Threshold for defining fever varies with age, especially in children: A multi‐site diagnostic accuracy study

Kasbekar, Rajesh S; Naz, Aftab; Marcos, Lorenzo S; Liu, Yingjie; Hendrickson, Kristine; Gorsich, James C; Baun, Matt

doi:10.1002/nop2.831

Cited by 3 publications

(1 citation statement)

References 37 publications

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“…Similar to previous studies, we found that there were significant differences in the optimal diagnostic threshold of fever between different body surface sites. 41 , 42 However, the optimal diagnostic thresholds of fever found in our study are different from previous studies. Wing P Chan et al found that when a tympanic temperature of 37.3°C or above was considered febrile, a corresponding cut-off value of 36.2°C when using an NCIT at the wrist was determined (0.864 sensitivity and 0.670 specificity).…”

Section: Discussioncontrasting

confidence: 99%

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

Lai¹,

X²,

Wang³

et al. 2022

RMHP

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Purpose Fever is one of the most typical clinical symptoms of coronavirus disease 2019 (COVID-19), and non-contact infrared thermometers (NCITs) are commonly used to screen for fever. However, there is a lack of authoritative data to define a “fever” when an NCIT is used and previous studies have shown that NCIT readings fluctuate widely depending on ambient temperatures and the body surface site screened. The aim of this study was to establish cut-off points for normal temperatures of different body sites (neck, forehead, temples, and wrist) and investigate the accuracy of NCITs at various ambient temperatures to improve the standardization and accuracy of fever screening. Patients and Methods A prospective investigation was conducted among 904 participants in the outpatient and emergency departments of Chengdu Women’s and Children’s Central Hospital. Body temperature was measured using NCITs and mercury axillary thermometers. A receiver operating characteristic curve was used to determine the accuracy of body temperature detection at the four body surface sites. Data on participant characteristics were also collected. Results Among the four surface sites, the neck temperature detection group had the highest accuracy. When the neck temperature was 37.35°C as the optimum fever diagnostic threshold, the sensitivity was 0.866. The optimum fever diagnostic thresholds for forehead, temporal, and wrist temperature were 36.65°C, 36.65°C, and 36.75°C, respectively. Moreover, triple neck temperature detection had the highest sensitivity, up to 0.998, whereas the sensitivity of triple wrist temperature detections was 0.949. Notably, the accuracy of NCITs significantly reduced when the temperature was lower than 18°C. Conclusion Neck temperature had the highest accuracy among the four NCIT temperature measurement sites, with an optimum fever diagnostic threshold of 37.35°C. Considering the findings reported in our study, we recommend triple neck temperature detection with NCITs as the fever screening standard for COVID-19.

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Section: Discussioncontrasting

confidence: 99%

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

Lai¹,

X²,

Wang³

et al. 2022

RMHP

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The Utilization of Acetaminophen for Managing PGE1-Induced Fever in Neonates with Critical Congenital Heart Disease

Kaya,

Akduman,

Dilli

et al. 2024

Children

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Introduction: We aimed to retrospectively evaluate the use of acetaminophen, which may be a risk factor for the ductal canal, in the treatment of fever due to prostaglandin E1 (PGE1) infusion in newborns with critical congenital heart disease (CCHD). Methods: The study included newborns who were followed-up in our neonatal intensive care unit with the diagnosis of critical congenital heart disease, developed fever due to PGE1 infusion and had acetaminophen administered for antipyretic treatment. The patent ductus arteriosus diameters of the patients were evaluated by echocardiographic imaging before intravenous acetaminophen treatment and at the end of the day of acetaminophen treatment. Results: PGE1 fever was observed in 10 (6%) of 156 infants with ductus-dependent congenital heart disease. Intravenous acetaminophen treatment administered as an antipyretic in these infants did not cause the narrowing or closure of the ductal canal diameter, which would lead to clinical decompensation if it was closed, and the patients remained hemodynamically stable until surgery. Conclusions: It can be considered that controlled and rapidly administered intravenous acetaminophen therapy in the management of fever in neonates with congenital heart disease who develop fever as a side effect of high-dose intravenous PGE1 infusion therapy (≥0.3 mcg/kg/min) may prevent hemodynamic decompensation in these critically ill infants, and as a secondary outcome, it can be speculated that avoiding rapid daily increases in PGE1 maintenance infusion doses may be necessary to limit the number of paracetamol administrations in these infants.

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Design of a hazard prediction system with intelligent multimodal fusion based on artificial intelligence & internet of things technology: taking a crib as an example

Yin,

Zhao,

Zhang

2024

PeerJ Computer Science

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Problem How to design an intelligent multimodal fusion hazard prediction system using AIoT (Artificial Intelligence & Internet of Things) technology to predict some potential dangers. This article will provide some ideas and methods. Introduction This article designs an intelligent multimodal fusion hazard prediction system based on AIoT technology. The system mainly consists of an IoT hardware device and an AI multimodal and multi-dimensional Hazard Prediction Algorithm. Method This article will take baby cribs as an example, using this system to empower traditional baby cribs and transform them into intelligent baby cribs. Results In this example, the system can detect the real-time status of the baby and predict upcoming dangers, including kicking the quilt, wetting the bed, fever, crying, climbing over the crib, and turning over. Hypothesis Assuming that intelligent systems can detect the status of infants in real-time and make predictions before potential dangers occur, to promptly alert parents. Perhaps it can prevent some irreversible dangers from occurring. Background This system solves the pain point problem of parents having to take care of their babies after working hard. Purpose In this scenario, the system provides a design scheme for an intelligent multimodal fusion hazard prediction system with a temporary care function. The application of this system to baby cribs not only reduces the burden on parents but also ensures the safety and comfort of the baby. Transferability At the same time, the system has transferability, and its design concept can be transferred to other application scenarios, such as hospital care for infants, young children, or elderly patients, as well as childcare stations for abandoned children in society. Significance This innovative system design scheme has a positive significance for family harmony and social development.

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Threshold for defining fever varies with age, especially in children: A multi‐site diagnostic accuracy study

Cited by 3 publications

References 37 publications

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19

The Utilization of Acetaminophen for Managing PGE1-Induced Fever in Neonates with Critical Congenital Heart Disease

Design of a hazard prediction system with intelligent multimodal fusion based on artificial intelligence & internet of things technology: taking a crib as an example

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