrate for high-efficiency OER electrocatalyst applications. The Co3O4 electrocatalysts are deposited while uniformly covering the surface of individual carbon fibers in the reaction temperature range from 400 to 800 °C under an ambient Ar atmosphere. It is found that the microstructure of deposits is dependent on the reaction temperature. The Co3O4 electrocatalysts prepared at 500 °C and over exhibit values of 355-384 mV in overpotential (η10) required to reach a current density of 10 mA cm-2 and 70-79 mV dec-1 in Tafel slope, measured in 1 M KOH aqueous solution. As a result, it is highlighted that the improved crystallinity of the Co3O4 electrocatalyst with the increased reaction temperature leads to an enhancement in electrode-level OER activity with the high electrochemically active surface area (ECSA), low charge transfer resistance (Rct), and low η10, due to the enhanced electrical conductivity. On the other hand, it is found that the inherent catalytic activity of the surface sites of the Co3O4, represented by the turnover frequency (TOF), decreases with reaction temperature due to the high-temperature sintering effect. This work provides the groundwork for the high-throughput fabrication and rational design of high-performance electrocatalysts.

Effects of very low-carbohydrate ketogenic diets on lipid profiles in normal-weight (body mass index < 25 kg/m2) adults: a meta-analysis.

CONTEXT: Very low-carbohydrate diets or ketogenic diets (KDs) have garnered attention for weight loss in patients with overweight or obesity as well as for normal-weight adults, yet the adverse effects of KDs, such as dyslipidemia in normal-weight adults, have not been studied extensively. OBJECTIVE: This meta-analysis aimed to identify the effects of KDs on the lipid profile in normal-weight (body mass index [BMI] < 25 kg/m2) adults from randomized controlled trials. DATA SOURCES: PubMed and Embase databases were searched on November 21, 2021, using search terms representing KDs and lipid profiles. Two researchers independently screened articles according to PICOS inclusion criteria. DATA EXTRACTION: General study information, dietary data, and lipid profiles were extracted from eligible studies. Risk of bias was assessed using the Cochrane risk of bias 2 tool. DATA ANALYSIS: Fixed- or random-effects meta-analysis was performed to estimate the effects of KDs on total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides, apolipoprotein A (apoA), and apolipoprotein B (apoB), considering heterogeneity across studies. The certainty of evidence was assessed using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach. RESULTS: Three studies were selected for meta-analysis. A KD significantly increased TC by 1.47 mmol/L (95%CI, 0.72-2.22 mmol/L), LDL-C by 1.08 mmol/L (95%CI, 0.37-1.79 mmol/L), and apoB by 0.35 g/L (95%CI, 0.06-0.65 g/L). In addition, a KD significantly increased HDL-C by 0.35 mmol/L (95%CI, 0.27-0.42 mmol/L) and apoA by 0.34 g/L (95%CI, 0.28-0.41 g/L) compared with control diets. Triglyceride levels were not significantly different between KDs and control diets (P = 0.63). CONCLUSION: This study suggests unfavorable effects of KDs on TC and LDL-C in normal-weight adults. Although an increase in HDL-C can compensate for unfavorable changes in lipids, normal-weight individuals should consider the risk of hypercholesterolemia when consuming a KD. Results for triglycerides were inconsistent.

Participation in and withdrawal from cancer clinical trials: A survey of clinical research coordinators.

Objective: Poor accrual and withdrawal are the main reasons for the failure of cancer clinical trials. As clinical research coordinators (CRCs) work at the frontlines of clinical trials, CRCs can best identify the main factors that influence patient participation and dropout and suggest potential remedial measures. This study aimed to investigate participation and withdrawal in cancer clinical trials through a survey of CRCs. Furthermore, we collected suggestions of CRCs to increase patient participation and reduce withdrawal from cancer clinical trials. Methods: This cross-sectional survey among 100 CRC nurses currently coordinating cancer clinical trials and having more than six months of experience was conducted at four hospitals in South Korea between March and August 2021. We designed a questionnaire based on prior studies, and the key items included characteristics of respondents, characteristics of clinical trials, clinical trial participation, and withdrawal. Results: Patients refused to participate due to concern about adverse events (46.5%) and negative perception of clinical trials (44.4%). The main reasons for study withdrawal were disease progression (71.5%), adverse events (10.6%), and withdrawal of consent due to personal issues (5.5%). The provision of sufficient explanation was suggested as a remedial measure for increasing consent to participate (67.4%) and reducing withdrawal (21.8%). Conclusions: A survey of CRCs revealed the reasons governing patient participation and withdrawal in cancer clinical trials, thereby providing a novel insight into strategies for promoting subject enrollment and reducing withdrawal from cancer clinical trials.

Fine-Tuning BERT Models to Classify Misinformation on Garlic and COVID-19 on Twitter.

Garlic-related misinformation is prevalent whenever a virus outbreak occurs. With the outbreak of COVID-19, garlic-related misinformation is spreading through social media, including Twitter. Bidirectional Encoder Representations from Transformers (BERT) can be used to classify misinformation from a vast number of tweets. This study aimed to apply the BERT model for classifying misinformation on garlic and COVID-19 on Twitter, using 5929 original tweets mentioning garlic and COVID-19 (4151 for fine-tuning, 1778 for test). Tweets were manually labeled as 'misinformation' and 'other.' We fine-tuned five BERT models (BERTBASE, BERTLARGE, BERTweet-base, BERTweet-COVID-19, and BERTweet-large) using a general COVID-19 rumor dataset or a garlic-specific dataset. Accuracy and F1 score were calculated to evaluate the performance of the models. The BERT models fine-tuned with the COVID-19 rumor dataset showed poor performance, with maximum accuracy of 0.647. BERT models fine-tuned with the garlic-specific dataset showed better performance. BERTweet models achieved accuracy of 0.897-0.911, while BERTBASE and BERTLARGE achieved accuracy of 0.887-0.897. BERTweet-large showed the best performance with maximum accuracy of 0.911 and an F1 score of 0.894. Thus, BERT models showed good performance in classifying misinformation. The results of our study will help detect misinformation related to garlic and COVID-19 on Twitter.

Frequently reported adverse events of rebamipide compared to other drugs for peptic ulcer and gastroesophageal reflux disease.

This study aimed to detect safety signals of rebamipide and search for adverse events (AEs) of rebamipide that are more common than those of other drugs for peptic ulcer disease (PUD) and gastroesophageal reflux disease (GERD) in the elderly population. A total of 101,735 AE reports for drugs used to treat PUD and GERD between 2009 and 2018 from the KIDS-KAERS database (KIDS-KD) were used. Disproportionality analysis was performed to calculate the proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC). Drug labels in Korea, Japan, and China were reviewed to identify signals that have been listed. AEs frequently reported in the elderly population were also analyzed. Seriousness and median time to AEs were evaluated for statistically significant AEs. A total of 14 signals were detected, and 4 signals (dry mouth, dermatitis, purpura/petechia, and fluid overload) were not listed on drug labels; however, they may be included as part of other listed AEs. In the elderly population, 11 AEs such as dyspepsia/indigestion/gastrointestinal distress, somnolence, dry mouth, and edema were common. These AEs were not serious and occurred within 2-9 days. This study identified possible AEs of rebamipide, a relatively safe drug.

Predicting completion of clinical trials in pregnant women: Cox proportional hazard and neural network models.

This study aimed to develop a model for predicting the completion of clinical trials involving pregnant women using the Cox proportional hazard model and neural network model (DeepSurv) and to compare the predictive performance of both methods. We collected data on 819 clinical trials performed on pregnant women and intervention studies using at least one drug as intervention from 2009 to 2018 from ClinicalTrials.gov. The Cox proportional hazard model and DeepSurv were used to develop models that predict clinical trial completion. The concordance index (C-index) was used to evaluate the predictive performance. The Cox proportional hazard model revealed that a sample size of n ≥ 329 (hazard ratio [HR] = 0.53), very high human development index (HDI) country (HR = 0.28), abortion (HR = 3.30), labor (HR = 2.16), and iron deficiency anemia (HR = 2.29) were significantly related to the probability of clinical trial completion (all p value < 0.01). The C-index of the model development dataset and test dataset were 0.72 and 0.73, respectively. DeepSurv model consisted of one hidden layer with 16 nodes. DeepSurv showed the C-index comparable to the Cox proportional hazard model. The C-index of the training dataset and test dataset were 0.76 and 0.72, respectively. Further a nomogram that calculate a probability of clinical trial completion at 1 year, 3 years, and 5 years was developed. Both the Cox proportional hazard model and DeepSurv yielded sufficient predicting performance. We hope that this study will contribute to the execution of future clinical trials in pregnant women.

Antihypertensive drug use and psoriasis: A systematic review, meta- and network meta-analysis.

AIMS: Diverse genetic and/or external factors may induce psoriasis. Drug exposure is 1 such prominent external factor; antihypertensive drugs are reportedly associated with psoriasis, but study results have been inconsistent. In this context, we investigated the associations between antihypertensive drugs and incidence if psoriasis via a systematic literature review and meta-analysis. METHODS: Literature search in databases such as PubMed, Embase and Web of Science was conducted on 8 January 2021, and obtained data were pooled for meta- and network meta-analysis. Fixed- or random effect models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for evaluating the strength of the associations between antihypertensive drugs and psoriasis incidence. In addition to meta-analysis, Bayesian network meta-analysis was performed. ResultsThirteen eligible studies were included for meta-analysis with 6 378 116 individuals and 8 studies for network meta-analysis with 5 615 918 individuals. All antihypertensive drugs were significantly associated with psoriasis incidence. In a meta-analysis, the pooled ORs were 1.67 (95% CI: 1.31-2.13) for angiotensin-converting enzyme (ACE) inhibitors, 1.40 (95% CI: 1.20-1.63) for ß-blockers, 1.53 (95% CI: 1.23-1.89) for calcium-channel blockers (CCBs), and 1.70 (95% CI: 1.40-2.06) for thiazide diuretics. For the comparative risks of psoriasis among antihypertensive drugs in the network meta-analysis, ORs were 2.09 (95% CI: 1.39-3.18) for ACE inhibitors, 1.35 (95% CI: 0.99-1.91) for BBs, 1.53 (95% CI: 1.07-2.24) for CCBs and 1.80 (95% CI: 1.23-2.66) for thiazide diuretics. CONCLUSION: This study confirmed the associations between antihypertensive drugs and psoriasis; ACE inhibitors, BBs, CCBs and thiazide diuretics increased the risk of psoriasis. Therefore, antihypertensive drug users should be carefully monitored for psoriasis.

The risk of pulmonary adverse drug reactions of rebamipide and other drugs for acid-related diseases: An analysis of the national pharmacovigilance database in South Korea.

OBJECTIVE: The objective of this case/non-case study was to detect rebamipide-related pulmonary adverse events (AE) compared with other drugs for acid-related disorders based on population-level data. METHODS: From 2009 to 2018, AE reports on drugs for acid-related disorders, which are anatomical therapeutic chemical code A02B drugs, in the Korea Adverse Events Reporting System (KAERS) database were examined. The reporting odds ratio (ROR) was calculated, and the odds of reporting pulmonary AE for rebamipide and all other A02B drugs were compared. Furthermore, a stratified analysis according to patients' age and sex was conducted. RESULTS: Altogether 13 (0.05%) and 157 (0.11%) cases of pulmonary AE were reported for rebamipide and all other A02B drugs, respectively. The risk of reporting pulmonary AE was significantly lower for rebamipide than for all other A02B drugs (ROR 0.49, 95% confidence interval [CI] 0.28-0.87). The number of reports of pulmonary AE for rebamipide was significantly higher among patients aged ≥65 years than those aged <65 years (ROR 19.36, 95% CI 2.50-149.97). CONCLUSIONS: Rebamipide was less often reported for pulmonary AE. However, healthcare professionals need to be aware of the risk of pulmonary AE in elderly patients.

Effects of Coffee Consumption on Insulin Resistance and Sensitivity: A Meta-Analysis.

Coffee is widely consumed worldwide and impacts glucose metabolism. After a previous meta-analysis that evaluated the effects of coffee consumption on insulin resistance and sensitivity, additional randomized controlled trials (RCTs) were conducted. This meta-analysis aimed to evaluate the effects of coffee consumption on insulin resistance or sensitivity. We selected RCTs that evaluated the effects of coffee consumption for seven days or more on insulin sensitivity or resistance using surrogate indices (homeostasis model assessment for insulin resistance (HOMA-IR) and Matsuda index). The fixed-effects or random-effects model was used according to heterogeneity. Four studies with 268 participants were analyzed in this meta-analysis. Coffee consumption significantly decreased HOMA-IR compared to control (mean difference (MD) = -0.13; 95% CI = -0.24--0.03; p-value = 0.01). However, the significance was not maintained in the sensitivity analysis (MD = -0.04; 95% CI = -0.18-0.10; p-value = 0.55) after excluding data from the healthy, young, normal-weight group. Matsuda index was not significantly different between coffee and control groups (standardized mean difference (SMD) = -0.33; 95% CI = -0.70-0.03; p-value = 0.08). In conclusion, long-term coffee consumption has a nonsignificant effect on insulin resistance and sensitivity. More studies evaluating the effects of coffee consumption in the healthy, young, and normal-weight individuals are needed.