Development of a Fever Detection Algorithm Based on Non-invasive Skin-based Sensor Values in Infants up to 18 Months of Age

greenTEG

Status

Suspended

Conditions

Fever

Treatments

Other: Unobtrusive data collection using wearable non-invasive sensors

Study type

Interventional

Funder types

Other

Industry

Identifiers

NCT04654559

6058_Baby_study_1

Details and patient eligibility

About

Fever of infants up to 18 months of age will be monitored in the hospital using the standard clinical methods and wearable research prototypes. These research prototypes will be measuring continuously and non-invasively skin based parameters, with which the feasibility of developing a fever detection algorithm will be investigated.

Full description

Background and Rationale:

In daily clinical practice, core body temperature (CBT) of infants with fever symptoms is monitored using sporadic rectal measurements. Because these sporadic invasive measurements are time consuming for the medical staff and displeasing for patients, an alternative method to assess CBT/fever is needed. The company greenTEG is developing a CBT algorithm which calculates CBT continuously form skin temperature (ST), corresponding heat flux (HF) and other skin-based parameters. The algorithm development will be achieved by collecting skin-based parameters and reference CBT values from infants having fever in a clinical setting.

Objective(s):

Develop and validate an algorithm that allows the detection of fever in infants through a non-invasive sensor system, which calculates CBT from ST, HF and other skin-based data streams, allowing a more effective patient management.

Statistical Considerations:

The measures of quality will be: 1) The mean absolute difference (MAD) between the CBT prediction and the reference signal where the mean is taken over the whole measurement of a single patient. An aggregate performance measure over a group of patients is defined by averaging the MAD values of each patient in the group. 2) the 2σ (standard deviation) range of the Bland-Altmann-Plot between the CBT prediction and the reference signal. This is calculated either for individual patient data or for the combined data of all patients together. As we have defined a group of patients for algorithm validation, the total improvement will be defined by comparing the above aggregate performance measures of old and new algorithm for the validation group. We expect the factors age, sex to influence the algorithmic prediction. Balancing the probability of occurrence of the factors in the population and the overall size of the study, a final size of 50 patients is reasonable.

Study procedures:

Infants will be recruited and screened 1 days before the measurements starts. Two research prototypes will be applied to the patient on the left side of the body (lateral ribcage and foot), after being admitted to the hospital and parents having signed the informed consent. For all infants rectal measurement will be asses every 8 hours, as reference temperature. For infants older than 6 months, in addition to rectal temperature, ear temperature will be assessed every 4 hours with an infrared ear thermometer. The whole measurement procedure will last 18-72 hours, depending on the stationary stay of the individual patient.

Enrollment

50 estimated patients

Sex

All

Ages

2 weeks to 18 months old

Volunteers

No Healthy Volunteers

Inclusion criteria

Infants from two weeks after birth and due date up to 18 months of age
Infants which are staying at the Nursery and the University Children's Hospital Zurich or Children's Hospital of Eastern Switzerland, St. Gallen for more than 1 day
Informed consent signed by parents or by legal representatives

Exclusion criteria

Acute medical contradiction against medical plaster and adhesives (e.g. skin diseases or allergies).
Irritated or damaged skin (e.g. burn, rush, eczema)
Infant with congenital anomalies (e.g. malformations of the anus)
Disease or brain injury which cause a disturbance of the thermoregulation
Comatose infant's
Infants with implants (e.g. pacemaker, cochlear implants)