Related Experiment Video
Updated: Feb 1, 2026
07:27
Simplified Whole Body Plethysmography to Characterize Lung Function During Respiratory Melioidosis
Published on: February 24, 2023
3.8K
Hypoglycemia- simplifying the ways to predict an old problem in the general ward.
Yosefa Bar-Dayan1, Julio Wainstein1, Louis Schorr2
1Diabetes Unit, Wolfson Medical Center, Holon, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
European Journal of Internal Medicine
|December 4, 2018
Summary
Hypoglycemia in hospitalized patients with diabetes significantly increases mortality risk. Low hemoglobin, albumin, and high creatinine are key risk factors for developing hypoglycemia.
Area of Science:
- Endocrinology
- Internal Medicine
- Clinical Research
Background:
- Hypoglycemia is a common complication in hospitalized patients with diabetes.
- Understanding risk factors for hypoglycemia is crucial for preventing adverse outcomes.
Purpose of the Study:
- To investigate the association between hypoglycemic events and mortality rates in hospitalized diabetic patients.
- To identify risk factors for hypoglycemia during hospitalization to enable early intervention.
Main Methods:
- Retrospective cohort study of 3410 hospitalized patients with diabetes in 2012.
- Analysis of biochemical markers, hypoglycemia severity, length of stay, and mortality at 30 days and 1 year post-discharge.
Main Results:
- Hypoglycemia occurred in 18.5% of patients.
- Both mild/moderate and severe hypoglycemia were associated with significantly higher 30-day and 1-year mortality rates.
- Low hemoglobin, low albumin, and high creatinine levels were strongly associated with hypoglycemia development.
Conclusions:
- Hospitalized diabetic patients with low hemoglobin, low albumin, or high creatinine are at increased risk of hypoglycemia.
- Early identification of these high-risk factors can prevent severe hypoglycemia and life-threatening complications.
Related Concept Videos
01:15Hypoglycemia and Glucagon
983
Without prolonged fasting, healthy individuals maintain blood glucose levels above 3.5 mM due to a well-adapted neuroendocrine counterregulatory system that effectively prevents acute hypoglycemia, a potentially life-threatening condition. The primary clinical scenarios for hypoglycemia encompass diabetes treatment, inappropriate production of endogenous insulin or insulin-like substances by tumors, and the use of glucose-lowering agents in non-diabetic individuals. Notably, hypoglycemia in the...
983
02:27Predicting Molecular Geometry
45.8K
VSEPR Theory for Determination of Electron Pair Geometries
45.8K
01:03Prediction Intervals
3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
3.4K
01:30Simplified Synchronous Machine Model
778
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
In this model, each generator is connected to a...
778
01:07End Point Prediction: Gran Plot
1.2K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
1.2K
01:13Sensitivity, Specificity, and Predicted Value
1.3K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Sensitivity is the...
1.3K