Continuous Temperature Measurement by Thermal Imaging Camera

NCT ID: NCT06256978

Last Updated: 2024-02-13

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 224 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-03-31
• Study Completion Date: 2025-01-31

Brief Summary

This study explores the significance of body temperature monitoring in hospitalized patients, particularly in critical care environments. With body temperature exhibiting considerable variability, fever, defined at a central temperature of 38.3°C, serves as a pertinent indicator across diverse medical conditions. Temperature measurement methods in Intensive Care Units (ICUs) range from routine peripheral measurements to more invasive central temperature monitoring.

Critical patients with fever often receive antibiotic treatment, even without conclusive evidence of infection, as early intervention is linked to improved survival in septic patients. However, the complexity of individual variability, circadian rhythms, medication effects, and methodological limitations underscores the impracticality of defining fever with a singular temperature value. The thermal curve, representing the temporal evolution of temperature, emerges as a nuanced parameter in this context.

This study seeks to establish the correlation between axillary temperature measurements, a conventional method, and temperatures recorded by thermal imaging cameras. Widely employed during the Covid-19 pandemic, these cameras offer non-invasive and contactless measurement, mitigating pathogen transmission risks, particularly in patients colonized by multidrug-resistant microorganisms or those with compromised skin integrity. The study also endeavors to evaluate the diagnostic validity of thermal imaging cameras for fever and hypothermia.

The integration of thermal imaging cameras into a system capable of automated, real-time peripheral temperature acquisition suggests a potential paradigm shift in ICU temperature monitoring practices. Beyond immediate clinical applications, the amassed data from this system holds promise for training intelligent systems through machine learning algorithms. This strategic integration aims to predict critical events, such as the onset of fever, nosocomial infections, or shock, marking a forward-looking approach to patient management.

Detailed Description

This study delves into the nuanced domain of body temperature monitoring in the context of hospitalized patients, with a particular emphasis on critical care settings. The primary physiological variable under scrutiny is body temperature, a parameter that has been extensively examined in the clinical realm. It is underscored that the normal range for body temperature hovers around 36.7°C, but with a significant degree of variability spanning from 35.3 to 37.7°C, both among different individuals and within the same person throughout the day.

Fever, a crucial clinical manifestation, is operationally defined by a consensus reached by the American College of Critical Care Medicine and the Infectious Diseases Society of America, placing it at a central temperature of 38.3°C. This central temperature refers to the temperature of internal organs, and the thermal elevation associated with fever is not exclusive to infectious processes but extends to various other conditions, including autoimmune diseases, oncological conditions, bleeding, inflammatory reactions, surgical procedures, and drug-induced scenarios.

The multifaceted landscape of temperature measurement methods in Intensive Care Units (ICUs) is acknowledged, with peripheral temperature measurements using contact thermometers in the axilla being the most common approach. For patients with sustained fever or those undergoing therapeutic hypothermia, continuous monitoring of central temperature through various methods such as rectal, tympanic, vesical, or esophageal measurements is considered. However, the more invasive nature of central temperature monitoring, coupled with technical challenges, higher economic costs, and potential complications, limits its widespread utilization.

The critical nature of thermal monitoring in the care of patients is highlighted, especially considering that fever often prompts antibiotic treatment, even in the absence of confirmed infection, due to the observed improvement in survival rates among septic patients with early intervention. The complex landscape surrounding temperature measurement, characterized by individual variability, circadian changes, diverse measurement methods, medication influence, and methodological deficiencies, prompts a reconsideration of the feasibility of defining fever based on a single temperature value. To address this complexity, the study introduces the concept of the thermal curve, representing the temporal evolution of temperature throughout the day, which may exhibit sustained elevation or peaks and may or may not respond to interventions like antipyretics, antibiotics, or other temperature control methods.

An additional challenge in fever monitoring, particularly with sporadic measurements rather than continuous monitoring, is the potential oversight of febrile peaks or the failure to capture the maximum or minimum temperature values experienced by the patient. This limitation underscores the need for innovative approaches to temperature monitoring that can overcome these challenges.

As a pioneering step, the primary objective of the study is outlined: to establish the concordance between axillary temperature measurements (a widely used method) and temperatures recorded by a thermal imaging camera at the same moments. Thermal imaging cameras, which have gained prominence during the Covid-19 pandemic for fever screening in healthcare settings and other facilities, are proposed for use in hospitalized patients. The advantages of thermal imaging cameras are expounded upon, including non-invasive and contactless measurement, which reduces the risk of pathogen transmission, especially in patients colonized by multidrug-resistant microorganisms. Furthermore, these cameras facilitate temperature measurement in patients with compromised skin integrity. The automated and continuous acquisition of temperature data provided by thermal imaging cameras is positioned as a potential game-changer, offering valuable information for patient management without imposing an additional burden on healthcare professionals. In fact, it is suggested that such automated systems may even reduce the nursing and auxiliary workload, enhancing overall efficiency in patient care.

Despite the potential advantages, the study acknowledges the existing challenges and limitations associated with thermal imaging cameras. The lack of diagnostic test validity studies for most thermal imaging cameras and contradictory results in published studies have led to their limited adoption in hospital environments. However, recent systematic reviews emphasize the considerable potential of these cameras, pending further validation studies.

Within the ambit of secondary objectives, the study aims to assess the validity of thermal imaging cameras as a diagnostic test for fever and hypothermia. This evaluation is crucial for determining the reliability and accuracy of thermal imaging cameras in a clinical context.

The discussion further extrapolates the potential transformative impact of integrating thermal imaging cameras into a system capable of automated and real-time peripheral temperature acquisition. This integration is posited as a potential paradigm shift in standard temperature monitoring practices within ICUs. Beyond the immediate clinical applications, the study suggests that the wealth of data generated by such a system could be utilized to train intelligent systems through machine learning algorithms. The overarching goal is to develop predictive models for critical events such as the onset of fever, nosocomial infections, or shock.

In summary, this study presents a comprehensive exploration of the complexities associated with body temperature monitoring in hospitalized patients, with a specific focus on critical care scenarios. The integration of thermal imaging cameras, while posing challenges, holds substantial promise for enhancing the precision and efficiency of temperature monitoring, thereby potentially revolutionizing patient care practices in ICUs.

Conditions

Critically Ill

Study Design

• Observational Model Type: CASE_ONLY
• Study Time Perspective: PROSPECTIVE

Study Groups

Critical care patients

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Patients admitted to the ICU in a room with a thermal imaging camera
• Patients who provide voluntary consent to participate in the study (Annex 2). If the participant is not in full physical or intellectual capacity to provide their signature in the informed consent, the responsible investigator will seek consent from their direct family member or the legally designated person to make decisions on their behalf regarding health matters. This measure is adopted to ensure the participant's rights are respected and the integrity of the consent process is maintained, even in situations where their decision-making capacity may be compromised.

Exclusion Criteria

• Patients from whom information from the thermal imaging camera cannot be obtained due to technical reasons.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 110 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Fundación ASISA

UNKNOWN

Sponsor Role: collaborator

Universidad Europea de Madrid

OTHER

Sponsor Role: lead

Responsible Party

Samuel Gonzalez Lopez

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Central Contacts

Samuel Gonzalez, Doctor

Role: CONTACT

samuel.gonzalez@grupohla.com

+34 917581196

Provided Documents

Document Type: Study Protocol

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

23-63

Identifier Type: -

Identifier Source: org_study_id