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1.
Sci Rep ; 13(1): 442, 2023 01 09.
Article in English | MEDLINE | ID: covidwho-2186073

ABSTRACT

Non-invasive oxygen saturation (SpO2) is a central vital sign used to shape the management of COVID-19 patients. Yet, there have been no report quantitatively describing SpO2 dynamics and patterns in COVID-19 patients using continuous SpO2 recordings. We performed a retrospective observational analysis of the clinical information and 27 K hours of continuous SpO2 high-resolution (1 Hz) recordings of 367 critical and non-critical COVID-19 patients hospitalised at the Rambam Health Care Campus, Haifa, Israel. An absolute SpO2 threshold of 93% most efficiently discriminated between critical and non-critical patients, regardless of oxygen support. Oximetry-derived digital biomarker (OBMs) computed per 1 h monitoring window showed significant differences between groups, notably the cumulative time below 93% SpO2 (CT93). Patients with CT93 above 60% during the first hour of monitoring, were more likely to require oxygen support. Mechanical ventilation exhibited a strong effect on SpO2 dynamics by significantly reducing the frequency and depth of desaturations. OBMs related to periodicity and hypoxic burden were markedly affected, up to several hours before the initiation of the mechanical ventilation. In summary, OBMs, traditionally used in the field of sleep medicine research, are informative for continuous assessment of disease severity and response to respiratory support of hospitalised COVID-19 patients. In conclusion, OBMs may improve risk stratification and therapy management of critical care patients with respiratory impairment.


Subject(s)
COVID-19 , Humans , COVID-19/therapy , Retrospective Studies , Oximetry , Oxygen , Respiratory Rate
2.
Front Med (Lausanne) ; 8: 656405, 2021.
Article in English | MEDLINE | ID: covidwho-1247875

ABSTRACT

Background: COVID-19 is a newly recognized illness with a predominantly respiratory presentation. It is important to characterize the differences in disease presentation and trajectory between COVID-19 patients and other patients with common respiratory illnesses. These differences can enhance knowledge of pathogenesis and help in guiding treatment. Methods: Data from electronic medical records were obtained from individuals admitted with respiratory illnesses to Rambam Health Care Campus, Haifa, Israel, between October 1st, 2014 and October 1st, 2020. Four groups of patients were defined: COVID-19 (693), influenza (1,612), severe acute respiratory infection (SARI) (2,292), and Others (4,054). The variable analyzed include demographics (7), vital signs (8), lab tests (38), and comorbidities (15) from a total of 8,651 hospitalized adult patients. Statistical analysis was performed on biomarkers measured at admission and for their disease trajectory in the first 48 h of hospitalization, and on comorobidity prevalence. Results: COVID-19 patients were overall younger in age and had higher body mass index, compared to influenza and SARI. Comorbidity burden was lower in the COVID-19 group compared to influenza and SARI. Severely- and moderately-ill COVID-19 patients older than 65 years of age suffered higher rate of in-hospital mortality compared to hospitalized influenza patients. At admission, white blood cells and neutrophils were lower among COVID-19 patients compared to influenza and SARI patients, while pulse rate and lymphoctye percentage were higher. Trajectories of variables during the first 2 days of hospitalization revealed that white blood count, neutrophils percentage and glucose in blood increased among COVID-19 patients, while decreasing among other patients. Conclusions: The intrinsic virulence of COVID-19 appeared higher than influenza. In addition, several critical functions, such as immune response, coagulation, heart and respiratory function, and metabolism were uniquely affected by COVID-19.

3.
J Am Med Inform Assoc ; 28(6): 1188-1196, 2021 06 12.
Article in English | MEDLINE | ID: covidwho-1043881

ABSTRACT

OBJECTIVE: The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a model helping planners assess expected COVID-19 hospital resource utilization based on individual patient characteristics. MATERIALS AND METHODS: We develop a model of patient clinical course based on an advanced multistate survival model. The model predicts the patient's disease course in terms of clinical states-critical, severe, or moderate. The model also predicts hospital utilization on the level of entire hospitals or healthcare systems. We cross-validated the model using a nationwide registry following the day-by-day clinical status of all hospitalized COVID-19 patients in Israel from March 1 to May 2, 2020 (n = 2703). RESULTS: Per-day mean absolute errors for predicted total and critical care hospital bed utilization were 4.72 ± 1.07 and 1.68 ± 0.40, respectively, over cohorts of 330 hospitalized patients; areas under the curve for prediction of critical illness and in-hospital mortality were 0.88 ± 0.04 and 0.96 ± 0.04, respectively. We further present the impact of patient influx scenarios on day-by-day healthcare system utilization. We provide an accompanying R software package. DISCUSSION: The proposed model accurately predicts total and critical care hospital utilization. The model enables evaluating impacts of patient influx scenarios on utilization, accounting for the state of currently hospitalized patients and characteristics of incoming patients. We show that accurate hospital load predictions were possible using only a patient's age, sex, and day-by-day clinical state (critical, severe, or moderate). CONCLUSIONS: The multistate model we develop is a powerful tool for predicting individual-level patient outcomes and hospital-level utilization.


Subject(s)
COVID-19 , Hospitalization/statistics & numerical data , Machine Learning , Models, Statistical , Adult , Aged , Aged, 80 and over , Female , Hospitals/statistics & numerical data , Humans , Israel , Length of Stay/statistics & numerical data , Male , Middle Aged , Prognosis , Proportional Hazards Models , Registries
4.
Pediatr Infect Dis J ; 39(8): e206-e207, 2020 08.
Article in English | MEDLINE | ID: covidwho-637482

ABSTRACT

Pediatric inflammatory multisystem syndromes associated with Severe Acute Respiratory Syndrome Coronavirus 2 are emerging in recent reports. We describe a patient with critical illness consistent with atypical Kawasaki disease with cardiac dysfunction and abdominal involvement presenting weeks after Severe Acute Respiratory Syndrome Coronavirus 2 infection. Our patient showed unique central nervous system involvement with small vessel vasculitis and profound hypocomplementemia, both not previously reported in case descriptions and may hint at possible disease mechanisms.


Subject(s)
Coronavirus Infections/complications , Coronavirus Infections/physiopathology , Pneumonia, Viral/complications , Pneumonia, Viral/physiopathology , Systemic Inflammatory Response Syndrome/complications , Systemic Inflammatory Response Syndrome/physiopathology , Adolescent , Betacoronavirus , Brain/diagnostic imaging , COVID-19 , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Glomerulonephritis, Membranoproliferative , Hemosiderosis/diagnostic imaging , Hospitalization , Humans , Male , Mucocutaneous Lymph Node Syndrome/complications , Nervous System , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , SARS-CoV-2 , Systemic Inflammatory Response Syndrome/diagnostic imaging , Systemic Inflammatory Response Syndrome/therapy
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