Discovery and Characterization of VU0542270, the First Selective Inhibitor of Vascular Kir6.1/SUR2B KATP Channels.

Vascular smooth muscle KATP channels critically regulate blood flow and blood pressure by modulating vascular tone and therefore represent attractive drug targets for treating several cardiovascular disorders. However, the lack of potent inhibitors that can selectively inhibit Kir6.1/SUR2B (vascular KATP) over Kir6.2/SUR1 (pancreatic KATP) has eluded discovery despite decades of intensive research. We therefore screened 47,872 chemically diverse compounds for novel inhibitors of heterologously expressed Kir6.1/SUR2B channels. The most potent inhibitor identified in the screen was an N-aryl-N'-benzyl urea compound termed VU0542270. VU0542270 inhibits Kir6.1/SUR2B with an IC50 of approximately 100 nM but has no apparent activity toward Kir6.2/SUR1 or several other members of the Kir channel family at doses up to 30 µM (>300-fold selectivity). By expressing different combinations of Kir6.1 or Kir6.2 with SUR1, SUR2A, or SUR2B, the VU0542270 binding site was localized to SUR2. Initial structure-activity relationship exploration around VU0542270 revealed basic texture related to structural elements that are required for Kir6.1/SUR2B inhibition. Analysis of the pharmacokinetic properties of VU0542270 showed that it has a short in vivo half-life due to extensive metabolism. In pressure myography experiments on isolated mouse ductus arteriosus vessels, VU0542270 induced ductus arteriosus constriction in a dose-dependent manner similar to that of the nonspecific KATP channel inhibitor glibenclamide. The discovery of VU0542270 provides conceptual proof that SUR2-specific KATP channel inhibitors can be developed using a molecular target-based approach and offers hope for developing cardiovascular therapeutics targeting Kir6.1/SUR2B. SIGNIFICANCE STATEMENT: Small-molecule inhibitors of vascular smooth muscle KATP channels might represent novel therapeutics for patent ductus arteriosus, migraine headache, and sepsis; however, the lack of selective channel inhibitors has slowed progress in these therapeutic areas. Here, this study describes the discovery and characterization of the first vascular-specific KATP channel inhibitor, VU0542270.

Evaluation of GPT-4 for 10-year cardiovascular risk prediction: Insights from the UK Biobank and KoGES data.

Cardiovascular disease (CVD) remains a pressing global health concern. While traditional risk prediction methods such as the Framingham and American College of Cardiology/American Heart Association (ACC/AHA) risk scores have been widely used in the practice, artificial intelligence (AI), especially GPT-4, offers new opportunities. Utilizing large scale of multi-center data from 47,468 UK Biobank participants and 5,718 KoGES participants, this study quantitatively evaluated the predictive capabilities of GPT-4 in comparison with traditional models. Our results suggest that the GPT-based score showed commendably comparable performance in CVD prediction when compared to traditional models (AUROC on UKB: 0.725 for GPT-4, 0.733 for ACC/AHA, 0.728 for Framingham; KoGES: 0.664 for GPT-4, 0.674 for ACC/AHA, 0.675 for Framingham). Even with omission of certain variables, GPT-4's performance was robust, demonstrating its adaptability to data-scarce situations. In conclusion, this study emphasizes the promising role of GPT-4 in predicting CVD risks across varied ethnic datasets, pointing toward its expansive future applications in the medical practice.

Structure-Based Discovery of Potent, Orally Bioavailable Benzoxazepinone-Based WD Repeat Domain 5 Inhibitors.

The chromatin-associated protein WDR5 (WD repeat domain 5) is an essential cofactor for MYC and a conserved regulator of ribosome protein gene transcription. It is also a high-profile target for anti-cancer drug discovery, with proposed utility against both solid and hematological malignancies. We have previously discovered potent dihydroisoquinolinone-based WDR5 WIN-site inhibitors with demonstrated efficacy and safety in animal models. In this study, we sought to optimize the bicyclic core to discover a novel series of WDR5 WIN-site inhibitors with improved potency and physicochemical properties. We identified the 3,4-dihydrobenzo[f][1,4]oxazepin-5(2H)-one core as an alternative scaffold for potent WDR5 inhibitors. Additionally, we used X-ray structural analysis to design partially saturated bicyclic P7 units. These benzoxazepinone-based inhibitors exhibited increased cellular potency and selectivity and favorable physicochemical properties compared to our best-in-class dihydroisoquinolinone-based counterparts. This study opens avenues to discover more advanced WDR5 WIN-site inhibitors and supports their development as novel anti-cancer therapeutics.

Changes in the Circadian Rhythm of High-Frequency Heart Rate Variability Associated With Depression.

BACKGROUND: Heart rate variability (HRV) extracted from electrocardiogram measured for a short period during a resting state is clinically used as a bio-signal reflecting the emotional state. However, as interest in wearable devices increases, greater attention is being paid to HRV extracted from long-term electrocardiogram, which may contain additional clinical information. The purpose of this study was to examine the characteristics of HRV parameters extracted through long-term electrocardiogram and explore the differences between participants with and without depression and anxiety symptoms. METHODS: Long-term electrocardiogram was acquired from 354 adults with no psychiatric history who underwent Holter monitoring. Evening and nighttime HRV and the ratio of nighttime-to-evening HRV were compared between 127 participants with depressive symptoms and 227 participants without depressive symptoms. Comparisons were also made between participants with and without anxiety symptoms. RESULTS: Absolute values of HRV parameters did not differ between groups based on the presence of depressive or anxiety symptoms. Overall, HRV parameters increased at nighttime compared to evening. Participants with depressive symptoms showed a significantly higher nighttime-to-evening ratio of high-frequency HRV than participants without depressive symptoms. The nighttime-to-evening ratio of HRV parameters did not show a significant difference depending on the presence of anxiety symptoms. CONCLUSION: HRV extracted through long-term electrocardiogram showed circadian rhythm. Depression may be associated with changes in the circadian rhythm of parasympathetic tone.

Synthesis and SAR of a novel Kir6.2/SUR1 channel opener scaffold identified by HTS.

Kir6.2/SUR1 is an ATP-regulated potassium channel that acts as an intracellular metabolic sensor, controlling insulin and appetite-stimulatory neuropeptides secretion. In this Letter, we present the SAR around a novel Kir6.2/SUR1 channel opener scaffold derived from an HTS screening campaign. New series of compounds with tractable SAR trends and favorable potencies are reported.

Discovery of a potent M5 antagonist with improved clearance profile. Part 2: Pyrrolidine amide-based antagonists.

This Letter describes our ongoing effort to improve the clearance of selective M5 antagonists. Herein, we report the replacement of the previously disclosed piperidine amide (4, disclosed in Part 1) with a pyrrolidine amide core. Several compounds within this series provided good potency, subtype selectivity, and low to moderate clearance profiles. Interestingly, the left-hand side SAR for this series diverged from our earlier efforts.

Discovery of a potent M5 antagonist with improved clearance profile. Part 1: Piperidine amide-based antagonists.

The lack of potent and selective tool compounds with pharmaceutically favorable properties limits the in vivo understanding of muscarinic acetylcholine receptor subtype 5 (M5) biology. Previously, we presented a highly potent and selective M5 antagonist VU6019650 with a suboptimal clearance profile as our second-generation tool compound. Herein, we disclose our ongoing efforts to generate next-generation M5 antagonists with improved clearance profiles. A mix and match approach between VU6019650 (lead) and VU0500325 (HTS hit) generated a piperidine amide-based novel M5 antagonist series. Several analogs within this series, including 29f, provided good on-target potency with improved clearance profiles, though room for improvement remains.

Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.

Coronary artery calcium (CAC), which can be measured in various types of computed tomography (CT) examinations, is a hallmark of coronary artery atherosclerosis. However, despite the clinical value of CAC scores in predicting cardiovascular events, routine measurement of CAC scores is limited due to high cost, radiation exposure, and lack of widespread availability. It would be of great clinical significance if CAC could be predicted by electrocardiograms (ECGs), which are cost-effective and routinely performed during various medical checkups. We aimed to develop binary classification artificial intelligence (AI) models that predict CAC using only ECGs as input. Moreover, we aimed to address the generalizability of our model in different environments by externally validating our model on a dataset from a different institution. Among adult patients, standard 12-lead ECGs were extracted if measured within 60 days before or after the CAC scores, and labeled with the corresponding CAC scores. We constructed deep convolutional neural network models based on residual networks using only the raw waveforms of the ECGs as input, predicting CAC at different levels, namely CAC score ≥100, ≥400 and ≥1,000. Our AI models performed well in predicting CAC in the training and internal validation dataset [area under the receiver operating characteristics curve (AUROC) 0.753 ± 0.009, 0.802 ± 0.027, and 0.835 ± 0.024 for the CAC score ≥100, ≥400, and ≥1,000 model, respectively]. Our models also performed well in the external validation dataset (AUROC 0.718, 0.777 and 0.803 for the CAC score ≥100, ≥400, and ≥1,000 model, respectively), indicating that our model can generalize well to different but plausibly related populations. Model performance in terms of AUROC increased in the order of CAC score ≥100, ≥400, and ≥1,000 model, indicating that higher CAC scores might be associated with more prominent structural changes of the heart detected by the model. With our AI models, a substantial proportion of previously unrecognized CAC can be afforded with a risk stratification of CAC, enabling initiation of prophylactic therapy, and reducing the adverse consequences related to ischemic heart disease.

Evaluating the Risk of Paroxysmal Atrial Fibrillation in Noncardioembolic Ischemic Stroke Using Artificial Intelligence-Enabled ECG Algorithm.

Background: The identification of latent atrial fibrillation (AF) in patients with ischemic stroke (IS) attributed to noncardioembolic etiology may have therapeutic implications. An artificial intelligence (AI) model identifying the electrocardiographic signature of AF present during normal sinus rhythm (NSR; AI-ECG-AF) can identify individuals with a high likelihood of paroxysmal AF (PAF) with NSR electrocardiogram (ECG). Objectives: Using AI-ECG-AF, we aimed to compare the PAF risk between noncardioembolic IS subgroups and general patients of a university hospital after controlling for confounders. Further, we sought to compare the risk of PAF among noncardioembolic IS subgroups. Methods: After training AI-ECG-AF with ECG data of university hospital patients, model inference outputs were obtained for the control group (i.e., general patient population) and NSRs of noncardioembolic IS patients. We conducted multiple linear regression (MLiR) and multiple logistic regression (MLoR) analyses with inference outputs (for MLiR) or their binary form (set at threshold = 0.5 for MLoR) used as dependent variables and patient subgroups and potential confounders (age and sex) set as independent variables. Results: The number of NSRs inferenced for the control group, cryptogenic, large artery atherosclerosis (LAA), and small artery occlusion (SAO) strokes were 133,340, 133, 276, and 290, respectively. The regression analyses indicated that patients with noncardioembolic IS had a higher PAF risk based on AI-ECG-AF relative to the control group, after controlling for confounders with the "cryptogenic" subgroup having the highest risk (odds ratio [OR] = 1.974, 95% confidence interval [CI]: 1.371-2.863) followed by the "LAA" (OR = 1.592, 95% CI: 1.238-2.056) and "SAO" subgroups (OR = 1.400, 95% CI: 1.101-1.782). Subsequent regression analyses failed to illustrate the differences in PAF risk based on AI-ECG-AF among noncardioembolic IS subgroups. Conclusion: Using AI-ECG-AF, we found that noncardioembolic IS patients had a higher PAF risk relative to the general patient population. The results from our study imply the need for more vigorous cardiac monitoring in noncardioembolic IS patients. AI-ECG-AF can be a cost-effective screening tool to identify high-risk noncardioembolic IS patients of PAF on-the-spot to be candidates for receiving additional prolonged cardiac monitoring. Our study highlights the potential of AI in clinical practice.

Development of VU6019650: A Potent, Highly Selective, and Systemically Active Orthosteric Antagonist of the M5 Muscarinic Acetylcholine Receptor for the Treatment of Opioid Use Disorder.

The muscarinic acetylcholine receptor (mAChR) subtype 5 (M5) represents a novel potential target for the treatment of multiple addictive disorders, including opioid use disorder. Through chemical optimization of several functional high-throughput screening hits, VU6019650 (27b) was identified as a novel M5 orthosteric antagonist with high potency (human M5 IC50 = 36 nM), M5 subtype selectivity (>100-fold selectivity against human M1-4) and favorable physicochemical properties for systemic dosing in preclinical addiction models. In acute brain slice electrophysiology studies, 27b blocked the nonselective muscarinic agonist oxotremorine-M-induced increases in neuronal firing rates of midbrain dopamine neurons in the ventral tegmental area, a part of the mesolimbic dopaminergic reward circuitry. Moreover, 27b also inhibited oxycodone self-administration in male Sprague-Dawley rats within a dose range that did not impair general motor output.

Generation of formaldehyde and formaldehyde-d2 for hydroxymethylations and hydroxydeuteromethylations of difluoroenolates and difluorobenzyl carbanions.

A method for the in situ production of formaldehyde from dimethylsulfoxide, bromine, and cesium carbonate is reported for reactions with difluoroenolates and difluorobenzyl carbanions. This process also generates formaldehyde-d2 for the production of 2,2-difluoro-1,1-deuteroethanols. Mechanistic and computational studies further characterize the production of hydroxymethylated and hydroxydeuteromethylated difluorinated organic molecules.

VU6036720: The First Potent and Selective In Vitro Inhibitor of Heteromeric Kir4.1/5.1 Inward Rectifier Potassium Channels.

Heteromeric Kir4.1/Kir5.1 (KCNJ10/KCNJ16) inward rectifier potassium (Kir) channels play key roles in the brain and kidney, but pharmacological tools for probing their physiology and therapeutic potential have not been developed. Here, we report the discovery, in a high-throughput screening of 80,475 compounds, of the moderately potent and selective inhibitor VU0493690, which we selected for characterization and chemical optimization. VU0493690 concentration-dependently inhibits Kir4.1/5.1 with an IC50 of 0.96 µM and exhibits at least 10-fold selectivity over Kir4.1 and ten other Kir channels. Multidimensional chemical optimization of VU0493690 led to the development of VU6036720, the most potent (IC50 = 0.24 µM) and selective (>40-fold over Kir4.1) Kir4.1/5.1 inhibitor reported to date. Cell-attached patch single-channel recordings revealed that VU6036720 inhibits Kir4.1/5.1 activity through a reduction of channel open-state probability and single-channel current amplitude. Elevating extracellular potassium ion by 20 mM shifted the IC50 6.8-fold, suggesting that VU6036720 is a pore blocker that binds in the ion-conduction pathway. Mutation of the "rectification controller" asparagine 161 to glutamate (N161E), which is equivalent to small-molecule binding sites in other Kir channels, led to a strong reduction of inhibition by VU6036720. Renal clearance studies in mice failed to show a diuretic response that would be consistent with inhibition of Kir4.1/5.1 in the renal tubule. Drug metabolism and pharmacokinetics profiling revealed that high VU6036720 clearance and plasma protein binding may prevent target engagement in vivo. In conclusion, VU6036720 represents the current state-of-the-art Kir4.1/5.1 inhibitor that should be useful for probing the functions of Kir4.1/5.1 in vitro and ex vivo. SIGNIFICANCE STATEMENT: Heteromeric inward rectifier potassium (Kir) channels comprising Kir4.1 and Kir5.1 subunits play important roles in renal and neural physiology and may represent inhibitory drug targets for hypertension and edema. Herein, we employ high-throughput compound library screening, patch clamp electrophysiology, and medicinal chemistry to develop and characterize the first potent and specific in vitro inhibitor of Kir4.1/5.1, VU6036720, which provides proof-of-concept that drug-like inhibitors of this channel may be developed.

Biosignal-Based Digital Biomarkers for Prediction of Ventilator Weaning Success.

We evaluated new features from biosignals comprising diverse physiological response information to predict the outcome of weaning from mechanical ventilation (MV). We enrolled 89 patients who were candidates for weaning from MV in the intensive care unit and collected continuous biosignal data: electrocardiogram (ECG), respiratory impedance, photoplethysmogram (PPG), arterial blood pressure, and ventilator parameters during a spontaneous breathing trial (SBT). We compared the collected biosignal data's variability between patients who successfully discontinued MV (n = 67) and patients who did not (n = 22). To evaluate the usefulness of the identified factors for predicting weaning success, we developed a machine learning model and evaluated its performance by bootstrapping. The following markers were different between the weaning success and failure groups: the ratio of standard deviations between the short-term and long-term heart rate variability in a Poincaré plot, sample entropy of ECG and PPG, α values of ECG, and respiratory impedance in the detrended fluctuation analysis. The area under the receiver operating characteristic curve of the model was 0.81 (95% confidence interval: 0.70-0.92). This combination of the biosignal data-based markers obtained during SBTs provides a promising tool to assist clinicians in determining the optimal extubation time.

Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals-Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study.

BACKGROUND: When using a smartwatch to obtain electrocardiogram (ECG) signals from multiple leads, the device has to be placed on different parts of the body sequentially. The ECG signals measured from different leads are asynchronous. Artificial intelligence (AI) models for asynchronous ECG signals have barely been explored. OBJECTIVE: We aimed to develop an AI model for detecting acute myocardial infarction using asynchronous ECGs and compare its performance with that of the automatic ECG interpretations provided by a commercial ECG analysis software. We sought to evaluate the feasibility of implementing multiple lead-based AI-enabled ECG algorithms on smartwatches. Moreover, we aimed to determine the optimal number of leads for sufficient diagnostic power. METHODS: We extracted ECGs recorded within 24 hours from each visit to the emergency room of Ajou University Medical Center between June 1994 and January 2018 from patients aged 20 years or older. The ECGs were labeled on the basis of whether a diagnostic code corresponding to acute myocardial infarction was entered. We derived asynchronous ECG lead sets from standard 12-lead ECG reports and simulated a situation similar to the sequential recording of ECG leads via smartwatches. We constructed an AI model based on residual networks and self-attention mechanisms by randomly masking each lead channel during the training phase and then testing the model using various targeting lead sets with the remaining lead channels masked. RESULTS: The performance of lead sets with 3 or more leads compared favorably with that of the automatic ECG interpretations provided by a commercial ECG analysis software, with 8.1%-13.9% gain in sensitivity when the specificity was matched. Our results indicate that multiple lead-based AI-enabled ECG algorithms can be implemented on smartwatches. Model performance generally increased as the number of leads increased (12-lead sets: area under the receiver operating characteristic curve [AUROC] 0.880; 4-lead sets: AUROC 0.858, SD 0.008; 3-lead sets: AUROC 0.845, SD 0.011; 2-lead sets: AUROC 0.813, SD 0.018; single-lead sets: AUROC 0.768, SD 0.001). Considering the short amount of time needed to measure additional leads, measuring at least 3 leads-ideally more than 4 leads-is necessary for minimizing the risk of failing to detect acute myocardial infarction occurring in a certain spatial location or direction. CONCLUSIONS: By developing an AI model for detecting acute myocardial infarction with asynchronous ECG lead sets, we demonstrated the feasibility of multiple lead-based AI-enabled ECG algorithms on smartwatches for automated diagnosis of cardiac disorders. We also demonstrated the necessity of measuring at least 3 leads for accurate detection. Our results can be used as reference for the development of other AI models using sequentially measured asynchronous ECG leads via smartwatches for detecting various cardiac disorders.

DARK Classics in Chemical Neuroscience: Loperamide.

Loperamide, a popular and inexpensive over-the-counter antidiarrheal medicine, is a potent µ-opioid receptor agonist approved by the U.S. Food and Drug Administration (FDA). It has been on the market since 1976 and is relatively safe with no central nervous system-related side effects when used for a short period of time at the recommended therapeutic dose (2-8 mg/day). In recent years, loperamide has become notoriously known as the "poor man's methadone" for people with substance dependence due to the increase in loperamide overdoses from self-administered medication to treat opioid withdrawal symptoms. As a result, in 2018, the FDA decided to limit the available packaged dose of loperamide to stop prominent abuse. This review provides the synthesis and chemical properties of loperamide as well as the pharmacology and adverse effects of its use and the social effects of such abuse.

Discovery of VU6028418: A Highly Selective and Orally Bioavailable M4 Muscarinic Acetylcholine Receptor Antagonist.

Herein, we report the SAR leading to the discovery of VU6028418, a potent M4 mAChR antagonist with high subtype-selectivity and attractive DMPK properties in vitro and in vivo across multiple species. VU6028418 was subsequently evaluated as a preclinical candidate for the treatment of dystonia and other movement disorders. During the characterization of VU6028418, a novel use of deuterium incorporation as a means to modulate CYP inhibition was also discovered.

Recent advancements in the measurement of pathogenic airborne viruses.

Air-transmissible pathogenic viruses, such as influenza viruses and coronaviruses, are some of the most fatal strains and spread rapidly by air, necessitating quick and stable measurements from sample air volumes to prevent further spread of diseases and to take appropriate steps rapidly. Measurements of airborne viruses generally require their collection into liquids or onto solid surfaces, with subsequent hydrosolization and then analysis using the growth method, nucleic-acid-based techniques, or immunoassays. Measurements can also be performed in real time without sampling, where species-specific determination is generally disabled. In this review, we introduce some recent advancements in the measurement of pathogenic airborne viruses. Air sampling and measurement technologies for viral aerosols are reviewed, with special focus on the effects of air sampling on damage to the sampled viruses and their measurements. Measurement of pathogenic airborne viruses is an interdisciplinary research area that requires understanding of both aerosol technology and biotechnology to effectively address the issues. Hence, this review is expected to provide some useful guidelines regarding appropriate air sampling and virus detection methods for particular applications.

Current status of the spontaneous reporting and classification/coding system for herbal and traditional medicine in pharmacovigilance.

BACKGROUND: While the use of herbal and traditional medicine (H&TM) has been extensive worldwide, the current status of H&TM management in pharmacovigilance remains to be investigated. To date, there is little information regarding the use of the classification/coding system (CCS) to detect signals for certain drugs within databases built on the basis of the spontaneous reporting system (SRS). The purpose of this study is to investigate the status of the SRS and CCS for H&TM in the pharmacovigilance systems of various countries around the world. METHODS: An e-mail survey was performed from late December 2018 to early January 2019 with 54 experts in pharmacovigilance. The results based on the information provided by the respondents were summarized. RESULTS: Fourteen experts from 13 countries responded to the survey. Eleven countries/regions were found to already include H&TM in their SRSs, managing only limited range of H&TM. Of the 9 countries/regions that provided the information on the status of CCS for H&TM in their domestic pharmacovigilance systems, only China had a separate CCS for H&TM. CONCLUSION: Revising the current pharmacovigilance systems to include or expand the range of H&TM, and developing an internationally harmonized system to classify and code H&TM suitable to the unique characteristics of H&TM are critical and overall beneficial.

Integrated microfluidic platform with electrohydrodynamic focusing and a carbon-nanotube-based field-effect transistor immunosensor for continuous, selective, and label-free quantification of bacteria.

Electrokinetic technologies such as AC electro-osmosis (EO) and dielectrophoresis (DEP) have been used for effective manipulation of bacteria to enhance the sensitivity of an assay, and many previously reported electrokinetics-enhanced biosensors are based on stagnant fluids. An effective region for positive DEP for particle capture is usually too close to the electrode for the flowing particles to move toward the detection zone of a biosensor against the flow direction; this poses a technical challenge for electrokinetics-assisted biosensors implemented within pressure-driven flows, especially if the particles flow with high speed and if the detection zone is small. Here, we present a microfluidic single-walled carbon nanotube (SWCNT)-based field-effect transistor immunosensor with electrohydrodynamic (EHD) focusing and DEP concentration for continuous and label-free detection of flowing Staphylococcus aureus in a 0.01× phosphate buffered saline (PBS) solution. The EHD focusing involved AC EO and negative DEP to align the flowing particles along lines close to the bottom surface of a microfluidic channel for facilitating particle capture downstream at the detection zone. For feasibility, 380 nm-diameter fluorescent beads suspended in 0.001× PBS were tested, and 14.6 times more beads were observed to be concentrated in the detection area with EHD focusing. Moreover, label-free, continuous, and selective measurement of S. aureus in 0.01× PBS was demonstrated, showing good linearity between the relative changes in electrical conductance of the SWCNTs and logarithmic S. aureus concentrations, a capture/detection time of 35 min, and a limit of detection of 150 CFU mL-1, as well as high specificity through electrical manipulation and biological interaction.

Electroacupuncture for post-stroke dysphagia: A protocol for systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Post-stroke dysphagia (PSD) requires effective treatment as it may cause aspiration pneumonia, dehydration, or malnutritution, which can increase the length of hospital stay as well as mortality. In the field of stroke, electroacupuncture (EA) has been widely used, and a number of clinical research papers have been published regarding its effects. This systematic review aims to evaluate the effectiveness of EA for the treatment of PSD. METHODS: Randomized controlled trials evaluating the use of EA in PSD will be included in this meta-analysis. The following electronic databases will be searched from inception to July 31, 2020, using terms relating to EA and PSD: PubMed, the Cochrane Library, the Excerpta Medica Database, China National Knowledge Infrastructure, the Korean Medical Database, KoreaMed, the National Digital Science Library, and the Oriental Medicine Advanced Searching Integrated System. Two reviewers will independently search these databases, select studies for inclusion, and evaluate the quality of the studies. Methodological quality will be assessed using the Cochrane Handbook for Systematic Reviews of Interventions (version 6.0). The primary outcome will be the total effective rate; secondary outcomes will include results of other assessments of dysphagia such as the water drinking test scale and videofluoroscopic swallowing study. We will also investigate the number and severity of adverse events. The Cochrane Review Manager (RevMan) software (version 5.3.5) will be employed to assess bias risk, data integration risk, and meta-analysis risk. Mean difference and standardized mean difference will be used to represent continuous data, while risk ratios will be used for pooled binary data. RESULTS: This study will provide a comprehensive review and evaluation of the available evidence regarding the efficacy and safety of EA as a treatment for PSD. CONCLUSION: This study will clarify whether EA could be an effective and safe treatment for PSD.