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Related Concept Videos

Review and Preview01:10

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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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While deriving the Doppler formula for the observed frequency of a sound wave, it is assumed that the speed of sound in the medium is greater than the source's speed through it. When this condition is breached, a shock wave occurs.
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Related Experiment Video

Updated: Feb 12, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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Cardiogenic Shock Detection Using Electronic Medical Records: A Review and Blueprint for Clinical Implementation and

Saraschandra Vallabhajosyula1,2, Chirag Mehta3, Atin Jindal4

  • 1Division of Cardiology, Department of Medicine Warren Alpert Medical School of Brown University Providence RI USA.

Journal of the American Heart Association
|February 11, 2026
PubMed
Summary

Early detection of cardiogenic shock (CS) using electronic health records can improve patient outcomes. This review proposes a blueprint for real-time CS detection and alerts to guide treatment decisions.

Keywords:
cardiogenic shockclinical informaticscritical care cardiologyelectronic medical recordsprotocols

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Area of Science:

  • Cardiology
  • Critical Care Medicine
  • Health Informatics

Background:

  • Cardiogenic shock (CS) has a high in-hospital mortality rate of nearly 50%, despite advances in medical technology.
  • Both the initial severity and clinical trajectory of CS significantly impact patient outcomes.
  • Delayed recognition and inappropriate treatment escalation/de-escalation worsen CS outcomes.

Purpose of the Study:

  • To propose a blueprint for electronic health record (EHR)-based detection of cardiogenic shock (CS).
  • To focus on EHR tools for early CS prediction and real-time alerts for treatment adjustments.
  • To improve reproducibility, convenience, clinical decision support, and research capabilities in CS management.

Main Methods:

  • Review of existing literature on CS detection and EHR-based tools.
  • Analysis of successful EHR implementations for other critical conditions like septic shock and acute kidney injury.
  • Development of a conceptual framework for EHR-based CS detection.

Main Results:

  • Current EHR studies in CS primarily focus on outcome prediction, with limited tools for early detection or real-time alerts.
  • Early detection of CS, potentially through EHRs, may allow intervention at earlier stages, preventing deterioration.
  • A proposed EHR-based detection system can aid in timely escalation or de-escalation of care.

Conclusions:

  • Electronic health record-based detection offers a promising avenue for improving cardiogenic shock recognition and management.
  • Implementing EHR tools for real-time CS alerts can enhance clinical decision-making and potentially reduce mortality.
  • Further research and development are needed to create robust, reproducible EHR systems for CS detection and clinical support.