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System, Renin-Angiotensin

The System, Renin-Angiotensin is a complex hormonal system that regulates blood pressure, fluid and electrolyte balance, and other physiological processes.
It involves the production and actions of the peptide hormones renin, angiotensin, and aldosterone.
Disturbances in this system have been implicated in various cardiovascular and renal disorders.
PubCompare.ai's AI-driven platform helps researchers optimize protocols for studying the Renin-Angiotensin system, ensuring enhanced reproducbility and accuracy.
By locating the best protocols from literature, preprints, and patents, and enabling seamless comparisons, PubCompare.ai empowers researchers to identify the most effective options and improve their research outcomes.

Most cited protocols related to «System, Renin-Angiotensin»

We identified patients with congestive heart failure from the combination of a previous diagnosis of heart failure (425, 4270, 4271, I110, I42, I50, J819) in the national patient registry and treatment with loop diuretics (C03C).18 (link) We identified patients with hypertension from combination treatment with at least two of the following classes of antihypertensive drugs: α adrenergic blockers (C02A, C02B, C02C), non-loop diuretics (C02DA, C02L, C03A, C03B, C03D, C03E, C03X, C07C, C07D, C08G, C09BA, C09DA, C09XA52), vasodilators (C02DB, C02DD, C02DG, C04, C05), β blockers (C07), calcium channel blockers (C07F, C08, C09BB, C09DB), and renin-angiotensin system inhibitors (C09). This definition of hypertension was validated in a previously described randomly selected cohort of people from the Danish population aged 16 years and older.19 (link) Of the 14 994 people in this cohort, 2028 reported having taken drugs for hypertension within a two week period before the interview. The positive predictive value of treatment with two classes of antihypertensive drugs to predict hypertension was 80.0%, and the specificity was 94.7%. We defined diabetes mellitus as a claimed prescription for a glucose lowering drug (A10). Information on previous thromboembolism—that is, peripheral artery embolism, stroke, transient ischaemic attack, and pulmonary embolism (433-438, 444, 450, G458, G459, I26, I63, I64, I74)—came from the national patient registry (from 1978), as did information on previous vascular disease—that is, myocardial infarction, peripheral artery disease, and aortic plaque (410, 440, I21, I22, I700, I702-I709), as defined by Lip and colleagues.13 (link)
20 (link)
21 (link)
22 (link)
23 (link)
The CHADS2 score was the sum of points obtained after addition of one point each for heart failure, hypertension, age≥75, and diabetes and two points for previous thromboembolism. This score thus ranged from 0 to 6.11 (link) The CHA2DS2-VASc score was the sum of points after addition of one point each for heart failure, hypertension, diabetes, vascular disease, age 65-74 years, and female sex and two points each for previous thromboembolism and age≥75 years. This score thus ranged from 0 to 9.13 (link) In both risk schemes, we considered a score of 0 to represent low risk, 1 to represent intermediate risk, and ≥2 to represent high risk of thromboembolism.
Publication 2011
Adrenergic Antagonists Antihypertensive Agents Aorta Arteries Calcium Channel Blockers Cerebrovascular Accident Congestive Heart Failure Diabetes Mellitus Diagnosis Embolism Females Glucose High Blood Pressures inhibitors Loop Diuretics Myocardial Infarction Patients Peripheral Arterial Diseases Pharmaceutical Preparations Pulmonary Embolism Senile Plaques System, Renin-Angiotensin Thromboembolism Transient Ischemic Attack Vascular Diseases Vasodilator Agents
In preliminary GWA analyses in HCT-treated European American PEAR Study participants, each SNP was tested for association with the BP response phenotypes using an additive model that included pretreatment blood pressure level, sex, and age as adjustment variables.12 (link) Although principal components (PC) analysis detected no population substructure, the first and second PCs were forced into all models. The SNP association results from both PEAR and GERA Study samples were combined in a meta-analysis, assuming fixed effects and using inverse-variance weighting as implemented in the METAL software program.13 (link) SNPs with meta-analysis p-values ≤5 × 10-8 were deemed genome-wide significant.14 (link) From SNPs with meta-analysis p-values ≤1 × 10-5, we selected 1-2 SNPs with the smallest p-values at each locus to test for replication in the HCT-treated NORDIL Study participants. Replication in NORDIL Study participants was defined as a Bonferroni-corrected one-sided p<0.05, since only SNPs with the same direction of effect as in PEAR and GERA Study participants were of interest. SNPs that replicated in NORDIL Study participants were further tested for replication in HCT-treated participants from the GENRES and the Milan (Italian) Study.
Additional validation of the SNP associations that replicated among HCT-treated European hypertensives was pursued in two ways. First, we assessed whether variation across the entire region of the genes identified (in hypertensives of European descent) may be associated with BP response to HCT among African Americans. Second, because known predictors of BP response to diuretics are inversely related to BP response to beta blockers and other inhibitors of the renin-angiotensin system,15 (link) we assessed whether the SNPs associated with BP response to HCT had opposite direction associations with BP response to a beta blocker in the PEAR Study European Americans randomized to atenolol.11 (link) Finally, we tested the PRKCA SNP most strongly and consistently associated with BP response to HCT (i.e., rs16960228) for association with lymphocyte mRNA expression (please see http://hyper.aha.journals.org, Supplementary Methods).
Publication 2013
Adrenergic beta-Antagonists African American Atenolol Blood Pressure Diuretics DNA Replication Europeans Genetic Diversity Genome Genome-Wide Association Study inhibitors Lymphocyte Metals Pears Phenotype PRKCA protein, human RNA, Messenger System, Renin-Angiotensin
Animals were divided into the following experimental groups and were exposed to the same treatment protocol as in series 1:

TGR + vehicle (n = 8)

HanSD + vehicle (n = 7)

TGR + c-AUCB (n = 8)

HanSD + c-AUCB (n = 7)

Since it is now recognized that plasma and tissue ANG II concentrations in anesthetized animals are higher than those obtained from decapitated conscious rats and that normotensive animals exhibit greater increases in renin secretion in response to anesthesia and surgery than ANG II-dependent hypertensive intrarenal renin-depleted animals [22 (link)], in the present study rats from each experimental group were killed by decapitation and plasma and tissue collected. Plasma, whole kidney, and LV myocardial ANG II levels were measured by radioimmunoassay as described previously [22 (link)]. This approach for blood and tissue sampling and ANG II assay, which is routinely used in our laboratory, allows comparison of the present results with those of our previous studies evaluating the role of the renin-angiotensin system (RAS) in the pathophysiology of hypertension and tissue damage [14 (link),21 (link)-23 (link)].
Publication 2012
Anesthesia Animals Biological Assay BLOOD Consciousness Decapitation High Blood Pressures Kidney Myocardium Operative Surgical Procedures Plasma Radioimmunoassay Rattus norvegicus Renin secretion System, Renin-Angiotensin Tissues Treatment Protocols

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Publication 2014
Blood Pressure Calcium Channel Blockers Diet, Protein-Restricted Disease Progression IGA Glomerulonephritis Immunosuppression Immunosuppressive Agents Kidney Kidney Diseases Lupus Nephritis Membranous Glomerulonephritis Patients Proteins System, Renin-Angiotensin Urine
Exposure information was collected from the regional registry of all drugs dispensed by public and private pharmacies (Pharm); this registry is described in detail elsewhere and in the appendix.18 (link) All drugs in this study were included in the patients' health care plans and are equally available to all residents in accordance with the universal health care coverage provided to residents of Italy.
Drug exposure was defined on the basis of recommendations by international and national guidelines for secondary prevention after AMI.1 (link),2 Information about prescriptions of platelet aggregation inhibitors Anatomical Therapeutic Chemical (ATC) classification system: B01AC04, B01AC05, B01AC06), beta blocking agents (ATC: C07), agents acting on the renin-angiotensin system (ATC: C09), and HMG-CoA reductase inhibitors (ATC: C10AA) were retrieved for all patients.
Adherence was calculated according to the proportion of days covered (PDC) on the basis of the defined daily doses (DDDs) and was calculated separately for each drug. The choice to use this approach was based on preliminary research.19 (link) Patients were defined as adherent when 75% or more of their individual follow-up was covered by a daily dose of the medication (i.e., PDC ≥ 75%). Inpatient regimens were excluded from this calculation because drugs are dispensed by the facility during inpatient treatment and thus cannot be retrieved from the Pharm database.
The following treatments were considered in the analysis: no EB drug therapy (<75% PDC of any of the drugs) and therapy with one, two, three, or four EB drugs. Sensitivity analyses were performed using a 50% cutoff for PDC and 50% and 75% cutoffs for the pill-count approach.
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Publication 2013
Adrenergic beta-Antagonists Contraceptives, Oral Hospitalization Hydroxymethylglutaryl-CoA Reductase Inhibitors Hypersensitivity Inpatient Patient Care Planning Patients Pharmaceutical Preparations Pharmacotherapy Platelet Aggregation Inhibitors Prescriptions Secondary Prevention System, Renin-Angiotensin Therapeutics Treatment Protocols

Most recents protocols related to «System, Renin-Angiotensin»

Baseline characteristics were recorded by clinical research associates from medical files or by interview. Data included age, sex, body mass index (BMI), hypertension (patients having an office blood pressure greater than or equal to 140/90 mmHg or an antihypertensive treatment), cardiovascular history (coronary artery disease, arrhythmic disorders, congestive heart failure, stroke, peripheral vascular disease and/or valvulopathy), diabetes (diabetes history or antidiabetic treatment or glycated hemoglobin ≥ 6.5% or fasting glycemia ≥ 7 mmol/l or non-fasting glycemia ≥ 11), gout history, dyslipidemia, primary kidney disease, time since CKD diagnosis (time elapsed from the date of CKD diagnosis found in the medical record and the cohort entry), number of consultation in the previous year with nephrologist and dietician, treatment (urate-lowering therapy (ULT), diuretics, antiplatelet agents, renin-angiotensin system inhibitors (RASi)), laboratory data (serum creatinine, eGFR estimated by the CKD-EPI equation, serum UA, albuminemia, C-reactive protein and, albuminuria—or equivalent—classified according to the KDIGO 2012 guidelines16 ), salt intake (estimated by 24-h natriuresis) and protein intake (estimated by 24-h urinary urea)17 (link), medication adherence according to the Girerd score in categories (good, minimal and poor)18 (link), health literacy according to their need for help reading medical documents (never need vs always or partly need)19 (link) and type of center (university, non-university hospital, private non-profit and private for-profit clinic).
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Publication 2023
Antidiabetics Antihypertensive Agents Antiplatelet Agents Blood Pressure Cardiovascular System Cerebrovascular Accident Congestive Heart Failure Coronary Artery Disease C Reactive Protein Creatinine Diabetes Mellitus Diagnosis Dietitian Diuretics Dyslipidemias EGFR protein, human Gout Health Literacy Hemoglobin, Glycosylated High Blood Pressures Index, Body Mass inhibitors Kidney Diseases Natriuresis Nephrologists Patients Peripheral Vascular Diseases Proteins Serum Sodium Chloride, Dietary System, Renin-Angiotensin Therapeutics Urate Urea Urine Valve Disease, Heart
This was a single-center, retrospective cohort study. The subjects comprised 63 patients with advanced heart failure in our Heart Failure Center from Nov 2017 to Dec 2020. Inclusion criteria: Left ventricle ejection fraction (LVEF) of <40% (measured with Simpson of Doppler Echocardiography); the definition of advanced heart failure with reduced ejection fraction (HFrEF, LVEF<40%). Exclusion criteria: (1) Symptomatic hypotension or blood pressure (BP) <85/60 mmHg; (2) Severe arrhythmia; (3) Severe infection and respiratory diseases; (4) Allergy to levosimendan or unable to tolerate long-term intravenous pumping treatment. The Estimated glomerular filtration rate (eGFR) is calculated following formula: male, Ccr = (140-age)*weight (kg)*1.23/Scr (μmol/L) (Ccr, Creatinine Clearance Rate; Scr, Serum creatinine; female); Ccr = (140-age)*weight (kg)*1.03/Scr (μmol/L). AF atrial fibrillation group (n = 29) based on ECG heart rhythm data. Two groups of patients with advanced heart failure received conventional treatment recommended by the guidelines, including diuretics, renin-angiotensin system (RAS) blockers, angiotensin receptor-neprilysin inhibitor (ARNI), aldosterone receptor antagonists, β-receptor blockers, digoxin, etc. Levosimendan was administered in accordance with our center’s approved treatment protocol (7 (link)) (the total dose was 12.5 mg, 0.05 ~ 0.2 μg kg−1 min−1, intravenous 24–48 h, repeated infusion every 2–4 weeks for 3 months). Levosimendan infusion was started at a rate of 0.1 μg kg−1·min−1 during the first hour and increased to 0.2 μg·kg−1·min−1 after that if well tolerated in the case of low systolic blood pressure (SBP) (<90 mmHg). Without applying a beginning bolus, levosimendan was infused via a 24 h lasting infusion (0.1 ug/kg/min) while being monitored for hemodynamic effects in an intermittent care scenario. We measured the levels of B-type natriuretic peptide (BNP) before and 3 days after the infusion. The patients will repeat the blood test with a total observation time of 6 months to assess the blood pressure, resting heart rate, body weight, NYHA classification, Creatinine (Crea), eGFR, LVEF, left ventricular end diastolic diameter (LVEDD) and BNP. Then proceed to investigate the differences between the two groups (as shown in Figure 1).
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Publication 2023
Angiotensin Receptor Atrial Fibrillation Blood Pressure Body Weight Cardiac Arrhythmia Congestive Heart Failure Creatinine Diastole Digoxin Diuretics Echocardiography, Doppler Glomerular Filtration Rate Heart Hematologic Tests Hypersensitivity Infection Left Ventricles Levosimendan Long-Term Care Males Metabolic Clearance Rate Mineralocorticoid Receptor Antagonists Neprilysin Nesiritide Patients Rate, Heart Respiration Disorders Serum System, Renin-Angiotensin Systolic Pressure Treatment Protocols Ventricular Ejection Fraction Woman
For our first aim, the outcome was the occurrence of DGF, which was defined as the need for dialysis in the first post-transplant week, failure of serum creatinine to decrease by more than 10% within the first 3 post-operative days or serum creatinine above 250 µmol/L on post-operative day 5 with evidence of acute tubular necrosis on the allograft scintigraphy (1 (link),10 (link)). The exposure, or main independent variable of interest, was high pre-transplant anti-LG3 antibody levels. High anti-LG3 was defined as a value in the highest quartile of the distribution (17 (link)). Anti-LG3 was measured with a locally-developed enzyme-linked immunosorbent assay (17 (link)). As potential interactions between anti-LG3 levels and ischemia/endothelial injury were suggested by our prior animal studies (17 (link)), we defined, a priori, use of hypothermic perfusion machine as an effect modifier to be tested. In the province of Quebec, the only pump available in the field of transplantation is hypothermic perfusion with LifePort® devices, which do not provide oxygenation. There is no protocol in place guiding the use of perfusion devices and the decision to use them is hence left to the discretion of the transplant surgeon recovering and/or transplanting the kidney.
For the second aim, the outcome was kidney allograft survival, which was defined as the time elapsed between transplantation and graft failure, either return to dialysis or retransplantation. Death with a functioning graft was taken into account as a competing risk for kidney graft failure. The exposure was high pre-transplant anti-LG3 antibodies, as defined above. The effect modifier was DGF, as defined above. Covariates for all models were selected on the basis of their previously reported associations with DGF or kidney graft survival (20 (link)–22 (link)). These included both recipient and donor characteristics. Recipient variables included age, sex, race, cause of chronic kidney disease (diabetes, vascular/hypertension, autoimmune and other), time on dialysis before transplantation, height and weight, diabetes, history of cardiovascular disease, smoking status (active, past, never smoker), cytomegalovirus serostatus, pre-transplant and peak panel reactive antibodies, previous transplantations, transfusions, pregnancies, induction (basiliximab as the standard protocol, thymoglobulin with or without intravenous immunoglobulins which are reserved for highly sensitized patients), statin and renin-angiotensin system blockers use on admission. Donor variables included age, sex, height and weight, stroke as cause of death, cytomegalovirus serostatus, history of hypertension, diabetes, vascular disease, terminal creatinine, and number of HLA mismatches with the recipient. Recipient age was the only variable with an a priori association with the exposure, anti-LG3 (17 (link)).
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Publication 2023
Acute Kidney Tubular Necrosis Allografts Animals Anti-Antibodies Antibodies Antibodies, Anti-Idiotypic Basiliximab Blood Transfusion Cardiovascular Diseases Cell Respiration Cerebrovascular Accident Chronic Kidney Diseases Creatinine Cytomegalovirus Diabetes Mellitus Dialysis Donors Endothelium Enzyme-Linked Immunosorbent Assay Grafts Graft Survival High Blood Pressures Hydroxymethylglutaryl-CoA Reductase Inhibitors Injuries Intravenous Immunoglobulins Ischemia Kidney Kidney Failure Kidney Transplantation Medical Devices Patients Perfusion Pregnancy Radionuclide Imaging Serum Surgeons System, Renin-Angiotensin thymoglobulin Transplantation Vascular Diseases
We first divided the patients into non‐HFpEF and HFpEF groups and compared the patient characteristics among the 3 phenogroups within each of these groups. Parametric and nonparametric variables, as well as their respective differences, were assessed using a 1‐way ANOVA or the Kruskal‐Wallis test. Significant differences between the independent categorical variables were assessed using the χ2 test. The incidence of composite events or all‐cause death was estimated using the Kaplan‐Meier survival function and compared among the 3 phenogroups using the log‐rank test. We also compared the incidence of composite events in patients who received both β‐blockers and renin‐angiotensin system inhibitors at the time of discharge and those who did not, in each of the non‐HFpEF phenogroup, using the log‐rank test. The incidence of each mode of death was estimated, accounting for competing risks. For this, cardiovascular deaths and noncardiovascular deaths were considered competing events.
Cox‐proportional hazard analyses were used to evaluate the risk for all‐cause death among phenogroups. The covariates included in the multivariable model were LVEF, Get With The Guidelines‐Heart Failure risk score at discharge, and New York Heart Association functional class ≥III at discharge. Furthermore, when analyzing patients with non‐HFpEF, we added the prescription of β‐blockers or angiotensin coenzyme inhibitor/angiotensin II receptor blockers as covariates. In addition, we conducted a weighted Cox proportional hazard model using odds ratio based on the probability for membership in each of the 3 phenogroups as a sensitivity analysis. Statistical significance was set at P<0.05. All statistical analyses were performed using R software (version 4.1.3; R Foundation for Statistical Computing, Vienna, Austria).
Publication 2023
Angiotensin II Receptor Antagonist Angiotensins Cardiovascular System Coenzymes Congestive Heart Failure Heart Hypersensitivity inhibitors neuro-oncological ventral antigen 2, human Patient Discharge Patients System, Renin-Angiotensin
We searched databases including Medline, Embase, Cochrane Library and Web of Science for articles by the end of 30 September 2022. Publications in any language were considered. We used the following items as keywords: (‘angiotensin converting enzyme inhibitor’ OR ‘angiotensin receptor blocker’ OR ‘renin angiotensin system’) AND (‘chronic obstructive pulmonary disease’ OR ‘COPD’ OR ‘chronic obstructive lung disease’, ‘emphysema’). Please see the details in online supplemental material 1.
Publication 2023
Angiotensin-Converting Enzyme Inhibitors Angiotensin Receptor Antagonists cDNA Library Chronic Obstructive Airway Disease Emphysema System, Renin-Angiotensin

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More about "System, Renin-Angiotensin"

The Renin-Angiotensin System (RAS) is a complex hormonal network that plays a crucial role in regulating blood pressure, fluid balance, and electrolyte homeostasis.
This system involves the production and actions of the peptide hormones renin, angiotensin, and aldosterone.
Disturbances in the RAS have been implicated in various cardiovascular and renal disorders, such as hypertension, heart failure, and chronic kidney disease.
Researchers studying the RAS often utilize sophisticated analytical tools and software to optimize their research protocols and ensure enhanced reproducibility and accuracy.
PubCompare.ai's AI-driven platform, for example, helps researchers identify the best protocols from the literature, preprints, and patents, enabling seamless comparisons to find the most effective options.
Other tools and software commonly used in RAS research include SNPlex for genetic analysis, SPSS Statistics version 21 for statistical analysis, ABI Prism 7300 for real-time PCR, Vytorin for cholesteral management, JMP version 11 for data visualization, CRE-S for clinical trial management, Stata software for econometric analysis, and R version 4.0.2 for advanced statistical computing.
These tools and software can be invaluable in helping researchers streamline their workflows, analyze their data, and draw meaningful insights from their studies.
By leveraging the power of cutting-edge technologies and platforms like PubCompare.ai, researchers can optimize their RAS research protocols, enhance the reproducibility and accuracy of their findings, and ultimately improve their overall research outcomes.
This can lead to a better understanding of the complex mechanisms underlying the RAS and its role in various health conditions, paving the way for more effective therapeutic interventions and improved patient outcomes.