Rapid, season-specific PCR testing versus traditional diagnostics for pneumonia in the emergency department

Abstract

Background

Traditional culture-based diagnostics for emergency-department (ED) pneumonia are slow and season-agnostic, delaying targeted therapy. We evaluated whether season-tailored multiplex PCR panels accelerate pathogen identification and improve antibiotic stewardship.

Methods

In a single-center, prospective study, adults with radiographically confirmed pneumonia were enrolled consecutively and allocated by a rotating week-on/week-off schedule to either a seasonal PCR panel or conventional diagnostics. Primary outcomes were (i) time to final pathogen report and (ii) diagnostic yield (≥ 1 pathogen detected). Secondary outcomes included empiric-antibiotic appropriateness within 24 h, regimen changes ≤ 72 h, antibiotic duration, length of stay (LOS) and 30-day mortality.

Results

Among 282 analyzable patients (spring = 140; autumn–winter = 142), PCR slashed turnaround time from 48 h to 12 h in spring and from 50 h to 14 h in autumn–winter (median difference − 36 h, 95% CI: − 42 to − 30; p < 0.001). Diagnostic yield rose from 61.6 to 80.6% in spring and from 56.8 to 80.0% in winter (risk differences 19.0 pp and 22.3 pp, respectively; both p < 0.01). In the winter cohort, guideline-concordant empiric therapy increased (78.7% vs. 64.9%; +13.8 pp) and antibiotic changes ≤ 72 h fell (14.7% vs. 28.4%; − 13.7 pp). Mean antibiotic courses shortened by 1.5–1.7 days across seasons, while LOS showed a non-significant 1–2-day reduction. Thirty-day mortality did not differ. Effects were consistent in older adults (≥ 65 y) and patients with COPD.

Conclusions

Locally adapted, season-specific multiplex PCR panels deliver near-four-fold faster, higher-yield pathogen detection and support measurable stewardship gains without compromising safety. Implementation in other settings should consider local pathogen seasonality, workflow, and cost structures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-025-03843-2.

Introduction

Pneumonia significantly impacts global health, being the leading infectious cause of mortality, particularly among vulnerable populations such as children and the elderly, with over 2.5 million deaths annually [1, 2]. Accurate and rapid diagnosis in emergency settings is crucial for effective management. Advanced imaging techniques, including chest X-rays and emerging methods like bedside ultrasound, are essential for timely identification of pneumonia [3, 4].

Beside the diagnosis of pneumonia, timely identification of pathogens causing the disease is critical for pneumonia management. Traditional diagnostic methods for pneumonia face significant shortcomings such as delayed results and limited sensitivity. These methods often fail to accurately distinguish between bacterial and viral causes, leading to challenges in appropriate treatment and contributing to antimicrobial resistance [5, 6]. While imaging techniques have gained prominence, they still rely heavily on subjective interpretation and may not provide timely results [7]. Additionally, microbiological tests are often insensitive, necessitating empirical antibiotic therapy, which can complicate management strategies [8]. Emerging techniques, such as lung ultrasonography and novel biomarkers, show promise but require further validation to enhance diagnostic accuracy and speed [5, 9]. Overall, there is a pressing need for more rapid, non-invasive diagnostic tools to improve patient outcomes in pneumonia [7].

Traditional methods for identifying pathogens causing pneumonia primarily include culture, microscopy, and serological tests, but these approaches often face limitations. Cultures, while historically the gold standard, frequently yield low detection rates due to prior antibiotic administration and the difficulty in obtaining high-quality samples [10]. Microscopy, including Gram staining, has shown poor agreement with molecular methods, particularly for bacterial detection [11]. In contrast, polymerase chain reaction (PCR) techniques have emerged as superior alternatives, significantly enhancing pathogen detection rates from 42 to 69% in severe cases [12]. PCR allows for the identification of both viral and bacterial pathogens [13]. Additionally, novel microfluidic systems have been developed to facilitate rapid, parallel identification of multiple pathogens, demonstrating high sensitivity and specificity [14]. Thus, while traditional methods remain in use, the integration of molecular techniques is crucial for accurate pneumonia diagnosis.

The identification of pneumonia pathogens through polymerase chain reaction (PCR) and next-generation sequencing (NGS) offers significant advantages over traditional methods. PCR, particularly multiplex PCR, allows for the simultaneous detection of multiple bacterial pathogens with high sensitivity and specificity, as demonstrated by a study that achieved 80–100% sensitivity across various bacteria [15]. NGS, especially metagenomic NGS (mNGS), enhances diagnostic yield by detecting a broader range of pathogens, including bacteria, viruses, and fungi, which conventional cultures often miss. For instance, mNGS identified pathogens in 86% of cancer patients with pneumonia, compared to 57% with traditional methods [16]. Additionally, NGS can reveal antimicrobial resistance genes, guiding appropriate treatment decisions [16, 17]. Overall, these molecular techniques significantly improve the speed and accuracy of pneumonia diagnosis, facilitating timely and tailored therapeutic interventions [18, 19].

Pathogen prevalence exhibits significant seasonal variation, influenced by environmental factors and human behavior. For instance, respiratory pathogens like influenza peak in winter, while diarrheal pathogens such as enterotoxigenic E. coli and Cryptosporidium are more prevalent during the rainy season in tropical regions [20, 21]. This seasonal pattern underscores the necessity for tailored PCR panels, which enhance diagnostic accuracy by detecting multiple pathogens simultaneously, thus addressing the high rate of undiagnosed cases in acute diarrhea [22]. Multiplex PCR not only improves sensitivity compared to traditional methods but also allows for timely public health responses, particularly in regions where specific pathogens dominate during certain seasons [23, 24]. By aligning diagnostic tools with seasonal epidemiology, healthcare providers can better manage outbreaks and allocate resources effectively.

The objective of this study is to evaluate the effectiveness of seasonal PCR test panels compared to traditional diagnostic methods in detecting respiratory pathogens in pneumonia patients across different seasons. The study aims to determine whether PCR panels achieve comparable pathogen detection rates, such as for Influenza A/B in winter and Rhinovirus/Enterovirus in spring, while also reducing the time to diagnosis. Additionally, it seeks to assess the clinical impact of PCR panels on decision-making, including the appropriateness of antibiotic use and overall patient management, to highlight their potential to improve outcomes in the emergency department.

Participants and methods

Study design and setting

We performed a prospective, single‑center, quasi‑randomized comparative study in the Emergency Department of Shanghai Public Health Clinical Center. The trial period ran from January 2022 to October 2024 and encompassed two predefined respiratory‑infection seasons. The study was approved by the Institutional Review Board (approval 2023‑S072‑01). All procedures complied with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment. Local meteorological data for Shanghai show that spring (March-May) is characterized by a mean ambient temperature of approximate 17 °C, average relative humidity 70%, and prevailing wind speeds of 7 m/s; in contrast, autumn–winter (October-February) averages 11 °C with comparable humidity (71%) and marginally lower winds (6 m/s).

Participant eligibility, recruitment, and allocation

Adults presenting with new respiratory symptoms ≤ 10 days and imaging‑confirmed pulmonary infiltrate were screened consecutively.

Inclusion criteria

1), Age ≥18 years; 2), Suspected pneumonia based on clinical presentation (new or worsening respiratory symptoms such as cough, dyspnea, sputum production) or fever ≥38 °C; 3), Radiographic evidence of new or worsening infiltrate consistent with pneumonia on chest X-ray or computed tomography CT; 4), Symptom onset within 10 days of the ED visit.

Exclusion criteria

1), Prolonged antibiotic exposure (>72 hours of systemic antibiotic therapy) before ED presentation; 2) Severely immunocompromised state (absolute neutrophil count < 500 cells/µL, AIDS with CD4 < 50 cells/µL, or solid organ transplant on prophylaxis); 3), Non infectious infiltrates (cardiogenic oedema, vasculitis, malignancy); 4), Unable or unwilling to provide written informed consent.

Eligible adults were screened and enrolled consecutively as they presented. Allocation followed a pre-specified rotating-week schedule: calendar weeks were alternately designated ‘PCR week’ or ‘Traditional week’ by a computer-generated list locked before recruitment commenced. Consequently, all participants in a given week received the same diagnostic pathway, after which the allocation switched for the next seven-day block. This quasi-randomized approach minimized selection bias while preserving emergency-department workflow. Treating clinicians were aware of the current week’s pathway; however, infectious-disease adjudicators and statistical analysts remained blinded to allocation.

Sample size calculation

A power analysis was conducted before study initiation, assuming a 15–20% improvement in pathogen detection rates or a 12–24-hour reduction in time to pathogen result with PCR panels: significance level (α): 0.05 (two-sided), power (1 − β): 80%, anticipated dropout or incomplete data: 10%.

Based on these assumptions, enrolling approximately 75 patients per arm for each season was estimated to detect clinically meaningful differences in diagnostic turnaround and detection rates.

Operational definition of seasonality and PCRpanel development

Historical surveillance data from the Shanghai Municipal CDC showed two distinct peaks in respiratorypathogen circulation: Spring (1 March– 31 May) and AutumnWinter (1 October– 28 February). These windows therefore defined the two study seasons; the intervening lowincidence summer period was excluded. Two distinct seasonal PCR panels were designed based on local surveillance data and known pathogen circulation patterns (Table 1). SARS‑CoV‑2 was not incorporated into either seasonal panel because, throughout the study period, every ED attendee underwent mandatory stand‑alone triage testing for SARS‑CoV‑2 under Shanghai infection‑control policy. Including the same target in the multiplex assay would have duplicated testing, increased per‑sample cost, and—owing to stricter biosafety workflows for SARS‑CoV‑2—significantly slowed batch processing of the seasonal panel.

Table 1.

Proposed seasonal PCR test panels for pneumonia

	Spring	Winter
Virus	Influenza A/B Parainfluenza Rhinovirus/Enterovirus Adenovirus	Influenza A/B Human Metapneumovirus Rhinovirus/Enterovirus Coronavirus (seasonal, non–SARS-CoV-2) Respiratory Syncytial Virus A/B
Bacteria	Streptococcus pneumoniae Haemophilus influenzae Mycoplasma pneumoniae Chlamydia pneumoniae Legionella pneumophila	Streptococcus pneumoniae Haemophilus influenzae Staphylococcus aureus Mycoplasma pneumoniae Chlamydia pneumoniae Legionella pneumophila Klebsiella pneumoniae

Traditional diagnostic protocol

Sputum Gram stain and culture on blood, chocolate, and MacConkey agar, incubated up to 72 h. Blood cultures (2–3 sets) if sepsis was suspected, monitored by an automated system for up to 5 days. Urinary antigens for Streptococcus pneumoniae or Legionella pneumophila, ordered at physician discretion. Rapid influenza/RSV antigen tests if clinically indicated (e.g., outbreak suspicion, typical influenza-like illness). Typically required 24–72 h for final bacterial identification, depending on culture growth.

Season-Specific PCR panel

Nasopharyngeal swabs (viral transport medium) for viral detection. Sputum or bronchoalveolar lavage (BAL) for bacterial detection. BAL was reserved for critically ill or intubated patients. PCR testing was performed in a dedicated molecular microbiology lab, with typical reporting in 8–16 h depending on batching.

PCR panel assay development

An infectious disease and microbiology working group at our institution designed two distinct multiplex PCR panels—one for spring and another for autumn–winter—based on five years of local surveillance data. Pathogens meeting a minimum prevalence threshold of 5% in a given season were prioritized to maximize diagnostic yield and cost-effectiveness. Each panel aimed to cover the most commonly circulating viral and bacterial agents, including newly emergent pathogens of public health concern. The Spring PCR Panel includes Influenza A/B, Parainfluenza virus, Rhinovirus/Enterovirus, Adenovirus, and five bacterial species (Streptococcus pneumoniae, Haemophilus influenzae, Mycoplasma pneumoniae, Chlamydia pneumoniae, Legionella pneumophila). The Autumn–Winter PCR Panel added coverage for RSV A/B, Human Metapneumovirus, seasonal human Coronaviruses, Staphylococcus aureus, and Klebsiella pneumoniae, while retaining several organisms from the spring panel.

All primer were adapted from published references or CDC guidelines, then validated in-house for specificity against a local clinical isolate collection. Final sequences and concentrations are provided in Supplementary Table S1.

Genomic RNA/DNA was extracted from 200 µL of nasopharyngeal swab using the MagNA Pure 96 System with the DNA and Viral NA Small‑Volume kit (Cat# 06543588001, Roche Diagnostics, Mannheim, Germany). Multiplex real‑time PCR was performed on a Rotor‑Gene Q 5‑plex HRM instrument (QIAGEN, Hilden, Germany) in 25 µL reactions containing 12.5 µL QIAGEN Multiplex PCR Master Mix, 0.4 µM of each primer, 0.2 µM hydrolysis probe (Sangon Biotech, Shanghai), 2.5 µL template and nuclease‑free water. Cycling conditions were 95 °C × 3 min, followed by 45 cycles of 95 °C × 15 s and 60 °C × 45 s with data acquisition on the green and yellow channels. Limits of detection, determined with quantified reference panels (AcroMetrix™), ranged from 2 × 10³ to 5 × 10³ genome copies per mL with intra‑run CV < 4%. The internal human RNase-P gene served as an endogenous extraction control to confirm sample adequacy. External negative and positive controls were run in parallel for each batch, including no-template controls (sterile water) and reference strain extracts. Cycle threshold (Ct) cutoffs were generally set at ≤ 40 for positivity, though borderline cases (Ct 38–40) were repeated once to rule out false positives.

Clinical management and antibiotic stewardship

All patients received standard-of-care supportive therapy and initial empiric antibiotic therapy in accordance with the 2021 Chinese CAP guidelines. Antibiotics could be modified early based on rapid test results (PCR or rapid antigen) or later based on conventional culture findings and clinical evolution. We defined an “antibiotic regimen change” as any escalation, de-escalation, or class switch of antimicrobial therapy within 72 h of admission. Reasons for these modifications were recorded prospectively and included: (1) de-escalation upon identification of a primarily viral etiology or upon clinical/laboratory indicators suggesting no bacterial coinfection; (2) escalation or coverage switch driven by bacterial culture results or PCR detection of pathogens not originally covered; (3) resistance-related changes following susceptibility findings on culture; and (4) clinical deterioration necessitating broader-spectrum therapy. To ensure consistency, antibiotic decisions were guided by local pneumonia treatment protocols, and in complex or severe cases, consultative input from an infectious disease specialist was obtained.

Data collection and outcome definitions

All clinical and laboratory data were recorded in a secure electronic database. Time zero was defined as the moment of initial specimen collection in the ED.

Primary outcomes

1), Time to final pathogen result: hours from collection of the first diagnostic sample to the moment the definitive laboratory report was posted and electronically signed off. 2), Diagnostic yield: proportion of participants with ≥ 1 respiratory pathogen identified.

Secondary outcomes

1), Appropriate empiric antibiotic within 24 h: concordance with 2021 Chinese CAP guidelines or, when a pathogen result was already available, pathogentargeted coverage (assessed by two blinded reviewers; κ = 0.86). 2), Change of antibiotic regimen within 72 h: any escalation, deescalation, or substitution. 3), Total antibiotic duration: calendar days of systemic antibiotic therapy from first ED dose to the last inpatient dose of the index admission. 4), Hospital length of stay (LOS): admission timestamp to discharge timestamp (days, one decimal place). 5), 30 day allcause mortality: death within 30 days of ED index visit, verified via electronic records or telephone followup.

Subgroup analyses

Two highrisk groups were analyzed apriori because of their distinct pathogen spectra and management challenges: 1), Older adults ≥ 65 years old: expected higher pneumonia severity and distinct pathogen distribution. 2), Patients with physiciandiagnosed COPD: known for exacerbations triggered by both viral and bacterial infections. The study was powered primarily to detect improvements in diagnostic turnaround and pathogen detection in the overall sample.

Statistical analysis

Continuous variables are reported as mean ± SD if normally distributed or as median (interquartile range, IQR) otherwise. We used Student’s t-tests or Mann–Whitney U-tests for continuous variables, depending on normality. Categorical variables are expressed as frequencies (percentages) and compared using chi-square tests or Fisher’s exact tests. For 30-day mortality, we constructed Kaplan–Meier survival curves and applied log-rank tests. Hazard ratios for mortality were further assessed via Cox proportional hazards models, adjusted for age, CURB-65 score, and major comorbidities. All tests were two-sided with a significance threshold of p < 0.05. We adhered to SAMPL guidelines for the reporting of statistical methods.

Result

Seasonal variation in PCR test panels for pneumonia diagnosis

The seasonal PCR panels were designed to target pathogens known to be prevalent during specific times of the year (Table 1). For each season we applied a ≥ 5% prevalence rule, derived from five-year (2017–2021) respiratory-culture surveillance at our center. In spring, the viral targets included Influenza A/B, Parainfluenza, Rhinovirus/Enterovirus, and Adenovirus, whereas the winter panel further incorporated Human Metapneumovirus, seasonal Coronaviruses, and RSV A/B. Bacterial targets were also season-specific: for spring, Streptococcus pneumoniae, Haemophilus influenzae, Mycoplasma pneumoniae, Chlamydia pneumoniae, and Legionella pneumophila were tested, while the winter panel additionally included Staphylococcus aureus and Klebsiella pneumoniae. This seasonal approach was intended to enhance diagnostic yield by aligning the test menu with local epidemiological data on circulating pathogens.

Participant flow and baseline characteristics

During the January 2022 to October 2024 study period, we screened a total of 356 adults presenting to the ED with suspected pneumonia. (Fig. 1). Twelve were withdrawn postenrolment for protocoldefined reasons (repeat ED visit within 30 d or imaging reinterpretation as noninfectious), leaving 282 participants (96.0%) for the intentiontodiagnose analysis. A total of 140 participants were enrolled in the spring cohort, and 142 in the autumn–winter cohort. Baseline and outcome data were complete for all 282 patients (no missing or censored data for primary outcomes) (Table 2).

Fig. 1.

Flowchart for patient screening, eligibility, allocation. Of 356 adults screened, 304 fulfilled inclusion criteria. Ten declined consents, and 12 were excluded after enrolment (non-infectious infiltrate = 5; imaging reinterpretation = 4; repeat ED visit within 30 days = 3). The remaining 282 participants constituted the ITT population. They were split a-priori into a spring cohort (n = 140) and an autumn–winter cohort (n = 142); each cohort was allocated by rotating-week schedule to the season-tailored multiplex PCR panel or to conventional diagnostics. Final numbers analyzed by arm are shown within each box

Table 2.

Baseline clinical characteristics

	Spring			Autumn-Winter
	Traditional (n = 73)	PCR panel (n = 72)	P value	Traditional (n = 74)	PCR panel (n = 75)	P value
Age, years, mean (SD)	62.1 (13.5)	63.6 (12.7)	0.55	64.8 (13.0)	63.9 (13.2)	0.64
Gender			0.77			0.78
Male, n (%)	40 (54.8%)	39 (54.2%)		38 (51.4%)	41 (54.7%)
Female, n (%)	33 (45.2%)	33 (45.8%)		36 (48.6%)	34 (45.3%)
Lifestyle/Exposure			0.79			0.82
Current smoker, n (%)	28 (38.4%)	30 (41.7%)		32 (43.2%)	31 (41.3%)
Recent viral exposure, n (%)	18 (24.7%)	20 (27.8%)		19 (25.7%)	21 (28.0%)
Clinical Presentation
Symptom duration before ED visit, days, median	5 (3–7)	6 (4–7)	0.48	5 (3–6)	6 (4–8)	0.48
Fever ≥ 38.0 °C, n (%)	45 (61.6%)	46 (63.9%)	0.88	48 (64.9%)	49 (65.3%)	0.64
Oxygen saturation < 92% on room air, n (%)	22 (30.1%)	23 (31.9%)	0.79	25 (33.8%)	26 (34.7%)	0.84
Bilateral infiltrates on initial CXR, n (%)	15 (20.5%)	16 (22.2%)	0.53	19 (25.7%)	18 (24.0%)	0.80
CURB-65 score ≥ 2, n (%)	9 (12.3%)	10 (13.9%)	0.91	11 (14.9%)	10 (13.3%)	0.92

As shown in Table 2, participants had a mean age of 63.6 years (SD, 13.1), and 53.6% (151/282) were men. COPD was the most common comorbidity (14.9%), followed by type 2 diabetes (13.5%), with no significant differences between the PCR and traditional arms within each season. About one-third presented with oxygen saturation below 92%, and 14.5% had a CURB-65 score of 2 or higher. Clinical severity, radiographic features (e.g., bilateral infiltrates), and lifestyle factors (e.g., smoking) were well-balanced between groups (all p > 0.10).

Primary outcomes

In Spring, the seasonal PCR arm achieved a median turnaround of 12 h (IQR 8–16) compared with 48 h (36–60) in the Traditional arm; the HodgesLehmann median difference was − 36 h (95% CI: − 40 to − 32; p < 0.001) (Table 3). A similar reduction was observed in AutumnWinter (14 h vs. 50 h; median difference − 36 h, 95%: CI − 42 to − 30; p < 0.001) (Table 3). The proportion of participants with ≥ 1 pathogen detected increased from 61.6 to 80.6% in Spring (risk difference 19.0%, 95% CI: 4.5–33.3) and from 56.8 to 80.0% in AutumnWinter (risk difference 22.3%, 95% CI: 8.8–37.7) (Table 3).

Table 3.

Primary outcome measures

	Spring				Autumn-Winter
	Traditional (n = 73)	PCR (n = 72)	Effect size (95% CI)	P	Traditional (n = 74)	PCR (n = 75)	Effect size (95% CI)	P
Time to Final Pathogen Result, hours, median (IQR)	48 (36–60)	12 (8–16)	–36 h (–40 to − 32)	< 0.001	50 (38–60)	14 (10–20)	–36 h (–42 to − 30)	< 0.001
Any Pathogen Detected, n (%)	45 (61.6%)	58 (80.6%)	+ 19.0 (4.5 to 33.3)	0.029	42 (56.8%)	60 (80.0%)	+ 22.3 (8.8 to 37.7)	0.006

Secondary outcomes

For the secondary outcomes, clinically meaningful—though season-dependent—differences emerged (Table 4). In autumn–winter, rapid PCR availability improved stewardship: guideline-concordant empiric therapy rose from 64.9 to 78.7% (absolute increase + 13.8pp, 95% CI: − 0.5 to 27.1; p = 0.041) and the need to alter antibiotics within 72 h almost halved (28.4% vs. 14.7%, − 13.7pp, 95% CI: − 26.7 to − 0.7; p = 0.046). Mean treatment duration shortened by 1.7 days (–2.73 to − 0.67; p = 0.02) and median length of stay trended two days lower (–2 d, − 4 to 0; p = 0.051). Mortality was numerically lower (5.3% vs. 9.5%), but the difference was not significant (–4.1pp, − 12.5 to 4.3). In spring, directional effects were similar yet smaller: appropriate empiric cover increased by 12.1pp (68.5–80.6%, − 2.0 to 26.1), regimen changes fell by 10.7pp, and mean antibiotic duration dropped 1.5 days (–2.48 to − 0.52; p = 0.04); however, other endpoints did not reach the 0.05 threshold. Across both seasons, 30-day mortality remained comparable between strategies.

Table 4.

Prespecified secondary outcomes by season

	Spring				Autumn-Winter
	Traditional	PCR	Effect size (95% CI)	P	Traditional	PCR	Effect size (95% CI)	P
Appropriate empiric antibiotic ≤ 24 h, n (%)	50 (68.5%)	58 (80.6%)	+ 12.1 (–2.0 to 26.1)	0.18	48 (64.9%)	59 (78.7%)	+ 13.8 (–0.5 to 27.1)	0.041
Antibiotic regimen change ≤ 72 h, n (%)	20 (27.4%)	12 (16.7%)	–10.7 (–24.1 to 2.6)	0.12	21 (28.4%)	11 (14.7%)	–13.7 (–26.7 to − 0.7)	0.046
Antibiotic duration, days (mean ± SD)	10.2 ± 3.1	8.7 ± 2.9	–1.5 (–2.48 to − 0.52)	0.04	11.1 ± 3.4	9.4 ± 3.0	–1.7 (–2.73 to − 0.67)	0.02
Hospital length of stay, days, Median (IQR)	8 (6–10)	7 (5–9)	–1 (–3 to 0)	0.08	9 (7–12)	7 (5–9)	–2 (–4 to 0)	0.051
30-day all-cause mortality, n (%)	5 (6.8%)	3 (4.2%)	–2.6 (–10.1 to 4.7)	0.47	7 (9.5%)	4 (5.3%)	–4.1 (–12.5 to 4.3)	0.35

Clinical outcomes in participants with no pathogen detected

Among the 89 participants in whom no pathogen was identified—65 in the Traditional arm and 24 in the PCR arm—clinical trajectories were largely comparable between diagnostic strategies (Supplementary Table S2). Guideline-concordant empiric therapy within 24 h occurred in 63% vs. 67% of cases (risk difference + 3.6%-points, 95% CI: − 17.8 to 25.0; p = 0.80). Mean antibiotic duration, however, was 1.7 days shorter after PCR testing (9.3 ± 3.0 d vs. 11.0 ± 3.5 d; difference − 1.7 d, 95% CI: − 3.1 to − 0.3; p = 0.02). Median hospital stay showed a non-significant one-day reduction (8 d vs. 9 d; Hodges-Lehmann − 1 d, 95% CI: − 3 to 1; p = 0.18), and 30-day mortality remained low and statistically indistinguishable (4.2% vs. 7.7%; risk difference − 3.5 pp, 95% CI: − 13.5 to 6.5; p = 0.68). These findings indicate that, even when no organism is recovered, rapid PCR reporting fosters slightly shorter antibiotic courses without adversely affecting other outcomes.

Enhanced pathogen detection with PCR panels across seasons

For viruses, increases were noted for Influenza A/B (spring: 9.6% vs. 18.1%; autumn-winter: 20.3% vs. 33.3%) and RSV A/B in winter (13.5% vs. 24.0%) (Table 5). Although not all differences reached statistical significance, the trend favored PCR for most viral targets (Table 5). Among bacterial pathogens, Streptococcus pneumoniae detection improved from 16.4 to 26.4% (p = 0.09) in spring and from 18.9 to 32.0% (p = 0.04) in autumn-winter (Table 5). Notably, Staphylococcus aureus detection in winter nearly doubled (9.5% vs. 21.3%, p = 0.03). These findings highlight that seasonal PCR panels not only accelerate pathogen identification but also increase overall detection rates, aligning diagnostics with known season-specific respiratory pathogen profiles (Table 5).

Table 5.

Pathogen detection across spring and winter

	Spring			Autumn-Winter
	Traditional (n = 73)	PCR (n = 72)	P value	Traditional (n = 74)	PCR (n = 75)	P value
VIRUSES
Influenza A/B	7 (9.6%)	13 (18.1%)	0.18	15 (20.3%)	25 (33.3%)	0.07
Parainfluenza	5 (6.8%)	11 (15.3%)	0.10	0	—	—
Rhinovirus/Enterovirus	8 (11.0%)	15 (20.8%)	0.12	6 (8.1%)	12 (16.0%)	0.12
Adenovirus	6 (8.2%)	10 (13.9%)	0.28	1 (1.3%)	—	—
Human Metapneumovirus	0	—	—	5 (6.8%)	9 (12.0%)	0.26
Coronavirus	0	—	—	4 (5.4%)	10 (13.3%)	0.09
Respiratory Syncytial Virus A/B	0	—	—	10 (13.5%)	18 (24.0%)	0.15
BACTERIA
Streptococcus pneumoniae	12 (16.4%)	19 (26.4%)	0.09	14 (18.9%)	24 (32.0%)	0.04
Haemophilus influenzae	7 (9.6%)	14 (19.4%)	0.07	8 (10.8%)	14 (18.7%)	0.14
Staphylococcus aureus	0	—	—	7 (9.5%)	16 (21.3%)	0.03
Mycoplasma pneumoniae	4 (5.5%)	9 (12.5%)	0.16	3 (4.1%)	7 (9.3%)	0.18
Chlamydia pneumoniae	3 (4.1%)	7 (9.7%)	0.20	2 (2.7)	6 (8.0%)	0.16
Legionella pneumophila	2 (2.7%)	5 (6.9%)	0.25	3 (4.1%)	5 (6.7%)	0.47
Klebsiella pneumoniae	1 (1.3%)	—	—	4 (5.4%)	9 (12.0%)	0.15

Subgroup analysis for seasonal PCR panel and traditional diagnostic methods

A detailed subgroup analysis was performed to examine whether certain high-risk populations derived particular benefit from the seasonal PCR panel (Table 6). Three key subgroups were evaluated: elderly patients (≥ 65 years old), and those with chronic obstructive pulmonary disease (COPD).

Table 6.

Subgroup analysis: seasonal PCR panel vs. Traditional diagnostic methods

Subgroup/Outcome Measure	Traditional	Seasonal PCR	P value
Elderly (≥ 65 years)	n = 67	n = 71
Time to final pathogen result (hours), median (IQR)	48 (36–60)	14 (10–20)	< 0.001
Pathogen detection, n (%)	38/67 (56.7%)	51/71 (71.8%)	0.040
Change of antibiotic regimen within 72 h, n (%)	18/67 (26.9%)	10/71 (14.1%)	0.070
30-day mortality, n (%)	5/67 (7.5%)	4/71 (5.6%)	0.680
Hospital length of stay (days), median (IQR)	8 (6–10)	7 (5–9)	0.050
COPD	n = 23	n = 19
Time to final pathogen result (hours), median (IQR)	52 (40–68)	20 (12–30)	< 0.001
Pathogen detection, n (%)	12/23 (52.2%)	14/19 (73.7%)	0.130
Change of antibiotic regimen within 72 h, n (%)	9/23 (39.1%)	3/19 (15.8%)	0.090
30-day mortality, n (%)	3/23 (13.0)	2/19 (10.5)	0.820
Hospital length of stay (days), median (IQR)	9 (7–12)	8 (6–10)	0.110

Among elderly patients, the median time to final pathogen result decreased from 48 h (IQR, 36–60) to 14 h (IQR, 10–20; p < 0.001). Pathogen detection improved significantly (56.7% vs. 71.8%; p = 0.040). Although 30-day mortality was somewhat lower with PCR (5.6% vs. 7.5%), the difference was not statistically significant (p = 0.680). The PCR group also showed a trend toward shorter hospital stays (median 7 vs. 8 days; p = 0.050) (Table 6).

In patients with COPD, time to final pathogen result was significantly shorter with PCR (median 20 vs. 52 h; p < 0.001). While detection rates were higher in the PCR group (73.7% vs. 52.2%), the difference did not reach significance (p = 0.130). Antibiotic regimen changes within 72 h were less frequent in the PCR arm (15.8% vs. 39.1%; p = 0.090), suggesting a potential benefit from rapid pathogen identification. Mortality and length of stay were numerically lower in the PCR group but lacked statistical significance (Table 6).

Discussion

Our prospective comparison showed that deploying season-tailored multiplex PCR in the emergency department cut the median time to a definitive microbiology report from roughly two days to half a day, raised overall pathogen yield by about 20%, and translated these diagnostic gains into tangible stewardship benefits—earlier guideline-concordant therapy, fewer empiric regimen switches, and 1- to 2-day shorter antibiotic courses—without increasing adverse events. Despite these process improvements, the rapid-testing strategy did not reduce 30-day mortality or produce a statistically significant shortening of hospital stay, underscoring that accelerated diagnosis and refined antimicrobial use, while valuable in their own right, may be insufficient alone to shift hard clinical end points in a single-center cohort of moderate sample size.

Our findings demonstrate that a season-specific multiplex PCR strategy significantly expedites pathogen detection and improves certain aspects of antimicrobial stewardship, aligning with the broader literature on rapid molecular diagnostics in pneumonia. Several studies have reported substantial gains in sensitivity and speed for detecting pathogens like S. pneumoniae, M. pneumoniae, C. pneumoniae, and L. pneumophila when using multiplex PCR, with detection rates in community-acquired pneumonia often increasing from around 23–46% with traditional methods to 41–68% with PCR-based tests [25, 26]. Consistent with these data, our study found that the proportion of patients with at least one pathogen identified rose substantially in both spring (61.6% vs. 80.6%) and autumn–winter cohorts (56.8% vs. 80.0%). While some studies have observed mortality benefits with faster pathogen identification [27, 28], our results, in line with others [29, 30], revealed no significant difference in 30-day mortality. There remains ongoing debate about the direct impact of rapid diagnostics on survival outcomes.

One of the distinguishing features of our approach is tailoring PCR panels to predominant seasonal pathogens, which corroborates data showing that targeted tests for high-prevalence organisms can be more effective than “mega-panels” in certain clinical and epidemiological contexts [31–33]. While broad year-round panels can detect a wide array of viruses and bacteria, they may include many low-prevalence targets. Our seasonal panel instead focuses on organisms like Influenza A/B, RSV, and S. pneumoniae during peak months, similar to approaches in other settings where local epidemiology guides assay selection [34–36]. In our study, this strategy aligned with established seasonal trends, offering clinicians a rapid and relevant diagnostic tool that uncovered a higher detection rate of S. aureus and K. pneumoniae in winter—an outcome reported in comparable studies emphasizing seasonally driven pneumonia surges [37, 38].

Several potential mechanisms may explain the observed benefits in antibiotic stewardship. First, rapid identification of bacterial pathogens facilitates earlier targeted therapy, reducing empiric broad-spectrum regimens. Our data was supported by findings from studies where multiplex PCR significantly improved time to appropriate antibiotic administration for infections like S. pneumoniae and L. pneumophila, thereby reducing antibiotic exposure and potentially enhancing patient outcomes [39, 40]. Second, the ability to quickly detect viral etiologies (e.g., Influenza A/B and RSV) often led to the de-escalation of antibiotics or initiation of antivirals in our population, consistent with reports of increased antiviral prescriptions and decreased antibiotic usage following rapid influenza PCR testing [41, 42]. By focusing on pathogens most likely to circulate during a given season, our approach potentially improves cost-effectiveness relative to broad panels [43–45].

Despite these positive findings, certain endpoints, such as 30-day mortality and hospital length of stay, did not reach statistical significance or only trended favorably—an observation that parallels results from other rapid diagnostic trials [29, 30, 46–48]. One explanation could be that mortality and length of stay are influenced by a range of factors beyond timelier pathogen detection, including comorbidities, severity of illness, and local treatment protocols. Furthermore, our study confirms that while PCR testing improved pathogen detection and antibiotic stewardship, it may not guarantee major mortality benefits in every clinical cohort—particularly in populations like those with advanced comorbidities or COPD, where treatment nuances and disease severity may overshadow the gains from faster diagnostics [47, 49].

Finally, it is important to acknowledge the complexity surrounding negative or inconclusive PCR results. Similar to what has been reported in other works [34, 50], we observed that clinicians were sometimes reluctant to de-escalate antibiotics absent a confirmed alternative diagnosis, limiting the full potential of rapid testing to curb unnecessary antibiotic use. Still, the consistent finding that antibiotic duration was shortened—even for patients without a confirmed pathogen—highlights the practical utility of having robust, same-day diagnostic information at the point of care. As the body of evidence evolves, further large-scale and multicenter studies are warranted to clarify the precise conditions under which season-specific PCR strategies most strongly influence outcomes such as mortality, hospital stay, and broader public health metrics.

Our study has several limitations, including its single-center design and quasi-randomized, rotating-week allocation scheme, which may limit external generalizability and introduce potential biases. In addition, the exclusion of severely immunocompromised patients and the local pathogen ecology may restrict the applicability of our findings to other populations and settings. Furthermore, focusing on a defined seasonal panel could miss atypical organisms outside our targeted pathogen list, and evolving epidemiology over the study period might affect detection rates for emerging strains. Future efforts should include multi-center trials across diverse regions and seasons to validate these results and assess cost-effectiveness on a broader scale.

In conclusion, our findings demonstrate the potential of season-specific PCR panels in accelerating pathogen detection, improving diagnostic yield, and supporting more targeted antibiotic stewardship practices. While the faster turnaround time and enhanced pathogen identification undoubtedly contribute to a more informed clinical decision-making process, further large-scale, multi-center investigations are warranted to determine whether these benefits translate into meaningful reductions in mortality or broader clinical endpoints.

Abbreviations

PCR

Polymerase Chain Reaction

ED

Emergency Department

CT

Computed Tomography

CXR

Chest X-Ray

BAL

Bronchoalveolar Lavage

IQR

Interquartile Range

SD

Standard Deviation

CURB-65

(A pneumonia severity assessment tool that evaluates Confusion, Urea, Respiratory rate, Blood pressure, and age ≥65)

IRB

Institutional Review Board

HIV

Human Immunodeficiency Virus

RSV

Respiratory Syncytial Virus

NGS

Next-Generation Sequencing

mNGS

Metagenomic Next-Generation Sequencing

COPD

Chronic Obstructive Pulmonary Disease

SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus 2

Authors’ contributions

The authors confirm contribution to the paper as follows: study conception and design: Q.L.; data collection: Y. Y.; analysis and interpretation of results: Y. Y.; draft manuscript preparation: Q.L., Y. Y. All authors reviewed the results and approved the final version of the manuscript.

Funding

N/A.

Data availability

Data sets generated during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Ethical approval was obtained from the hospital’s institutional review board Shanghai Public Health Clinical Center (2023-S072-01). All procedures complied with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.