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Systolic Pressure

Systolic Pressure: The pressure exerted on the walls of blood vessels during the contraction of the heart muscle.
It represents the maximum pressure in the arteries and is one of the fundamental vital signs used to assess cardiovascular health.
This pressure is an important indicator of cardiac function and can provide insights into the overall cardiovascular system.
Monitoring and optimizing systolic pressure is crucial for the management of various cardiovascular conditions, such as hypertension, heart disease, and stroke.
Researchers can leverage PubCompare.ai's AI-driven comparison and optimization tool to easily locate the best protocols from literature, pre-prints, and patents, while its intelligent algorithms identify the optimal approach to maximize the efectiveness of their systolic pressure research and improve their outcomes.

Most cited protocols related to «Systolic Pressure»

1
Secure and Accurate Data Collection with REDCap

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2008
Administrators Dietary Fiber Lanugo Secure resin cement Systolic Pressure TNFSF10 protein, human
2
Gait Speed and Survival in Older Adults
Gait speed was calculated for each participant using distance in meters and time in seconds. All studies used instructions to walk at usual pace and from a standing start. The walk distance varied from 8 ft to 6 m. For 8 ft, we converted to 4-m gait speed by formula.24 (link) For 6 m, we created a conversion formula (4-m speed=−0.0341 + (6-mspeed)×0.9816 withR2=0.93, based on a cohort of 61 individuals with concurrent 4- and 6-m walks). For 15 feet (4.57 m),23 (link) speed was simply meters divided by time. Where available, data on fast gait speed (walk as fast as comfortably able25 (link)) and the Short Physical Performance Battery were obtained.26 (link) Survival for each individual used study monitoring methods, including the National Death Index and individual study follow-up. Time from gait speed baseline to death was calculated in days. Five-year survival status was confirmed for more than 99% of participants.
Additional variables include sex, age, race/ethnicity (white, black, Hispanic, other, defined by participant), height(centimeters), weight(kilograms), body mass index (BMI), calculated as weight in kilograms divided by height in meters squared (<25, 25–30, and >30), smoking (never, past, current), use of mobility aids (none, cane, walker), systolic blood pressure, self-reports of health (excellent or very good vs good, fair, or poor), hospitalization in the past year (yes/no), and physician-diagnosed medical conditions (cancer, arthritis, diabetes, and heart disease, all yes/no). Measures of self-reported functional status were not collected in all studies and varied in content and form. We created a dichotomous variable reflecting dependence in basic activities of daily living (ADLs) based on report of being unable or needing help from another person to perform any basic activity, including eating, toileting, hygiene, transfer, bathing, and dressing. For individuals independent in ADLs, we created a dichotomous variable reflecting difficulty in instrumental ADLs based on report of difficulty or dependence with shopping, meal preparation, or heavy housework due to a health or physical problem. Participants were then classified into 1 of 3 groups; dependent in ADLs, difficulty with instrumental ADLs, or independent. Physical activity data were collected in 6 studies, but time frames and items varied widely. Two studies used the Physical Activity Scale for the Elderly (PASE).27 (link) We dichotomized the PASEs core at 100.28 (link) We created operational definitions of other covariates that were reasonably consistent across studies. Covariates were identical for height, weight, BMI, and systolic blood pressure. Hospitalization within the prior year was determined largely by self-report, and chronic conditions were by self-report of physician diagnosis, with heart disease encompassing angina, coronary artery disease, heart attack, and heart failure.
Studenski S., Perera S., Patel K., Rosano C., Faulkner K., Inzitari M., Brach J., Chandler J., Cawthon P., Connor E.B., Nevitt M., Visser M., Kritchevsky S., Badinelli S., Harris T., Newman A.B., Cauley J., Ferrucci L, & Guralnik J. (2011). Gait Speed and Survival in Older Adults. JAMA : the journal of the American Medical Association, 305(1), 50-58.
Publication 2011
Acquired Immunodeficiency Syndrome Aged Angina Pectoris Arthritis Canes Chronic Condition Congestive Heart Failure Coronary Artery Disease Diabetes Mellitus Diagnosis Ethnicity Foot Heart Diseases Hispanics Hospitalization Index, Body Mass Malignant Neoplasms Myocardial Infarction Neoplasm Metastasis Performance, Physical Physical Examination Physicians Range of Motion, Articular Reading Frames Systolic Pressure Walkers
3
Comparative Risk Assessment for GBD 2019
The GBD 2019 estimation of attributable burden followed the general framework established for comparative risk assessment (CRA)14 (link), 15 (link) used in GBD since 2002. Here, we provide a general overview and details on major innovations since GBD 2017. More detailed methods are available in appendix 1. CRA can be divided into six key steps: inclusion of risk–outcome pairs in the analysis; estimation of relative risk as a function of exposure; estimation of exposure levels and distributions; determination of the counterfactual level of exposure, the level of exposure with minimum risk called the theoretical minimum risk exposure level (TMREL); computation of population attributable fractions and attributable burden; and estimation of mediation of different risk factors through other risk factors such as high body-mass index (BMI) and ischaemic heart disease, mediated through elevated systolic blood pressure (SBP), elevated fasting plasma glucose (FPG), and elevated LDL cholesterol, to compute the burden attributable to various combinations of risk factors.10 (link)
Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. (2020). Lancet (London, England), 396(10258), 1223-1249.
Publication 2020
Coronary Arteriosclerosis Glucose Health Risk Assessment Hypercholesterolemia Index, Body Mass Innovativeness Plasma Systolic Pressure
4
Intensive Blood Pressure Reduction Outcomes
Definitions of study outcomes are outlined in the Supplementary Appendix. A committee whose members were unaware of the study-group assignments adjudicated the clinical outcomes specified in the protocol. The primary hypothesis was that treatment to reach a systolic blood-pressure target of less than 120 mm Hg, as compared with a target of less than 140 mm Hg, would result in a lower rate of the composite outcome of myocardial infarction, acute coronary syndrome not resulting in myocardial infarction, stroke, acute decompensated heart failure, or death from cardiovascular causes. Secondary outcomes included the individual components of the primary composite outcome, death from any cause, and the composite of the primary outcome or death from any cause.
We also assessed renal outcomes, using a different definition for patients with chronic kidney disease (eGFR <60 ml per minute per 1.73 m2) at baseline and those without it. The renal outcome in participants with chronic kidney disease at baseline was a composite of a decrease in the eGFR of 50% or more (confirmed by a subsequent laboratory test) or the development of ESRD requiring long-term dialysis or kidney transplantation. In participants without chronic kidney disease at baseline, the renal outcome was defined by a decrease in the eGFR of 30% or more to a value of less than 60 ml per minute per 1.73 m2. Incident albuminuria, defined for all study participants by a doubling of the ratio of urinary albumin (in milligrams) to creatinine (in grams) from less than 10 at baseline to greater than 10 during follow-up, was also a prespecified renal outcome.
Prespecified subgroups of interest for all outcomes were defined according to status with respect to cardiovascular disease at baseline (yes vs. no), status with respect to chronic kidney disease at baseline (yes vs. no), sex, race (black vs. non-black), age (<75 vs. ≥75 years), and baseline systolic blood pressure in three levels (≤132 mm Hg, >132 to <145 mm Hg, and ≥145 mm Hg). We also planned a comparison of the effects of systolic blood-pressure targets on incident dementia, changes in cognitive function, and cerebral small-vessel ischemic disease; these results are not presented here.
A Randomized Trial of Intensive versus Standard Blood-Pressure Control. (2015). The New England journal of medicine, 373(22), 2103-2116.
Publication 2015
Acute Coronary Syndrome Albumins Cardiovascular Diseases Cardiovascular System Cerebral Small Vessel Diseases Cerebrovascular Accident Chronic Kidney Diseases Cognition Congestive Heart Failure Creatinine Dementia Dialysis EGFR protein, human Kidney Kidney Failure, Chronic Kidney Transplantation Myocardial Infarction Patients Systolic Pressure Urine
5
Validation of Logistic Regression Sample Size
Validation was conducted to verify the accuracy between statistics and parameters. The validation was performed using real patient data from “An Audit of Diabetes Control and Management (ADCM) 2009”, which included all data collection (at a national-level) of patients with diabetes mellitus from all government health clinics in Malaysia in 2009. The methodology of this data collection process was explained in a previous paper and published elsewhere (13 ). We selected one government health clinic which had a relatively high number of patients with a total population of 1,595, and re-analysis was done by using different sub-samples (n = 30, 50, 100, 150, 200, 300, 500, 700 and 1,000).
We tested a multivariable model by using eight explanatory (or independent) variables and one outcome (or dependent variable). The dependent variable was glycemic control (HbA1c) in binary form (< 7.0 versus ≥ 7.0) while a set of independent variables included gender, age, body mass index, diabetes treatment, duration of diabetes mellitus, systolic blood pressure, status of co-morbidity and low-density lipoprotein level. Since data was not collected in a prospective manner, the model developed could only be used to test for an association between the independent variables and the outcome; rather than to identify and determine the risk factors or determinants for HbA1c (14 (link)–15 (link)).
The findings obtained from the validation were then analysed. The statistics such as r-squared and coefficients derived from the samples were compared with the respective true values (parameters) in the targeted population. The analysis was conducted using logistic regression where the sample sizes (n = 30, 50, 100, 150, 200, 300, 500, 700 and 1,000) were selected at random. From the results, guidelines of sample size estimation for logistic regression based on the concept of event per variable (EPV) and sample size formula (n = 100 + xi, where x is integer and i represents the number of independent variables in the final model) were introduced.
After the guidelines of the sample size were identified, these guidelines (based on EPV and sample size formula) were re-evaluated based on another extremely large population with total population of 70,899 records. This population was also from ADCM 2009 registry but included all notification records from participating health clinics in 2009. The approach in the analysis of the logistic regression model is similar to the approach of analysis as presented in Table 1. Existing rules of thumb for sample size using logistic regression are highly dependent on the number of independent variables. Therefore, the evaluation using very large population is necessary to determine whether these guidelines can still provide satisfactory results (results yield minimal bias between results derived from parameters and statistics, respectively).
For data management, single imputation technique was applied to replace the missing values where the missing in numerical values were replaced with mean and missing in categorical values were replaced with mode. The logistic regression was conducted without stepwise method (enter method). All the analyses were carried out using IBM SPSS version 21.0 (IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.).
Bujang M.A., Sa’at N., Sidik T.M, & Joo L.C. (2018). Sample Size Guidelines for Logistic Regression from Observational Studies with Large Population: Emphasis on the Accuracy Between Statistics and Parameters Based on Real Life Clinical Data. The Malaysian Journal of Medical Sciences : MJMS, 25(4), 122-130.
Publication 2018
Diabetes Mellitus Gender Glycemic Control Index, Body Mass Low-Density Lipoproteins Patients Systolic Pressure Target Population

Most recents protocols related to «Systolic Pressure»

1
Catheter-Based Renal Neuromodulation for Hypertension
Not available on PMC !

Example 2

Example 2 describes the outcome of catheter-based renal neuromodulation on human patients diagnosed with hypertension. Patients selected having a baseline systolic blood pressure of 160 mm Hg or more (≥150 mm Hg for patients with type 2 diabetes) and taking three or more antihypertensive drugs, were randomly allocated into two groups: 51 assessed in a control group (antihypertensive drugs only) and 49 assessed in a treated group (undergone renal neuromodulation and antihypertensive drugs).

Patients in both groups were assessed at 6 months. Office-based blood pressure measurements in the treated group were reduced by 32/12 mm Hg (SD 23/11, baseline of 178/96 mm Hg, p<0.0001), whereas they did not differ from baseline in the control group (change of I/O mm Hg, baseline of 178/97 mm Hg, p=0.77 systolic and p=0.83 diastolic). Between-group differences in blood pressure at 6 months were 33/11 mm Hg (p<0.0001). At 6 months, 41 (84%) of 49 patients who underwent renal neuromodulation had a reduction in systolic blood pressure of 10 mm Hg or more, compared with 18 (35%) of 51 control patients (p<0.0001).

US11865343B2. Methods for treating post-traumatic stress disorder in patients via renal neuromodulation (2024-01-09). Medtronic Ireland Manufacturing Unlimited Company [IE]. Inventors: Marcia Gallagher [IE], Douglas A. Hettrick [US].
Patent 2024
Antihypertensive Agents BLOOD Blood Pressure Catheters Determination, Blood Pressure Diabetes Mellitus, Non-Insulin-Dependent Diastole High Blood Pressures Homo sapiens Kidney Patients Post-Traumatic Stress Disorder Pressure Systole Systolic Pressure
2
Cardiometabolic Risk Factors in NHANES
The following covariates were considered in the study: age, sex, race/ethnicity, family poverty income ratio (PIR), education level, marital status, the complication of hypertension, and diabetes mellitus (DM), smoker, drinker, body mass index (BMI), waist circumference, systolic blood pressure (SBP), diastolic blood pressure (DBP), mean energy intake, hemoglobin (Hb), fast glucose (FBG), glycosylated hemoglobin (HbA1c), alanine transaminase (Alt), aspartate aminotransferase (Ast), albumin, total cholesterol (TC), triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C), uric acid (UA), blood urea nitrogen (BUN), serum creatinine (Scr), and estimated glomerular filtration rate (eGFR). Individuals who have smoked less than 100 cigarettes in their lifetime/smoked less than 100 cigarettes in their lifetime, do not smoke at all at present/smoked more than 100 cigarettes in their lifetime, and smoke some days or every day were defined as never smoke, former smokers, and now smokers, respectively. There are three categories of drinkers: current heavy alcohol consumption were defined as ≥3 drinks per day for females, ≥4 drinks per day for males, or binge drinking [≥4 drinks on same occasion for females, ≥5 drinks on same occasion for males] on 5 or more days per month; current moderate alcohol consumption were defined as ≥2 drinks per day for females, ≥3 drinks per day for males, or binge drinking ≥2 days per month. Those who did not meet the above criteria were classified as current mild alcohol user.21 (link) Hypertension was defined as an average systolic blood pressure more than 140 mmHg/diastolic blood pressure greater than 90 mmHg or self-reported use of antihypertensive medication. DM will be assessed by measures of blood glycohemoglobin, fasting plasma glucose, 2-hour glucose (Oral Glucose Tolerance Test), serum insulin in participants aged 12 years and over. Hb, FBG, HbA1c, Alt, Ast, albumin, TC, TG, HDL-C, UA, BUN, Scr, and eGFR were all determined in the laboratory. More information regarding the variables used is available at https://www.cdc.gov/nchs/nhanes/index.htm.
Xiao S., Wang Z., Zuo R., Zhou Y., Yang Y., Chen T, & Liu N. (2023). Association of Systemic Immune Inflammation Index with All-Cause, Cardiovascular Disease, and Cancer-Related Mortality in Patients with Cardiovascular Disease: A Cross-Sectional Study. Journal of Inflammation Research, 16, 941-961.
Publication 2023
Alanine Transaminase Albumins Alcohols Antihypertensive Agents BLOOD Cholesterol Creatinine Diabetes Mellitus Ethnicity Females Glomerular Filtration Rate Glucose Hemoglobin Hemoglobin, Glycosylated High Blood Pressures High Density Lipoprotein Cholesterol Index, Body Mass Insulin Males Oral Glucose Tolerance Test Plasma Pressure, Diastolic Serum Smoke Systolic Pressure Transaminase, Serum Glutamic-Oxaloacetic Triglycerides Urea Nitrogen, Blood Uric Acid Waist Circumference
3
Hypotensive Patients' Arterial Blood Gas

Patients with systolic blood pressure less than 90 mmHg or MAP less than 65 mmHg in the emergency department who require ABG as a part of routine care

Patients more than 18 years of age

Prasad H., Vempalli N., Agrawal N., Ajun U.N., Salam A., Subhra Datta S., Singhal A., Ranjan N., Shabeeba Sherin P.P, & Sundareshan G. (2023). Correlation and agreement between arterial and venous blood gas analysis in patients with hypotension—an emergency department-based cross-sectional study. International Journal of Emergency Medicine, 16, 18.
Publication 2023
Patients Systolic Pressure
4
Hypotension Patients Protocol
Patients with systolic blood pressure less than 90 mmHg or mean arterial blood pressure less than 65 mmHg.
Prasad H., Vempalli N., Agrawal N., Ajun U.N., Salam A., Subhra Datta S., Singhal A., Ranjan N., Shabeeba Sherin P.P, & Sundareshan G. (2023). Correlation and agreement between arterial and venous blood gas analysis in patients with hypotension—an emergency department-based cross-sectional study. International Journal of Emergency Medicine, 16, 18.
Publication 2023
Patients Systolic Pressure
5
Noninvasive Myocardial Work Assessment via Echocardiography
In the EchoPAC software, the MW parameters were obtained through the pressure-strain loop (PSL) area module constructed from the curves for noninvasively estimated LV pressures and LV strains. The peak LV systolic pressure was assumed to be equal to the brachial cuff systolic BP measured during the echocardiographic study. This noninvasive method was validated by various research teams [1 (link), 3 (link), 4 (link), 21 , 22 (link)]. The myocardial work was calculated as the integral of power between mitral valve closure and mitral valve opening. The timings for the valvular events were defined on Doppler spectrums before entering the automated function imaging (AFI). The global work index (GWI) was defined as the total MW within the PSL area, from mitral valve closure to mitral valve opening. Global constructive work (GCW) was defined as the MW performed for shortening during ventricular systole and lengthening during IVR. Global wasted work (GWW) was defined as the MW performed for lengthening during ventricular systole and shortening during IVR. Global work efficiency (GWE) was calculated as the percentage of myocardial constructive work in the total MW (GCW / [GCW + GWW] × 100).
Guo Y., Wang X., Yang C.G., Meng X.Y., Li Y., Xia C.X., Xu T., Weng S.X., Zhong Y., Zhang R.S, & Wang F. (2023). Noninvasive assessment of myocardial work during left ventricular isovolumic relaxation in patients with diastolic dysfunction. BMC Cardiovascular Disorders, 23, 129.
Publication 2023
Echocardiography Heart Ventricle Mitral Valve Myocardium Pressure Strains Systole Systolic Pressure

Top products related to «Systolic Pressure»

1
Sas version 9 by SAS Institute
Sourced in United States, Austria, Japan, Cameroon, Germany, United Kingdom, Canada, Belgium, Israel, Denmark, Australia, New Caledonia, France, Argentina, Sweden, Ireland, India
SAS version 9.4 is a statistical software package. It provides tools for data management, analysis, and reporting. The software is designed to help users extract insights from data and make informed decisions.
2
Bp 98a by Softron
Sourced in Japan, China
The BP-98A is a laboratory instrument designed for measuring blood pressure. It provides accurate readings of systolic and diastolic blood pressure values.
3
Powerlab by ADInstruments
Sourced in Australia, United States, United Kingdom, New Zealand, Germany, Japan, Spain, Italy, China
PowerLab is a data acquisition system designed for recording and analyzing physiological signals. It provides a platform for connecting various sensors and transducers to a computer, allowing researchers and clinicians to capture and analyze biological data.
4
Powerlab system by ADInstruments
Sourced in Australia, United States, United Kingdom, New Zealand, Germany, Japan, Canada
The PowerLab system is a versatile data acquisition hardware platform designed for laboratory research and teaching applications. It offers a range of input channels and signal conditioning options to accommodate a variety of experimental setups. The PowerLab system is capable of recording and analyzing various physiological signals, enabling researchers to capture and study relevant data for their studies.
5
Bp 2000 by Visitech
Sourced in United States, New Caledonia
The BP-2000 is a laboratory equipment designed for measuring blood pressure. It provides accurate and reliable readings to support various research and testing applications.
6
Sas 9 by SAS Institute
Sourced in United States, Austria, Japan, Belgium, United Kingdom, Cameroon, China, Denmark, Canada, Israel, New Caledonia, Germany, Poland, India, France, Ireland, Australia
SAS 9.4 is an integrated software suite for advanced analytics, data management, and business intelligence. It provides a comprehensive platform for data analysis, modeling, and reporting. SAS 9.4 offers a wide range of capabilities, including data manipulation, statistical analysis, predictive modeling, and visual data exploration.
7
Hem 907 by Omron
Sourced in Japan, United Kingdom, United States, Greece, Australia
The HEM-907 is a digital blood pressure monitor device designed for professional use in a medical or clinical setting. The device measures and displays systolic and diastolic blood pressure, as well as pulse rate. It is intended for use by healthcare professionals to assist in the diagnosis and management of hypertension.
8
Hem 907xl by Omron
Sourced in Japan, United States, United Kingdom
The HEM-907XL is an automated blood pressure monitor designed for professional use in clinical settings. It is capable of measuring systolic and diastolic blood pressure, as well as pulse rate. The device features a large, easy-to-read display and is powered by AC adapter.
9
Powerlab data acquisition system by ADInstruments
Sourced in Australia, United States, New Zealand, United Kingdom, Germany, Japan, Colombia
The PowerLab data acquisition system is a versatile and powerful tool for recording, analyzing, and presenting physiological and other experimental data. It provides high-quality data acquisition capabilities, supporting a wide range of signal types and sensors. The PowerLab system is designed to be easy to use and integrate seamlessly with various software applications for data processing and visualization.
10
Vivid 7 by GE Healthcare
Sourced in United States, Norway, United Kingdom, Japan, France, Canada, Germany, Belgium
The Vivid 7 is a high-performance ultrasound system designed for cardiovascular and general imaging applications. It features advanced imaging technologies and versatile capabilities to support comprehensive diagnostic assessments.

More about "Systolic Pressure"

Systolic blood pressure, SBP, arterial pressure, cardiac contraction, cardiovascular health, hypertension, heart disease, stroke, vital signs, BP-98A, PowerLab, PowerLab system, BP-2000, SAS 9.4, HEM-907, HEM-907XL, PowerLab data acquisition system, Vivid 7.
Systolic pressure is the maximum pressure exerted on the blood vessel walls during the contraction of the heart muscle.
It's a fundamental vital sign used to assess cardiovascular health and a crucial indicator of cardiac function.
Monitoring and optimizing systolic pressure is key for managing various cardiovascular conditions, such as hypertension, heart disease, and stroke.
Researchers can leverage PubCompare.ai's AI-driven comparison and optimization tool to easily locate the best protocols from literature, pre-prints, and patents, while its intelligent algorithms identify the optimal approach to maximize the efectiveness of their systolic pressure research and improve their outcomes.
This powerful tool can help streamline the research workflow and enhance the effectiveness of studies focusing on systolic pressure and related cardiovascular metrics.