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Related Concept Videos

Introduction to z Scores01:06

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A z score (or standardized value) is measured in units of the standard deviation. It tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
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A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
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z Scores and Area Under the Curve01:17

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z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
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The z score is one of the three measures of relative standing. It describes the location of a value in a dataset relative to the mean. z scores are obtained after the standardization of the values in a dataset. The z score for the mean is 0.
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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Septins are the recently discovered fourth major protein component of the cytoskeleton, along with microfilaments, microtubules, and intermediate filaments. These proteins can associate with other cytoskeletal filaments and carry out varied roles or can be free-floating in the cytoplasm.
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A Data-Driven Approach to Quantifying Immune States in Sepsis
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Multi-Marker Approach in Sepsis: A Clinical Role Beyond SOFA Score.

Gun Hyuk Lee1, Hanah Kim2, Hee-Won Moon2

  • 1Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.

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|January 28, 2026
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Summary
This summary is machine-generated.

A multi-marker approach using procalcitonin, presepsin, interferon-λ3, and bioactive adrenomedullin improved sepsis diagnosis and mortality prediction. This combination offers better prognostic performance than the SOFA score alone, especially in older adults.

Keywords:
SOFA scoreadrenomedullininterferonpresepsinprocalcitoninsepsis

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Area of Science:

  • Biomarkers and diagnostics
  • Sepsis research
  • Clinical utility assessment

Background:

  • Procalcitonin (PCT), presepsin (PSEP), interferon-λ3 (IFN-λ3), and bioactive adrenomedullin (bio-ADM) are emerging sepsis biomarkers.
  • Assessing their combined diagnostic and prognostic value is crucial for clinical application.

Purpose of the Study:

  • To evaluate the clinical utility of a multi-marker approach using PCT, PSEP, IFN-λ3, and bio-ADM in patients with suspected sepsis.
  • To compare the performance of this multi-marker strategy against the Sequential Organ Failure Assessment (SOFA) score for sepsis diagnosis and in-hospital mortality prediction.

Main Methods:

  • Conducted a study on 248 patients with suspected sepsis.
  • Measured PCT, PSEP, IFN-λ3, and bio-ADM levels.
  • Analyzed diagnostic and prognostic performance using receiver operating characteristic curves (AUC) and survival analyses.
  • Compared multi-marker approach with SOFA score.

Main Results:

  • All four biomarkers demonstrated significant diagnostic performance (AUC = 0.61-0.95).
  • The multi-marker approach significantly increased sepsis detection rates and outperformed the SOFA score in predicting in-hospital mortality (mortality rate 58.3% vs. 31.3%).
  • The multi-marker approach showed enhanced prognostic value in patients aged ≥75 years.

Conclusions:

  • Individual biomarkers hold clinical utility for suspected sepsis.
  • A multi-marker approach provides complementary value to the SOFA score.
  • This combined strategy offers superior prognostic performance, particularly in elderly patients (≥75 years).