Lung ultrasound performed by primary care physicians as a prognostic and diagnostic tool in COVID-19 patients

Lung ultrasound performed by primary care physicians as a prognostic and diagnostic tool in COVID-19 patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Lung ultrasound performed by primary care physicians as a prognostic and diagnostic tool in COVID-19 patients Bernardino Oliva-Fanlo, Magdalena Esteva-Cantó, José Ignacio Ramírez-Manent, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7640052/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Apr, 2026 Read the published version in npj Primary Care Respiratory Medicine → Version 1 posted 10 You are reading this latest preprint version Abstract Objective To assess the value of abnormal findings of lung POCUS performed by PCPs in patients with SARS-CoV-2 virus infection confined at home in predicting hospitalisations, intensive care admissions, and mortality. Additionally, this study aims to assess the validity of lung POCUS performed by PCPs for FIGURECOVID pneumonia diagnosis. Methods This prospective observational study, conducted in Mallorca and Salamanca, Spain, between January and December 2021, assessed 624 consecutive adult patients (mean age 52.5 ± 18.3 years; 45.7% female) with confirmed SARS-CoV-2 infection and worsening symptoms via home visits or community health centres. Eight primary care physicians received a standardised 5-hour training in lung POCUS. Examinations followed a 12-zone protocol, and POCUS was considered positive if at least one abnormality - ≥ 3 B-lines, subpleural consolidation, or lobar consolidation - was present. Patients were followed for 30 days to confirm pneumonia diagnosis via chest X-ray, CT scan, or inpatient records and to record hospital referral, hospitalisation, ICU admission, and death. Results Abnormal POCUS findings were observed in 58.8% of patients, of whom 50.3% presented pleural line abnormalities, 27.6% subpleural consolidations, and 3.4% lobar consolidations. Patients with positive POCUS were referred to the hospital more frequently than those with negative findings (72.4% vs. 22.8%; OR = 8.83). They also had higher rates of hospitalisation (54.3% vs. 31.7%; OR = 2.57) and mortality (4.3% vs. 0.8%; OR = 5.52), while ICU admission did not differ significantly. For the diagnosis of COVID-19 pneumonia, overall POCUS sensitivity was 68.3%, specificity 43.6%, positive predictive value 78.7%, and negative predictive value 31.1%. Conclusions Lung POCUS performed by primary care physicians demonstrates acceptable prognostic utility for COVID-19 patients in community settings; however, it has limited diagnostic accuracy compared with chest radiography. These findings support its use in resource-limited environments and highlight the need for standardised scanning protocols and training. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Signs and symptoms Figures Figure 1 Figure 2 Background The COVID-19 pandemic meant a major challenge for healthcare services worldwide, requiring them to adapt their services to the urgent needs of these patients. COVID-19 has a highly variable course, ranging from asymptomatic to extremely severe and often fatal. Many nearly asymptomatic or mildly symptomatic patients developed after 5–8 days viral pneumonia with hypoxemia and pulmonary infiltrates that led to hospitalization in 14% of the patients and acute respiratory distress syndrome in 12% of hospitalised patients 1 – 3 . Early in the outbreak, studies suggested that lung ultrasound (LUS) could be a valuable tool for predicting the probability of clinical worsening of COVID-19, defined as the deterioration of several disease severity markers or other outcomes, such as hospitalization, intensive inpatient care, or death. The results of these studies demonstrate consistency in supporting the use of LUS as a prognostic tool for patients with COVID-19, despite the diversity of the population and the variability in LUS measurements and scores. Most of these studies have been conducted in hospital wards 4 – 7 or emergency departments 8 – 10 . However, very few studies have assessed the value of lung point-of-care ultrasound (POCUS) in patients with suspected or confirmed COVID-19 in primary care settings 11 , 12 . In the last decade, Spain has adopted POCUS as an imaging tool at the patient's bedside with the goal of improving primary care's resolution capability. Additionally, primary care physicians' (PCPs) training in lung POCUS had a significant boost with the COVID-19 pandemic 13 , 14 . In this context, it is necessary to get evidence to support the use of lung POCUS by PCPs to follow up patients with mild to moderate symptoms of SARS-CoV-2 infection in the community. Such evidence might lessen treatment uncertainty for patients, aid in the early detection of lung involvement, and prevent referring patients with minimal potential benefit, thereby alleviating stress on hospital emergency departments. The most common approach for diagnosing pneumonia involves a combination of plain chest X-rays, clinical findings, and symptomatology. Nonetheless, chest X-rays have demonstrated limited sensitivity for this purpose 15 , 16 . Although chest CT scans are more sensitive, they have drawbacks in terms of cost, accessibility, and radiation exposure. Furthermore, the requirement to transport the patient to a radiology centre for an imaging test was an additional restriction on its use in the context of COVID-19, given the uncertainty and lack of knowledge surrounding the situation, which encouraged limiting visits to hospitals and health centres as much as possible to avoid contagion 17 . Prior to the COVID-19 pandemic, several studies found LUS to be more sensitive than chest X-rays in diagnosing pneumonia 18 . LUS was already considered for the diagnosis of pneumonia in emergency medicine 19 and paediatrics 20 . LUS offers good repeatability across operators with varying degrees of experience between them 21 . Sonographic findings associated with COVID-19 pneumonia (anomalies in the pleural line thickness, focal, multifocal, and merging B-lines, and consolidations with sporadic mobile air bronchograms) are comparable to those reported in patients diagnosed with pneumonia prior to the COVID-19 pandemic 22 – 24 . A recent systematic review and meta-analysis has indicated that LUS has a sensitivity of 87.2% and a specificity of 69.5% for the diagnosis of COVID-19 pneumonia in high-prevalence settings 25 . LUS is more sensitive (97.6%) than chest X-ray (69.9%) in identifying COVID-19 pneumonia 26 and has a diagnostic accuracy equivalent to chest CT for COVID-19 pneumonia 27 . Several LUS protocols have been developed for scanning zones 6, 8, 12, or 14. Nevertheless, there are few studies assessing the diagnostic accuracy of lung POCUS in COVID-19 patients with suspected pneumonia visited in primary care. Two retrospective studies found sensitivity values ranging from 82% to 93% in primary care, comparable to those obtained in hospital settings. 28,29 The only prospective study on the diagnostic value of lung POCUS for the diagnosis of COVID-19 pneumonia found a sensitivity of 87.8% and a specificity of 58.5% using the radiologist's report of the chest X-ray as the reference test 30 . 30 The main objective of this study is to assess the value of abnormal findings of lung POCUS performed by PCPs in patients with SARS-CoV-2 virus infection confined at home in predicting hospitalizations, intensive care admissions, and mortality. Additionally, this study aims to assess the validity of lung POCUS performed by PCPs for COVID pneumonia diagnosis. Methods Study design and setting Our study is a prospective observational study conducted on the island of Majorca and in the Salamanca region (Spain) by specific units dedicated to attending COVID-19 patients. In Majorca, the study was carried out by the ‘UVACs’ (COVID-19 Mobile Care Units). These units, comprising PCPs, nurses, and health technicians, attended to patients with confirmed or suspected COVID-19 at home. In Salamanca, the study was conducted at the so-called 'Point Covid’, a community health centre where PCPs and primary care nurses attended patients with confirmed or suspected COVID-19. We included all consecutive patients over 18 years old who attended both units between January and December 2021, with a positive SARS-CoV-2 test whose symptoms had worsened in previous days. Symptoms may include high fever, generalized malaise, persistent cough, dyspnoea, or digestive symptoms. Patients were excluded if they were not in good condition to sign informed consent. In the first visit, the doctor validated the inclusion and exclusion criteria, explained the study, and required signed consent. If the patient accepted, the PCP performed a lung POCUS, and the nurse measured the clinical parameters. The UProbe-C5PL (Sonostar, Guangzhou, China) portable ultrasound device was used for examinations performed at patients’ homes by the Majorcan 'UVACs', and the Versana Premier (GE HealthCare, Chicago, USA) was used for examinations at the 'Point Covid' in Salamanca. Lung POCUS was performed according to the 12-area method 31 , 32 . The eight participating physicians received a 5-hour training course in lung ultrasound before participating in the COVID-19 community Units. Patients were followed up for up to 30 days after the index visit to confirm the pneumonia diagnosis. Variables Sociodemographic data (age, sex), clinical data (days of evolution, temperature, pulse oximetry, respiratory rate, and heart rate), and ultrasound findings (B-lines, subpleural consolidations, and lobar consolidations) were registered at the index visit. Hospital referrals or follow-up at home were also recorded. Ultrasound was considered positive for COVID-19 pneumonia when the patient had a positive SARS-CoV-2 test and at least one of the following lung POCUS alterations: more than 3 B-lines, subpleural consolidations and lobar consolidation. Lung POCUS findings were not the only reason for the patient's further management. PCPs probably decided to refer patients, considering the clinical situation, family and social support, and the possibility of isolation at the patient's home. Subsequently, 30 days after the index visit, an independent data manager collected pneumonia diagnosis either in chest X-ray reports, CT scan reports, or inpatient electronic medical records. Furthermore, hospitalization, ICU admission and patient death were recorded, as well as the realization and results of chest X-ray and/or chest CT scan. Analysis We performed a descriptive analysis of all selected variables to describe sample characteristics. A bivariate analysis was conducted comparing the presence of lung POCUS findings with the baseline characteristics of the patients. We used the chi-square test for categorical variables and the Student’s T-test for continuous variables. Odds ratios and 95% CI were calculated. A multivariate logistic regression analysis was done to assess the independent relationships between the variables and the lung POCUS findings using the backward stepwise method. Variables with p ≤ 0.20 were included in the model. We assessed changes in the coefficients at each step to detect confusion and tested interactions. Due to the small numbers, we created a composite outcome with ICU admission and/or death. Sensitivity, specificity, positive and negative predictive values (PPVs, NPVs), and positive and negative likelihood ratios (LR+, LR −) were calculated for the overall lung POCUS findings and for each of them independently. We considered true positive cases of those patients with positive ultrasound findings for pneumonia, in which, after a hospital contact, pneumonia was confirmed either with X-ray or CT-scan after 30 days of the index visit. False positive cases were those with ultrasound positive findings for pneumonia that were not confirmed in the hospital through X-ray or CT-scan after 30 days of the index visit. We considered true negatives for those patients with negative ultrasound findings for pneumonia and no verified pneumonia through X-ray or CT scan after 30 days of the index visit. Finally, false negative cases were defined as patients without ultrasound findings for pneumonia who were confirmed to have pneumonia through chest X-ray or CT scan after 30 days of the index visit. SPSS software version 26 was used. Results During the period of the study, 624 patients were included, 527 by the Majorcan COVID-19 Mobile Care Units and 97 at the COVID-Point in Salamanca. The flowchart of patients included is shown in Fig. 1. Baseline characteristics of patients included in the study are presented in Table 1 . The mean age was 52.5 years (SD = 18.3), and 45.7% of them were female. The mean number of days from the beginning of symptoms until POCUS was performed was 7.2 (SD = 4.3), and 5.3 days (SD = 4.1) since a positive SARS-CoV-2 result was reported. Out of the 624 patients, 8.9% had a temperature higher than 38ºC, 22.5% had pulse oximetry readings of peripheral oxygen saturation (SpO2) lower than 93%, 34.3% had tachypnoea, and 22.1% had tachycardia. Table 1: Baseline characteristics Total sample 624 N, % Age (mean ± SD) (623) 52.5 ± 18.3 years Age ≤ 50 years 299/623 (48.0) > 50 years 324/623 (52.0) Sex Female 285/624 (45.7) Male 339/624 (54.3) Days since symptoms until POCUS (mean ± SD) (605) 7.2 ± 4.3 Days since COVID diagnosis until POCUS (mean ± SD) 5.3 ± 4.1 Temperature ºC (mean ± SD) (496) 36.6 ± 0.82 Temperature ºC < 37ºC 347/496 (70.0) 37.0-37.9ºC 105/496 (21.2) ≥ 38.0ºC 44/496 (8.9%) Pulse oximetry (mean ± SD) (623) 95.1 ± 4.3 Pulse oximetry 20 bpm 188/548 (34.3%) Cardiac rate bpm (mean ± SD) (615) 88.6 ± 16.0 Cardiac rate ≤ 100 bpm 479/615 (77.9) > 100 bpm 136/615 (22.1) POCUS findings Pleural line abnormalities 314/624 (50.3) Sub-pleural consolidation 172/624 (27.6) Lobar consolidation 21/624 (3.4) POCUS positive findings for pneumonia 367/624 (58.8) GP decision-making Referral to the hospital 323/620 (52.1) Home care 297/620 (47.9) Regarding lung POCUS findings, 367 patients (58.8%) had positive findings for pneumonia (Table 2 ). The most common findings were the presence of three or more B-lines with pleural line abnormalities (50.3%), followed by sub-pleural condensation (27.6%) and lobar condensation (3.4%). Patients with positive lung POCUS findings were older and had a longer interval between COVID-19 diagnosis and POCUS performance. Moreover, these patients had higher body temperature, lower pulse oximetry values, and higher respiratory and cardiac rates. Some comorbidities were more prevalent among patients with abnormal lung POCUS findings compared to patients without suspicious lung POCUS findings, like hypertension, type 2 diabetes, anxiety, chronic obstructive pulmonary disease, and heart failure. There were no differences in thyroid diseases, asthma, depression, cardiac arrhythmias, or ischemic heart disease. Table 2 Comparative findings in patients with positive POCUS findings versus negative POCUS findings Positive POCUS findings 367/624 (58.8%) N (%) Negative POCUS findings 257/624 (41.2%) N (%) p-value Age (mean ± SD) 55.8 ± 17.6 years 47.9 ± 18.4 years 0.00 Age ≤ 50 years 147/366 (40.2) 152/257 (59.1) 0.00 > 50 years 219/366 (59.8) 105/257 (40.9) Sex Female 188/367 (51.2) 151/257 (58.8) 0.07 Male 179/367 (48.8) 106/257 (41.2) Days since symptoms until POCUS (mean ± SD) 7.25 ± 4.2days 7.1 ± 4.4 0.60 Days since COVID diagnosis until POCUS (mean ± SD) 5.4 ± 3.8 days 5.2 ± 4.6 0.01 Temperature ºC (mean ± SD) 36.7 ± 0.9 ºC 36.4 ± 0.7 0.00 Temperature < 37ºC 194/304 (63.9) 153/192 (79.7) 0.00 37.0-37.9ºC 72/304 (23.7) 33/192 (17.2) ≥ 38.0ºC 38/304 (12.5) 6/192 (3.1) Pulse oximetry (mean ± SD) 93.9 ± 5.0% 96.7 ± 2.0% 0.00 Pulse oximetry 20 bpm 143/331 (43.2) 45/217 (20.7) Cardiac rate bpm (mean ± SD) 89.7 ± 16.4 bpm 87.0 ± 15.1 0.04 Cardiac rate ≤ 100 bpm 271/364 (74.5) 208/251 (82.9) 0.01 > 100 bpm 93/364 (25.5) 43/251 (17.1) Comorbidities High blood pressure 118/347 (34.0) 50/247 (20.2) 0.00 Type 2 Diabetes 61/347 (17.6) 20/247 (8.1) 0.01 Anxiety 24/347 (6.9) 30/247 (12.1) 0.03 Thyroid disorders 30/347 (8.6) 23/247 (9.3) 0.77 Asthma 20/347 (5.8) 25/247 (10.1) 0.06 COPD 27/347 (7.8) 5/247 (2.0) 0.01 Heart failure 23/347 (6.6) 7/247 (2.8) 0.04 Arrythmias 17/347 (4.9) 12/247 (4.9) 1.00 Depression 17/347 (4.9) 13/247 (5.3 0.85 Ischemic heart disease 18/347 (5.2) 7/247 (2.8%) 0.21 Outcomes GP Decision making Referral 265/366 (72.4) 58/254 (22.8) 0.00 Home care 101/366 (27.6) 196/254 (77.2) Hospitalised 188/346 (54.3) 78/247 (31.7) 0.00 Intensive care 25/347 (7.2) 9/247 (3.6) 0.07 Death 15/347 (4.3) 2/247 (0.8) 0.01 About PCPs' decision-making and patient prognosis, patients with abnormal lung POCUS findings were more frequently referred to the hospital than patients with normal lung POCUS findings (72.4% vs 22.8%; OR = 8.83, IC95%:6.11–12.88). Furthermore, patients with positive lung POCUS findings of suspected pneumonia were more frequently admitted to the hospital (54.3% vs 31.7%; OR = 2.57, IC95%:1.83–3.66) and died because of the process (4.3% vs 0.8%; OR = 5.52, IC95%:1.43–35.99) during the month following the POCUS. No statistical differences were observed between the two groups with respect to patient admission to the intensive care unit. In the multivariate analysis (Fig. 2) abnormal POCUS is again associated with hospitalisation independently of age and other clinical variables as pulse oximetry < 93%, hypertension or diabetes. Regarding the composite indicator of ICU admission and/or death, we could not find any association with abnormal POCUS findings, but with cardiac failure and pulse oximetry results. The pneumonia diagnosis could be determined through chest X-ray in 381 patients (Table 3 ). The overall sensitivity of lung POCUS for the diagnosis of COVID-19 pneumonia was 68.3%, and the specificity was 43.6%. The positive predictive value (PPV) was 78.7%. The better values of the individual findings associated with pneumonia were a sensitivity of 64.9%, a PPV of 80.4% and a positive likelihood ratio (LR+) of 4.1 for the presence of at least 3 B-lines, and a specificity of 89.1% for lobar consolidation. Table 3 POCUS estimated sensitivity and specificity for pneumonia in COVID-19 patients Prevalence % (95% CI) Sensitivity % (95% CI) Specificity % (95% CI) PPV % (95% CI) NPV % (95% CI) LR+ (95% CI) LR- (95% CI) Overall (381) 75.3% (70.6%-79.5%) 68.3% (62.5%-73.6%) 43.6% (33.5%-54.2%) 78.7% (73.0%-83.5%) 31.1% (23.5%-39.8%) 1.21 (0.99–1.47) 0.73 (0.6–0.89) POCUS findings Lobar consolidation (146) 68.5% (60.2%-75.8%) 9.0% (4.5%-16.8%) 89.1% (75.6%-95.9%) 64.3% (35.6%-86.0%) 31.1% (23.5%-39.8%) 0.83 (0.06–11.08) 1.02 (0.99–1.05) Sub-pleural consolidation (252) 73.4% (67.4%-78.7%) 50.8% (43.4%-58.2%) 61.2% (48.5%-72.6%) 78.3% (69.7%-85.1%) 31.1% (23.5%-39.8%) 1.31 (1.09–1.44) 0.8 (0.76–0.85) Pleural lines abnormalities (341) 76.0% (70.1%-80.3%) 64.9% (58.7%-70.6%) 50.0% (38.8%-61.2%) 80.4% (74.2%-85.4%) 31.1% (23.5%-39.8%) 1.3 (1.23–1.37) 0.7 (0.66–0.75) Discussion This study is one of the few studies conducted in primary care to assess the predictive value of lung POCUS for adverse events in COVID-19 patients. The study shows an acceptable value for lung POCUS findings, performed by PCPs in a primary care health centre or in the patient's home, for the prognosis of COVID-19 patients. The most common findings on lung POCUS were the presence of three or more B-lines with pleural line abnormalities (50.3%), followed by subpleural condensation (27.6%) and lobar condensation (3.4%). Patients with positive lung POCUS findings were more frequently referred to a hospital emergency department, and the risk of being admitted to the hospital was twofold more frequent than those without lung involvement. The likelihood that their illness would turn out to be fatal was higher in univariate analysis but not confirmed in multivariate analysis. We have also observed that lung POCUS is independently associated with SpO2 and certain comorbidities in predicting hospitalization. The results reveal a limited diagnostic value for COVID-19 pneumonia compared to chest X-rays. Previous studies conducted in hospital settings have shown good prognostic performance of lung POCUS performed on patients with SARS-CoV-2 infection. Studies with hospitalised patients found a significant positive correlation between LUS findings and several markers of disease severity, including C-reactive protein 5 , 9 , 33 , ferritin 33 , D-dimer, hypersensitive troponin I, creatine kinase muscle-brain 5 , lactate dehydrogenase, and fibrinogen 9 . LUS findings have also been associated with an elevated risk of intensive care unit admission and death in several studies 4 – 9 , 34 , 35 , while others, probably due to small sample size, did not find this association 33 . When comparing the two studies performed in a primary care environment, we found that their results correlate well with the findings in our study in terms of hospitalisation risk and ultrasound findings. Calvo-Cebrian et al. observed an association between the severity of lung POCUS findings and the appropriateness of referral to the hospital emergency department, defining appropriateness as the referral that benefits patients in terms of hospital admission or prescription of a specific treatment 11 . Another study carried out in a health centre in Catalonia showed that evolutionary patterns, diffuse, attenuated diffuse, and unilateral predominant interstitial patterns represented risk factors for hospitalization 12 . These two studies have some differences from ours. Our patients had SARS-CoV-2 infection confirmed by RT-PCR, whereas the Calvo et al. study only includes patients with suspected infection, and the Martinez et al. study includes patients with and without laboratory confirmation. Furthermore, there are notable variations in the expertise of the medical professionals who conducted the ultrasounds. In Martínez's study, all ultrasounds were performed by a single doctor who was an expert in ultrasound. In Calvo's study, however, five experts participated. Our research was conducted in two distinct regions, with the involvement of a range of medical professionals with varying degrees of experience. The lung POCUS sensitivity for the diagnosis of pneumonia in COVID-19 patients is comparable to that achieved by chest X-ray compared with CT scan in COVID-19 26 and non-COVID-19 patients 18 . The positive likelihood ratio is also similar to the LR + of lung POCUS for the diagnosis of pneumonia in primary care, disregarding the causal agent 30 . The diagnostic value of lung POCUS in this study is lower than the results achieved in previous studies, both in the hospital and emergency department 27 , 36 – 38 and in primary care 12 , 28 . Several circumstances may partly explain the differences found. Several meta-analyses conducted before and after the pandemic show high variability in the way the outcome of pneumonia is defined. 19,25 Some studies define the outcome according to the result of the PCR performed, with or without the opinion of a multidisciplinary team 27 , 28 , 36 , 38 . Other studies compare lung POCUS with hospital admission and certain clinical findings in patients 12 . Few studies used CT scans as the gold standard diagnostic test 18 , 39 , and in some studies, CT scans were only performed in patients with abnormalities on lung POCUS or chest X-ray 26 . In our study, all patients had a positive RT-PCR at the time of enrolment, and all but one of the patients included in the diagnostic validation analysis received a chest X-ray. Only 31 had a CT scan. Strengths and limitations The prospective design of this study facilitates accurate and comprehensive data collection, thereby minimizing recall and selection biases. The sample size of this study is the largest among studies on the diagnosis of COVID-19 using lung POCUS in a primary care setting. The use of POCUS in primary care has experienced a surge in recent years and evaluating its diagnostic value in conditions as close to real-life scenarios as possible, including patients visited in their own homes, is of paramount importance. Our patients have fewer comorbidities than those in previous studies conducted in hospital departments 10 , 33 , 35 , 40 . These differences could be explained by the fact that patients in primary care generally present less severe symptoms and fewer concomitant diseases than those attended in hospitals. In this sense, 58% of our patients had POCUS abnormal findings, compared with 81% in patients in emergency departments 33 , and 91–96% in studies done in hospital wards. 8,34 In any case, studies conducted in primary care do not document the presence of comorbidities. This limitation hinders the capacity to undertake direct comparisons. The same applies to the clinical signs recorded. Studies that collect data such as heart rate, respiratory rate, SpO2, and temperature show variable results, although, in general, their patients present a worse clinical situation than ours 10 , 35 , 41 . Our study was unable to use CT scan as a gold standard due to the circumstances at the time of the study, when its use was restricted as much as possible. Despite the existence of previous recommendations for the use of lung POCUS 42 , there is a high variability in different aspects of the methodology used. The findings to be considered, the number of zones scanned, and the competency of LUS examiners remain undefined 22 , 23 . The most common recommendations were adopted, including the findings to be considered and the 12-zone protocol. The 12-zone protocol has the advantage of being more specific and thus provides a general impression of lung compromise 31 . B-lines, the ultrasound most frequently observed sign in cases of COVID-19 pneumonia, have been identified in a range of other lung conditions, including pulmonary oedema of various aetiologies (e.g. heart failure), diffuse parenchymal lung disease (pulmonary fibrosis), lymphangitic neoplastic dissemination, and ARDS (adult respiratory distress syndrome) 42 . Training time in lung POCUS also needs to be addressed. PCPs who participated in the study received a short 5-hour training due to the urgency in assessing COVID-19 patients with worsening symptoms in the community. Although basic ultrasound image acquisition and interpretation skills can be learned by physicians of varying experience after a brief training course 43 , there is a lack of clear guidelines for LUS training and certification 44 . A consensus of 28 experts considered that LUS has a steep learning curve in the evaluation of interstitial syndrome 38 . Other authors have proposed at least 10–25 LUS scans supervised by experts to acquire sufficient competence 45 . A study on the use of LUS in the diagnosis of pneumonia in children found significant differences in performance between novice and LUS-experienced professionals 20 . Nevertheless, even among LUS experts, the levels of inter- and intra-observer agreement tend to be moderate, with higher disagreement specifically in findings related to COVID-19 pneumonia, like pleural thickening and B-lines 46 . The use of mobile devices for performing and registering POCUS can be considered both as a strength and as a limitation. A strength because mobile devices allow POCUS outside health centres, and a limitation due to the possible discrepancy in performance between portable ultrasound scanners and the high-end devices available in healthcare centres. A systematic review on this topic found that portable devices demonstrated comparable performance to high-end devices in specific domains, such as the detection of ascites, hydronephrosis, screening for abdominal aortic aneurysms, and care of obstetric and gynaecological patients 47 . Nonetheless, the review determined that there remained a paucity of evidence to support the utilization of portable devices in the abdominal or pleural regions. In conclusion, this study indicates that lung POCUS performed by PCPs in primary care settings or at the patient's home offers acceptable prognostic utility for patients with COVID-19, although its diagnostic value for COVID-19 pneumonia compared to chest X-ray appears to be limited. These findings may be of interest in settings with limited access to radiology, whether due to availability or distance. They may also be of interest to home-based patients whose mobility is compromised for one reason or another. Furthermore, the findings presented here emphasise the importance of the development of standardised guidelines and highlight the relevance of achieving consensus on lung ultrasound scanning methodology, as well as on the training requirements for PCPs. This standardisation work will help to ensure the reliable use of lung POCUS in primary care settings. Moreover, further research is necessary to evaluate the role of lung POCUS in diagnosing pneumonia of any aetiology in primary care. Declarations Competing interests All authors declare no financial or non-financial competing interests. Ethics This study obtained the approval of the Balearic Islands (IB 4530/21 PI) and the Salamanca (PI-2021-10881) Research Ethics Committees. Funding This study has been funded by Instituto de Salud Carlos III (ISCIII) through the project "PI21/01521" and co-funded by the European Union, and Primary Care and Health Promotion Network (RICAPPS) RD21/0016/0009, co-financed by Next Generation (EU) funds from the Recovery and Resilience Mechanism. Author Contribution ME, JIRM, JC, CG, AM, and AA conceptualised the study. JC and AA participated in training PCPs. ME, CG, AM, JIRM, and AA designed the research. ME, CG, AM, and OB coordinated data acquisition and information management. OB performed the statistical analysis. BO, OB, and ME wrote the main manuscript text and prepared all the figures and tables . All authors reviewed and edited all draft versions and the final one and approved it for submission. Acknowledgement We want to thank the healthcare professionals (doctors, nurses, and healthcare technicians) who collaborated in carrying out this study, as well as the patients and caregivers who gave their consent to use their data in those challenging times. Data Availability Data are available upon request to Oana Bulilete at [ [email protected] ]on reasonable request. References Huang, C. et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet 395, 497–506 (2020). Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). https://www.who.int/publications/i/item/report-of-the-who-china-joint-mission-on-coronavirus-disease-2019-(covid-19 ). Stokes, E. K. Coronavirus Disease 2019 Case Surveillance — United States, January 22–May 30, 2020. MMWR Morb. Mortal. Wkly. Rep. 69, (2020). Fuchs, L. et al. 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Lung ultrasound as diagnostic tool for SARS-CoV-2 infection. Intern. Emerg. Med. 16, 471–476 (2021). Brahier, D. T. et al. Lung ultrasonography for risk stratification in patients with COVID-19: a prospective observational cohort study. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. (2021) doi: 10.1093/cid/ciaa1408 . Calvo-Cebrián, A., Alonso‐Roca, R., Rodriguez‐Contreras, F. J., Rodríguez‐Pascual, M. N. & Calderín-Morales, M. P. Usefulness of Lung Ultrasound Examinations Performed by Primary Care Physicians in Patients With Suspected COVID ‐19. J. Ultrasound Med. 40, 741–750 (2021). Martínez-Redondo, J. et al. The Risk of Hospitalization in COVID-19 Patients Can Be Predicted by Lung Ultrasound in Primary Care. Int. J. Environ. Res. Public. Health 18, 6083 (2021). Conangla-Ferrin, L. et al. Ultrasound in primary care: Consensus recommendations on its applications and training. Results of a 3-round Delphi study. Eur. J. Gen. Pract. 28, 253–259 (2022). Diaz Sánchez, S. et al. Utilidad y fiabilidad de la ecografía clínica en Medicina Familiar: ecocardioscopia y ecografía pulmonar. Aten. Primaria 51, 172–183 (2019). Hagaman, J. T., Panos, R. J., Rouan, G. W. & Shipley, R. T. Admission Chest Radiograph Lacks Sensitivity in the Diagnosis of Community-Acquired Pneumonia. Am. J. Med. Sci. 337, 236–240 (2009). Hayden, G. E. & Wrenn, K. W. Chest Radiograph vs. Computed Tomography Scan in the Evaluation for Pneumonia. J. Emerg. Med. 36, 266–270 (2009). Raptis, C. A. et al. Chest CT and Coronavirus Disease (COVID-19): A Critical Review of the Literature to Date. Am. J. Roentgenol. 215, 839–842 (2020). Liu, X., Lian, R., Tao, Y., Gu, C. & Zhang, G. Lung ultrasonography: an effective way to diagnose community-acquired pneumonia. Emerg. Med. J. 32, 433–438 (2015). Staub, L. J., Mazzali Biscaro, R. R., Kaszubowski, E. & Maurici, R. Lung Ultrasound for the Emergency Diagnosis of Pneumonia, Acute Heart Failure, and Exacerbations of Chronic Obstructive Pulmonary Disease/Asthma in Adults: A Systematic Review and Meta-analysis. J. Emerg. Med. 56, 53–69 (2019). Tsou, P.-Y. et al. Diagnostic Accuracy of Lung Ultrasound Performed by Novice Versus Advanced Sonographers for Pneumonia in Children: A Systematic Review and Meta-analysis. Acad. Emerg. Med. 26, 1074–1088 (2019). De Molo, C. et al. Interoperator Reliability of Lung Ultrasound during the COVID-19 Pandemic. Ultraschall Med. - Eur. J. Ultrasound 44, 75–80 (2023). Gil-Rodríguez, J. et al. Ultrasound findings of lung ultrasonography in COVID-19: A systematic review. Eur. J. Radiol. 148, 110156 (2022). Kameda, T., Mizuma, Y., Taniguchi, H., Fujita, M. & Taniguchi, N. Point-of-care lung ultrasound for the assessment of pneumonia: a narrative review in the COVID-19 era. J. Med. Ultrason. 48, 31–43 (2021). Mohamed, M. F. H. et al. Frequency of Abnormalities Detected by Point-of-Care Lung Ultrasound in Symptomatic COVID-19 Patients: Systematic Review and Meta-Analysis. Am. J. Trop. Med. Hyg. 103, 815–821 (2020). Matthies, A., Trauer, M., Chopra, K. & Jarman, R. D. Diagnostic accuracy of point-of-care lung ultrasound for COVID-19: a systematic review and meta-analysis. Emerg. Med. J. 40, 407–417 (2023). Gibbons, R. C. et al. Lung Ultrasound vs. Chest X-Ray Study for the Radiographic Diagnosis of COVID-19 Pneumonia in a High-Prevalence Population. J. Emerg. Med. 60, 615–625 (2021). Lieveld, A. W. E. et al. Diagnosing COVID-19 pneumonia in a pandemic setting: Lung Ultrasound versus CT – a multicentre, prospective, observational study. ERJ Open Res. 6, 00539–02020 (2020). Guzmán-García, M. B. et al. Lung Ultrasound as a Triage Method in Primary Care for Patients with Suspected SARS-CoV-2 Pneumonia. J. Clin. Med. 11, 6420 (2022). Martínez Redondo, J. et al. Higher Accuracy of Lung Ultrasound over Chest X-ray for Early Diagnosis of COVID-19 Pneumonia. Int. J. Environ. Res. Public. Health 18, 3481 (2021). Rodríguez-Contreras, F. J. et al. Lung Ultrasound Performed by Primary Care Physicians for Clinically Suspected Community-Acquired Pneumonia: A Multicenter Prospective Study. Ann. Fam. Med. 20, 227–236 (2022). Kok, B. et al. Comparing lung ultrasound: extensive versus short in COVID-19 (CLUES): a multicentre, observational study at the emergency department. BMJ Open 11, e048795 (2021). Via, G. et al. Lung ultrasound in the ICU: from diagnostic instrument to respiratory monitoring tool. Minerva Anestesiol. 78, 1282–1296 (2012). Espersen, C. et al. Lung Ultrasound Findings Associated With COVID-19 ARDS, ICU Admission, and All-Cause Mortality. Respir. Care 67, 66–75 (2022). Casella, F. et al. Lung ultrasonography: A prognostic tool in non-ICU hospitalized patients with COVID-19 pneumonia. Eur. J. Intern. Med. 85, 34–40 (2021). Perrone, T. et al. A New Lung Ultrasound Protocol Able to Predict Worsening in Patients Affected by Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia. J. Ultrasound Med. 40, 1627–1635 (2021). Haak, S. L., Renken, I. J., Jager, L. C., Lameijer, H. & Van Der Kolk, B. (Britt) Y. Diagnostic accuracy of point-of-care lung ultrasound in COVID-19. Emerg. Med. J. 38, 94–99 (2021). Sorlini, C. et al. The role of lung ultrasound as a frontline diagnostic tool in the era of COVID-19 outbreak. Intern. Emerg. Med. 16, 749–756 (2021). Volpicelli, G. et al. Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study. Intensive Care Med. 47, 444–454 (2021). Buda, N. et al. Lung Ultrasound Examination in Patients with SARS-CoV-2 Infection: Multicenter Study. J. Clin. Med. 10, 3255 (2021). Boero, E. et al. The COVID-19 Worsening Score (COWS)-a predictive bedside tool for critical illness. Echocardiogr. Mt. Kisco N 38, 207–216 (2021). Espersen, C. et al. Lung ultrasound findings following COVID-19 hospitalization: A prospective longitudinal cohort study. Respir. Med. 197, 106826 (2022). Volpicelli, G. et al. International evidence-based recommendations for point-of-care lung ultrasound. Intensive Care Med. 38, 577–591 (2012). Yamada, T. et al. Skills acquisition for novice learners after a point-of-care ultrasound course: does clinical rank matter? BMC Med. Educ. 18, 202 (2018). Pietersen, P. I. et al. Lung ultrasound training: a systematic review of published literature in clinical lung ultrasound training. Crit. Ultrasound J. 10, 23 (2018). Blazic, I. et al. The use of lung ultrasound in COVID-19. ERJ Open Res. 9, 00196–02022 (2023). Lerchbaumer, M. H. et al. Point-of-care lung ultrasound in COVID-19 patients: inter- and intra-observer agreement in a prospective observational study. Sci. Rep. 11, 10678 (2021). Rykkje, A., Carlsen, J. F. & Nielsen, M. B. Hand-Held Ultrasound Devices Compared with High-End Ultrasound Systems: A Systematic Review. Diagnostics 9, 61 (2019). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Apr, 2026 Read the published version in npj Primary Care Respiratory Medicine → Version 1 posted Editorial decision: Revision requested 06 Nov, 2025 Reviews received at journal 05 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviews received at journal 14 Oct, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 24 Sep, 2025 Reviewers invited by journal 23 Sep, 2025 Editor assigned by journal 17 Sep, 2025 Submission checks completed at journal 17 Sep, 2025 First submitted to journal 17 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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09:18:24","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":138803,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7640052/v1/2cbac898a1d16a731b3ff987.html"},{"id":92845289,"identity":"e58e9592-49dc-44c4-a298-0fb1ec0edf81","added_by":"auto","created_at":"2025-10-06 09:26:23","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88420,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7640052/v1/b0ee22f2b42239c301dc979a.jpeg"},{"id":92843425,"identity":"92f044b5-c048-43b6-b710-800c07b002d3","added_by":"auto","created_at":"2025-10-06 09:18:23","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":47898,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7640052/v1/8f3c4b93b353376610bb56fa.jpeg"},{"id":107928980,"identity":"a83fed3a-bbbc-48ab-8f3b-a715769ac599","added_by":"auto","created_at":"2026-04-27 16:13:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":574119,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7640052/v1/c5678ec2-6dbe-4dea-879a-ba4733eebde8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Lung ultrasound performed by primary care physicians as a prognostic and diagnostic tool in COVID-19 patients","fulltext":[{"header":"Background","content":"\u003cp\u003eThe COVID-19 pandemic meant a major challenge for healthcare services worldwide, requiring them to adapt their services to the urgent needs of these patients. COVID-19 has a highly variable course, ranging from asymptomatic to extremely severe and often fatal. Many nearly asymptomatic or mildly symptomatic patients developed after 5\u0026ndash;8 days viral pneumonia with hypoxemia and pulmonary infiltrates that led to hospitalization in 14% of the patients and acute respiratory distress syndrome in 12% of hospitalised patients \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEarly in the outbreak, studies suggested that lung ultrasound (LUS) could be a valuable tool for predicting the probability of clinical worsening of COVID-19, defined as the deterioration of several disease severity markers or other outcomes, such as hospitalization, intensive inpatient care, or death. The results of these studies demonstrate consistency in supporting the use of LUS as a prognostic tool for patients with COVID-19, despite the diversity of the population and the variability in LUS measurements and scores. Most of these studies have been conducted in hospital wards \u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e or emergency departments \u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, very few studies have assessed the value of lung point-of-care ultrasound (POCUS) in patients with suspected or confirmed COVID-19 in primary care settings \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In the last decade, Spain has adopted POCUS as an imaging tool at the patient's bedside with the goal of improving primary care's resolution capability. Additionally, primary care physicians' (PCPs) training in lung POCUS had a significant boost with the COVID-19 pandemic \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In this context, it is necessary to get evidence to support the use of lung POCUS by PCPs to follow up patients with mild to moderate symptoms of SARS-CoV-2 infection in the community. Such evidence might lessen treatment uncertainty for patients, aid in the early detection of lung involvement, and prevent referring patients with minimal potential benefit, thereby alleviating stress on hospital emergency departments.\u003c/p\u003e\u003cp\u003eThe most common approach for diagnosing pneumonia involves a combination of plain chest X-rays, clinical findings, and symptomatology. Nonetheless, chest X-rays have demonstrated limited sensitivity for this purpose \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Although chest CT scans are more sensitive, they have drawbacks in terms of cost, accessibility, and radiation exposure. Furthermore, the requirement to transport the patient to a radiology centre for an imaging test was an additional restriction on its use in the context of COVID-19, given the uncertainty and lack of knowledge surrounding the situation, which encouraged limiting visits to hospitals and health centres as much as possible to avoid contagion \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Prior to the COVID-19 pandemic, several studies found LUS to be more sensitive than chest X-rays in diagnosing pneumonia \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. LUS was already considered for the diagnosis of pneumonia in emergency medicine \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e and paediatrics \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. LUS offers good repeatability across operators with varying degrees of experience between them \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Sonographic findings associated with COVID-19 pneumonia (anomalies in the pleural line thickness, focal, multifocal, and merging B-lines, and consolidations with sporadic mobile air bronchograms) are comparable to those reported in patients diagnosed with pneumonia prior to the COVID-19 pandemic \u003csup\u003e\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. A recent systematic review and meta-analysis has indicated that LUS has a sensitivity of 87.2% and a specificity of 69.5% for the diagnosis of COVID-19 pneumonia in high-prevalence settings \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. LUS is more sensitive (97.6%) than chest X-ray (69.9%) in identifying COVID-19 pneumonia \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and has a diagnostic accuracy equivalent to chest CT for COVID-19 pneumonia \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Several LUS protocols have been developed for scanning zones 6, 8, 12, or 14.\u003c/p\u003e\u003cp\u003eNevertheless, there are few studies assessing the diagnostic accuracy of lung POCUS in COVID-19 patients with suspected pneumonia visited in primary care. Two retrospective studies found sensitivity values ranging from 82% to 93% in primary care, comparable to those obtained in hospital settings. \u003csup\u003e28,29\u003c/sup\u003e The only prospective study on the diagnostic value of lung POCUS for the diagnosis of COVID-19 pneumonia found a sensitivity of 87.8% and a specificity of 58.5% using the radiologist's report of the chest X-ray as the reference test\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. 30\u003c/p\u003e\u003cp\u003eThe main objective of this study is to assess the value of abnormal findings of lung POCUS performed by PCPs in patients with SARS-CoV-2 virus infection confined at home in predicting hospitalizations, intensive care admissions, and mortality. Additionally, this study aims to assess the validity of lung POCUS performed by PCPs for COVID pneumonia diagnosis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and setting\u003c/h2\u003e\u003cp\u003eOur study is a prospective observational study conducted on the island of Majorca and in the Salamanca region (Spain) by specific units dedicated to attending COVID-19 patients. In Majorca, the study was carried out by the \u0026lsquo;UVACs\u0026rsquo; (COVID-19 Mobile Care Units). These units, comprising PCPs, nurses, and health technicians, attended to patients with confirmed or suspected COVID-19 at home. In Salamanca, the study was conducted at the so-called 'Point Covid\u0026rsquo;, a community health centre where PCPs and primary care nurses attended patients with confirmed or suspected COVID-19.\u003c/p\u003e\u003cp\u003eWe included all consecutive patients over 18 years old who attended both units between January and December 2021, with a positive SARS-CoV-2 test whose symptoms had worsened in previous days. Symptoms may include high fever, generalized malaise, persistent cough, dyspnoea, or digestive symptoms. Patients were excluded if they were not in good condition to sign informed consent. In the first visit, the doctor validated the inclusion and exclusion criteria, explained the study, and required signed consent. If the patient accepted, the PCP performed a lung POCUS, and the nurse measured the clinical parameters. The UProbe-C5PL (Sonostar, Guangzhou, China) portable ultrasound device was used for examinations performed at patients\u0026rsquo; homes by the Majorcan 'UVACs', and the Versana Premier (GE HealthCare, Chicago, USA) was used for examinations at the 'Point Covid' in Salamanca. Lung POCUS was performed according to the 12-area method \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The eight participating physicians received a 5-hour training course in lung ultrasound before participating in the COVID-19 community Units. Patients were followed up for up to 30 days after the index visit to confirm the pneumonia diagnosis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eSociodemographic data (age, sex), clinical data (days of evolution, temperature, pulse oximetry, respiratory rate, and heart rate), and ultrasound findings (B-lines, subpleural consolidations, and lobar consolidations) were registered at the index visit. Hospital referrals or follow-up at home were also recorded. Ultrasound was considered positive for COVID-19 pneumonia when the patient had a positive SARS-CoV-2 test and at least one of the following lung POCUS alterations: more than 3 B-lines, subpleural consolidations and lobar consolidation. Lung POCUS findings were not the only reason for the patient's further management. PCPs probably decided to refer patients, considering the clinical situation, family and social support, and the possibility of isolation at the patient's home.\u003c/p\u003e\u003cp\u003eSubsequently, 30 days after the index visit, an independent data manager collected pneumonia diagnosis either in chest X-ray reports, CT scan reports, or inpatient electronic medical records. Furthermore, hospitalization, ICU admission and patient death were recorded, as well as the realization and results of chest X-ray and/or chest CT scan.\u003c/p\u003e\n\u003ch3\u003eAnalysis\u003c/h3\u003e\n\u003cp\u003eWe performed a descriptive analysis of all selected variables to describe sample characteristics. A bivariate analysis was conducted comparing the presence of lung POCUS findings with the baseline characteristics of the patients. We used the chi-square test for categorical variables and the Student\u0026rsquo;s T-test for continuous variables. Odds ratios and 95% CI were calculated. A multivariate logistic regression analysis was done to assess the independent relationships between the variables and the lung POCUS findings using the backward stepwise method. Variables with p\u0026thinsp;\u0026le;\u0026thinsp;0.20 were included in the model. We assessed changes in the coefficients at each step to detect confusion and tested interactions. Due to the small numbers, we created a composite outcome with ICU admission and/or death. Sensitivity, specificity, positive and negative predictive values (PPVs, NPVs), and positive and negative likelihood ratios (LR+, LR \u0026minus;) were calculated for the overall lung POCUS findings and for each of them independently. We considered true positive cases of those patients with positive ultrasound findings for pneumonia, in which, after a hospital contact, pneumonia was confirmed either with X-ray or CT-scan after 30 days of the index visit. False positive cases were those with ultrasound positive findings for pneumonia that were not confirmed in the hospital through X-ray or CT-scan after 30 days of the index visit. We considered true negatives for those patients with negative ultrasound findings for pneumonia and no verified pneumonia through X-ray or CT scan after 30 days of the index visit. Finally, false negative cases were defined as patients without ultrasound findings for pneumonia who were confirmed to have pneumonia through chest X-ray or CT scan after 30 days of the index visit. SPSS software version 26 was used.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDuring the period of the study, 624 patients were included, 527 by the Majorcan COVID-19 Mobile Care Units and 97 at the COVID-Point in Salamanca. The flowchart of patients included is shown in Fig.\u0026nbsp;1. Baseline characteristics of patients included in the study are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age was 52.5 years (SD\u0026thinsp;=\u0026thinsp;18.3), and 45.7% of them were female. The mean number of days from the beginning of symptoms until POCUS was performed was 7.2 (SD\u0026thinsp;=\u0026thinsp;4.3), and 5.3 days (SD\u0026thinsp;=\u0026thinsp;4.1) since a positive SARS-CoV-2 result was reported. Out of the 624 patients, 8.9% had a temperature higher than 38\u0026ordm;C, 22.5% had pulse oximetry readings of peripheral oxygen saturation (SpO2) lower than 93%, 34.3% had tachypnoea, and 22.1% had tachycardia.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 1: Baseline characteristics \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTotal sample 624\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN, %\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (623)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3 years\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;50 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e299/623 (48.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;50 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e324/623 (52.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e285/624 (45.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e339/624 (54.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDays since symptoms until POCUS (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (605)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDays since COVID diagnosis until POCUS (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTemperature \u0026ordm;C (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (496)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eTemperature\u0026nbsp;\u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;37\u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e347/496 (70.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37.0-37.9\u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e105/496 (21.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;38.0\u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44/496 (8.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePulse oximetry (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (623)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePulse oximetry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e140/623 (22.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e483/623 (77.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eRespiratory rate bpm (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (548)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRespiratory rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;20 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e360/548 (65.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;20 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e188/548 (34.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCardiac rate bpm (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (615)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCardiac rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;100 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e479/615 (77.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;100 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e136/615 (22.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePOCUS findings\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePleural line abnormalities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e314/624 (50.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSub-pleural consolidation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e172/624 (27.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLobar consolidation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21/624 (3.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePOCUS positive findings for pneumonia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e367/624 (58.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGP decision-making\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReferral to the hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e323/620 (52.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHome care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e297/620 (47.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003cp\u003eRegarding lung POCUS findings, 367 patients (58.8%) had positive findings for pneumonia (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The most common findings were the presence of three or more B-lines with pleural line abnormalities (50.3%), followed by sub-pleural condensation (27.6%) and lobar condensation (3.4%). Patients with positive lung POCUS findings were older and had a longer interval between COVID-19 diagnosis and POCUS performance. Moreover, these patients had higher body temperature, lower pulse oximetry values, and higher respiratory and cardiac rates. Some comorbidities were more prevalent among patients with abnormal lung POCUS findings compared to patients without suspicious lung POCUS findings, like hypertension, type 2 diabetes, anxiety, chronic obstructive pulmonary disease, and heart failure. There were no differences in thyroid diseases, asthma, depression, cardiac arrhythmias, or ischemic heart disease.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative findings in patients with positive POCUS findings versus negative POCUS findings\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003cp\u003ePOCUS findings\u003c/p\u003e\u003cp\u003e367/624 (58.8%)\u003c/p\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eNegative POCUS\u0026nbsp;findings\u003c/p\u003e\u003cp\u003e257/624 (41.2%)\u003c/p\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e55.8\u0026thinsp;\u0026plusmn;\u0026thinsp;17.6 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;18.4 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;50 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e147/366 (40.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e152/257 (59.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;50 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e219/366 (59.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e105/257 (40.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e188/367 (51.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e151/257 (58.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e179/367 (48.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e106/257 (41.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eDays since symptoms until POCUS (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e7.25\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eDays since COVID diagnosis until POCUS (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8 days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eTemperature \u0026ordm;C\u0026nbsp;(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e36.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 \u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e36.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e\u003cp\u003eTemperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;37\u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e194/304 (63.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e153/192 (79.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c11\" namest=\"c10\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.0-37.9\u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e72/304 (23.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e33/192 (17.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;38.0\u0026ordm;C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e38/304 (12.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e6/192 (3.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003ePulse oximetry (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e93.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e96.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003ePulse oximetry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e122/367 (33.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e18/256 (7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e245/367 (66.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e238/256 (93.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eRespiratory rate bpm (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e21.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eRespiratory rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;20 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e188/331 (56.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e172/217 (79.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;20 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e143/331 (43.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e45/217 (20.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eCardiac rate bpm (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e89.7\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e87.0\u0026thinsp;\u0026plusmn;\u0026thinsp;15.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eCardiac rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;100 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e271/364 (74.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e208/251 (82.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;100 bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e93/364 (25.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e43/251 (17.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eComorbidities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eHigh blood pressure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e118/347 (34.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e50/247 (20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eType 2 Diabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e61/347 (17.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e20/247 (8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e24/347 (6.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e30/247 (12.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eThyroid disorders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e30/347 (8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e23/247 (9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eAsthma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e20/347 (5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e25/247 (10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eCOPD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e27/347 (7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e5/247 (2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eHeart failure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e23/347 (6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e7/247 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eArrythmias\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e17/347 (4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e12/247 (4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eDepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e17/347 (4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e13/247 (5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eIschemic heart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e\u003cp\u003e18/347 (5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e7/247 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOutcomes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eGP Decision making\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReferral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e265/366 (72.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e58/254 (22.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHome care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003e101/366 (27.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e196/254 (77.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eHospitalised\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e188/346 (54.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e78/247 (31.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eIntensive care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25/347 (7.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e9/247 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eDeath\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15/347 (4.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e2/247 (0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e\u003c/h2\u003e\u003cp\u003eAbout PCPs' decision-making and patient prognosis, patients with abnormal lung POCUS findings were more frequently referred to the hospital than patients with normal lung POCUS findings (72.4% vs 22.8%; OR\u0026thinsp;=\u0026thinsp;8.83, IC95%:6.11\u0026ndash;12.88). Furthermore, patients with positive lung POCUS findings of suspected pneumonia were more frequently admitted to the hospital (54.3% vs 31.7%; OR\u0026thinsp;=\u0026thinsp;2.57, IC95%:1.83\u0026ndash;3.66) and died because of the process (4.3% vs 0.8%; OR\u0026thinsp;=\u0026thinsp;5.52, IC95%:1.43\u0026ndash;35.99) during the month following the POCUS. No statistical differences were observed between the two groups with respect to patient admission to the intensive care unit. In the multivariate analysis (Fig.\u0026nbsp;2) abnormal POCUS is again associated with hospitalisation independently of age and other clinical variables as pulse oximetry\u0026thinsp;\u0026lt;\u0026thinsp;93%, hypertension or diabetes. Regarding the composite indicator of ICU admission and/or death, we could not find any association with abnormal POCUS findings, but with cardiac failure and pulse oximetry results.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe pneumonia diagnosis could be determined through chest X-ray in 381 patients (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The overall sensitivity of lung POCUS for the diagnosis of COVID-19 pneumonia was 68.3%, and the specificity was 43.6%. The positive predictive value (PPV) was 78.7%. The better values of the individual findings associated with pneumonia were a sensitivity of 64.9%, a PPV of 80.4% and a positive likelihood ratio (LR+) of 4.1 for the presence of at least 3 B-lines, and a specificity of 89.1% for lobar consolidation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePOCUS estimated sensitivity and specificity for pneumonia in COVID-19 patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrevalence\u0026nbsp;%\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSensitivity %\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSpecificity %\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePPV %\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNPV %\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLR+\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eLR-\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOverall (381)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75.3%\u003c/p\u003e\u003cp\u003e(70.6%-79.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.3%\u003c/p\u003e\u003cp\u003e(62.5%-73.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e43.6%\u003c/p\u003e\u003cp\u003e(33.5%-54.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e78.7%\u003c/p\u003e\u003cp\u003e(73.0%-83.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31.1%\u003c/p\u003e\u003cp\u003e(23.5%-39.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.21\u003c/p\u003e\u003cp\u003e(0.99\u0026ndash;1.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003cp\u003e(0.6\u0026ndash;0.89)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePOCUS\u003c/p\u003e\u003cp\u003efindings\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLobar consolidation (146)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.5%\u003c/p\u003e\u003cp\u003e(60.2%-75.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.0%\u003c/p\u003e\u003cp\u003e(4.5%-16.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e89.1%\u003c/p\u003e\u003cp\u003e(75.6%-95.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e64.3%\u003c/p\u003e\u003cp\u003e(35.6%-86.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31.1%\u003c/p\u003e\u003cp\u003e(23.5%-39.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003cp\u003e(0.06\u0026ndash;11.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003cp\u003e(0.99\u0026ndash;1.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSub-pleural consolidation (252)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.4%\u003c/p\u003e\u003cp\u003e(67.4%-78.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.8%\u003c/p\u003e\u003cp\u003e(43.4%-58.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.2%\u003c/p\u003e\u003cp\u003e(48.5%-72.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e78.3%\u003c/p\u003e\u003cp\u003e(69.7%-85.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31.1%\u003c/p\u003e\u003cp\u003e(23.5%-39.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003cp\u003e(1.09\u0026ndash;1.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003cp\u003e(0.76\u0026ndash;0.85)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePleural lines abnormalities (341)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.0%\u003c/p\u003e\u003cp\u003e(70.1%-80.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64.9%\u003c/p\u003e\u003cp\u003e(58.7%-70.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50.0%\u003c/p\u003e\u003cp\u003e(38.8%-61.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80.4%\u003c/p\u003e\u003cp\u003e(74.2%-85.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e31.1%\u003c/p\u003e\u003cp\u003e(23.5%-39.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003cp\u003e(1.23\u0026ndash;1.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003cp\u003e(0.66\u0026ndash;0.75)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study is one of the few studies conducted in primary care to assess the predictive value of lung POCUS for adverse events in COVID-19 patients. The study shows an acceptable value for lung POCUS findings, performed by PCPs in a primary care health centre or in the patient's home, for the prognosis of COVID-19 patients. The most common findings on lung POCUS were the presence of three or more B-lines with pleural line abnormalities (50.3%), followed by subpleural condensation (27.6%) and lobar condensation (3.4%). Patients with positive lung POCUS findings were more frequently referred to a hospital emergency department, and the risk of being admitted to the hospital was twofold more frequent than those without lung involvement. The likelihood that their illness would turn out to be fatal was higher in univariate analysis but not confirmed in multivariate analysis. We have also observed that lung POCUS is independently associated with SpO2 and certain comorbidities in predicting hospitalization. The results reveal a limited diagnostic value for COVID-19 pneumonia compared to chest X-rays.\u003c/p\u003e\u003cp\u003ePrevious studies conducted in hospital settings have shown good prognostic performance of lung POCUS performed on patients with SARS-CoV-2 infection. Studies with hospitalised patients found a significant positive correlation between LUS findings and several markers of disease severity, including C-reactive protein \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, ferritin \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, D-dimer, hypersensitive troponin I, creatine kinase muscle-brain \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, lactate dehydrogenase, and fibrinogen \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. LUS findings have also been associated with an elevated risk of intensive care unit admission and death in several studies \u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, while others, probably due to small sample size, did not find this association \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. When comparing the two studies performed in a primary care environment, we found that their results correlate well with the findings in our study in terms of hospitalisation risk and ultrasound findings. Calvo-Cebrian et al. observed an association between the severity of lung POCUS findings and the appropriateness of referral to the hospital emergency department, defining appropriateness as the referral that benefits patients in terms of hospital admission or prescription of a specific treatment \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Another study carried out in a health centre in Catalonia showed that evolutionary patterns, diffuse, attenuated diffuse, and unilateral predominant interstitial patterns represented risk factors for hospitalization \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. These two studies have some differences from ours. Our patients had SARS-CoV-2 infection confirmed by RT-PCR, whereas the Calvo et al. study only includes patients with suspected infection, and the Martinez et al. study includes patients with and without laboratory confirmation. Furthermore, there are notable variations in the expertise of the medical professionals who conducted the ultrasounds. In Mart\u0026iacute;nez's study, all ultrasounds were performed by a single doctor who was an expert in ultrasound. In Calvo's study, however, five experts participated. Our research was conducted in two distinct regions, with the involvement of a range of medical professionals with varying degrees of experience.\u003c/p\u003e\u003cp\u003eThe lung POCUS sensitivity for the diagnosis of pneumonia in COVID-19 patients is comparable to that achieved by chest X-ray compared with CT scan in COVID-19 \u003csup\u003e26\u003c/sup\u003e and non-COVID-19 patients \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The positive likelihood ratio is also similar to the LR\u0026thinsp;+\u0026thinsp;of lung POCUS for the diagnosis of pneumonia in primary care, disregarding the causal agent \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The diagnostic value of lung POCUS in this study is lower than the results achieved in previous studies, both in the hospital and emergency department \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and in primary care \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Several circumstances may partly explain the differences found. Several meta-analyses conducted before and after the pandemic show high variability in the way the outcome of pneumonia is defined. \u003csup\u003e19,25\u003c/sup\u003e Some studies define the outcome according to the result of the PCR performed, with or without the opinion of a multidisciplinary team \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Other studies compare lung POCUS with hospital admission and certain clinical findings in patients\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Few studies used CT scans as the gold standard diagnostic test \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, and in some studies, CT scans were only performed in patients with abnormalities on lung POCUS or chest X-ray \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In our study, all patients had a positive RT-PCR at the time of enrolment, and all but one of the patients included in the diagnostic validation analysis received a chest X-ray. Only 31 had a CT scan.\u003c/p\u003e\n\u003ch3\u003eStrengths and limitations\u003c/h3\u003e\n\u003cp\u003eThe prospective design of this study facilitates accurate and comprehensive data collection, thereby minimizing recall and selection biases. The sample size of this study is the largest among studies on the diagnosis of COVID-19 using lung POCUS in a primary care setting. The use of POCUS in primary care has experienced a surge in recent years and evaluating its diagnostic value in conditions as close to real-life scenarios as possible, including patients visited in their own homes, is of paramount importance.\u003c/p\u003e\u003cp\u003eOur patients have fewer comorbidities than those in previous studies conducted in hospital departments \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. These differences could be explained by the fact that patients in primary care generally present less severe symptoms and fewer concomitant diseases than those attended in hospitals. In this sense, 58% of our patients had POCUS abnormal findings, compared with 81% in patients in emergency departments \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, and 91\u0026ndash;96% in studies done in hospital wards. \u003csup\u003e8,34\u003c/sup\u003e In any case, studies conducted in primary care do not document the presence of comorbidities. This limitation hinders the capacity to undertake direct comparisons. The same applies to the clinical signs recorded. Studies that collect data such as heart rate, respiratory rate, SpO2, and temperature show variable results, although, in general, their patients present a worse clinical situation than ours \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur study was unable to use CT scan as a gold standard due to the circumstances at the time of the study, when its use was restricted as much as possible. Despite the existence of previous recommendations for the use of lung POCUS \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, there is a high variability in different aspects of the methodology used. The findings to be considered, the number of zones scanned, and the competency of LUS examiners remain undefined \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The most common recommendations were adopted, including the findings to be considered and the 12-zone protocol. The 12-zone protocol has the advantage of being more specific and thus provides a general impression of lung compromise \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. B-lines, the ultrasound most frequently observed sign in cases of COVID-19 pneumonia, have been identified in a range of other lung conditions, including pulmonary oedema of various aetiologies (e.g. heart failure), diffuse parenchymal lung disease (pulmonary fibrosis), lymphangitic neoplastic dissemination, and ARDS (adult respiratory distress syndrome) \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTraining time in lung POCUS also needs to be addressed. PCPs who participated in the study received a short 5-hour training due to the urgency in assessing COVID-19 patients with worsening symptoms in the community. Although basic ultrasound image acquisition and interpretation skills can be learned by physicians of varying experience after a brief training course \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, there is a lack of clear guidelines for LUS training and certification \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. A consensus of 28 experts considered that LUS has a steep learning curve in the evaluation of interstitial syndrome \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Other authors have proposed at least 10\u0026ndash;25 LUS scans supervised by experts to acquire sufficient competence\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. A study on the use of LUS in the diagnosis of pneumonia in children found significant differences in performance between novice and LUS-experienced professionals \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Nevertheless, even among LUS experts, the levels of inter- and intra-observer agreement tend to be moderate, with higher disagreement specifically in findings related to COVID-19 pneumonia, like pleural thickening and B-lines \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe use of mobile devices for performing and registering POCUS can be considered both as a strength and as a limitation. A strength because mobile devices allow POCUS outside health centres, and a limitation due to the possible discrepancy in performance between portable ultrasound scanners and the high-end devices available in healthcare centres. A systematic review on this topic found that portable devices demonstrated comparable performance to high-end devices in specific domains, such as the detection of ascites, hydronephrosis, screening for abdominal aortic aneurysms, and care of obstetric and gynaecological patients \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Nonetheless, the review determined that there remained a paucity of evidence to support the utilization of portable devices in the abdominal or pleural regions.\u003c/p\u003e\u003cp\u003eIn conclusion, this study indicates that lung POCUS performed by PCPs in primary care settings or at the patient's home offers acceptable prognostic utility for patients with COVID-19, although its diagnostic value for COVID-19 pneumonia compared to chest X-ray appears to be limited. These findings may be of interest in settings with limited access to radiology, whether due to availability or distance. They may also be of interest to home-based patients whose mobility is compromised for one reason or another. Furthermore, the findings presented here emphasise the importance of the development of standardised guidelines and highlight the relevance of achieving consensus on lung ultrasound scanning methodology, as well as on the training requirements for PCPs. This standardisation work will help to ensure the reliable use of lung POCUS in primary care settings. Moreover, further research is necessary to evaluate the role of lung POCUS in diagnosing pneumonia of any aetiology in primary care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eAll authors declare no financial or non-financial competing interests.\u003c/p\u003e\u003ch2\u003eEthics\u003c/h2\u003e\u003cp\u003eThis study obtained the approval of the Balearic Islands (IB 4530/21 PI) and the Salamanca (PI-2021-10881) Research Ethics Committees.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis study has been funded by Instituto de Salud Carlos III (ISCIII) through the project \"PI21/01521\" and co-funded by the European Union, and Primary Care and Health Promotion Network (RICAPPS) RD21/0016/0009, co-financed by Next Generation (EU) funds from the Recovery and Resilience Mechanism.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eME, JIRM, JC, CG, AM, and AA conceptualised the study. JC and AA participated in training PCPs. ME, CG, AM, JIRM, and AA designed the research. ME, CG, AM, and OB coordinated data acquisition and information management. OB performed the statistical analysis. BO, OB, and ME wrote the main manuscript text and prepared all the figures and tables . All authors reviewed and edited all draft versions and the final one and approved it for submission.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe want to thank the healthcare professionals (doctors, nurses, and healthcare technicians) who collaborated in carrying out this study, as well as the patients and caregivers who gave their consent to use their data in those challenging times.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData are available upon request to Oana Bulilete at [[email protected]]on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHuang, C. \u003cem\u003eet al.\u003c/em\u003e Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. \u003cem\u003eThe Lancet\u003c/em\u003e 395, 497\u0026ndash;506 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReport of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/report-of-the-who-china-joint-mission-on-coronavirus-disease-2019-(covid-19\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/report-of-the-who-china-joint-mission-on-coronavirus-disease-2019-(covid-19\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStokes, E. 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Ultrasound J.\u003c/em\u003e 10, 23 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlazic, I. \u003cem\u003eet al.\u003c/em\u003e The use of lung ultrasound in COVID-19. \u003cem\u003eERJ Open Res.\u003c/em\u003e 9, 00196\u0026ndash;02022 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLerchbaumer, M. H. \u003cem\u003eet al.\u003c/em\u003e Point-of-care lung ultrasound in COVID-19 patients: inter- and intra-observer agreement in a prospective observational study. \u003cem\u003eSci. Rep.\u003c/em\u003e 11, 10678 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRykkje, A., Carlsen, J. F. \u0026amp; Nielsen, M. B. Hand-Held Ultrasound Devices Compared with High-End Ultrasound Systems: A Systematic Review. \u003cem\u003eDiagnostics\u003c/em\u003e 9, 61 (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-primary-care-respiratory-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjpcrm","sideBox":"Learn more about [npj Primary Care Respiratory Medicine](https://www.nature.com/npjpcrm/)","snPcode":"41533","submissionUrl":"https://submission.springernature.com/new-submission/41533/3","title":"npj Primary Care Respiratory Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7640052/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7640052/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo assess the value of abnormal findings of lung POCUS performed by PCPs in patients with SARS-CoV-2 virus infection confined at home in predicting hospitalisations, intensive care admissions, and mortality. Additionally, this study aims to assess the validity of lung POCUS performed by PCPs for FIGURECOVID pneumonia diagnosis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis prospective observational study, conducted in Mallorca and Salamanca, Spain, between January and December 2021, assessed 624 consecutive adult patients (mean age 52.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3 years; 45.7% female) with confirmed SARS-CoV-2 infection and worsening symptoms via home visits or community health centres. Eight primary care physicians received a standardised 5-hour training in lung POCUS. Examinations followed a 12-zone protocol, and POCUS was considered positive if at least one abnormality - \u0026ge; 3 B-lines, subpleural consolidation, or lobar consolidation - was present. Patients were followed for 30 days to confirm pneumonia diagnosis via chest X-ray, CT scan, or inpatient records and to record hospital referral, hospitalisation, ICU admission, and death.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAbnormal POCUS findings were observed in 58.8% of patients, of whom 50.3% presented pleural line abnormalities, 27.6% subpleural consolidations, and 3.4% lobar consolidations. Patients with positive POCUS were referred to the hospital more frequently than those with negative findings (72.4% vs. 22.8%; OR\u0026thinsp;=\u0026thinsp;8.83). They also had higher rates of hospitalisation (54.3% vs. 31.7%; OR\u0026thinsp;=\u0026thinsp;2.57) and mortality (4.3% vs. 0.8%; OR\u0026thinsp;=\u0026thinsp;5.52), while ICU admission did not differ significantly. For the diagnosis of COVID-19 pneumonia, overall POCUS sensitivity was 68.3%, specificity 43.6%, positive predictive value 78.7%, and negative predictive value 31.1%.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eLung POCUS performed by primary care physicians demonstrates acceptable prognostic utility for COVID-19 patients in community settings; however, it has limited diagnostic accuracy compared with chest radiography. These findings support its use in resource-limited environments and highlight the need for standardised scanning protocols and training.\u003c/p\u003e","manuscriptTitle":"Lung ultrasound performed by primary care physicians as a prognostic and diagnostic tool in COVID-19 patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-06 09:18:19","doi":"10.21203/rs.3.rs-7640052/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-06T11:54:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-05T17:46:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319012141887916114363468043893929848727","date":"2025-11-05T10:48:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-14T06:15:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235282895567366595173217354008317842343","date":"2025-09-25T12:58:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136383822294194692420204785421720432013","date":"2025-09-24T16:43:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-23T09:44:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-18T00:18:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-18T00:18:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Primary Care Respiratory Medicine","date":"2025-09-17T12:06:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-primary-care-respiratory-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjpcrm","sideBox":"Learn more about [npj Primary Care Respiratory Medicine](https://www.nature.com/npjpcrm/)","snPcode":"41533","submissionUrl":"https://submission.springernature.com/new-submission/41533/3","title":"npj Primary Care Respiratory Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bde614a9-74ee-49e7-963f-41efcdcb997e","owner":[],"postedDate":"October 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":55716187,"name":"Health sciences/Diseases"},{"id":55716188,"name":"Health sciences/Health care"},{"id":55716189,"name":"Health sciences/Medical research"},{"id":55716190,"name":"Health sciences/Signs and symptoms"}],"tags":[],"updatedAt":"2026-04-27T16:09:47+00:00","versionOfRecord":{"articleIdentity":"rs-7640052","link":"https://doi.org/10.1038/s41533-026-00515-4","journal":{"identity":"npj-primary-care-respiratory-medicine","isVorOnly":false,"title":"npj Primary Care Respiratory Medicine"},"publishedOn":"2026-04-24 15:58:51","publishedOnDateReadable":"April 24th, 2026"},"versionCreatedAt":"2025-10-06 09:18:19","video":"","vorDoi":"10.1038/s41533-026-00515-4","vorDoiUrl":"https://doi.org/10.1038/s41533-026-00515-4","workflowStages":[]},"version":"v1","identity":"rs-7640052","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7640052","identity":"rs-7640052","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}