key: cord-0941428-lbwh9zhm authors: Marino, Luca; Suppa, Marianna; Rosa, Antonello; Servello, Adriana; Coppola, Alessandro; Palladino, Mariangela; Mazzocchitti, Anna Maria; Bresciani, Emanuela; Petramala, Luigi; Bertazzoni, Giuliano; Pastori, Daniele title: Time to hospitalisation, CT pulmonary involvement and in‐hospital death in COVID‐19 patients in an Emergency Medicine Unit date: 2021-06-16 journal: Int J Clin Pract DOI: 10.1111/ijcp.14426 sha: 96305c04809b2384db8edfa2f0142c7ece1d518f doc_id: 941428 cord_uid: lbwh9zhm BACKGROUND: Patients with coronavirus disease 2019 (COVID‐19) are often treated at home given the limited healthcare resources. Many patients may have sudden clinical worsening and may be already compromised at hospitalisation. We investigated the burden of lung involvement according to the time to hospitalisation. METHODS: In this observational cohort study, 55 consecutive COVID‐19‐related pneumonia patients were admitted to the Emergency Medicine Unit. Groups of lung involvement at computed tomography were classified as follows: 0 (<5%), 1 (5%‐25%), 2 (26%‐50%), 3 (51%‐75%) and 4 (>75%). We also investigated in‐hospital death and the predictive value of Yan‐XGBoost model and PREDI‐CO scores for death. RESULTS: The median age was 74 years and 34 were men. Time to admission increased from 2 days in group 0 to 8.5‐9 days in groups 3 and 4. A progressive increase in LDH, CRP and d‐dimer was found across groups, while a decrease of lymphocytes paO(2)/FiO(2) ratio and SpO(2) was found. Ten (18.2%) patients died during the in‐hospital staying. Patients who died were older, with a trend to lower lymphocytes, a higher d‐dimer, creatine phosphokinase and troponin T. The Yan‐XGBoost model did not accurately predict in‐hospital death with an AUC of 0.57 (95% confidence interval [CI] 0.37‐0.76), which improved after the addition of the lung involvement groups (AUC 0.68, 95%CI 0.45‐0.90). Conversely, a good predictive value was found for the original PREDI‐CO score with an AUC of 0.76 (95% CI 0.58‐0.93) which remained similar after the addition of the lung involvement (AUC 0.76, 95% CI 0.57‐0.94). CONCLUSION: We found that delayed hospital admission is associated with higher lung involvement. Hence, our data suggest that patients at risk for more severe disease, such as those with high LDH, CRP and d‐dimer, should be promptly referred to hospital care. The present pandemic of the severe acute respiratory syndrome cor-onavirus2(SARS-CoV-2)-relateddisease hasputmany severe issues to all the world health systems. Currently, the vaccination programme is moving the first steps all over the world, but it is quite clear that the burden on hospitals and health organisations will be still significant in the next months even if a great expectation is placed on the immunisation of a large part of the population. Asignificantnumberofinfectedpeopleisasymptomatic,witha percentagevaryingfrom40%to70%,dependingontheparticular analysis considered. 1, 2 The clinical scenario of the symptomatic infections spans from paucisymptomatic conditions, sometimes classified as mild disease, 3 to a severe or critical disease according to clinical and laboratory data. The latter includes patients with interstitial lung disease and pneumonia or patients with venous and arterial thrombotic complications. 4, 5 The average incubation for clinical manifestation for the main symptomsisaround3-5days, [6] [7] [8] and the most common symptoms are drycough,myalgiasandheadache.Additionalfeaturesincluderhinorrhea,gastro-intestinalsymptoms,smelland/ortastealterations,and conjunctivitis is also reported in some cases. [9] [10] [11] In the most serious infections, the pulmonary involvement carries dyspnoea and fever. Since the initial mild symptoms, the disease can proceed to a more severe conditioninatemporalwindowof7-12days, 12, 13 and in these cases, the admission to hospital is almost always necessary. Characteristics identification and management of patients with poor outcomes; these include clinical factors such as cerebrovascular and cardiovascular disease, chronic obstructive pulmonary disease, diabetes, hypertension, smokingandmalesexandlaboratoryfindingssuchasincreasedprocalcitonin, increased d-dimerandthrombocytopenia. [14] [15] [16] [17] The management of the hospitalised patients is based on clinical, laboratory and imaging data. In particular, chest computed tomography(CT)isoneofthefundamentalexamsforthesuccessivetherapeutic course. 18 The typical pattern at the chest CT is represented by bilateral interstitial involvement sometimes with consolidative abnormalities. Additional features found in some patients are septal thickening superposesonthegroundglassopacification(crazypattern),bronchiectasis, pleural effusion, 19 pericardial effusion and lymphadenopathy. The lung involvement is almost always bilateral, with the prevalence of peripheral distribution and focused at the lower lobes of the lungs, at least in the less severe conditions. Correlation between clinical features and radiological severity score was proved for chest X-ray 20 and chest CT 18, 20 and, even if none of the two techniques cannot be adopted as a unique diagnostictool,theyprovedtobehelpfultostratifytheprognosticriskand to improve the management of the patient. However, it is unclear whether time to hospitalisation is associated with an increased burden of symptoms and lung involvement. This is an important issue considering that in the middle of what has been named the "second wave" of the pandemic disease the issue of the overcrowded hospital has become crucial and, in many cases, physicians are trying to treat patients at home as much as possible unless increasing respiratory failure. The aim of the study was to analyse the possible relationship between the clinical/radiological lung conditions and the time delay betweentheonsetofsymptomsrelatedtoCOVID-19andthetime of admission to the Emergency Department. We also tested the predictive value of two scores namely Yan-XGBoost model 21 and PREDI-COscore 22 forin-hospitalmortality. We carried out a retrospective analysis on 55 patients, affected 18, 23 Anexperiencedradiologist finally gave a global estimation of the overall lung involvement and patients were divided into five groups according to the following percentageoflunginvolvement:group0(<5%involvement),group 1(5%-25%involvement),group2(26%-50%involvement),group3 (51%-75%involvement)andgroup4(>75%involvement).Onepoint for each group of lung involvement was then added to the clinical riskscorestoseeifitimprovedtheirpredictivevalue. Continuous variables are reported as median and interquartile range. Median values between two groups were compared by the Mann-Whitney U test, while comparison among the four groups of lung involvementwasperformedbytheKruskal-Wallistest.Categorical variables were reported as count and percentage and compared by Pearsonchi-squaredtest.Afirstdescriptiveanalysisofclinicalcharacteristics of patients was performed according to lung involvement. We also analysed clinical and biochemical differences between survivorandnon-survivorpatients. Finally,webuiltthereceiveroperatingcharacteristic(ROC)curve totestthepredictivevalueagainstin-hospitalmortalitybeforeand after the addition of the lung involvement score as previously de- The statistical significance was set at a P value <.005. All the analyses were performed using the IBM software SPSS 25.0. The clinical and radiological features are reported in Table 1 Timetoadmissionincreasedfrom2daysingroup0to8.5-9days ingroups3and4(Table1). Ten (18.2%) patients died during the in-hospital staying. Patients who died were older, with a trend to lower lymphocytes, a higher d-dimer,creatinephosphokinase,andtroponinT(Table2). The two groups of patients did not present a significant difference in term of median time admission, but a significantly higher lung involvementwasfoundinnon-survivorspatients. Wealsotestedthepredictivevalueofclinicalriskscoresinour group of patients. In this study, performed in the Emergency Medicine Unit, we found that delayed time to admission was significantly associated with a moreseverelunginvolvement,whichwasassociatedwithhigherinhospital death. We also found that the addition of lung involvement toapre-existingscoreincreaseditspredictivevalue. Patientswithworselunginvolvementweremorelikelytohave increased LDH, CRP, d-dimer and lower lymphocytes, PaO 2 /FiO 2 ratio and SpO 2 . Our results are in keeping with a previous report showing that CT scores of lung involvement were correlated with CRP and LDH serum levels. 24 In particular, in the study by Francone etaltheCTscorewassignificantlycorrelatedwithCRP(P < .0001, r =0.6204)andd-dimer(P < .0001, r =0.6625)levels. 18 These biomarkers may be useful to identify outpatients with a higherriskofseverelungdisease.Anewfindingofthestudyisthat the time to hospital admission increased progressively across lung involvement severity groups. During the in-hospital staying, 18% of patients died. This casefatality rate is similar to the reported in other studies conducted in Italy. 25 In our study, we found that lung involvement degree was higher innon-survivorpatients.Inthelastmonths,severalclinicalscoreswere developed to assess the severity of the disease and to predict patient evolution to critical illness or death. 26 The proposed scores are quite heterogeneous in terms of predictors which span from demographic 8.5 (7) (8) (9) (10) .002 .007 Hypertension(%) .070 .045 Creatinine ( .006 Yan-XGBoostmodel+ lung involvement score 4(3-5) 4(2-5) 5.5 (3.25-6) .031 PREDI-CO+ lung involvement score 6(5-8) 6(5-8) 8 (6) (7) (8) (9) (10) (11) .014 F I G U R E 1 ROC curves with and without the addition of lung involvement groups to laboratory and/or radiological features. However, some of them are complex and with some variables which are difficult to be obtained especially in an emergency setting. In our study, we decided to test two scores which include simple clinical and laboratory variables. WefoundthattheadditionofCTdatatothebiomarker-based score improved its clinical value, suggesting that laboratory alone cannotbeenoughtocorrectlystratifytheriskofdeathinpatients withCOVID-19relatedpneumonia. Limitations of the study. The present contribution is limited by the small sample size that could affect the statistical significance, but, from these preliminary results, we can conclude that time delay between COVID-19 symptoms onset and hospital admission can actually affect the disease progression, especially for the evolution of the lung damage. This issue is particularly significant for older patients who proved to be the most dramatically affected by the pandemic. In conclusion, our study suggests that delayed time to hospitalisation is associated with a worse lung involvement evaluated by CT. Our results challenge the actual advice of health systems of many countriestodelayhospitaladmissionfornon-severecases,inorder to ease the hospitals burden that struggles to manage the continuously increasing rate of infected people. Our opinion is that people with clinical and laboratory features suggestive of significant lung involvement(ie,highLDH,CRPandd-dimer)shouldnotwaittobe referred to the hospital. The authors declare no conflict of interest. In keeping with statements by the Italian Regulatory Authorities Awaiverofinformedconsentfromstudyparticipantsisappliedfor retrospective studies. This study was conducted in compliance with thedeclarationofHelsinki. Alldatageneratedoranalysedduringthisstudyareincludedinthis published article. 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Time to hospitalisation, CT pulmonary involvement and in-hospitaldeathinCOVID-19patientsinanEmergency