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1.
BMC Emerg Med ; 22(1): 68, 2022 04 29.
Article in English | MEDLINE | ID: covidwho-1951060

ABSTRACT

BACKGROUND: COVID-19 remains a major healthcare concern. Vital signs are routinely measured on admission and may provide an early, cost-effective indicator of outcome - more so in developing countries where such data is scarce. We sought to describe the association between six routinely measured admission vital signs and COVID-19 mortality, and secondarily to derive potential applications for resource-limited settings. METHODS: Retrospective analysis of consecutive patients admitted to King Edward VIII Hospital, South Africa, with COVID-19 during June-September 2020 was undertaken. The sample was subdivided into survivors and non-survivors and comparisons made in terms of demographics and admission vital signs. Univariate and multivariate analysis of predictor variables identified associations with in-hospital mortality, with the resulting multivariate regression model evaluated for its predictive ability with receiver operating characteristic (ROC) curve analysis. RESULTS: The 236 participants enrolled comprised 153(77.54%) survivors and 53(22.46%) non-survivors. Most participants were Black African(87.71%) and female(59.75%) with a mean age of 53.08(16.96) years. The non-survivor group demonstrated a significantly lower median/mean for admission oxygen saturation (%) [87(78-95) vs. 96(90-98)] and diastolic BP (mmHg) [70.79(14.66) vs. 76.3(12.07)], and higher median for admission respiratory rate (breaths/minute) [24(20-28) vs. 20(20-23)] and glucose (mmol/l) [10.2(6.95-16.25) vs. 7.4(5.5-9.8)]. Age, oxygen saturation, respiratory rate, glucose and diastolic BP were found to be significantly associated with mortality on univariate analysis. A log rank test revealed significantly lower survival rates in patients with an admission oxygen saturation < 90% compared with ≥90% (p = 0.001). Multivariate logistic regression revealed a significant relationship between age and oxygen saturation with in-hospital mortality (OR 1.047; 95% CI 1.016-1.080; p = 0.003 and OR 0.922; 95% CI 0.880-0.965; p = 0.001 respectively). A ROC curve analysis generated an area under the curve (AUC) of 0.778 (p < 0.001) when evaluating the predictive ability of oxygen saturation, respiratory rate, glucose and diastolic BP for in-hospital death. This improved to an AUC of 0.832 (p < 0.001) with the inclusion of age. CONCLUSION: A multivariate regression model comprising admission oxygen saturation, respiratory rate, glucose and diastolic BP (with/without age) demonstrated promising predictive capacity, and may provide a cost-effective means for early prognostication of patients admitted with COVID-19 in resource-limited settings.


Subject(s)
COVID-19 , Cross-Sectional Studies , Female , Glucose , Hospital Mortality , Humans , Middle Aged , Retrospective Studies , Vital Signs
2.
Prev Chronic Dis ; 19: E33, 2022 06 23.
Article in English | MEDLINE | ID: covidwho-1912045

ABSTRACT

INTRODUCTION: Physical activity is important to prevent and manage multiple chronic medical conditions. The objective of this study was to describe the implementation of a physical activity vital sign (PAVS) in a primary care setting and examine the association between physical activity with demographic characteristics and chronic disease burden. METHODS: We extracted data from the electronic medical records of patients who had visits from July 2018 through January 2020 in a primary care clinic in which PAVS was implemented as part of the intake process. Data collected included self-reported physical activity, age, sex, body mass index, race, ethnicity, and a modified Charlson Comorbidity Index score indicating chronic disease burden. We classified PAVS into 3 categories of time spent in moderate to strenuous intensity physical activity: consistently inactive (0 min/wk), inconsistently active (<150 min/wk), and consistently active (≥150 min/wk). We used χ2 tests of independence to test for association between PAVS categories and all other variables. RESULTS: During the study period, 13,704 visits, corresponding to 8,741 unique adult patients, had PAVS recorded. Overall, 18.1% of patients reported being consistently inactive, 48.3% inconsistently active, and 33.7% consistently active. All assessed demographic and clinical covariates were associated with PAVS classification (all P < .001). Larger percentages of consistent inactivity were reported for female, older, and underweight or obese patients. Larger percentages of consistent activity were reported for male, younger, and normal weight or overweight patients. CONCLUSION: Using PAVS as a screening tool in primary care enables physicians to understand the physical activity status of their patients and can be useful in identifying inactive patients who may benefit from physical activity counseling.


Subject(s)
Exercise , Vital Signs , Adult , Chronic Disease , Demography , Female , Humans , Male , Primary Health Care
4.
Front Public Health ; 10: 864197, 2022.
Article in English | MEDLINE | ID: covidwho-1877515

ABSTRACT

Objective: To explore the current knowledge and application of vital sign zero and the identify-isolate-inform (3I) system among healthcare workers in China in order to provide a reference for future improvement of healthcare workers' awareness of personal protection and prevention and control measures of infectious diseases. Methods: The questionnaire was used to investigate the basic information of health care workers, their knowledge and application of Vital sign zero and the 3I system. A total of 602 forms of health care workers from tertiary hospitals were randomly collected and included for analysis. Results: The survey showed that 45.30% and 57.30% of the healthcare workers from Chinese tertiary hospitals know about vital sign zero and 3I system while 51.80% and 57.30% of them applied these measures in their clinical practices. Logistics regression analysis results showed that healthcare workers aged 35 years old and below were less aware of vital sign zero than those above 50 years old (OR = 0.405, 95% CI: 0.174-0.942, P = 0.036). Compared with those in Northwest China, healthcare workers who worked in East China (OR = 0.147, 95% CI: 0.031-0.702, P = 0.016), Central China (OR = 0.085, 95% CI: 0.018-0.403, P = 0.002), Southwest China (OR = 0.083, 95% CI: 0.014-0.48, P = 0.006) and North China (OR = 0.201, 95% CI: 0.042-0.966, P = 0.045) were less aware of vital sign zero while the healthcare workers in Northeast China (OR=9.714, 95% CI: 1.091-86.521, P = 0.042), East China (OR = 18.049, 95% CI: 2.258-144.259, P = 0.006), Central China (OR = 25.560, 95% CI: 3.210-203.502, P = 0.002), South China (OR = 11.141, 95% CI: 1.395-88.947, P = 0.023), Southwest China (OR = 23.200, 95% CI: 2.524-213.286, P = 0.005) and North China (OR = 14.078, 95% CI: 1.756-112.895, P = 0.013) had a better understanding of the 3I system than those in Northwest China. Healthcare workers with more than 20 years of working experience showed less knowledge of the 3I system than those with less than 5 years of working experience (OR = 0.409, 95% CI: 0.215-0.77, P = 0.006). Conclusion: The current levels of knowledge and application of vital sign zero and the 3I system in the healthcare workers of Chinese tertiary hospitals need to be improved. The concept of vital sign zero should be incorporated into the prevention triage system of infectious diseases.


Subject(s)
Communicable Diseases , Health Personnel , Adult , Health Knowledge, Attitudes, Practice , Humans , Middle Aged , Tertiary Care Centers , Vital Signs
5.
Infect Dis (Lond) ; 54(9): 677-686, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1873825

ABSTRACT

BACKGROUND: Vital signs are critical in assessing the severity and prognosis of infections, for example, COVID-19, influenza, sepsis, and pneumonia. This study aimed to evaluate a new method for rapid camera-based non-contact measurement of heart rate, blood oxygen saturation, respiratory rate, and blood pressure. METHODS: Consecutive adult patients attending a hospital emergency department for suspected COVID-19 infection were invited to participate. Vital signs measured with a new camera-based method were compared to the corresponding standard reference methods. The camera device observed the patient's face for 30 s from ∼1 m. RESULTS: Between 1 April and 1 October 2020, 214 subjects were included in the trial, 131 female (61%) and 83 male (39%). The mean age was 44 years (range 18-81 years). The new camera-based device's vital signs measurements were, on average, very close to the gold standard but the random variation was larger than the reference methods. CONCLUSIONS: The principle of contactless measurement of blood pressure, pulse, respiratory rate, and oxygen saturation works, which is very promising. However, technical improvements to the equipment used in this study to reduce its random variability is required before clinical implementation. This will likely be a game changer once this is sorted out. CLINICAL TRIAL REGISTRATION: Universal Trial Number (UTN) U1111-1251-4114 and the ClinicalTrials.gov Identifier NCT04383457.


Subject(s)
COVID-19 , Adolescent , Adult , Aged , Aged, 80 and over , Blood Pressure , COVID-19/diagnosis , Female , Heart Rate , Humans , Male , Middle Aged , Oxygen Saturation , Respiratory Rate , Vital Signs , Young Adult
6.
MMWR Morb Mortal Wkly Rep ; 71(19): 656-663, 2022 May 13.
Article in English | MEDLINE | ID: covidwho-1847855

ABSTRACT

INTRODUCTION: The majority of homicides (79%) and suicides (53%) in the United States involved a firearm in 2020. High firearm homicide and suicide rates and corresponding inequities by race and ethnicity and poverty level represent important public health concerns. This study examined changes in firearm homicide and firearm suicide rates coinciding with the emergence of the COVID-19 pandemic in 2020. METHODS: National vital statistics and population data were integrated with urbanization and poverty measures at the county level. Population-based firearm homicide and suicide rates were examined by age, sex, race and ethnicity, geographic area, level of urbanization, and level of poverty. RESULTS: From 2019 to 2020, the overall firearm homicide rate increased 34.6%, from 4.6 to 6.1 per 100,000 persons. The largest increases occurred among non-Hispanic Black or African American males aged 10-44 years and non-Hispanic American Indian or Alaska Native (AI/AN) males aged 25-44 years. Rates of firearm homicide were lowest and increased least at the lowest poverty level and were higher and showed larger increases at higher poverty levels. The overall firearm suicide rate remained relatively unchanged from 2019 to 2020 (7.9 to 8.1); however, in some populations, including AI/AN males aged 10-44 years, rates did increase. CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: During the COVID-19 pandemic, the firearm homicide rate in the United States reached its highest level since 1994, with substantial increases among several population subgroups. These increases have widened disparities in rates by race and ethnicity and poverty level. Several increases in firearm suicide rates were also observed. Implementation of comprehensive strategies employing proven approaches that address underlying economic, physical, and social conditions contributing to the risks for violence and suicide is urgently needed to reduce these rates and disparities.


Subject(s)
COVID-19 , Firearms , Suicide , Cause of Death , Homicide , Humans , Male , Pandemics , Population Surveillance , United States/epidemiology , Vital Signs
8.
BMJ Open ; 12(4): e057693, 2022 04 05.
Article in English | MEDLINE | ID: covidwho-1779377

ABSTRACT

INTRODUCTION: Remote patient monitoring (RPM) has emerged as a potential avenue for optimising the management of symptoms in patients undergoing chemotherapy. However, RPM is a complex, multilevel intervention with technology, workflow, contextual and patient experience components. The purpose of this pilot study is to determine the feasibility of RPM protocol implementation with respect to decentralised recruitment, patient retention, adherence to reporting recommendations, RPM platform usability and patient experience in ambulatory cancer patients at high risk for chemotherapy-related symptoms. METHODS AND ANALYSIS: This protocol describes a single-arm decentralised feasibility pilot study of technology-enhanced outpatient symptom management system in patients with gastrointestinal and thoracic cancer receiving chemotherapy and cancer care at a single site (MD Anderson Cancer Center, Houston Texas). An anticipated total of 25 patients will be recruited prior to the initiation of chemotherapy and provided with a set of validated questionnaires at enrollment and after our 1-month feasibility pilot trial period. Our intervention entails the self-reporting of symptoms and vital signs via a HIPAA-compliant, secure tablet interface that also enables (1) the provision of self-care materials to patients, (2) generation of threshold alerts to a dedicated call-centre and (3) videoconferencing. Vital sign information (heart rate, blood pressure, pulse, oxygen saturation, weight and temperature) will be captured via Bluetooth-enabled biometric monitoring devices which are integrated with the tablet interface. Protocolised triage and management of symptoms will occur in response to the alerts. Feasibility and acceptability metrics will characterise our recruitment process, protocol adherence, patient retention and usability of the RPM platform. We will also document the perceived effectiveness of our intervention by patients. ETHICS AND DISSEMINATION: This study has been granted approval by the institutional review board of MD Anderson Cancer Center. We anticipate dissemination of our pilot and subsequent effectiveness trial results via presentations at national conferences and peer-reviewed publications in the relevant medical journals. Our results will also be made available to cancer survivors, their caregivers and hospital administration. TRIAL REGISTRATION NUMBER: NCI202107464.


Subject(s)
Neoplasms , Watchful Waiting , Electronics , Feasibility Studies , Humans , Neoplasms/drug therapy , Patient Reported Outcome Measures , Pilot Projects , Vital Signs
9.
Work ; 71(4): 843-850, 2022.
Article in English | MEDLINE | ID: covidwho-1731745

ABSTRACT

BACKGROUND: In order for nurses to provide the desired/expected care during the COVID-19 pandemic, the personal protective equipment (PPE) they use should not cause additional damage. OBJECTIVE: The current study examined the effect of nurses' use of PPE on their vital signs during the COVID-19 pandemic. METHODS: The present study was executed in a public hospital located in Turkey between October 2020 and December 2020 with a total of 112 nurses, 54 of them were serving in COVID-19 clinics, and 58 of them were working in other clinics. The data of the study was collected by using the introductory information form, the vital signs measurement, and the Visual Analogue Scale. The numbers, percentages, means, standard deviation, Chi-square, ANOVA, Mann-Whitney U and Wilcoxon tests were used to analyze the data. RESULTS: The mean scores of SpO2, respiratory rate, body temperature, heart rate and blood pressure measurements of the nurses in the experimental group were compared before and after putting on the PPE. It was found that the difference between the two averages was statistically significant (p < 0.05). CONCLUSION: It was found that the use of PPE for a long time causes a decrease in SpO2, increase in respiratory rate, pulse and blood pressure, as well as the aches in face, ear, nose and head.


Subject(s)
COVID-19 , Nurses , COVID-19/epidemiology , COVID-19/prevention & control , Cross-Sectional Studies , Humans , Pandemics/prevention & control , Personal Protective Equipment , SARS-CoV-2 , Vital Signs
11.
JAMA Netw Open ; 5(2): e2143151, 2022 02 01.
Article in English | MEDLINE | ID: covidwho-1669321

ABSTRACT

Importance: Understanding of SARS-CoV-2 infection in US children has been limited by the lack of large, multicenter studies with granular data. Objective: To examine the characteristics, changes over time, outcomes, and severity risk factors of children with SARS-CoV-2 within the National COVID Cohort Collaborative (N3C). Design, Setting, and Participants: A prospective cohort study of encounters with end dates before September 24, 2021, was conducted at 56 N3C facilities throughout the US. Participants included children younger than 19 years at initial SARS-CoV-2 testing. Main Outcomes and Measures: Case incidence and severity over time, demographic and comorbidity severity risk factors, vital sign and laboratory trajectories, clinical outcomes, and acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C), and Delta vs pre-Delta variant differences for children with SARS-CoV-2. Results: A total of 1 068 410 children were tested for SARS-CoV-2 and 167 262 test results (15.6%) were positive (82 882 [49.6%] girls; median age, 11.9 [IQR, 6.0-16.1] years). Among the 10 245 children (6.1%) who were hospitalized, 1423 (13.9%) met the criteria for severe disease: mechanical ventilation (796 [7.8%]), vasopressor-inotropic support (868 [8.5%]), extracorporeal membrane oxygenation (42 [0.4%]), or death (131 [1.3%]). Male sex (odds ratio [OR], 1.37; 95% CI, 1.21-1.56), Black/African American race (OR, 1.25; 95% CI, 1.06-1.47), obesity (OR, 1.19; 95% CI, 1.01-1.41), and several pediatric complex chronic condition (PCCC) subcategories were associated with higher severity disease. Vital signs and many laboratory test values from the day of admission were predictive of peak disease severity. Variables associated with increased odds for MIS-C vs acute COVID-19 included male sex (OR, 1.59; 95% CI, 1.33-1.90), Black/African American race (OR, 1.44; 95% CI, 1.17-1.77), younger than 12 years (OR, 1.81; 95% CI, 1.51-2.18), obesity (OR, 1.76; 95% CI, 1.40-2.22), and not having a pediatric complex chronic condition (OR, 0.72; 95% CI, 0.65-0.80). The children with MIS-C had a more inflammatory laboratory profile and severe clinical phenotype, with higher rates of invasive ventilation (117 of 707 [16.5%] vs 514 of 8241 [6.2%]; P < .001) and need for vasoactive-inotropic support (191 of 707 [27.0%] vs 426 of 8241 [5.2%]; P < .001) compared with those who had acute COVID-19. Comparing children during the Delta vs pre-Delta eras, there was no significant change in hospitalization rate (1738 [6.0%] vs 8507 [6.2%]; P = .18) and lower odds for severe disease (179 [10.3%] vs 1242 [14.6%]) (decreased by a factor of 0.67; 95% CI, 0.57-0.79; P < .001). Conclusions and Relevance: In this cohort study of US children with SARS-CoV-2, there were observed differences in demographic characteristics, preexisting comorbidities, and initial vital sign and laboratory values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission. Further work is needed to translate this knowledge into improved outcomes.


Subject(s)
COVID-19/epidemiology , Adolescent , Age Distribution , COVID-19/complications , COVID-19/diagnosis , COVID-19/therapy , COVID-19/virology , Child , Child, Preschool , Comorbidity , Disease Progression , Early Diagnosis , Female , Humans , Infant , Male , Risk Factors , SARS-CoV-2 , Severity of Illness Index , Sociodemographic Factors , Systemic Inflammatory Response Syndrome/diagnosis , Systemic Inflammatory Response Syndrome/epidemiology , Systemic Inflammatory Response Syndrome/therapy , Systemic Inflammatory Response Syndrome/virology , United States/epidemiology , Vital Signs
12.
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
13.
Womens Health (Lond) ; 17: 17455065211013262, 2021.
Article in English | MEDLINE | ID: covidwho-1595974

ABSTRACT

BACKGROUND: The 2019 coronavirus disease pandemic poses unique challenges to healthcare delivery. To limit the exposure of providers and patients to severe acute respiratory syndrome coronavirus 2, the Centers for Disease Control and Prevention encourages providers to use telehealth platforms whenever possible. Given the maternal mortality crisis in the United States and the compounding 2019 coronavirus disease public health emergency, continued access to quality preconception, prenatal, intrapartum, and postpartum care are essential to the health and well-being of mother and baby. OBJECTIVE: This commentary explores unique opportunities to optimize virtual obstetric care for low-risk and high-risk mothers at each stage of pregnancy. METHODS: In this review paper, we present evidence-based literature and tools from first-hand experience implementing telemedicine in obstetric care clinics during the pandemic. RESULTS: Using the best evidence-based practices with telemedicine, health care providers can deliver care in the safest, most respectful, and appropriate way possible while providing the critical support necessary in pregnancy. In reviewing the literature, several studies endorse the implementation of specific tools outlined in this article, to facilitate the implementation of telemedicine. From a quality improvement standpoint, evidence-based telemedicine provides a solution for overburdened healthcare systems, greater confidentiality for obstetric services, and a personalized avenue for health care providers to meet maternal health needs in the pandemic. CONCLUSION: During the COVID-19 pandemic, continued access to quality prenatal, intrapartum, and postpartum care are essential to the health and well-being of mother and baby.


Subject(s)
COVID-19 , Telemedicine , Female , Humans , Mothers , Pandemics , Pregnancy , SARS-CoV-2 , United States , Vital Signs
14.
Annu Int Conf IEEE Eng Med Biol Soc ; 2021: 6845-6850, 2021 11.
Article in English | MEDLINE | ID: covidwho-1566212

ABSTRACT

The novel coronavirus disease (COVID-19), as a pandemic, has intensely impacted the global healthcare systems. Remote health monitoring of positive COVID-19 patients isolating at home has been identified as a practical approach to minimize the mortality rate. This work proposes a cost-effective and ease-to-use wristband with the capability of continuous real-time monitoring of heart rate (HR), respiration rate (RR), and blood oxygen saturation (SpO2), temperature and accelerometry. The proposed wristband comprises three different sensing elements, namely, PPG sensor, temperature sensor, and accelerometer. The sensors' output signals are transmitted via Bluetooth. Process of the PPG signals measured from the wrist anatomical position provides essential information regarding HR, RR, and SpO2. The deployed temperature sensor and accelerometer, measure the wearers' body temperature and physical activities. Experimental results obtained from a group of subjects demonstrate that the wristband can monitor HR, RR, SpO2, and body temperature with the Mean Absolute Errors (MAEs) of 2.75 bpm, 1.25 breaths/min, 0.64%, and 0.22 Co, respectively. Such a small variation confirms that the wristband can be potentially deployed in the public health network to determine and track patients infected by COVID-19.


Subject(s)
COVID-19 , Humans , Monitoring, Physiologic , SARS-CoV-2 , Vital Signs
15.
Sensors (Basel) ; 21(23)2021 Dec 05.
Article in English | MEDLINE | ID: covidwho-1555018

ABSTRACT

This study introduces machine learning predictive models to predict the future values of the monitored vital signs of COVID-19 ICU patients. The main vital sign predictors include heart rate, respiration rate, and oxygen saturation. We investigated the performances of the developed predictive models by considering different approaches. The first predictive model was developed by considering the following vital signs: heart rate, blood pressure (systolic, diastolic and mean arterial, pulse pressure), respiration rate, and oxygen saturation. Similar to the first approach, the second model was developed using the same vital signs, but it was trained and tested based on a leave-one-subject-out approach. The third predictive model was developed by considering three vital signs: heart rate (HR), respiration rate (RR), and oxygen saturation (SpO2). The fourth model was a leave-one-subject-out model for the three vital signs. Finally, the fifth predictive model was developed based on the same three vital signs, but with a five-minute observation rate, in contrast with the aforementioned four models, where the observation rate was hourly to bi-hourly. For the five models, the predicted measurements were those of the three upcoming observations (on average, three hours ahead). Based on the obtained results, we observed that by limiting the number of vital sign predictors (i.e., three vital signs), the prediction performance was still acceptable, with the average mean absolute percentage error (MAPE) being 12%,5%, and 21.4% for heart rate, oxygen saturation, and respiration rate, respectively. Moreover, increasing the observation rate could enhance the prediction performance to be, on average, 8%,4.8%, and 17.8% for heart rate, oxygen saturation, and respiration rate, respectively. It is envisioned that such models could be integrated with monitoring systems that could, using a limited number of vital signs, predict the health conditions of COVID-19 ICU patients in real-time.


Subject(s)
COVID-19 , Humans , Intensive Care Units , SARS-CoV-2 , Vital Signs
17.
Expert Rev Cardiovasc Ther ; 19(10): 877-880, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1462212
18.
Pediatr Cardiol ; 42(7): 1658-1659, 2021 10.
Article in English | MEDLINE | ID: covidwho-1453707
20.
Am J Epidemiol ; 190(10): 2094-2106, 2021 10 01.
Article in English | MEDLINE | ID: covidwho-1447568

ABSTRACT

Longitudinal trajectories of vital signs and biomarkers during hospital admission of patients with COVID-19 remain poorly characterized despite their potential to provide critical insights about disease progression. We studied 1884 patients with severe acute respiratory syndrome coronavirus 2 infection from April 3, 2020, to June 25, 2020, within 1 Maryland hospital system and used a retrospective longitudinal framework with linear mixed-effects models to investigate relevant biomarker trajectories leading up to 3 critical outcomes: mechanical ventilation, discharge, and death. Trajectories of 4 vital signs (respiratory rate, ratio of oxygen saturation (Spo2) to fraction of inspired oxygen (Fio2), pulse, and temperature) and 4 laboratory values (C-reactive protein (CRP), absolute lymphocyte count (ALC), estimated glomerular filtration rate, and D-dimer) clearly distinguished the trajectories of patients with COVID-19. Before any ventilation, log(CRP), log(ALC), respiratory rate, and Spo2-to-Fio2 ratio trajectories diverge approximately 8-10 days before discharge or death. After ventilation, log(CRP), log(ALC), respiratory rate, Spo2-to-Fio2 ratio, and estimated glomerular filtration rate trajectories again diverge 10-20 days before death or discharge. Trajectories improved until discharge and remained unchanged or worsened until death. Our approach characterizes the distribution of biomarker trajectories leading up to competing outcomes of discharge versus death. Moving forward, this model can contribute to quantifying the joint probability of biomarkers and outcomes when provided clinical data up to a given moment.


Subject(s)
Biomarkers/metabolism , COVID-19/metabolism , Outcome Assessment, Health Care , Pneumonia, Viral/metabolism , COVID-19/diagnosis , COVID-19/epidemiology , Case-Control Studies , Disease Progression , Female , Humans , Longitudinal Studies , Male , Maryland/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Predictive Value of Tests , Retrospective Studies , SARS-CoV-2 , Vital Signs
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