This was a multicentre cohort study of immunocompetent adult patients admitted with CAP at three academic hospitals in Denmark between 1 November 2017 and 30 July 2020. The cohort is an extension of the Optimizing Treatment of Community-Acquired Pneumonia (optiCAP) cohort established by Fally et al. [22].

CAP was defined as the presence of a new infiltrate on the chest X-ray and at least one of the following signs and symptoms: cough, sputum production, dyspnea, core body temperature > 38.0˚C, and auscultatory findings of rales [22]. Patients were excluded if they had been admitted to hospital during the last 14 days, had Mycobacterium tuberculosis disease or were immunosuppressed, as previously described [22]. For this study, patients were also excluded if they had not received antibiotic treatment within 24 hours of hospital admission.

Covariates included in the study were age, sex, smoking, number of previous hospitalizations, hospitalization in a specialized ward, and comorbidities. Comorbidities included chronic obstructive pulmonary disease (COPD), congestive heart failure, diabetes, cerebrovascular disease, hypertension, ischemic heart disease, and cancer (Supplementary Table S1). A specialized ward was defined as one specializing in pulmonary medicine or infectious diseases.

We collected data on hematology and blood chemistry, initial chest X-ray, microbiological test results, and antibiotic treatment prior to and during hospitalization. Data on microbiological testing included results from UAT, oropharyngeal swabs, sputum cultures and blood cultures. All sputum samples underwent microscopy to assess their quality before being cultured.

Disease severity was defined according to the pneumonia severity score CURB-65 that includes confusion, uremia (urea > 7 mmol/l), respiratory rate > 30 per minute, systolic blood pressure < 90 mmHg or diastolic blood pressure ≤ 60 mmHg, and age ≥ 65 years, documented at hospital admission [23]. Patients were classified as having mild disease if they had a CURB-65 score of 0–2 and moderate-severe disease if they had a CURB-65 score of 3–5.

Other markers of disease severity were selected based on previous literature and included plasma C-reactive protein (CRP) levels, peripheral oxygen saturation, and the need for oxygen therapy, all documented at hospital admission (Supplementary Table S1) [24, 25].

Exposure was defined as having a UAT performed within the first 48 hours of hospital admission, regardless of whether patients were tested before or after initiating antibiotic treatment. The test used in our study was the Immuview® urinary antigen test, which detects all serotypes of S. pneumoniae as well as serogroup 1 of L. pneumophila in a single sample.

Individuals were followed from day 2 of hospitalization for up to 30 days. To prevent immortal time bias, follow-up began on day 2, ensuring patients were not followed before their exposure status was determined.

Broad-spectrum antibiotic treatment was defined as having received therapy with piperacillin/tazobactam, any cephalosporin, any carbapenem or amoxicillin/clavulanic acid (Supplementary Table S2). Atypical antibiotic coverage was defined as treatment targeting M. pneumoniae, L. pneumophila and C. pneumoniae and included any macrolide or respiratory fluoroquinolone, as specified in Supplementary Table S2.

The primary outcome was 30-day mortality. Secondary outcomes included broad-spectrum antibiotic treatment and atypical antibiotic coverage on day three of hospitalization and at discharge. Day three was chosen to reflect the typical timing for the evaluation of microbiological results, based on time of initial sample collection and usual turnaround times. Antibiotic treatment at discharge was included to account for patients discharged before day three. For the secondary outcomes, we exclusively looked at the most recently administered antibiotics. In our analysis of atypical coverage, we excluded any patients testing positive for L. pneumophila on UAT, as these patients are more likely to have received atypical coverage than the remaining cohort.

In addition, we compared primary and secondary outcomes in patients with a positive pneumococcal UAT, and UAT-negative patients. Due to the small size of this sub cohort, we only compared antibiotic treatment at discharge, thereby also including patients discharged before day three.

Data on age, sex, smoking, severity scores, microbiological testing, blood works, vital signs, chest x-ray results, number of previous hospitalizations, hospital ward, and antibiotic treatment were retrieved from electronic medical records. Comorbidity data were obtained from the Danish National Patient Registry [26].

Data on vital status following hospital stay were obtained from the Danish Civil Registration System [27].

We used descriptive statistics to illustrate the distribution of baseline characteristics.

Logistic regression was used to estimate odds ratios (OR) with 95% confidence intervals (CI) for both primary and secondary outcomes. To adjust for potentially confounding baseline covariates, we applied the propensity-score method for all outcomes, to match patients based on their likelihood of having a UAT performed. Patients were matched 1:1 using the nearest neighbor technique with a caliper of 0.2 [28]. Variables for the propensity-score matching were selected based on the literature and included age, sex, plasma CRP levels, peripheral oxygen saturation at admission, any antibiotic treatment prior to hospitalization, smoking status, multilobar infiltration on chest X-ray, CURB-65 score, oxygen treatment at admission, collection of other microbiological tests (blood cultures, sputum cultures and oropharyngeal swabs), number of previous hospitalizations, and certain comorbidities (Supplementary Table S1) [25, 29, 30].

For comparing antibiotic treatment in patients with a positive pneumococcal UAT and UAT-negative patients, we also included results from sputum and blood cultures in our propensity score (Supplementary Table S1). The propensity score method was employed for all analyses of primary and secondary outcomes.

Standardized mean differences (SMDs) were used to assess covariate balance between the tested and untested group before and after matching, with a cut-off of 0.1 to deem covariates unevenly distributed, as recommended by guidelines [31,32,33].

Subgroup analyses for the primary and secondary outcomes were conducted, stratifying subjects by age, plasma CRP levels, CURB-65 score, admission to a specialized hospital ward, and extent of infiltration on chest X-ray (Supplementary Table S3). These analyses aimed to explore whether the association between UAT and 30-day mortality and antibiotic treatment varied among patients in different clinical settings and with different levels of disease severity or frailty.

Lastly, we performed sensitivity analyses for all outcomes, where exposure was defined as having a UAT performed within 24 hours instead of 48 hours.

Since the number of patients with missing data was limited (7%), only complete case analysis was performed. The amount of missing data is shown in Fig. 1.

Flowchart of the study population. 208 patients (7%) were excluded due to missing data on antibiotic treatment (1.2%), oxygen saturation (0.03%), oxygen therapy (3.8%), plasma levels of C-reactive protein (1.8%) and CURB-65 -scores (0.7%). Abbreviations: UAT, urinary antigen test. Mild disease: CURB 65-score 0-2. Moderate-severe disease: CURB 65-score 3-5. Created using Miro.com

This study was approved by the Danish Patient Safety Authority (31-1521-101) and the Regional Data Protection Centre (P-2020-1116), with a waiver of informed consent in accordance with Danish legislation.