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Related Concept Videos

Assessment of Ventilation I: Respiratory Rate01:20

Assessment of Ventilation I: Respiratory Rate

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Assessment of Ventilation
A Ventilation assessment is critical for monitoring a patient's health status. Respiration, one of the most accessible vital signs, provides insights into the function of numerous body systems and can indicate serious health issues, such as brainstem injuries from head trauma.
Critical Guidelines for Assessing Ventilation:
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Assessment of Respiration01:23

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The respiratory system's basic structures and primary functions lay the foundation for nurses' comprehensive respiratory assessments. This assessment includes subjective and objective data to gauge the patient's respiratory health.
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Respiratory assessment is a cornerstone of nursing assessments, crucial for the early detection of patient deterioration. This evaluation transcends routine procedures, representing a critical skill nurses must master to ensure optimal patient care.
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Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

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Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
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MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
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Physical Assessment of the Respiratory Tract II: Inspection01:27

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Physical assessment of the respiratory tract through inspection is a crucial step in understanding the patient's respiratory health. It provides insights into the functioning of the respiratory system, the musculoskeletal structure, and even the patient's nutritional status. This comprehensive approach involves observing several vital aspects: chest configuration, breathing patterns, respiratory rates, skin color, and use of accessory muscles.
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Related Experiment Video

Updated: Oct 12, 2025

A Standardized Method for Measuring Internal Lung Surface Area via Mouse Pneumonectomy and Prosthesis Implantation
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Assessing the accuracy of the lung allocation score.

William F Parker1, Nicole E Dussault2, Renea Jablonski3

  • 1Department of Medicine, Section of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, Illinois; MacLean Center for Clinical Medical Ethics, University of Chicago, Chicago, Illinois.

The Journal of Heart and Lung Transplantation : the Official Publication of the International Society for Heart Transplantation
|November 22, 2021
PubMed
Summary

The US Lung Allocation Score (LAS) survival models are inaccurate, failing to correctly rank lung transplant candidates and recipients. Updating these models is crucial for fair organ allocation.

Keywords:
Survival analysislung transplantorgan allocationtransplant ethics

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Area of Science:

  • Transplantation Science
  • Medical Informatics
  • Biostatistics

Background:

  • The United States (US) Lung Allocation Score (LAS) utilizes two survival models to predict waitlist and post-transplant outcomes.
  • These models were developed using data from 2005-2008, raising questions about their current accuracy.

Purpose of the Study:

  • To evaluate the accuracy of the LAS waitlist and post-transplant survival models.
  • To assess if the current LAS accurately ranks lung transplant candidates and recipients.

Main Methods:

  • An observational cohort study of US lung transplantation candidates and recipients (age >12) from 2015-2019.
  • Evaluation of LAS models using concordance probability and comparison of predicted vs. observed survival times.
  • Comparison of nonparametric observed LAS with predicted LAS across recipient percentiles.

Main Results:

  • The waitlist model correctly ranked candidates 72% of the time and underestimated survival by 136 days in the highest risk decile.
  • The post-transplant model correctly ranked recipients 57% of the time and underestimated survival by 70 days in the highest risk decile.
  • The LAS explained only 56% of outcome variation and showed decreased accuracy for higher predicted values.

Conclusions:

  • The LAS waitlist and post-transplant models are inaccurate, impairing the accurate risk stratification of candidates.
  • Modernization and updating of the LAS survival models are recommended to improve the lung allocation system.