Derivation and validation of new prehospital phenotypes for adults with COVID-19

Objective. To characterize phenotypes of prehospital patients with COVID-19 to facilitate early identification of at-risk groups. Methods. Multicenter observational noninterventional study of a retrospective cohort of 3789 patients, analyzing 52 prehospital variables. The main outcomes were 4 clusters of prehospital variables describing the phenotypes. Secondary outcomes were hospitalization, mechanical ventilation, admission to an intensive care unit, and cumulative mortality inside or outside the hospital on days 1, 2, 3, 7, 14, 21, and 28 after hospitalization and after start of prehospital care. Results. We used a principal components multiple correspondence analysis (factor analysis) followed by decomposition into 4 clusters as follows: cluster 1, 1090 patients (28.7%);cluster 2, 1420 (37.4%);cluster 3, 250 (6.6%), and cluster 4, 1029 (27.1%). Cluster 4 was comprised of the oldest patients and had the highest frequencies of residence in group facilities and low arterial oxygen saturation. This group also had the highest mortality (44.8% at 28 days). Cluster 1 was comprised of the youngest patients and had the highest frequencies of smoking, fever, and requirement for mechanical ventilation. This group had the most favorable prognosis and the lowest mortality. Conclusions. Patients with COVID-19 evaluated by emergency medical responders and transferred to hospital emergency departments can be classified into 4 phenotypes with different clinical, therapeutic, and prognostic characteristics. The phenotypes can help health care professionals to quickly assess a patient’s future risk, thus informing clinical decisions. © 2022, Saned. All rights reserved.

Mortality risk model for patients with suspected COVID-19 based on information available from an emergency dispatch center

Objective. To develop and validate a scale to stratify risk of 2-day mortality based on data collected during calls to an emergency dispatch center from patients with suspected coronavirus disease 2019 (COVID-19). Methods. Retrospective multicenter study of consecutive patients over the age of 18 years with suspected COVID-19 who were transported from home over the course of 3 months after telephone interviews with dispatchers. We analyzed clinical and epidemiologic variables and comorbidities in relation to death within 2 days of the call. Using data from the development cohort, we built a risk model by means of logistic regression analysis of categorical variables that were independently associated with 2-day mortality. The scale was validated first in a validation cohort in the same province and then in a cohort in a different province. Results. A total of 2320 patients were included. The mean age was 79 years, and 49.8% were women. The overall 2-day mortality rate was 22.6% (376 deaths of patients with severe acute respiratory syndrome coronavirus 2 infection). The model included the following factors: age, location (rural location as a protective factor), institutionalization, desaturation, lung sounds (rhonchi), and altered mental status. The area under the receiver operating characteristic curve for death within 2 days was 0.763 (95% CI, 0.725-0.802;P < .001). Mortality in patients at high risk (more than 2.4 points on the scale) was 60%. Conclusions. This risk scale derived from information available to an emergency dispatch center is applicable to patients with suspected COVID-19. It can stratify patients by risk of early death (within 2 days), possibly helping with decision making regarding whether to transport from home or what means of transport to use, and destination.

Risk models for predicting in-hospital mortality from COVID-19 pneumonia in the elderly

Objective. To compare the prognostic value of 3 severity scales: the Pneumonia Severity Index (PSI), the CURB-65 pneumonia severity score, and the Severity Community-Acquired Pneumonia (SCAP) score. To build a new predictive model for in-hospital mortality in patients over the age of 75 years admitted with pneumonia due to the coronavirus disease 2019 (COVID-19). Methods. Retrospective study of patients older than 75 years admitted from the emergency department for COVID-19 pneumonia between March 12 and April 27, 2020. We recorded demographic (age, sex, living in a care facility or not), clinical (symptoms, comorbidities, Charlson Comorbidity Index [CCI]), and analytical (serum biochemistry, blood gases, blood count, and coagulation factors) variables. A risk model was constructed, and the ability of the 3 scales to predict all-cause in-hospital mortality was compared. Results. We included 186 patients with a median age of 85 years (interquartile range, 80-89 years);44.1% were men. Mortality was 47.3%. The areas under the receiver operating characteristic curves (AUCs) were as follows for each tool: PSI, 0.74 (95% CI, 0.64-0.82);CURB-65 score, 0.71 (95% CI, 0.62-0.79);and SCAP score, 0.72 (95% CI, 0.63-0.81). Risk factors included in the model were the presence or absence of symptoms (cough, dyspnea), the CCI, and analytical findings (aspartate aminotransferase, potassium, urea, and lactate dehydrogenase. The AUC for the model was 0.81 (95% CI, 0.73-0.88). Conclusions. This study shows that the predictive power of the PSI for mortality is moderate and perceptibly higher than the CURB-65 and SCAP scores. We propose a new predictive model for mortality that offers significantly better performance than any of the 3 scales compared. However, our model must undergo external validation.

[Analysis of the demand for detection of SARSCoV-2 in a health area of Spain]. / Análisis de la demanda de detección de SARS-CoV-2 en un área de salud de España.

OBJECTIVE: Since the discovery of the SARS-CoV-2 virus, the polymerase chain reaction technique (RT-PCR) has become the fundamental method for diagnosing the disease in its acute phase. The objective is to describe the demand-based series of RT-PCR determinations received at a Microbiology Service at a third-level reference hospital for a health area for three months spanning from the onset of the epidemic by SARS-CoV-2. METHODS: A retrospective analysis of the total of the RT-PCR requested in the Microbiology Service analyzed from 02/25/2020 to 05/26/2020 (90 days) has been carried out. They have been grouped by epidemiological weeks and by the petitioner service. A descriptive analysis was carried out by age, gender and number of requests for each patient. In the tests carried out, a confidence level of 95% (p <0.05) was considered significant. RESULTS: A total of 27,106 requests was received corresponding to 22,037 patients. Median age 53.7 (RIC 40.9-71.7) years, women: 61.3%. Proportion of patients with any positive RT-PCR: 14%. Of the total requests for RT-PCR, positive 3,710. Week 13 had the highest diagnosis performance (39.0%). The primary care has been the service thar has made the most requests (15,953). Patients with 3 or more RT-PCR: 565, of them, 19 patients had a positive result after previously having a negative one. CONCLUSIONS: Requests have been increasing depending on the evolution of the epidemic. The RT-PCR has a high diagnostic performance in the phases of highest contagiousness and / or transmissibility of the virus.