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1.
BMJ Open ; 12(4): e057073, 2022 04 26.
Article in English | MEDLINE | ID: covidwho-1854347

ABSTRACT

INTRODUCTION: Neonatal hypoxic-ischaemic encephalopathy (HIE) is an important illness associated with death or cerebral palsy. This study aims to assess the safety and tolerability of the allogenic human multilineage-differentiating stress-enduring cell (Muse cell)-based product (CL2020) cells in newborns with HIE. This is the first clinical trial of CL2020 cells in neonates. METHODS AND ANALYSIS: This is a single-centre, open-label, dose-escalation study enrolling up to 12 patients. Neonates with HIE who receive a course of therapeutic hypothermia therapy, which cools to a body temperature of 33°C-34°C for 72 hours, will be included in this study. A single intravenous injection of CL2020 cells will be administered between 5 and 14 days of age. Subjects in the low-dose and high-dose cohorts will receive 1.5 and 15 million cells per dose, respectively. The primary outcome is the occurrence of any adverse events within 12 weeks after administration. The main secondary outcome is the Bayley Scales of Infant and Toddler Development Third Edition score and the developmental quotient per the Kyoto Scale of Psychological Development 2001 at 78 weeks. ETHICS AND DISSEMINATION: This study will be conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. The Nagoya University Hospital Institutional Review Board (No. 312005) approved this study on 13 November 2019. The results of this study will be published in peer-reviewed journal and reported in international conferences. TRIAL REGISTRATION NUMBERS: NCT04261335, jRCT2043190112.


Subject(s)
Hypothermia, Induced , Hypoxia-Ischemia, Brain , Body Temperature , Humans , Hypothermia, Induced/methods , Hypoxia-Ischemia, Brain/therapy , Infant , Infant, Newborn , Protective Devices , Research
2.
Zhongguo Yi Liao Qi Xie Za Zhi ; 46(2): 160-163, 2022 Mar 30.
Article in Chinese | MEDLINE | ID: covidwho-1786151

ABSTRACT

Body temperature is an essential physiological parameter. Conducting non-contact, fast and accurate measurement of temperature is increasing important under the background of COVID-19. The study introduces an infrared temperature measurement system based on the thermopile infrared temperature sensor ZTP-135SR. Extracting original temperature date of sensor, post-amplification and filter processing have been performed to ensure accuracy of the system. In addition, the temperature data of environmental compensation which obtained by polynomial fitting is added to the system to further improve measurement accuracy.


Subject(s)
Body Temperature , COVID-19 , Algorithms , Humans , Temperature , Thermometers
3.
Crit Care Med ; 50(2): 212-223, 2022 02 01.
Article in English | MEDLINE | ID: covidwho-1735675

ABSTRACT

OBJECTIVES: Body temperature trajectories of infected patients are associated with specific immune profiles and survival. We determined the association between temperature trajectories and distinct manifestations of coronavirus disease 2019. DESIGN: Retrospective observational study. SETTING: Four hospitals within an academic healthcare system from March 2020 to February 2021. PATIENTS: All adult patients hospitalized with coronavirus disease 2019. INTERVENTIONS: Using a validated group-based trajectory model, we classified patients into four previously defined temperature trajectory subphenotypes using oral temperature measurements from the first 72 hours of hospitalization. Clinical characteristics, biomarkers, and outcomes were compared between subphenotypes. MEASUREMENTS AND MAIN RESULTS: The 5,903 hospitalized coronavirus disease 2019 patients were classified into four subphenotypes: hyperthermic slow resolvers (n = 1,452, 25%), hyperthermic fast resolvers (1,469, 25%), normothermics (2,126, 36%), and hypothermics (856, 15%). Hypothermics had abnormal coagulation markers, with the highest d-dimer and fibrin monomers (p < 0.001) and the highest prevalence of cerebrovascular accidents (10%, p = 0.001). The prevalence of venous thromboembolism was significantly different between subphenotypes (p = 0.005), with the highest rate in hypothermics (8.5%) and lowest in hyperthermic slow resolvers (5.1%). Hyperthermic slow resolvers had abnormal inflammatory markers, with the highest C-reactive protein, ferritin, and interleukin-6 (p < 0.001). Hyperthermic slow resolvers had increased odds of mechanical ventilation, vasopressors, and 30-day inpatient mortality (odds ratio, 1.58; 95% CI, 1.13-2.19) compared with hyperthermic fast resolvers. Over the course of the pandemic, we observed a drastic decrease in the prevalence of hyperthermic slow resolvers, from representing 53% of admissions in March 2020 to less than 15% by 2021. We found that dexamethasone use was associated with significant reduction in probability of hyperthermic slow resolvers membership (27% reduction; 95% CI, 23-31%; p < 0.001). CONCLUSIONS: Hypothermics had abnormal coagulation markers, suggesting a hypercoagulable subphenotype. Hyperthermic slow resolvers had elevated inflammatory markers and the highest odds of mortality, suggesting a hyperinflammatory subphenotype. Future work should investigate whether temperature subphenotypes benefit from targeted antithrombotic and anti-inflammatory strategies.


Subject(s)
Body Temperature , COVID-19/pathology , Hyperthermia/pathology , Hypothermia/pathology , Phenotype , Academic Medical Centers , Aged , Anti-Inflammatory Agents/therapeutic use , Biomarkers/blood , Blood Coagulation , Cohort Studies , Dexamethasone/therapeutic use , Female , Humans , Inflammation , Male , Middle Aged , Organ Dysfunction Scores , Retrospective Studies , SARS-CoV-2
4.
Turk J Med Sci ; 51(SI-1): 3215-3220, 2021 12 17.
Article in English | MEDLINE | ID: covidwho-1726143

ABSTRACT

Background/aim: Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has been appeared first in China since December 2019. Transmission of SARS-CoV-2 occurs primarily with droplets through coughing and sneezing and also occurs through inhalation of aerosolized secretions, which travel, remain suspended in the air longer. Materials and methods: Since early stages of the outbreak, COVID-19 cases have been described in healthcare workers (HCWs). However, in the early stages, the disease may be asymptomatic. This may lead to incorrect diagnosis or delayed diagnosis and may lead to the nosocomial spread of the virus. One of the most important causes of transmission among HCWs is being exposed to an aerosolized virus in a closed environment for a long time. It is possible to prevent and control the spread of COVID-19 in hospitals with outpatient treatment and triage. Results: Infection control measures, including wearing surgical masks, hand hygiene, and social distance are considered essential in preventing human-to-human transmissions of SARS-CoV-2. Immediate response and practices of infection control measures are critical for saving lives during an epidemic inside and outside the hospital. Conclusion: Analyzing current knowledge about the features of SARS-CoV-2 infection, screening, personal protection protocols, triage and psychological support practices for healthcare professionals can be promising in terms of controlling the infection.


Subject(s)
COVID-19/prevention & control , Hand Hygiene , Infection Control/organization & administration , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Pandemics/prevention & control , Adult , Asymptomatic Infections/epidemiology , Body Temperature , COVID-19/epidemiology , Hand Hygiene/methods , Health Personnel , Hospitals , Humans , Infection Control/methods , Infection Control/standards , Masks , Physical Distancing , SARS-CoV-2
5.
Sci Rep ; 12(1): 3463, 2022 03 02.
Article in English | MEDLINE | ID: covidwho-1721583

ABSTRACT

Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.


Subject(s)
Body Temperature , COVID-19/diagnosis , Wearable Electronic Devices , Adolescent , Adult , Aged , Aged, 80 and over , Algorithms , COVID-19/virology , Female , Humans , Male , Middle Aged , SARS-CoV-2/isolation & purification , Young Adult
6.
Biosensors (Basel) ; 12(2)2022 Jan 27.
Article in English | MEDLINE | ID: covidwho-1700284

ABSTRACT

Pathogen detection by nucleic acid amplification proved its significance during the current coronavirus disease 2019 (COVID-19) pandemic. The emergence of recombinase polymerase amplification (RPA) has enabled nucleic acid amplification in limited-resource conditions owing to the low operating temperatures around the human body. In this study, we fabricated a wearable RPA microdevice using poly(dimethylsiloxane) (PDMS), which can form soft-but tight-contact with human skin without external support during the body-heat-based reaction process. In particular, the curing agent ratio of PDMS was tuned to improve the flexibility and adhesion of the device for better contact with human skin, as well as to temporally bond the microdevice without requiring further surface modification steps. For PDMS characterization, water contact angle measurements and tests for flexibility, stretchability, bond strength, comfortability, and bendability were conducted to confirm the surface properties of the different mixing ratios of PDMS. By using human body heat, the wearable RPA microdevices were successfully applied to amplify 210 bp from Escherichia coli O157:H7 (E. coli O157:H7) and 203 bp from the DNA plasmid SARS-CoV-2 within 23 min. The limit of detection (LOD) was approximately 500 pg/reaction for genomic DNA template (E. coli O157:H7), and 600 fg/reaction for plasmid DNA template (SARS-CoV-2), based on gel electrophoresis. The wearable RPA microdevice could have a high impact on DNA amplification in instrument-free and resource-limited settings.


Subject(s)
Body Temperature , Nucleic Acid Amplification Techniques/instrumentation , Nucleic Acids , Wearable Electronic Devices , COVID-19/diagnosis , DNA , Escherichia coli O157 , Humans , Nucleic Acid Amplification Techniques/methods , Nucleic Acids/isolation & purification , Recombinases/chemistry , Recombinases/genetics , SARS-CoV-2/genetics , Sensitivity and Specificity
7.
Med Eng Phys ; 102: 103777, 2022 04.
Article in English | MEDLINE | ID: covidwho-1693116

ABSTRACT

Non-contact infrared sensors are widely used as a diagnostic tool for elevated body temperature during initial screening for coronaviruses. The aim of this study was to investigate the thermal differences at three anatomical points: temple, forehead, and wrist, in the initial screening for temperature indicative of febrile and non-febrile states in skin pigmentation variations in Black, Half-Black and Caucasian skins, correlated with height and weight variables. Temperatures were obtained by means of an infrared thermometer in 289 volunteers with mean age of 18.30 ± 0.76, in a controlled environment according to Singapore Standard, SS582 part 1 and 2, normative standard IEC 80601-2-59, with standard technical protocols established by the International Organization for Standardization, ISO / TR 13154. The data were processed in MATLAB® R2021a, and data normality verified by Kolmogorov-Smirnov test, non-parametric data paired between temple / forehead / wrist were compared using the Wilcoxon signed-rank test. The results show different median temperatures in these anatomical regions, 37.2°C at the temple, 36.8°C at the forehead and 36.4°C at the wrist. As the temple region presents a temperature higher than the other investigated regions and, therefore, close to the core temperature, it should be considered for the initial screening of SARS-CoV-2 when using non-contact infrared thermometers. Furthermore, no significant changes were found due to variation in skin tone, height, or weight.


Subject(s)
COVID-19 , Forehead , Adolescent , Adult , Body Temperature , COVID-19/diagnosis , Humans , SARS-CoV-2 , Technology , Temperature , Wrist , Young Adult
8.
Sensors (Basel) ; 22(3)2022 Jan 22.
Article in English | MEDLINE | ID: covidwho-1686937

ABSTRACT

There is a need to rapidly screen individuals for heat strain and fever using skin temperature (Tsk) as an index of deep body temperature (Tb). This study's aim was to assess whether Tsk could serve as an accurate and valid index of Tb during a simulated heatwave. Seven participants maintained a continuous schedule over 9-days, in 3-day parts; pre-/post-HW (25.4 °C), simulated-HW (35.4 °C). Contact thermistors measured Tsk (Tforehead, Tfinger); radio pills measured gastrointestinal temperature (Tgi). Proximal-distal temperature gradients (ΔTforehead-finger) were also measured. Measurements were grouped into ambient conditions: 22, 25, and 35 °C. Tgi and Tforehead only displayed a significant relationship in 22 °C (r: 0.591; p < 0.001) and 25 °C (r: 0.408; p < 0.001) conditions. A linear regression of all conditions identified Tforehead and ΔTforehead-finger as significant predictors of Tgi (r2: 0.588; F: 125.771; p < 0.001), producing a root mean square error of 0.26 °C. Additional residual analysis identified Tforehead to be responsible for a plateau in Tgi prediction above 37 °C. Contact Tforehead was shown to be a statistically suitable indicator of Tgi in non-HW conditions; however, an error of ~1 °C makes this physiologically redundant. The measurement of multiple sites may improve Tb prediction, though it is still physiologically unsuitable, especially at higher ambient temperatures.


Subject(s)
Body Temperature , Skin Temperature , Fever , Forehead , Hot Temperature , Humans , Temperature
9.
Sensors (Basel) ; 22(2)2022 Jan 14.
Article in English | MEDLINE | ID: covidwho-1625927

ABSTRACT

In this study, a contactless vital signs monitoring system was proposed, which can measure body temperature (BT), heart rate (HR) and respiration rate (RR) for people with and without face masks using a thermal and an RGB camera. The convolution neural network (CNN) based face detector was applied and three regions of interest (ROIs) were located based on facial landmarks for vital sign estimation. Ten healthy subjects from a variety of ethnic backgrounds with skin colors from pale white to darker brown participated in several different experiments. The absolute error (AE) between the estimated HR using the proposed method and the reference HR from all experiments is 2.70±2.28 beats/min (mean ± std), and the AE between the estimated RR and the reference RR from all experiments is 1.47±1.33 breaths/min (mean ± std) at a distance of 0.6-1.2 m.


Subject(s)
COVID-19 , Algorithms , Body Temperature , Heart Rate , Humans , Monitoring, Physiologic , Respiratory Rate , SARS-CoV-2 , Vital Signs
11.
Sensors (Basel) ; 22(1)2021 Dec 29.
Article in English | MEDLINE | ID: covidwho-1615852

ABSTRACT

Infrared thermographs (IRTs) implemented according to standardized best practices have shown strong potential for detecting elevated body temperatures (EBT), which may be useful in clinical settings and during infectious disease epidemics. However, optimal IRT calibration methods have not been established and the clinical performance of these devices relative to the more common non-contact infrared thermometers (NCITs) remains unclear. In addition to confirming the findings of our preliminary analysis of clinical study results, the primary intent of this study was to compare methods for IRT calibration and identify best practices for assessing the performance of IRTs intended to detect EBT. A key secondary aim was to compare IRT clinical accuracy to that of NCITs. We performed a clinical thermographic imaging study of more than 1000 subjects, acquiring temperature data from several facial locations that, along with reference oral temperatures, were used to calibrate two IRT systems based on seven different regression methods. Oral temperatures imputed from facial data were used to evaluate IRT clinical accuracy based on metrics such as clinical bias (Δcb), repeatability, root-mean-square difference, and sensitivity/specificity. We proposed several calibration approaches designed to account for the non-uniform data density across the temperature range and a constant offset approach tended to show better ability to detect EBT. As in our prior study, inner canthi or full-face maximum temperatures provided the highest clinical accuracy. With an optimal calibration approach, these methods achieved a Δcb between ±0.03 °C with standard deviation (σΔcb) less than 0.3 °C, and sensitivity/specificity between 84% and 94%. Results of forehead-center measurements with NCITs or IRTs indicated reduced performance. An analysis of the complete clinical data set confirms the essential findings of our preliminary evaluation, with minor differences. Our findings provide novel insights into methods and metrics for the clinical accuracy assessment of IRTs. Furthermore, our results indicate that calibration approaches providing the highest clinical accuracy in the 37-38.5 °C range may be most effective for measuring EBT. While device performance depends on many factors, IRTs can provide superior performance to NCITs.


Subject(s)
Body Temperature , Thermography , Calibration , Fever , Humans , Infrared Rays , Thermometers
12.
BMC Pulm Med ; 22(1): 1, 2022 Jan 03.
Article in English | MEDLINE | ID: covidwho-1608729

ABSTRACT

BACKGROUND: Quantitative evaluation of radiographic images has been developed and suggested for the diagnosis of coronavirus disease 2019 (COVID-19). However, there are limited opportunities to use these image-based diagnostic indices in clinical practice. Our aim in this study was to evaluate the utility of a novel visually-based classification of pulmonary findings from computed tomography (CT) images of COVID-19 patients with the following three patterns defined: peripheral, multifocal, and diffuse findings of pneumonia. We also evaluated the prognostic value of this classification to predict the severity of COVID-19. METHODS: This was a single-center retrospective cohort study of patients hospitalized with COVID-19 between January 1st and September 30th, 2020, who presented with suspicious findings on CT lung images at admission (n = 69). We compared the association between the three predefined patterns (peripheral, multifocal, and diffuse), admission to the intensive care unit, tracheal intubation, and death. We tested quantitative CT analysis as an outcome predictor for COVID-19. Quantitative CT analysis was performed using a semi-automated method (Thoracic Volume Computer-Assisted Reading software, GE Health care, United States). Lungs were divided by Hounsfield unit intervals. Compromised lung (%CL) volume was the sum of poorly and non-aerated volumes (- 500, 100 HU). We collected patient clinical data, including demographic and clinical variables at the time of admission. RESULTS: Patients with a diffuse pattern were intubated more frequently and for a longer duration than patients with a peripheral or multifocal pattern. The following clinical variables were significantly different between the diffuse pattern and peripheral and multifocal groups: body temperature (p = 0.04), lymphocyte count (p = 0.01), neutrophil count (p = 0.02), c-reactive protein (p < 0.01), lactate dehydrogenase (p < 0.01), Krebs von den Lungen-6 antigen (p < 0.01), D-dimer (p < 0.01), and steroid (p = 0.01) and favipiravir (p = 0.03) administration. CONCLUSIONS: Our simple visual assessment of CT images can predict the severity of illness, a resulting decrease in respiratory function, and the need for supplemental respiratory ventilation among patients with COVID-19.


Subject(s)
COVID-19/classification , COVID-19/diagnostic imaging , Tomography, X-Ray Computed , Adult , Aged , Amides/therapeutic use , Antiviral Agents/therapeutic use , Body Temperature , C-Reactive Protein/metabolism , COVID-19/drug therapy , COVID-19/physiopathology , Female , Fibrin Fibrinogen Degradation Products/metabolism , Humans , L-Lactate Dehydrogenase/blood , Lung/diagnostic imaging , Lymphocyte Count , Male , Middle Aged , Mucin-1/blood , Neutrophils , Predictive Value of Tests , Prognosis , Pyrazines/therapeutic use , Radiographic Image Interpretation, Computer-Assisted , Retrospective Studies , SARS-CoV-2 , Steroids/therapeutic use
13.
Annu Int Conf IEEE Eng Med Biol Soc ; 2021: 6894-6898, 2021 11.
Article in English | MEDLINE | ID: covidwho-1566208

ABSTRACT

This paper describes a method for estimating core body temperature from radiation heat of the caruncle and an eyeglass-type device for measuring the temperature of the caruncle to prescreen for infectious diseases such as COVID-19. As a precise prescreening method, monitoring a person's continuous core body temperature is desired. By monitoring the continuous core body temperature, including circadian rhythm, in our daily life, infections can potentially be discovered when body temperature is higher than normal. Although monitoring the core body temperature is effective, continuous and precise monitoring requires the use of an invasive instrument. To overcome this, we (1) design an eyeglass-type device for measuring the caruncle temperature and (2) model the correlation between the caruncle temperature and the core body temperature. Experimental results revealed that hypothalamic temperature could be estimated within ± 0.3 °C between 20 and 30 °C by using the eyeglass-type device.


Subject(s)
COVID-19 , Hot Temperature , Body Temperature , Humans , SARS-CoV-2 , Temperature
14.
Antimicrob Resist Infect Control ; 10(1): 165, 2021 11 27.
Article in English | MEDLINE | ID: covidwho-1538092

ABSTRACT

BACKGROUND: Even though children seem to be less vulnerable to the Coronavirus disease 2019 (COVID-19) infection, still a diverse range of clinical presentations and symptoms have been reported in children. Few studies assessed the clinical presentations of COVID-19 among Iranian children. We aimed to evaluate the clinical and paraclinical characteristics of COVID-19 infected children. METHODS: All COVID-19 suspected and confirmed children were referred to the Ali-ibn-Abitaleb Hospital, Zahedan, Iran. Patients were included in this longitudinal study. Patients were evaluated at admission and during hospitalization. Patients with some of the main COVID symptoms with positive PCR test were defined as confirmed cases. Clinical, imaging and laboratory results were collected for all patients. RESULTS: A total of 62 patients participated in this study. The male:female ratio was 1:1.03. There was a significant difference in fatigue prevalence between age groups (P = 0.002). There was no significant difference between groups in terms of fever duration (P = 0.624) and maximum temperature (P = 0.629). There was a significant difference between PCR positive and negative patients in terms of neurologic signs (P = 0.003), Intensive care unit admission (P = 0.001), white blood cell (P = 0.047). CONCLUSIONS: Even though our population was small, most of the findings matched other studies conducted on pediatric cases in Iran or other countries. It was also found that some clinical features such as pneumonia, cough, diarrhea, and tachycardia at admission time were statistically different among age groups.


Subject(s)
COVID-19/epidemiology , Adolescent , Age Distribution , Body Temperature , Child , Child, Preschool , Fatigue , Female , Hospitalization , Humans , Infant , Iran/epidemiology , Longitudinal Studies , Male
15.
PLoS One ; 16(11): e0260269, 2021.
Article in English | MEDLINE | ID: covidwho-1526701

ABSTRACT

BACKGROUND: Feasibility of mobile Apps to monitor diseases has not been well documented particularly in developing countries. We developed and studied the feasibility of using a mobile App to collect daily data on COVID-19 symptoms and people's movements. METHODS: We used an open source software "KoBo Toolbox" to develop the App and installed it on low cost smart mobile phones. We named this App "Wetaase" ("protect yourself"). The App was tested on 30 selected households from 3 densely populated areas of Kampala, Uganda, and followed them for 3 months. One trained member per household captured the data in the App for each enrolled member and uploaded it to a virtual server on a daily basis. The App is embedded with an algorithm that flags participants who report fever and any other COVID-19 related symptom. RESULTS: A total of 101 participants were enrolled; 61% female; median age 23 (interquartile range (IQR): 17-36) years. Usage of the App was 78% (95% confidence interval (CI): 77.0%-78.8%). It increased from 40% on day 1 to a peak of 81% on day 45 and then declined to 59% on day 90. Usage of the App did not significantly vary by site, sex or age. Only 57/6617 (0.86%) records included a report of at least one of the 17 listed COVID-19 related symptoms. The most reported symptom was flu/runny nose (21%) followed by sneezing (15%), with the rest ranging between 2% and 7%. Reports on movements away from home were 45% with 74% going to markets or shops. The participants liked the "Wetaase" App and recommended it for use as an alert system for COVID-19. CONCLUSION: Usage of the "Wetaase" App was high (78%) and it was similar across the three study sites, sex and age groups. Reporting of symptoms related to COVID-19 was low. Movements were mainly to markets and shops. Users reported that the App was easy to use and recommended its scale up. We recommend that this App be assessed at a large scale for feasibility, usability and acceptability as an additional tool for increasing alerts on COVID-19 in Uganda and similar settings.


Subject(s)
COVID-19/diagnosis , Contact Tracing/methods , Mobile Applications , Telemedicine/methods , Adolescent , Adult , Body Temperature , COVID-19/epidemiology , COVID-19/prevention & control , Feasibility Studies , Female , Humans , Male , Sensitivity and Specificity , Telemedicine/standards , Travel/statistics & numerical data , Uganda
16.
Comput Math Methods Med ; 2021: 8591036, 2021.
Article in English | MEDLINE | ID: covidwho-1523094

ABSTRACT

During the ongoing COVID-19 pandemic, Internet of Things- (IoT-) based health monitoring systems are potentially immensely beneficial for COVID-19 patients. This study presents an IoT-based system that is a real-time health monitoring system utilizing the measured values of body temperature, pulse rate, and oxygen saturation of the patients, which are the most important measurements required for critical care. This system has a liquid crystal display (LCD) that shows the measured temperature, pulse rate, and oxygen saturation level and can be easily synchronized with a mobile application for instant access. The proposed IoT-based method uses an Arduino Uno-based system, and it was tested and verified for five human test subjects. The results obtained from the system were promising: the data acquired from the system are stored very quickly. The results obtained from the system were found to be accurate when compared to other commercially available devices. IoT-based tools may potentially be valuable during the COVID-19 pandemic for saving people's lives.


Subject(s)
COVID-19/physiopathology , Computer Systems , Internet of Things , Monitoring, Physiologic/instrumentation , Adult , Body Temperature , COVID-19/diagnosis , COVID-19/epidemiology , Computational Biology , Computer Systems/statistics & numerical data , Equipment Design , Female , Heart Rate , Humans , Male , Middle Aged , Mobile Applications , Monitoring, Physiologic/statistics & numerical data , Pandemics , SARS-CoV-2 , User-Computer Interface , Young Adult
17.
Sensors (Basel) ; 21(22)2021 Nov 12.
Article in English | MEDLINE | ID: covidwho-1512573

ABSTRACT

Existing wearable systems that use G-sensors to identify daily activities have been widely applied for medical, sports and military applications, while body temperature as an obvious physical characteristic that has rarely been considered in the system design and relative applications of HAR. In the context of the normalization of COVID-19, the prevention and control of the epidemic has become a top priority. Temperature monitoring plays an important role in the preliminary screening of the population for fever. Therefore, this paper proposes a wearable device embedded with inertial and temperature sensors that is used to apply human behavior recognition (HAR) to body surface temperature detection for body temperature monitoring and adjustment by evaluating recognition algorithms. The sensing system consists of an STM 32-based microcontroller, a 6-axis (accelerometer and gyroscope) sensor, and a temperature sensor to capture the original data from 10 individual participants under 4 different daily activity scenarios. Then, the collected raw data are pre-processed by signal standardization, data stacking and resampling. For HAR, several machine learning (ML) and deep learning (DL) algorithms are implemented to classify the activities. To compare the performance of different classifiers on the seven-dimensional dataset with temperature sensing signals, evaluation metrics and the algorithm running time are considered, and random forest (RF) is found to be the best-performing classifier with 88.78% recognition accuracy, which is higher than the case of the absence of temperature data (<78%). In addition, the experimental results show that participants' body surface temperature in dynamic activities was lower compared to sitting, which can be associated with the possible missing fever population due to temperature deviations in COVID-19 prevention. According to different individual activities, epidemic prevention workers are supposed to infer the corresponding standard normal body temperature of a patient by referring to the specific values of the mean expectation and variance in the normal distribution curve provided in this paper.


Subject(s)
COVID-19 , Activities of Daily Living , Algorithms , Body Temperature , Human Activities , Humans , SARS-CoV-2
18.
Sci Rep ; 11(1): 22079, 2021 11 11.
Article in English | MEDLINE | ID: covidwho-1510625

ABSTRACT

Non-contact infrared thermometers (NCITs) are being widely used during the COVID-19 pandemic as a temperature-measurement tool for screening and isolating patients in healthcare settings, travelers at ports of entry, and the general public. To understand the accuracy of NCITs, a clinical study was conducted with 1113 adult subjects using six different commercially available NCIT models. A total of 60 NCITs were tested with 10 units for each model. The NCIT-measured temperature was compared with the oral temperature obtained using a reference oral thermometer. The mean difference between the reference thermometer and NCIT measurement (clinical bias) was different for each NCIT model. The clinical bias ranged from just under - 0.9 °C (under-reporting) to just over 0.2 °C (over-reporting). The individual differences ranged from - 3 to + 2 °C in extreme cases, with the majority of the differences between - 2 and + 1 °C. Depending upon the NCIT model, 48% to 88% of the individual temperature measurements were outside the labeled accuracy stated by the manufacturers. The sensitivity of the NCIT models for detecting subject's temperature above 38 °C ranged from 0 to 0.69. Overall, our results indicate that some NCIT devices may not be consistently accurate enough to determine if subject's temperature exceeds a specific threshold of 38 °C. Model-to-model variability and individual model accuracy in the displayed temperature were found to be outside of acceptable limits. Accuracy and credibility of the NCITs should be thoroughly evaluated before using them as an effective screening tool.


Subject(s)
COVID-19 , Fever/diagnosis , Thermometers , Adult , Body Temperature , COVID-19/diagnosis , Female , Humans , Infrared Rays , Male , Pandemics , Sensitivity and Specificity , Young Adult
19.
PLoS One ; 16(6): e0253110, 2021.
Article in English | MEDLINE | ID: covidwho-1496435

ABSTRACT

BACKGROUND: The World Health Organization recommends inpatient hospital treatment of young infants up to two months old with any sign of possible serious infection. However, each sign may have a different risk of death. The current study aims to calculate the case fatality ratio for infants with individual or combined signs of possible serious infection, stratified by inpatient or outpatient treatment. METHODS: We analysed data from the African Neonatal Sepsis Trial conducted in five sites in the Democratic Republic of the Congo, Kenya and Nigeria. Trained study nurses classified sick infants as pneumonia (fast breathing in 7-59 days old), severe pneumonia (fast breathing in 0-6 days old), clinical severe infection [severe chest indrawing, high (> = 38°C) or low body temperature (<35.5°C), stopped feeding well, or movement only when stimulated] or critical illness (convulsions, not able to feed at all, or no movement at all), and referred them to a hospital for inpatient treatment. Infants whose caregivers refused referral received outpatient treatment. The case fatality ratio by day 15 was calculated for individual and combined clinical signs and stratified by place of treatment. An infant with signs of clinical severe infection or severe pneumonia was recategorised as having low- (case fatality ratio ≤2%) or moderate- (case fatality ratio >2%) mortality risk. RESULTS: Of 7129 young infants with a possible serious infection, fast breathing (in 7-59 days old) was the most prevalent sign (26%), followed by high body temperature (20%) and severe chest indrawing (19%). Infants with pneumonia had the lowest case fatality ratio (0.2%), followed by severe pneumonia (2.0%), clinical severe infection (2.3%) and critical illness (16.9%). Infants with clinical severe infection had a wide range of case fatality ratios for individual signs (from 0.8% to 11.0%). Infants with pneumonia had similar case fatality ratio for outpatient and inpatient treatment (0.2% vs. 0.3%, p = 0.74). Infants with clinical severe infection or severe pneumonia had a lower case fatality ratio among those who received outpatient treatment compared to inpatient treatment (1.9% vs. 6.5%, p<0.0001). We recategorised infants into low-mortality risk signs (case fatality ratio ≤2%) of clinical severe infection (high body temperature, or severe chest indrawing) or severe pneumonia and moderate-mortality risk signs (case fatality ratio >2%) (stopped feeding well, movement only when stimulated, low body temperature or multiple signs of clinical severe infection). We found that both categories had four times lower case fatality ratio when treated as outpatient than inpatient treatment, i.e., 1.0% vs. 4.0% (p<0.0001) and 5.3% vs. 22.4% (p<0.0001), respectively. In contrast, infants with signs of critical illness had nearly two times higher case fatality ratio when treated as outpatient versus inpatient treatment (21.7% vs. 12.1%, p = 0.097). CONCLUSIONS: The mortality risk differs with clinical signs. Young infants with a possible serious infection can be grouped into those with low-mortality risk signs (high body temperature, or severe chest indrawing or severe pneumonia); moderate-mortality risk signs (stopped feeding well, movement only when stimulated, low body temperature or multiple signs of clinical severe infection), or high-mortality risk signs (signs of critical illness). New treatment strategies that consider differential mortality risks for the place of treatment and duration of inpatient treatment could be developed and evaluated based on these findings. CLINICAL TRIAL REGISTRATION: This trial was registered with the Australian New Zealand Clinical Trials Registry under ID ACTRN 12610000286044.


Subject(s)
Fever/complications , Health Facilities/statistics & numerical data , Hospitalization/statistics & numerical data , Infant Mortality/trends , Infections/mortality , Pneumonia/mortality , Anti-Infective Agents/therapeutic use , Body Temperature , Democratic Republic of the Congo/epidemiology , Female , Humans , Infant , Infant, Newborn , Infections/drug therapy , Infections/epidemiology , Kenya/epidemiology , Male , Nigeria/epidemiology , Pneumonia/drug therapy , Pneumonia/epidemiology
20.
Am J Infect Control ; 49(11): 1445-1447, 2021 11.
Article in English | MEDLINE | ID: covidwho-1482406

ABSTRACT

Infrared temperature measurement is a common form of mass screening for febrile illnesses such as COVID-19 infection. Efficacy of infrared monitoring is debated, and external factors can affect accuracy. We determine that outside temperature, wind, and humidity can affect infrared temperature measurements and partially account for inaccurate results.


Subject(s)
COVID-19 , Body Temperature , Humans , Humidity , Mass Screening , SARS-CoV-2 , Temperature
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