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Related Concept Videos

Standard Deviation01:10

Standard Deviation

27.6K
The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more variation.
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Mean Absolute Deviation01:13

Mean Absolute Deviation

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The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
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Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

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In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
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Standard Deviation of Calculated Results01:14

Standard Deviation of Calculated Results

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Standard deviation measures the spread of data around the mean value. Many large data sets follow a Gaussian distribution, also known as a normal distribution. This distribution is bell-shaped curved, with the most frequently observed value (mean or central value) in the middle. The farther away from the central value, the greater the deviation from the central value, and the lower the frequency.
A broad Gaussian distribution curve has a wider standard deviation, representing a data set with...
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Calculating Standard Deviation01:08

Calculating Standard Deviation

12.5K
The standard deviation is the most common measure of variation. It is a value that tells us how far a data value is from the mean value in a dataset. Further, the standard deviation is always a positive value or zero.
The standard deviation value is small when all the data is concentrated close to the mean. Here the data exhibits low variation. The standard deviation value is larger when the data values are more spread out from the mean. Here, the data displays high...
12.5K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

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To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
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A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis
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Feeding protocol deviation after esophagectomy: A retrospective multicenter study.

Gijs H K Berkelmans1, B Feike Kingma2, Laura F C Fransen1

  • 1Department of Surgery, Catharina Hospital, Michelangelolaan 2, Eindhoven, the Netherlands.

Clinical Nutrition (Edinburgh, Scotland)
|June 9, 2019
PubMed
Summary

More than half of esophagectomy patients deviate from feeding protocols, often due to complications like anastomotic leakage. This highlights challenges in optimizing postoperative recovery and oral intake timing after surgery.

Keywords:
ComplicationsEsophagectomyFeeding protocol deviation

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Area of Science:

  • Gastroenterology
  • Surgical Oncology
  • Critical Care Medicine

Background:

  • Esophagectomy carries high postoperative morbidity, impacting recovery and quality of life.
  • Enhanced Recovery After Surgery (ERAS) protocols improve recovery, but optimal oral intake timing remains uncertain.
  • Conservative feeding protocols include nil-by-mouth periods to reduce complications like anastomotic leakage and pneumonia.

Purpose of the Study:

  • To evaluate adherence to postoperative feeding protocols after minimally invasive esophagectomy.
  • To identify factors contributing to deviations from the established feeding protocol.

Main Methods:

  • Retrospective analysis of 186 consecutive patients undergoing esophagectomy with gastric tube reconstruction (2014-2016).
  • Patients received planned enteral tube feeding via jejunostomy post-surgery.
  • Data collected on feeding-related symptoms (nausea, vomiting, regurgitation) and protocol adherence.

Main Results:

  • Feeding protocol deviation occurred in 59% of patients (109/186).
  • Deviations were significantly higher in patients with anastomotic leakage, chyle leakage, and acute respiratory distress.
  • Feeding-related symptoms affected 58% of patients, more common in females and those with cervical anastomosis.

Conclusions:

  • Over half of esophagectomy patients deviated from their prescribed feeding protocol.
  • Postoperative complications were the primary driver for feeding protocol non-adherence.
  • Established feeding protocols, including oral fasting, are frequently overridden due to surgical complications.