Usefulness of repeated procalcitonin measurements in the management of severe SARS-CoV-2 pneumonia

Usefulness of repeated procalcitonin measurements in the management of severe SARS-CoV-2 pneumonia | 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 Usefulness of repeated procalcitonin measurements in the management of severe SARS-CoV-2 pneumonia Matthieu Turpin, Camille Urien-Maisonnave, Guillaume Voiriot, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7808903/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 18 You are reading this latest preprint version Abstract Bacterial respiratory co-infection and secondary superinfection are complications of severe acute respiratory coronavirus 2 (SARS-CoV2) pneumonia. Despite the relative low incidence rate of bacterial coinfection, most patients receive empirical antibiotic therapy on ICU admission. To help antibiotic prescribing, we evaluated the effectiveness of repeated PCT measurements in predicting bacterial co-infection and superinfection. This was an ancillary study of the MultiCoV study. All adult patients admitted to one of 13 participating ICUs with PCR-confirmed severe SARS-CoV2 pneumonia and a PCT measurement upon admission were included. The primary endpoint was the performance of the admission PCT level in diagnosing bacterial co-infection. Of the 182 patients included in the study, bacterial co-infection was diagnosed in 62 (34%) of them. The median admission PCT level was 0.3 ng/mL [0.11; 1.56] versus 0.25 ng/mL [0.11; 0.59] in the groups of patients with and without bacterial co-infection respectively. Admission PCT level greater or equal than 1.50 ng/mL was associated with bacterial co-infection (OR 2.43, 95% CI [1.11; 5.34]; p = 0.026). Moreover, median PCT levels at day 3 were higher in the superinfection group (0.31 ng/mL [0.12; 1.36] versus 0.14 ng/mL [0.10; 0.44]) and in the group of patients who died at day 28 (> 1 ng/mL in 16.3% versus 8.6%). Daily PCT measurements for patients with severe SARS-CoV2 pneumonia could help in antibiotic prescribing in the first days of ICU admission. Health sciences/Diseases Health sciences/Medical research Biological sciences/Microbiology Procalcitonin Pneumonia Sars-CoV2 Diagnosis Bacterial infection Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Bacterial respiratory co-infection and secondary superinfection are well known complications of severe acute respiratory coronavirus 2 (SARS-CoV2) pneumonia. Previous studies have estimated the prevalence of bacterial respiratory co-infection to 10% to 15% in the intensive care unit (ICU) ( 1 ). Despite the relative low rate of bacterial co-infection, most ICU patients with severe SARS-CoV-2 pneumonia received empirical antibiotic therapy on admission ( 1 ). A few retrospective studies failed to demonstrate an association between admission procalcitonin (PCT) levels and bacterial co-infection. In ICU patients, admission PCT level alone showed low specificity and low accuracy in predicting bacterial co-infection. Greater performances of PCT were observed in association with other biomarkers of inflammation (C-reactive protein) and with clinical contextualization ( 2 , 3 ). In the MultiCoV multicenter randomized controlled trial, a strategy combining daily PCT measurements and respiratory broad panel multiplex polymerase chain reaction (mPCR) did not affect 28-day antibiotics exposure in patients with severe SARS-CoV2 pneumonia ( 4 ). Bacterial superinfection (hospital acquired and ventilator associated pneumonia) were clinically suspected in 50% of patients. This high rate may have impacted antibiotic exposure and complicated the interpretation of PCT kinetics during ICU stay. Indeed, a previous retrospective study showed that patients with bacterial superinfection had higher PCT levels on admission and during the hospital stay ( 5 ). This study investigated the kinetics of PCT levels during the first 72 hours of the ICU stay in adult patients with severe SARS-CoV2 pneumonia. Our aim was to evaluate the effectiveness of this biomarker in predicting bacterial co-infection and superinfection. Methods This was an ancillary study based on data collected prospectively as part of the MultiCoV study ( 4 ). This study included all adult patients admitted to one of 13 participating ICUs in France from 20 April 2020 to 23 November 2020 with PCR-confirmed severe SARS-CoV2 pneumonia and a PCT measurement upon admission. Non-inclusion criteria were those of MultiCoV study ( 4 ). Briefly, patients were randomized (1:1) to the interventional antibiotic stewardship strategy using mPCR with enlarged respiratory panel (BioFire FilmArray Pneumonia plus) on respiratory tract samples and daily PCT measurements within the first 7 days of ICU admission (day-2, day-3, and day-7), or to the control strategy. In the control group, PCT measurements were required at inclusion, whereas repeated daily procalcitonin measurements were discouraged, but allowed as per routine practice in each participating center. In the interventional group, interventional strategy encouraged early discontinuation of antibiotic therapy; specifically, antibiotic continuation was encouraged when PCT was > 1 ng/mL and discouraged if < 1 ng/mL or decreased by 80% from baseline level. In the control group, antibiotic prescription remained at the discretion of the clinicians in charge. Bacterial co-infection was defined by the positivity of at least one of the following microbiological investigations performed within 24 hours before or after inclusion: respiratory tract secretions sample for Gram stain examination and culture, mPCR, blood cultures and Streptococcus pneumoniae and Legionella pneumophilia urinary antigen assays. Early bacterial superinfection was clinically suspected after 48 hours of admission and up to 7 days, and confirmed by the positivity of respiratory tract secretions sample cultures, blood cultures or S. pneumoniae or L. pneumophilia urinary antigen assays. The primary endpoint was the performance of the admission PCT level for diagnosing bacterial co-infection in severe SARS-CoV2 pneumonia. Secondary endpoints were the performance of PCT levels at admission and kinetics during the first 72 hours, for predicting the occurrence of bacterial superinfection and vital status at day 28. Statistical analysis was performed using SASv9.4 and RStudio 2022.02.0 software. Results were expressed as frequency and percentage for categorical variables, and mean and standard deviation or median and interquartile range for continuous variables, according to their distribution. PCT level was expressed as median and interquartile range. PCT levels were dichotomized into 4 predefined classes of mutually exclusive values (< 0.25; ≥0.25 and < 0.5; ≥0.5 and < 1; ≥1) and the distribution was expressed as frequency and percentage. The association between PCT levels and bacterial co-infection was studied using logistic regression model, and Receiver operating characteristic (ROC) was performed. This study is based on data from MultiCoV trial, whose protocol was approved by the French ethical committee (Comité de Protection des Personnes Sud-Méditerranée V; April 9, 2020) and health authorities (Agence Nationale de Sécurité du Médicament et des Produits de Santé). All patients (or next of kin) received written information about the study and gave their informed consent to participate before enrollment, in compliance with French regulations (Law n° 2012 − 300; March 5, 2012). This study was conducted in accordance with French regulations on clinical research and the principles of the Declaration of Helsinki. Results A total of 182 patients were included in the MultiCoV trial, contrasting 98 in the control group and 93 in the interventional group. We excluded from analysis 9 patients for whom the admission PCT was not available. Procalcitonin measurements were available on admission, day-2 and day-3 for 71 patients in the interventional group. Altogether, bacterial co-infection was diagnosed in 62 patients (34%). The main characteristics of the patients are detailed in Table 1 , according to bacterial co-infection diagnosis. Most patients were males (70.9%), with a mean age of 64.4 years (± 13.2), and a body mass index of 30.4 kg/m2 (± 6.2). More than half of them had cardiovascular comorbidities (56%). Table 1 Characteristics of patients, according to bacterial coinfection diagnosis Variables All patients (n = 182) Patients with bacterial coinfection (n = 62) Patients without bacterial coinfection (n = 120) Demographics and comorbid conditions Age , years 64.4 ± 13.2 62.4 ± 14.4 65.4 ± 12.5 Gender , male 129 (70.9) 42 (67.7) 87 (72.5) Body mass index , kg/m² 30.4 ± 6.2 30.1 ± 4.5 30.5 ± 7.0 Comorbidities Diabetes mellitus 61 (33.5) 19 (30.6) 42 (35.0) Arterial hypertension 90 (49.5) 28 (45.2) 62 (51.7) Cardiovascular disease 102 (56.0) 33 (53.2) 69 (57.5) Chronic respiratory disease 41 (22.5) 14 (22.6) 27 (22.5) Before ICU admission Time from diagnosis to ICU admission , days 2.0 [0.0; 5.0] 2.0 [0.0; 4.0] 3.0 [0.0; 6.0] Antibiotic therapy within 7 days before study inclusion 150 (82.4) 52 (83.9) 98 (81.7) Specific medication within 7 days before ICU admission 113 (62.1) 41 (66.1) 72 (60.0) NSAIDs 5 (2.7) 4 (6.5) 1 (0.8) Antiviral agents 5 (2.7) 2 (3.2) 3 (2.5) Immune-based agents 2 (1.1) 0 (0) 2 (1.7) Steroids 112 (61.5) 41 (66.1) 71 (59.2) On ICU admission Baseline SOFA score 4.0 [3.0; 7.0] 4.0 [3.0; 7.0] 4,0 [3.0; 7.0] Baseline SAPSII score 40.0 ± 16.6 39.4 ± 17.9 40.3 ± 16.0 Respiratory support No oxygen therapy 4 (2.2) 0 (0) 4 (3.4) Conventional oxygen therapy 30 (16.7) 14 (23.0) 16 (13.4) Non-invasive mechanical ventilation or High-flow nasal canula 99 (55) 31 (50.8) 68 (57.1) Invasive mechanical ventilation 24 (13.3) 6 (9.8) 18 (15.1) Invasive mechanical ventilation, vasopressor support or ECMO 23 (12.8) 10 (16.4) 13 (10.9) Laboratory findings PaO2 / FiO2 ratio , mmHg 122.5 [81.0; 187.5] 111.1 [77.0; 178.0] 128.3 [83.2; 189.3] Lactates , mmol/L 1.4 ± 0.6 1.4 ± 0.5 1.5 ± 0.6 Leucocyte count , G/L 9.2 ± 4.7 9.4 ± 4.4 9.1 ± 4.8 Lymphocyte count , G/L 0.7 [0.5; 1.0] 0.7 [0.5; 1.1] 0.7 [0.5; 0.9] Admission procalcitonin , µg/L 0.3 [0.1; 0.8] 0.3 [0.11; 1.56] 0.25 [0.11; 0.59] C-reactive protein , mg/mL 0.3 [0.1; 120.8] 0.6 [0.1; 109.5] 0.3 [0.1; 120.9] Data are n (%) or median [IQR 25; 75%] or mean ± SD ICU, intensive care unit; NSAIDs, non-steroidal anti-inflammatory drugs; SOFA, Sequential Organ Failure Assessment; SAPSII, Simplified Acute Physiology Score; ECMO, extra corporal membrane oxygenation; PaO2 / FiO2 ratio, ratio of partial pressure of arterial oxygen (PaO2) to the fraction of inspired oxygen (FiO2) The median admission PCT level was 0.3 ng/mL [0.11; 1.56] in the group of patients with bacterial co-infection, and 0.25 ng/mL [0.11; 0.59] in the group of patients without bacterial co-infection. ROC curve analysis yielded AUC of 0.54 (Fig. 1 ). Distribution of admission PCT levels according to the predefined four classes of values and the diagnosis of bacterial co-infection is shown Fig. 2 . PCT levels on admission were more often greater or equal than 1 in the bacterial co-infection group (27% versus 18%). Noteworthy, admission PCT level greater or equal than 1.50 ng/mL was associated with bacterial co-infection (OR 2.43, 95% CI [1.11; 5.34]; p = 0.0263) (Table 2 ). In the unadjusted model, admission PCT level was not associated with bacterial co-infection (OR 1.01, 95% CI [0.98; 1.04]) (Table 3 ). Table 2 Association between the distribution of admission PCT levels, according to predefined value classes, and bacterial co-infection, using logistic regression model Proportion of patients with bacterial coinfection Non-adjusted logistic regression model n/N (%) OR (95% CI) P-Value Admission PCT (ng/mL) 0.7596 < 0.25 29/88 (33.0) 1 ≥ 0.25 33/94 (35.1) 1.10 (0.60; 2.03) Admission PCT (ng/mL) 0.1704 < 0.50 36/118 (30.5) 1 ≥ 0.50 26/64 (40.6) 1.56 (0.83; 2.94) Admission PCT (ng/mL) 0.1592 < 1.00 45/143 (31.5) 1 ≥ 1.00 17/39 (43.6) 1.68 (0.82; 3.47) Admission PCT (ng/mL) 0.0263 < 1.50 46/151 (30.5) 1 ≥ 1.50 16/31 (51.6) 2.43 (1.11; 5.34) PCT, procalcitonin; OR, odds ratio; CI, confident interval Table 3 Association between admission PCT level and bacterial co-infection using logistic regression model Non-adjusted logistic regression model OR (95% CI) P-Value Admission PCT level (ng/mL) 1.01 (0.98 ; 1.04) 0.3966 PCT, procalcitonin; OR, odds ratio; CI, confident interval Among the 182 patients included, 33 (18.2%) presented with bacterial superinfection. As shown in Fig. 3 , median admission and day-2 PCT levels were similar between the group of patients with bacterial superinfection and the group of those without. On the other hand, median day-3 PCT levels were higher in the superinfection group (0.31 ng/mL [0.12; 1.36] versus 0.14 ng/mL [0.10; 0.44]). PCT levels at day 3 were greater or equal than 1 ng/mL in 21.2% of patients with bacterial superinfection, as compared with 8.1% of their counterparts (Fig. 3 ). At day 28, 43 patients (23.7%) died. Median admission and day-3PCT levels were respectively 0.37 ng/mL [0.17; 1.37] and 0.28 ng/mL [0.14; 2.59] for patients who died at day 28, as compared with 0.23 ng/mL [0.10; 0.67] and 0.14 ng/mL [0.09; 0.45] in surviving patients. Median admission PCT levels were greater or equal than 1 ng/mL in 27.9% of patients who died at day 28, as compared with 19.4% in surviving patients. This difference persisted at day 2 and day 3, as shown in Fig. 4 . Conclusion PCT levels on ICU admission alone are not helpful for the diagnosis of bacterial co-infection in patients with severe SARS-CoV2 pneumonia. The cutoff value greater or equal than 1.50 ng/mL is associated with bacterial co-infection, encouraging the continuation of initial empiric antibiotic therapy. After admission, PCT levels may be useful for prognostic endpoints, such early bacterial superinfection (day-3 PCT levels) and 28-day mortality (admission and day-3 PCT levels greater or equal than 1 ng/ml). Altogether, these data suggest the usefulness of daily PCT measurements for ICU patients with severe SARS-CoV2 pneumonia to guide antibiotic therapy in the first days of ICU admission. Declarations Authors’ contribution : All authors met authorship criteria. M.T., C.U.M., G.V. and M.F. were involved in study conception and design. S.F. provided the access to the original database and performed statistical analysis. M.T., C.U.M. and M.F. wrote the manuscript. All authors read and approved the final manuscript. Data availability : Deidentified individual-participant data underlying the findings described in the manuscript of the study will be available and shared on reasonable request through an approving committee (mail to the corresponding author). Consultation by an editorial board may be considered, subjected to prior determination of the terms and conditions of such consultation and with respect to compliance with the applicable regulations. Funding : Our study has not been sponsored by any academic or industrial organization. Competing interest statement: M.T. reports financial support from Oxyvie and GSK, all outside the submitted work. C.U.M. declares no conflict of interest. G.V. reports research grants from BioMérieux and SOS Oxygène, and financial support from SOS Oxygène and Oxyvie, all outside the submitted work. M.F. reports grant support from BioMérieux, speaker fees from BioMérieux and Fischer & Paykel, financial support from SOS Oxygène and consultancy fees from Pfizer, all outside the submitted work. References Rouzé A, Martin-Loeches I, Povoa P, Metzelard M, Du Cheyron D, Lambiotte F, et al. Early Bacterial Identification among Intubated Patients with COVID-19 or Influenza Pneumonia: A European Multicenter Comparative Clinical Trial. Am J Respir Crit Care Med. 2021 Sep;204(5):546–56. Galli F, Bindo F, Motos A, Fernández-Barat L, Barbeta E, Gabarrús A, et al. Procalcitonin and C-reactive protein to rule out early bacterial coinfection in COVID-19 critically ill patients. Intensive Care Med. 2023 Aug;49(8):934–45. van Berkel M, Kox M, Frenzel T, Pickkers P, Schouten J, RCI-COVID-19 study group. Biomarkers for antimicrobial stewardship: a reappraisal in COVID-19 times? Crit Care Lond Engl. 2020 Oct 6;24(1):600. Fartoukh M, Nseir S, Mégarbane B, Cohen Y, Lafarge A, Contou D, et al. Respiratory multiplex PCR and procalcitonin to reduce antibiotic exposure in severe SARS-CoV-2 pneumonia: a multicentre randomized controlled trial. Clin Microbiol Infect Off Publ Eur Soc Clin Microbiol Infect Dis. 2023 Jan 18;S1198-743X(23)00031-9. Pink I, Raupach D, Fuge J, Vonberg RP, Hoeper MM, Welte T, et al. C-reactive protein and procalcitonin for antimicrobial stewardship in COVID-19. Infection. 2021 Oct;49(5):935–43. Additional Declarations No competing interests reported. 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Previous studies have estimated the prevalence of bacterial respiratory co-infection to 10% to 15% in the intensive care unit (ICU) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Despite the relative low rate of bacterial co-infection, most ICU patients with severe SARS-CoV-2 pneumonia received empirical antibiotic therapy on admission (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA few retrospective studies failed to demonstrate an association between admission procalcitonin (PCT) levels and bacterial co-infection. In ICU patients, admission PCT level alone showed low specificity and low accuracy in predicting bacterial co-infection. Greater performances of PCT were observed in association with other biomarkers of inflammation (C-reactive protein) and with clinical contextualization (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In the MultiCoV multicenter randomized controlled trial, a strategy combining daily PCT measurements and respiratory broad panel multiplex polymerase chain reaction (mPCR) did not affect 28-day antibiotics exposure in patients with severe SARS-CoV2 pneumonia (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Bacterial superinfection (hospital acquired and ventilator associated pneumonia) were clinically suspected in 50% of patients. This high rate may have impacted antibiotic exposure and complicated the interpretation of PCT kinetics during ICU stay. Indeed, a previous retrospective study showed that patients with bacterial superinfection had higher PCT levels on admission and during the hospital stay (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study investigated the kinetics of PCT levels during the first 72 hours of the ICU stay in adult patients with severe SARS-CoV2 pneumonia. Our aim was to evaluate the effectiveness of this biomarker in predicting bacterial co-infection and superinfection.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis was an ancillary study based on data collected prospectively as part of the MultiCoV study (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This study included all adult patients admitted to one of 13 participating ICUs in France from 20 April 2020 to 23 November 2020 with PCR-confirmed severe SARS-CoV2 pneumonia and a PCT measurement upon admission. Non-inclusion criteria were those of MultiCoV study (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Briefly, patients were randomized (1:1) to the interventional antibiotic stewardship strategy using mPCR with enlarged respiratory panel (BioFire FilmArray Pneumonia plus) on respiratory tract samples and daily PCT measurements within the first 7 days of ICU admission (day-2, day-3, and day-7), or to the control strategy. In the control group, PCT measurements were required at inclusion, whereas repeated daily procalcitonin measurements were discouraged, but allowed as per routine practice in each participating center. In the interventional group, interventional strategy encouraged early discontinuation of antibiotic therapy; specifically, antibiotic continuation was encouraged when PCT was \u0026gt;\u0026thinsp;1 ng/mL and discouraged if\u0026thinsp;\u0026lt;\u0026thinsp;1 ng/mL or decreased by 80% from baseline level. In the control group, antibiotic prescription remained at the discretion of the clinicians in charge.\u003c/p\u003e \u003cp\u003eBacterial co-infection was defined by the positivity of at least one of the following microbiological investigations performed within 24 hours before or after inclusion: respiratory tract secretions sample for Gram stain examination and culture, mPCR, blood cultures and \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e and \u003cem\u003eLegionella pneumophilia\u003c/em\u003e urinary antigen assays. Early bacterial superinfection was clinically suspected after 48 hours of admission and up to 7 days, and confirmed by the positivity of respiratory tract secretions sample cultures, blood cultures or \u003cem\u003eS. pneumoniae\u003c/em\u003e or \u003cem\u003eL. pneumophilia\u003c/em\u003e urinary antigen assays.\u003c/p\u003e \u003cp\u003eThe primary endpoint was the performance of the admission PCT level for diagnosing bacterial co-infection in severe SARS-CoV2 pneumonia.\u003c/p\u003e \u003cp\u003eSecondary endpoints were the performance of PCT levels at admission and kinetics during the first 72 hours, for predicting the occurrence of bacterial superinfection and vital status at day 28.\u003c/p\u003e \u003cp\u003eStatistical analysis was performed using SASv9.4 and RStudio 2022.02.0 software. Results were expressed as frequency and percentage for categorical variables, and mean and standard deviation or median and interquartile range for continuous variables, according to their distribution. PCT level was expressed as median and interquartile range. PCT levels were dichotomized into 4 predefined classes of mutually exclusive values (\u0026lt;\u0026thinsp;0.25; \u0026ge;0.25 and \u0026lt;\u0026thinsp;0.5; \u0026ge;0.5 and \u0026lt;\u0026thinsp;1; \u0026ge;1) and the distribution was expressed as frequency and percentage. The association between PCT levels and bacterial co-infection was studied using logistic regression model, and Receiver operating characteristic (ROC) was performed.\u003c/p\u003e \u003cp\u003e This study is based on data from MultiCoV trial, whose protocol was approved by the French ethical committee (Comit\u0026eacute; de Protection des Personnes Sud-M\u0026eacute;diterran\u0026eacute;e V; April 9, 2020) and health authorities (Agence Nationale de S\u0026eacute;curit\u0026eacute; du M\u0026eacute;dicament et des Produits de Sant\u0026eacute;). All patients (or next of kin) received written information about the study and gave their informed consent to participate before enrollment, in compliance with French regulations (Law n\u0026deg; 2012\u0026thinsp;\u0026minus;\u0026thinsp;300; March 5, 2012). This study was conducted in accordance with French regulations on clinical research and the principles of the Declaration of Helsinki.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 182 patients were included in the MultiCoV trial, contrasting 98 in the control group and 93 in the interventional group. We excluded from analysis 9 patients for whom the admission PCT was not available. Procalcitonin measurements were available on admission, day-2 and day-3 for 71 patients in the interventional group. Altogether, bacterial co-infection was diagnosed in 62 patients (34%). The main characteristics of the patients are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, according to bacterial co-infection diagnosis. Most patients were males (70.9%), with a mean age of 64.4 years (\u0026plusmn;\u0026thinsp;13.2), and a body mass index of 30.4 kg/m2 (\u0026plusmn;\u0026thinsp;6.2). More than half of them had cardiovascular comorbidities (56%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of patients, according to bacterial coinfection diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients (n\u0026thinsp;=\u0026thinsp;182)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients with bacterial coinfection (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePatients without bacterial coinfection (n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics and comorbid conditions\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e, male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87 (72.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index\u003c/b\u003e, kg/m\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (33.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (35.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eArterial hypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (51.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiovascular disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (53.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (57.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic respiratory disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (22.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBefore ICU admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime from diagnosis to ICU admission\u003c/b\u003e, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0 [0.0; 5.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 [0.0; 4.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 [0.0; 6.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAntibiotic therapy within 7 days before study inclusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150 (82.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (83.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (81.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpecific medication within 7 days before ICU admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72 (60.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNSAIDs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAntiviral agents\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eImmune-based agents\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteroids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 (59.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOn ICU admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBaseline SOFA score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0 [3.0; 7.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0 [3.0; 7.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,0 [3.0; 7.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBaseline SAPSII score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.0\u0026thinsp;\u0026plusmn;\u0026thinsp;16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.4\u0026thinsp;\u0026plusmn;\u0026thinsp;17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRespiratory support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo oxygen therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConventional oxygen therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (13.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-invasive mechanical ventilation or High-flow nasal canula\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99 (55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (50.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68 (57.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInvasive mechanical ventilation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (15.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInvasive mechanical ventilation, vasopressor support or ECMO\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (10.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePaO2 / FiO2 ratio\u003c/b\u003e, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122.5 [81.0; 187.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111.1 [77.0; 178.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128.3 [83.2; 189.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLactates\u003c/b\u003e, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeucocyte count\u003c/b\u003e, G/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocyte count\u003c/b\u003e, G/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7 [0.5; 1.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7 [0.5; 1.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7 [0.5; 0.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdmission procalcitonin\u003c/b\u003e, \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3 [0.1; 0.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3 [0.11; 1.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25 [0.11; 0.59]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC-reactive protein\u003c/b\u003e, mg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3 [0.1; 120.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 [0.1; 109.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3 [0.1; 120.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are n (%) or median [IQR 25; 75%] or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eICU, intensive care unit; NSAIDs, non-steroidal anti-inflammatory drugs; SOFA, Sequential Organ Failure Assessment; SAPSII, Simplified Acute Physiology Score; ECMO, extra corporal membrane oxygenation; PaO2 / FiO2 ratio, ratio of partial pressure of arterial oxygen (PaO2) to the fraction of inspired oxygen (FiO2)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe median admission PCT level was 0.3 ng/mL [0.11; 1.56] in the group of patients with bacterial co-infection, and 0.25 ng/mL [0.11; 0.59] in the group of patients without bacterial co-infection. ROC curve analysis yielded AUC of 0.54 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Distribution of admission PCT levels according to the predefined four classes of values and the diagnosis of bacterial co-infection is shown Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e. PCT levels on admission were more often greater or equal than 1 in the bacterial co-infection group (27% versus 18%). Noteworthy, admission PCT level greater or equal than 1.50 ng/mL was associated with bacterial co-infection (OR 2.43, 95% CI [1.11; 5.34]; p\u0026thinsp;=\u0026thinsp;0.0263) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the unadjusted model, admission PCT level was not associated with bacterial co-infection (OR 1.01, 95% CI [0.98; 1.04]) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003eAssociation between the distribution of admission PCT levels, according to predefined value classes, and bacterial co-infection, using logistic regression model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion of patients with bacterial coinfection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNon-adjusted logistic regression model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdmission PCT (ng/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7596\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29/88 (33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33/94 (35.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10 (0.60; 2.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdmission PCT (ng/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36/118 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26/64 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56 (0.83; 2.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdmission PCT (ng/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45/143 (31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17/39 (43.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.68 (0.82; 3.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdmission PCT (ng/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46/151 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16/31 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.43 (1.11; 5.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ePCT, procalcitonin; OR, odds ratio; CI, confident interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eAssociation between admission PCT level and bacterial co-infection using logistic regression model\u003c/p\u003e \u003c/div\u003e \u003c/caption\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\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNon-adjusted logistic regression model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eP-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdmission PCT level (ng/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.98 ; 1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3966\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003ePCT, procalcitonin; OR, odds ratio; CI, confident interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong the 182 patients included, 33 (18.2%) presented with bacterial superinfection. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e, median admission and day-2 PCT levels were similar between the group of patients with bacterial superinfection and the group of those without. On the other hand, median day-3 PCT levels were higher in the superinfection group (0.31 ng/mL [0.12; 1.36] versus 0.14 ng/mL [0.10; 0.44]). PCT levels at day 3 were greater or equal than 1 ng/mL in 21.2% of patients with bacterial superinfection, as compared with 8.1% of their counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt day 28, 43 patients (23.7%) died. Median admission and day-3PCT levels were respectively 0.37 ng/mL [0.17; 1.37] and 0.28 ng/mL [0.14; 2.59] for patients who died at day 28, as compared with 0.23 ng/mL [0.10; 0.67] and 0.14 ng/mL [0.09; 0.45] in surviving patients. Median admission PCT levels were greater or equal than 1 ng/mL in 27.9% of patients who died at day 28, as compared with 19.4% in surviving patients. This difference persisted at day 2 and day 3, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePCT levels on ICU admission alone are not helpful for the diagnosis of bacterial co-infection in patients with severe SARS-CoV2 pneumonia. The cutoff value greater or equal than 1.50 ng/mL is associated with bacterial co-infection, encouraging the continuation of initial empiric antibiotic therapy. After admission, PCT levels may be useful for prognostic endpoints, such early bacterial superinfection (day-3 PCT levels) and 28-day mortality (admission and day-3 PCT levels greater or equal than 1 ng/ml).\u003c/p\u003e\n\u003cp\u003eAltogether, these data suggest the usefulness of daily PCT measurements for ICU patients with severe SARS-CoV2 pneumonia to guide antibiotic therapy in the first days of ICU admission.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors’ contribution\u003c/strong\u003e: All authors met authorship criteria. M.T., C.U.M., G.V. and M.F. were involved in study conception and design. S.F. provided the access to the original database and performed statistical analysis. M.T., C.U.M. and M.F. wrote the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e: Deidentified individual-participant data underlying the findings described in the manuscript of the study will be available and shared on reasonable request through an approving committee (mail to the corresponding author). Consultation by an editorial board may be considered, subjected to prior determination of the terms and conditions of such consultation and with respect to compliance with the applicable regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: Our study has not been sponsored by any academic or industrial organization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM.T.\u003c/strong\u003e reports financial support from Oxyvie and GSK, all outside the submitted work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC.U.M.\u003c/strong\u003e declares no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG.V.\u003c/strong\u003e reports research grants from BioMérieux and SOS Oxygène, and financial support from SOS Oxygène and Oxyvie, all outside the submitted work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM.F.\u003c/strong\u003e reports grant support from BioMérieux, speaker fees from BioMérieux and Fischer \u0026amp; Paykel, financial support from SOS Oxygène and consultancy fees from Pfizer, all outside the submitted work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRouz\u0026eacute; A, Martin-Loeches I, Povoa P, Metzelard M, Du Cheyron D, Lambiotte F, et al. Early Bacterial Identification among Intubated Patients with COVID-19 or Influenza Pneumonia: A European Multicenter Comparative Clinical Trial. Am J Respir Crit Care Med. 2021 Sep;204(5):546\u0026ndash;56. \u003c/li\u003e\n\u003cli\u003eGalli F, Bindo F, Motos A, Fern\u0026aacute;ndez-Barat L, Barbeta E, Gabarr\u0026uacute;s A, et al. Procalcitonin and C-reactive protein to rule out early bacterial coinfection in COVID-19 critically ill patients. Intensive Care Med. 2023 Aug;49(8):934\u0026ndash;45. \u003c/li\u003e\n\u003cli\u003evan Berkel M, Kox M, Frenzel T, Pickkers P, Schouten J, RCI-COVID-19 study group. Biomarkers for antimicrobial stewardship: a reappraisal in COVID-19 times? Crit Care Lond Engl. 2020 Oct 6;24(1):600. \u003c/li\u003e\n\u003cli\u003eFartoukh M, Nseir S, M\u0026eacute;garbane B, Cohen Y, Lafarge A, Contou D, et al. Respiratory multiplex PCR and procalcitonin to reduce antibiotic exposure in severe SARS-CoV-2 pneumonia: a multicentre randomized controlled trial. Clin Microbiol Infect Off Publ Eur Soc Clin Microbiol Infect Dis. 2023 Jan 18;S1198-743X(23)00031-9. \u003c/li\u003e\n\u003cli\u003ePink I, Raupach D, Fuge J, Vonberg RP, Hoeper MM, Welte T, et al. C-reactive protein and procalcitonin for antimicrobial stewardship in COVID-19. Infection. 2021 Oct;49(5):935\u0026ndash;43. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Procalcitonin, Pneumonia, Sars-CoV2, Diagnosis, Bacterial infection","lastPublishedDoi":"10.21203/rs.3.rs-7808903/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7808903/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBacterial respiratory co-infection and secondary superinfection are complications of severe acute respiratory coronavirus 2 (SARS-CoV2) pneumonia. Despite the relative low incidence rate of bacterial coinfection, most patients receive empirical antibiotic therapy on ICU admission. To help antibiotic prescribing, we evaluated the effectiveness of repeated PCT measurements in predicting bacterial co-infection and superinfection.\u003c/p\u003e \u003cp\u003eThis was an ancillary study of the MultiCoV study. All adult patients admitted to one of 13 participating ICUs with PCR-confirmed severe SARS-CoV2 pneumonia and a PCT measurement upon admission were included. The primary endpoint was the performance of the admission PCT level in diagnosing bacterial co-infection.\u003c/p\u003e \u003cp\u003eOf the 182 patients included in the study, bacterial co-infection was diagnosed in 62 (34%) of them. The median admission PCT level was 0.3 ng/mL [0.11; 1.56] versus 0.25 ng/mL [0.11; 0.59] in the groups of patients with and without bacterial co-infection respectively. Admission PCT level greater or equal than 1.50 ng/mL was associated with bacterial co-infection (OR 2.43, 95% CI [1.11; 5.34]; p\u0026thinsp;=\u0026thinsp;0.026). Moreover, median PCT levels at day 3 were higher in the superinfection group (0.31 ng/mL [0.12; 1.36] versus 0.14 ng/mL [0.10; 0.44]) and in the group of patients who died at day 28 (\u0026gt;\u0026thinsp;1 ng/mL in 16.3% versus 8.6%).\u003c/p\u003e \u003cp\u003eDaily PCT measurements for patients with severe SARS-CoV2 pneumonia could help in antibiotic prescribing in the first days of ICU admission.\u003c/p\u003e","manuscriptTitle":"Usefulness of repeated procalcitonin measurements in the management of severe SARS-CoV-2 pneumonia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 09:35:20","doi":"10.21203/rs.3.rs-7808903/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-25T11:34:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T07:37:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-22T16:02:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7483863002283793956795387642628696053","date":"2026-02-19T19:53:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"320681493937841115746873527549742728246","date":"2026-02-19T11:37:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-19T10:45:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-19T10:39:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257035500833984720386444714575921303200","date":"2026-02-19T06:31:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273574161321731019693371572972984081459","date":"2026-02-19T04:47:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219469841724935464770866048075027975630","date":"2026-02-18T20:12:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"14532975143774552060515781875164285237","date":"2026-02-18T17:33:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T12:06:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147117742366231892255626359479281380697","date":"2026-02-17T08:44:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-17T04:42:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-10T11:18:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-16T13:59:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-15T07:46:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-15T07:43:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d7687387-358f-4a27-ba39-a3a56e7e3a3a","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63360145,"name":"Health sciences/Diseases"},{"id":63360146,"name":"Health sciences/Medical research"},{"id":63360147,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-05-08T06:38:05+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 09:35:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7808903","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7808903","identity":"rs-7808903","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}