Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies01:27

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies

Assessing and diagnosing Chronic Obstructive Pulmonary Disease (COPD) involves a detailed approach that includes a comprehensive review of medical history, physical examination, and a variety of diagnostic tests. This thorough evaluation is essential to ensure an accurate diagnosis and guide effective management strategies.
Medical History
Physical Assessment of the Respiratory Tract II: Inspection01:27

Physical Assessment of the Respiratory Tract II: Inspection

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.
Chest Configuration
The chest configuration can...
Assessment of Respiration01:23

Assessment of Respiration

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.
Subjective Assessment: Nurses interview the patient to gather information directly during the subjective assessment. It includes questions about the individual's medical history, medications, and symptoms, focusing on past respiratory conditions like asthma or COPD,...
Assessment of Airway, Skin Color, and Use of Accessory Muscles01:30

Assessment of Airway, Skin Color, and Use of Accessory Muscles

A thorough assessment of respiratory health is paramount in clinical settings to identify and manage respiratory distress and ensure adequate oxygenation. This article elaborates on the critical aspects of respiratory evaluation, including airway assessment, skin color examination, and the observation of accessory muscle use, which are integral to effectively diagnosing and managing patients with respiratory conditions.
Introduction
The initial evaluation of a patient's respiratory system...
Respiratory Assessment: Purpose and Indications01:19

Respiratory Assessment: Purpose and Indications

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.
Objectives and Importance:
The primary goal of respiratory assessment is to evaluate patients at early risk of clinical deterioration. Since respiratory distress often precedes other signs of declining health, breathing patterns and sounds become a...
Physical Assessment of the Respiratory Tract I: Health History01:28

Physical Assessment of the Respiratory Tract I: Health History

Physical assessment of the respiratory tract is critical to patient care. It allows healthcare professionals to identify and manage various respiratory conditions. The process involves a combination of subjective and objective data collection.
Subjective Data
Subjective data provides vital information about the patient's health history and symptoms. This data is typically collected through interviews in which patients describe their experiences, symptoms, and concerns.
Health history and key...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Diversity of Factors Associated with Physical Inactivity in Patients with Asthma Based on Activity Intensity.

Journal of clinical medicine·2026
Same author

Secondary Pulmonary Alveolar Proteinosis Associated With Ruxolitinib After Bone-Marrow Transplantation: A Case With Transient Improvement Following Drug Discontinuation.

Respirology case reports·2026
Same author

Optimizing preoperative planning for total hip arthroplasty using random forest models to predict stem size and compatibility.

BMC musculoskeletal disorders·2026
Same author

Heterogeneous pathways to depressive and anxiety disorders: A cluster-based predictive study in a nationwide longitudinal cohort.

Psychological medicine·2026
Same author

Unsupervised comprehensive CT imaging clusters reveal distinct morphological phenotypes in asthma: insights from two prospective cohorts.

Respiratory research·2026
Same author

Pneumonia Risk in Institutionalized Older Adults With Severe Functional Dependency: An Exploratory Analysis Using Standardized Long-Term Care Assessment Data.

Geriatrics & gerontology international·2026

Related Experiment Video

Updated: Jul 16, 2026

Frailty Assessment in an Aging Mouse Model
06:58

Frailty Assessment in an Aging Mouse Model

Published on: September 23, 2025

Novel Frailty Assessment Based on Multidimensional Physical Frailty Parameters Using Unsupervised Clustering in

Keiko Doi1,2, Yoshiyuki Asai3,4,5, Tsunahiko Hirano1

  • 1Department of Respiratory Medicine and Infectious Disease, Graduate School of Medicine, Yamaguchi University, 1-1-1 Minami-Kogushi, Ube 755-8505, Japan.

Journal of Clinical Medicine
|July 15, 2026
PubMed
Summary

This pilot study developed a novel frailty assessment model using unsupervised clustering of physical function tests. The model identified four frailty clusters, offering a more granular approach to managing respiratory disease prognosis.

Keywords:
frailtymachine learningrespiratory disease

More Related Videos

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
05:53

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty

Published on: July 24, 2013

Identifying Frailty Using Point-of-Care Ultrasonography: Image Acquisition and Assessment
04:00

Identifying Frailty Using Point-of-Care Ultrasonography: Image Acquisition and Assessment

Published on: July 26, 2024

Related Experiment Videos

Last Updated: Jul 16, 2026

Frailty Assessment in an Aging Mouse Model
06:58

Frailty Assessment in an Aging Mouse Model

Published on: September 23, 2025

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
05:53

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty

Published on: July 24, 2013

Identifying Frailty Using Point-of-Care Ultrasonography: Image Acquisition and Assessment
04:00

Identifying Frailty Using Point-of-Care Ultrasonography: Image Acquisition and Assessment

Published on: July 26, 2024

Area of Science:

  • Gerontology
  • Pulmonology
  • Biostatistics

Background:

  • Frailty significantly impacts respiratory disease prognosis but lacks standardized evaluation criteria.
  • Current frailty assessment methods may not capture the full spectrum of physical decline.

Purpose of the Study:

  • To develop a novel frailty assessment method using unsupervised clustering of physical function tests.
  • To explore a more granular approach to frailty assessment in patients with respiratory diseases.

Main Methods:

  • Unsupervised hierarchical clustering and Principal Component Analysis were applied to clinical data, including strength tests (handgrip, lower limb), walk tests (6 min, 5 m), body composition (SMI, WBPhA), and pulmonary function.
  • Frailty status was initially categorized using established tools (J-CHS, Kihon Checklist).

Main Results:

  • Ninety-eight participants were divided into four clusters, representing a spectrum from robust to pronounced frailty.
  • Principal Component Analysis revealed two key dimensions: exercise tolerance (FEV1, walk tests) and physical elements (strength, body composition).
  • Follow-up data suggested reproducible cluster shifts, though interpretation requires caution due to sample size.

Conclusions:

  • This pilot study presents a novel, data-driven frailty model for respiratory disease patients.
  • The model offers a more granular assessment than traditional methods, potentially aiding management decisions.
  • External validation in larger cohorts is necessary before widespread clinical application.