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. 2024 Dec 11;19(12):e0311201. doi: 10.1371/journal.pone.0311201

Accuracy of the diagnosis of pneumonia in Canadian pediatric emergency departments: A prospective cohort study

Joan L Robinson 1,*, James D Kellner 2, Jennifer Crotts 2, Gabino Travassos 2, Guanmin Chen 3, Valerie G Kirk 2, Martin Pusic 4, Martin Reed 5, Sarah Reid 6, Michael Weinstein 7, Ravi Bhargava 1, Maala Bhatt 6, Kathy Boutis 7, Sarah Curtis 1, Serge Gouin 8, Tim Lynch 9, Richard van Wylick 10, David W Johnson 2
Editor: Maurizio Balbi11
PMCID: PMC11633949  PMID: 39661638

Abstract

Background

The diagnosis of pediatric pneumonia and determination of the likely pathogen are complicated as the clinical picture overlaps with other respiratory illnesses, interpretation of radiographs is subjective, and laboratory results are rarely diagnostic. This study was designed to describe the relative rates of bacterial and viral pneumonia in the pediatric Emergency Department (ED), determine the accuracy of pediatric ED physicians’ ability to diagnose pneumonia and distinguish bacterial from viral etiology, and to determine clinical and laboratory predictors of bacterial pneumonia.

Methods

Children 3 months to 16 years of age presenting to seven Canadian pediatric EDs before the COVID-19 pandemic with fever and cough who had a chest radiograph performed for possible pneumonia were enrolled and underwent standardized clinical investigations. An expert panel was convened and reached a Consensus Diagnosis of typical or atypical bacterial pneumonia, viral pneumonia or not pneumonia for each case.

Results

The expert panel assessed 247 cases with the Consensus Diagnosis being typical bacterial pneumonia (N = 44(18%)), atypical bacterial pneumonia (N = 18(7%)), viral pneumonia (N = 46(19%)) and no pneumonia (N = 139(56%)). Treating ED physician diagnoses were typical bacterial pneumonia (N = 126(51%)), atypical bacterial pneumonia (N = 3(1%)), viral pneumonia (N = 10(4%)) and no pneumonia (N = 108(44%)) with low agreement between a diagnosis of bacterial pneumonia by the ED physician and the panel’s Consensus Diagnosis (Kappa 0.15 (95% CI 0.08, 0.21)). Cut off values that predicted bacterial pneumonia as the Consensus Diagnosis were ESR ≥ 47 mm/hour, CRP ≥ 42 mg/L and procalcitonin ≥0.85 ng/m. Age greater than 5 years and cough for 5 or more days also predict bacterial pneumonia.

Conclusion

In this cohort, pediatric ED physicians over-diagnosed typical bacterial pneumonia and underdiagnosed viral and atypical bacterial pneumonia. Bacterial pneumonia is most likely in children over 5 years of age, with cough for 5 or more days and/or with elevated inflammatory markers.

Introduction

In high-income countries, pneumonia results in significant childhood morbidity and, rarely, mortality. Hospitalization rates in the United States are estimated to be 15.7–22.5 per 100,000 children [1]. Establishing the suspected pathogen leads to appropriate treatment but is challenging. Typical and atypical bacteria or viruses cause the vast majority of cases, with viruses predominating in young children [2]. For typical bacterial pneumonia, antibiotics appear to hasten resolution, prevent almost all deaths, and may decrease the incidence of complications including empyema or abscess. Atypical pneumonia is commonly self-resolving, but effective antibiotics hasten resolution [3]. Antibiotics play no role in the management of viral pneumonia.

Given the absence of a proven reference standard [4], clinicians struggle with the accurate diagnosis of bacterial pneumonia. The presenting symptoms and physical examination findings overlap with those of upper respiratory viral infections, bronchiolitis, asthma and viral pneumonia [5]. Beyond history and physical examination, a common investigation includes chest radiograph (CXR), yet even pediatric radiologists may disagree about the presence of pneumonia or consolidation [6]. Less often, laboratory and microbiologic tests are performed but these can be distressing for the child and are time consuming. As a result, these tests are often not used. C-reactive protein (CRP) and procalcitonin (PCT) are more useful biomarkers than white blood cell counts in differentiating bacterial pneumonia from other causes of respiratory distress, but sensitivity and specificity are only approximately 70% and 65% for CRP or PCT respectively [7]. In Canadian pediatric EDs, PCT is often not readily available. Viruses and bacteria detected from upper respiratory tract specimens may or may not be the cause of pneumonia. Lower tract specimens can be contaminated from the upper tract and can only be obtained if a child requires intubation.

There is evidence that expert panels using formalized consensus methods provide accurate diagnoses comparable to that of reference standards, are highly reproducible and are increasingly used in lieu of definitive reference standards [811]. For these reasons we utilized an expert panel and a formal method for reaching consensus to achieve the following study objectives: 1) describe the occurrence of viral and bacterial pneumonia in children presenting to the Emergency Department (ED) with suspected pneumonia, 2) determine the accuracy of ED physicians in diagnosing pneumonia and distinguishing bacterial from viral pneumonia, and 3) determine the accuracy and reliability of individual clinical findings and common laboratory tests for predicting bacterial pneumonia.

Materials and methods

Study design and setting

We used a prospective cohort design, with standardized collection of history, physical examination findings, laboratory and microbial testing results, CXR reports and telephone follow-up assessments after ED discharge for children clinically suspected to have pneumonia. A panel of experienced pediatric sub-specialists reviewed each case using their individual clinical expertise to achieve consensus. The recommendations of a systematic review of studies using expert panels to define a reference standard were incorporated [9]. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement guidelines for reporting observational studies were followed [12].

Inclusion criteria

Eligible patients were those aged 3 months to 16 years presenting to one of seven Canadian pediatric EDs from August 1, 2008 through April 30, 2011 with both fever (either on history or on physical exam) and cough for whom the ED physician ordered a CXR.

Exclusion criteria

Patients were excluded if: the presumptive diagnosis was croup, bronchiolitis, or moderate or severe asthma (defined as treatment with more than two bronchodilator aerosols in the ED); if the child had a significant chronic comorbidity; or a history of pneumonia confirmed by CXR in the preceding 8 weeks, or receiving antibiotic treatment between 6 hours and 14 days prior to arriving in the ED. Other exclusions included significant language barrier, previous enrolment in the study, or anticipated inability to complete telephone follow-up.

Ethics approval and study enrollment

The study was approved by the research ethics board of all seven sites. Trained study nurses were on-call at each site, typically between 20 and 40 hours per week and were notified of potentially eligible patients by ED personnel. Study nurses determined whether patients met all eligibility criteria, obtained written informed consent from parents and ensured standardized data collection.

Data collection

Demographic variables and clinical signs and symptoms at presentation and during the course of ED assessment and the final diagnosis by the ED physician were documented. Complete blood count (CBC), erythrocyte sedimentation rate (ESR), CRP and blood culture were analyzed locally at each site. Serum for PCT and nasopharyngeal swabs (NPS) were transported on dry ice by express delivery to the central study site and stored at minus 80 centigrade until processing. NPS were cultured for pneumococcus, Haemophilus species, Staphylococcus aureus, group A streptococcus, Moraxella catarrhalis and Bordetellae and molecular detection using a validated technique was performed for influenza, adenovirus, bocavirus, endemic coronaviruses, enterovirus, human metapneumovirus, parainfluenza virus, respiratory syncytial virus (RSV), rhinovirus), Chlamydiae, and Mycoplasma [13].

Parents were asked to maintain a fever log for seven days following the ED visit. Specifically, they were asked to periodically assess their child for fever by palpation, and if the child was noted to be warm, measure and log their axillary temperature using the provided digital thermometer (AccuflexPro digital, Physiologic®). Parents were contacted for follow-up assessments by telephone at day 7 and day 28 to ask about return visits to a physician or to an ED, complications including hospital admission, empyema or abscess formation, therapeutic changes, and results of the fever log (day 7 only).

Interpretation of CXRs

CXRs were interpreted by the ED physician and radiologist at the site where the patient was enrolled. At the completion of the study, all CXRs were also interpreted by the study radiologist (a senior pediatric radiologist) using the Standardization of Interpretation of Chest Radiographs for the Diagnosis of Pneumonia in Children (WHO/V&B/01.35/2001).

Consensus (expert) panel

A consensus panel was assembled, consisting of the following seven members all of whom are board certified in their specialty and sub-specialty: two pediatric ED physicians, two pediatric infectious disease physicians, one pediatric radiologist, one pediatric respirologist and one pediatric hospitalist. Panelists had a median 26 years of clinical experience, ranging between 15 and 47 years. Each panelist used their clinical expertise to interpret the significance of laboratory test results and chest radiographs; no interpretation standards were imposed on panelists.

Data visualization by panelists

A customized secured-access web portal was developed which allowed panelists to view all data asynchronously including high quality digital CXR images (Figs 16); the web portal was hosted by the central study site. Panelists made their diagnoses three separate times per case, based on three successive waves of data: 1) immediate clinical information: history, vital signs and other findings on physical examination (PE); 2) clinical plus immediate laboratory information: CXR image and CBC and differential results; and 3) all other data including follow-up PCT, ESR, CRP, blood culture and NPS results, interpretation of the CXR by a) site ED physician, b) site radiologist, and c) study radiologist, discharge information including patient disposition and treatment at discharge, results of follow-up assessment at day 7 including graph of the fever pattern and results of the follow-up telephone assessment at day 28 (Figs 16).

Fig 1. Home screen.

Fig 1

Screenshot of Home Screen which summarized case status and allowed panelists to navigate between cases.

Fig 6. Day 28 follow-up and full data assessment.

Fig 6

Screenshot of Day 28 Follow-up and Full-Data Assessment [labeled in screenshot “Gold Standard Assessment”] which includes panelist certainty (expressed in 1 to 100%).

Fig 2. Clinical assessment.

Fig 2

Screen shot of history, physical examination and clinical assessment.

Fig 3. Laboratories, CXR and ED assessment.

Fig 3

Screenshot of Test Results, CXR image, and Emergency Department Assessment.

Fig 4. Discharge information, follow-up laboratories and CXR interpretations.

Fig 4

Screenshot of Discharge information, follow-up laboratory results, and various CXR interpretations.

Fig 5. Day 7 follow-up.

Fig 5

Screenshot of Day 7 Follow-up.

Process for panelists to select their diagnosis and indicate their degree of certainty

After reviewing each of the three waves of information, panelists adjusted an onscreen slider ranging between 0 and 100 with 0–49 indicating they chose ‘no pneumonia’ and 51 to 100 indicating they chose ‘pneumonia’. Selecting a number approaching ‘0’ or ‘100’ indicated they were very certain of their diagnosis whereas choosing a number approaching 50 indicated they were very uncertain. If they selected ‘pneumonia’, they were presented with a second slider that was identical except the polar choices were ‘viral pneumonia’ and ‘bacterial pneumonia’. After reviewing all data from the three phases, panelists who selected bacterial pneumonia were presented with an additional slider identical except the polar choices were ‘atypical bacterial pneumonia’ and ‘typical bacterial pneumonia’.

The panelist diagnosis selected following review of the first data set (history and PE findings) is referred to as the Immediate Clinical Assessment. The panelist diagnosis selected following review of the second data set (CXR image and CBC) is referred to as the Full ED Assessment. The panelist diagnosis selected following review of third and final data set (inflammatory markers and microbiological results, and discharge and follow-up information) is referred to as the Full Follow-up Assessment.

Process for achieving panel’s consensus diagnosis

After all panelists chose their Full Follow-up Assessment (their diagnosis based on all three data sets) for a case, if the majority of the seven panelists (i.e. minimum of four members) chose the same diagnosis (no pneumonia, viral pneumonia, atypical bacterial pneumonia, or typical bacterial pneumonia), this was considered the Consensus Diagnosis. If not, consensus was “forced” as follows. If the majority selected pneumonia but disagreed on the type of pneumonia, those who selected “no pneumonia” were required to choose between the three types of pneumonia and change the slider that recorded their degree of certainty. If after this re-vote, four or more members chose the same type of pneumonia, this was considered the Consensus Diagnosis. If not, then for example if the majority chose typical or atypical bacterial pneumonia, those who chose viral pneumonia were required to choose between typical and atypical bacterial pneumonia. At any point in this process, panelists who strongly disagreed with the choice they were being “forced” to make could send a written argument to all panelists, asking those in the majority to reconsider their choice. If after seven days the panelists in the majority did not change their diagnosis, the dissenting minority panelist was “forced” to conform with the majority diagnosis. The diagnosis (no pneumonia, viral pneumonia, atypical bacterial pneumonia, or typical bacterial pneumonia) eventually selected by four or more panelists was the Consensus Diagnosis, and any panelists not in agreement were “forced” to select this diagnosis. However, if they still disagreed, they were able to reflect this by indicating a low degree of certainty by moving their slider toward 50%. Certainty was determined by calculating the percentage difference between the chosen value and 50.0%, then this number was multiplied by 2. This allowed certainty to range from a minimum of 0 and a maximum of 100. For example, if a panelist chose 51.0%, then the calculated certainty would be 2.0%.

Estimation of panel’s aggregate immediate clinical, full ED and full follow-up assessments

In order to assess agreement between the Panel’s Consensus Diagnosis and the Panel’s aggregate Immediate Clinical, Full ED and Full Follow-up Assessments, the latter was represented by determining the majority vote of the seven panelists combined with their diagnostic certainty.

Sample size

Based on a pediatric ED study enrolling children with suspected pneumonia with fever and cough which reported 37% had focal infiltrates on CXR [14], we conservatively estimated that 30% of enrolled children enrolled in our study would have a Consensus Diagnosis of bacterial pneumonia. As our funding for this study limited the number of patients we could enroll to 250, we anticipated approximately 75 children (95% CI 60, 90) would have a consensus diagnosis of bacterial pneumonia.

Data analysis

Descriptive statistics (i.e. frequencies, percentage, means, and standard deviations, IQR) were used to describe demographic, clinical characteristics, examination findings and laboratory results for overall study population and stratified by the Consensus Diagnosis. Pneumonia was classified as any pneumonia (either viral or bacteria), any bacterial pneumonia (either typical or atypical bacteria), or typical bacteria pneumonia.

Patient findings were compared between the consensus pneumonia types using chi-square test for proportions, Students t-test for means, or Kruskal-Wallis test for medians. Diagnostic agreement (kappa, sensitivity, specificity, positive predictive value (PPV), negative value (NPV)) between Consensus Diagnosis and the Site ED Physician Diagnosis were calculated for overall study population.

For ESR, CRP and PCT, optimal cut-points were determined using area under the Receiver Operation Curve (ROC) and logistic regression modeling. These cut-points were then used to predict each laboratory test’s diagnostic accuracy for bacterial pneumonia.

We used logistic regression modeling to explore the association between clinal characteristics and laboratory results, and pneumonia types. To explore the accuracy of clinical and laboratory variables for predicting a diagnosis of pneumonia, area under the ROC were estimated for each variable in the logistic regression model. An alpha of 0.05 was used to determine statistical significance. A Sanky flowchart was used to show the diagnostic comparison between the site ED physician and Consensus Diagnoses. All analyses were performed using SAS statistical software (SAS version 9.4, SAS Institute, Cary, North Carolina).

Results

Characteristics of enrolled children

The health records of 2,634 children were screened of whom 1294 met study eligibility. Of these, a study nurse was not available or contacted for 652. Of the 642 patients whose parents were approached about the study, 373 refused consent, resulting in the enrollment of 269 children. Of these children, 10 withdrew, 8 had major protocol violations, and another 4 had insufficient data to be included in the consensus panel review, leaving 247 cases. Of these 247 cases, 11 could not be contacted for follow-up and another 31 did not complete the fever diary but provided the other follow-up data. The number enrolled at each of the seven sites ranged from 4 to 81 (median 30). Consensus Diagnosis was bacterial pneumonia in 62 cases (25%), viral pneumonia in 46 cases (19%) and no pneumonia in 139 cases (56%) (Table 1). The majority were 1 to 5 years of age (63%). Fever had been present for median 3 days and cough for median 5 days on presentation, with 80% presenting October through March.

Table 1. Characteristics of children assessed in the ED with cough and fever who had a CXR performed.

  No pneumonia1 (N = 139) Bacterial pneumonia1 (N = 62) Viral pneumonia1 (N = 46) Total (N = 247)
Age category (years)  <1 n (%) 12 (8.6) 4 (6.5) 9 (19.6) 25 (10.1)
1–5 n (%) 91 (65.5) 28 (45.2) 37 (80.4) 156 (63.2)
6–9 n (%) 19 (13.7) 16 (25.8) 0 (0.0) 35 (14.2)
10–16 n (%) 17 (12.2) 14 (22.6) 0 (0.0) 31 (12.6)
Age (years) Mean (SD) 4.3 (3.9) 6.2 (4.1) 2.5 (1.5) 4.5 (3.9)
O2 sat room air in ED (%) Mean (SD) 96.5 (2.6) 96.1 (3.2) 95.4 (3.2) 96.2 (2.9)
Respiratory rate (breaths per minute) Mean (SD) 31.6 (10.6) 31.4 (12.3) 37.0 (9.8) 32.5 (11.1)
Heart rate (beats per minute) Mean (SD) 134.4 (30.8) 128.8 (28.4) 145.0 (20.6) 135.0 (28.9)
Temperature in ED (°C) Mean (SD) 37.8 (1.0) 37.9 (1.0) 38.2 (1.1) 37.9 (1.1)
Fever (≥38°C) in ED n (%) 58 (41.7) 32 (51.6) 23 (50.0) 113 (45.7)
Fever duration (days)   Median (IQR) 3 (1, 5) 3 (2, 5) 3 (1, 5) 3 (1, 5)
Fever (≥ 5 days)   n (%) 36 (25.9) 19 (30.6) 12 (26.1) 67 (27.1)
Cough duration (days) Median (IQR) 4 (2, 7) 6 (3, 7) 5 (3, 7) 5 (3, 7)
Cough (≥5days)   n (%) 61 (43.9) 39 (62.9) 27 (58.7) 127 (51.4)
Season  Apr-Jun n (%) 18 (12.9) 8 (12.9) 8 (17.4) 34 (13.8)
Jan-Mar n (%) 61 (43.9) 24 (38.7) 15 (32.6) 100 (40.5)
Jul-Sep n (%) 8 (5.8) 7 (11.3) 1 (2.2) 16 (6.5)
Oct-Dec n (%) 52 (37.4) 23 (37.1) 22 (47.8) 97 (39.3)

CXR–chest radiograph; ED–emergency department; IQR–inter-quartile range; SD—standard deviation

1 This diagnosis was based on the Consensus Diagnosis of an expert panel.

Laboratory results

See Table 2 for a summary of laboratory and microbiological testing results. At least one virus was detected from 153 of 247 cases (62%), including 17 of 62 cases (27%) with a Consensus Diagnosis of bacterial pneumonia.

Table 2. Laboratory results from children assessed in the ED with cough and fever who had a CXR performed.

Laboratory Test value statistic No pneumonia1 (N = 139) Bacterial pneumonia1 (N = 62) Viral pneumonia1 (N = 46) Total (N = 247)
White blood cell count (X109/L) Median (IQR) 9.1 (6.5, 13.5) 15.6 (9.1, 19.6) 10.1 (6.9, 15.1) 10.0 (6.9, 15.6)
ESR (mm/hr) Median (IQR) 20.0 (11.0, 30.0) 45.0 (20.0, 78.0) 29.0 (18.0, 39.0) 24.0 (14.0, 40.0)
CRP (mg/L) Median (IQR) 11.5 (4.7, 32.4) 58.8 (24.8, 227.0) 19.4 (7.6, 46.7) 17.2 (7.0, 55.2)
PCT (μg/L) Median (IQR) 0.1 (0.1, 0.3) 1.0 (0.1, 7.8) 0.2 (0.1, 1.0) 0.1 (0.1, 1.0)
Positive NP swab n (%) 102 (75.0) 26 (44.1) 37 (88.1) 165 (69.6)
NP swab—first potential pathogen (N = 165)2 102 26 37 165
Adenovirus n (%) 4 (3.9) 1 (3.8) 3 (8.1) 8 (4.8)
Bocavirus n (%) 13 (12.7) 3 (11.5) 3 (8.1) 19 (11.5)
Coronavirus n (%) 1 (1.0) 0 (0.0) 0 (0.0) 1 (0.6)
Enterovirus/Rhinovirus n (%) 20 (19.6) 8 (30.8) 2 (5.4) 30 (18.2)
Influenza n (%) 17 (16.7) 2 (7.7) 4 (10.8) 23 (13.9)
Metapneumovirus n (%) 7 (6.9) 0 (0.0) 2 (5.4) 9 (5.5)
Parainfluenza n (%) 9 (8.8) 1 (3.8) 5 (13.5) 15 (9.1)
RSV n (%) 29 (28.4) 2 (7.7) 18 (48.6) 49 (29.7)
Chlamydophila pneumoniae n (%) 1 (1.0) 0 (0.0) 0 (0.0) 1 (0.6)
Mycoplasma pneumoniae n (%) 1 (1.0) 9 (34.6) 0 (0.0) 10 (6.1)
NP swab—second potential pathogen (N = 25) 15 4 6 25
Adenovirus n (%) 3 (20.0) 0 (0.0) 0 (0.0) 3 (12.0)
Bocavirus n (%) 0 (0.0) 2 (50.0) 0 (0.0) 2 (8.0)
Coronavirus n (%) 0 (0.0) 1 (25.0) 0 (0.0) 1 (4.0)
Enterovirus/Rhinovirus n (%) 9 (60.0) 0 (0.0) 3 (50.0) 12 (48.0)
Metapneumovirus n (%) 0 (0.0) 0 (0.0) 1 (16.7) 1 (4.0)
Parainfluenza n (%) 1 (6.7) 0 (0.0) 0 (0.0) 1 (4.0)
RSV n (%) 2 (13.3) 0 (0.0) 2 (33.3) 4 (16.0)
Mycoplasma pneumoniae n (%) 0 (0.0) 1 (25.0) 0 (0.0) 1 (4.0)
NP swab—third potential pathogen (N = 2) 0 2 0 2
Enterovirus/Rhinovirus n (%) 1 (50.0) 1 (50.0)
RSV n (%) 1 (50.0) 1 (50.0)
Positive blood culture3 n (%) 3/135 (2.2) 4/62 (6.5) 0/45 (0.0) 7/242 (2.9)

CRP–C-reactive protein; CXR–chest radiograph; ED–emergency department; ESR–erythrocyte sedimentation rate; IQR–inter-quartile range; NP–nasopharyngeal; PCT–procalcitonin; RSV -respiratory syncytial virus; SD—standard deviation

1This diagnosis was based on the Consensus Diagnosis of an expert panel

2 NP cultures were all negative for pneumococcus, Haemophilus species, Staphylococcus aureus, group A streptococcus, Moraxella catarrhalis, and Bordetellae

3Blood cultures were positive for Streptococcus pneumoniae (n = 5 (2 “Bacterial Pneumonia/ 3 “No Pneumonia”), Staphylococcus aureus (N = 1 (“Bacterial Pneumonia”) and Gram-negative bacilli (N = 1 (“Bacterial Pneumonia”))

Panel’s clinical, ED and full data assessments compared to consensus diagnosis

The 247 cases were each reviewed by seven panelists which yielded 1729 individual decisions in each of the three data waves. With dichotomization of the panelists’ diagnosis into bacterial pneumonia or not (combining no or viral pneumonia), panelists changed their diagnosis 61 of 1729 times (3.5%) between their Immediate Clinical Assessment and their Full ED Assessments, and an additional 28 of 1729 times (1.6%) between their Full ED and Full Follow-up Assessments. Consensus Diagnosis was reached with no “forcing” (i.e. all seven panelists independently made the same diagnosis) for 73 of the 247 cases (30%). The agreement between the majority of the Panelists’ Immediate Clinical Assessment (based on history and physical exam only) and the Panel’s Consensus Diagnosis was low (Kappa 0.30 (0.18, 0.41)). However, the majority of the Panelists’ Full ED Assessment (adding CBC and viewing of the CXR) showed substantial agreement (Kappa 0.76 (0.68, 0.84)), as did the Panelists’ Full Follow-up Assessment with the Panel’s Consensus Diagnosis (Kappa .93 (0.89, 0.88)).

The panelists’ degree of certainty on a scale from 0 to 100 for their: Immediate Clinical Assessment was median 35 (IQR 30–45); Full ED assessment was median 50 (IQR 43–60); Full Follow-up Assessment was median 62 (IQR 52–72); and Consensus Diagnosis was median 79 (IQR 73–84).

ED versus panel consensus diagnosis

The diagnosis of typical bacterial pneumonia was considerably higher for ED physicians (126/247 (51%)) than the Panel’s Consensus Diagnosis (44/247 (18%)) (Table 3). The agreement between a diagnosis of bacterial pneumonia by the ED physician and the Panel’s Consensus Diagnosis was low (Kappa 0.15 (0.08, 0.21)). The Sankey Diagram (Fig 7) shows the most common specific discrepancy was an ED diagnosis of viral pneumonia when the Consensus Diagnosis was “not pneumonia”.

Table 3. Differences in frequency and percentage for ED physician diagnoses versus panel consensus diagnosis for children assessed in the ED with cough and fever who had a CXR performed.

Pneumonia Classification ED MD diagnosis n (%) Consensus diagnosis n (%)
Not Pneumonia 108 (43.7) 139 (56.3)
Atypical Bacteria 3 (1.2) 18 (7.3)
Typical Bacteria 126 (51.0) 44 (17.8)
Viral pneumonia 10 (4.0) 46 (18.6)

CXR–chest radiograph; ED–emergency department; MD–medical doctor

Fig 7. Comparison of ED physician to panel consensus diagnosis for 247 children assessed in the ED with cough and fever who had a CXR performed for possible pneumonia.

Fig 7

NP = No Pneumonia; VP = Viral Pneumonia; TBP = Typical Bacterial Pneumonia; ABP = Atypical Bacterial Pneumonia; ER diagnosis = diagnosis by site treating ED physician; Panel vote = Expert Panel’s Consensus Diagnosis.

Accuracy of individual demographics, symptoms, signs, and laboratory tests

The optimal cut-off values for ESR, CRP and PCT for diagnosis of the types of pneumonia are shown in Table 4. The sensitivity of laboratory cut-offs ranged from 35% to 50% for a diagnosis of pneumonia, but increased to 50% to 64% and 66% to 87% for a diagnosis of bacterial and typical bacterial pneumonia, respectively. A WBC count > 15 X 109/ was 67% sensitive and 83% specific for typical bacterial pneumonia.

Table 4. Laboratory features that predicted pneumonia diagnosis for children assessed in the ED with cough and fever who had a CXR performed.

N Sensitivity % (n/N) Specificity % (n/N) PPV % (n/N) NPV % (n/N)
Pneumonia versus not pneumonia WBC >15 vs ≤15 X109/L 238 40.4(42/104) 84.3(113/134) 66.7(42/ 63) 64.6(113/175)
WBC<4 vs 4–15 X109/L 175 3.3(4/62) 95(108/113) 44.4(4/9) 65.1(108/166)
WBC>15 vs 4–15 X109/L 229 42.0(42/100) 83.7(108/129) 66.7(42/63) 65.1(108/166)
ESR≥47 vs <47 mm/hr 221 35.1(33/ 94) 92.9(118/127) 78.6(33/42) 65.9(118/179)
CRP> = 42 vs <42 mg/L 231 50.0(49/ 98) 80.5(107/133) 65.3(49/ 75) 68.6(107/156)
PCT> = 0.85 vs<0.85 ng/mL 225 43.4(43/ 99) 84.9(107/126) 69.4(43/ 62) 65.6(107/163)
Bacterial pneumonia versus viral pneumonia or no pneumonia WBC >15 vs ≤15 X109/L 238 50.8(31/ 61) 81.9(145/177) 49.2(31/ 63) 82.9(145/175)
WBC<4 vs 4–15 X109/L 175 3.3(1/30) 84.5(137/145) 11.1(1/9) 82.5(137/166)
WBC>15 vs 4–15 X109/L 229 51.7(31/ 60) 81.1(137/169) 49.2(31/ 63) 82.5(137/166)
ESR≥47 vs <47 mm/hr 221 50.0(28/ 56) 91.5(151/165) 66.7(28/ 42) 84.4(151/179)
CRP> = 42 vs <42 mg/L 231 64.3(36/56) 77.7(136/175) 48.0(36/75) 87.2(136/156)
PCT> = 0.85 vs<0.85 ng/mL 225 52.6(30/57) 81.0(136/168) 48.4(30/62) 83.4(136/163)
Typical bacterial pneumonia versus atypical pneumonia, viral pneumonia or no pneumonia WBC >15 vs ≤15 X109/L 238 67.4(29/43) 82.6(161/195) 46.0(29/63) 92.0(161/175)
WBC<4 vs 4–15 X109/L 175 7.1(1/14) 95.0(153/161) 11.1(1/9) 92.2(153/166)
WBC>15 vs 4–15 X109/L 229 69.0(29/ 42) 81.8(153/187) 46.0(29/ 63) 92.2(153/166)
ESR≥47 vs <47 mm/hr 221 65.8(25/38) 90.7(166/183) 59.5(25/42) 92.7(166/179)
CRP > = 42 vs <42 mg/L 231 86.8(33/38) 78.2(151/193) 44.0(33/75) 96.8(151/156)
PCT> = 0.85 vs<0.85 ng/mL 225 75.0(30/ 40) 82.7(153/185) 48.4(30/ 62) 93.9(153/163)

CRP—C-reactive protein; ESR–erythrocyte sedimentation rate; NPV–negative predictive value; PCT–procalcitonin; PPV–positive predictive value

The odds ratio of demographic, clinical and laboratory features for predicting the presence of pneumonia, bacterial pneumonia and typical bacterial pneumonia are shown in Tables 57 respectively. WBC, ESR, CRP and PCT were consistently predictive across all three categories of pneumonia with ORs for bacterial pneumonia ranging from 4 up to 11. Cough for 5 or more days was predictive for both pneumonia (Table 5) and bacterial pneumonia (Table 6). The presence of nasal flaring was predictive for pneumonia (Table 5). Age 6–16 years was predictive for bacterial pneumonia (Table 6). Absence of wheeze was a significant predictor of bacterial pneumonia (Table 6) when documented by a nurse but not when documented by a physician and, in contrast, absence of wheeze was a significant predictor for typical bacterial pneumonia when documented by a physician but not when documented by a nurse (Table 7).

Table 5. Demographic, clinical and laboratory features that predicted pneumonia versus no pneumonia for children assessed in the ED with cough and fever who had a CXR performed.

OR with 95%CI Area under ROC with 95% CI Pr > Chi-Square
Male gender 1.130(0.682–1.872) 0.5152(0.4523–0.5780) 0.6348
Age 1–5 years (versus < 1 year or 6–17 years) 0.797(0.474–1.342) 0.5264(0.4654–0.5874) 0.3936
Age 6–16 years (versus <6 years) 1.134(0.638–2.015) 0.5120(0.4567–0.5672) 0.6690
Admission temperature ≥38˚Celsius 1.449(0.874–2.404) 0.5460(0.4833–0.6087) 0.1506
Fever for ≥ 5 days versus for a shorter duration 1.152(0.656–2.024) 0.5140(0.4577–0.5703) 0.6230
Cough for ≥ 5 days versus for a shorter duration 2.009(1.204–3.352) 0.5861(0.5241–0.6482) 0.0075
Oxygen saturation on room air < 93% versus higher 0.665(0.364–1.214) 0.5372(0.4818–0.5925) 0.1842
Crackles recorded on physical examination by RN 1.848(1.093–3.122) 0.5711(0.5105–0.6318) 0.0218
Wheeze recorded on physical examination by RN 0.864(0.406–1.839) 0.5082(0.4661–0.5502) 0.7049
Prolonged expiration recorded on physical examination by RN 0.897(0.409–1.968) 0.5056(0.4652–0.5460) 0.7864
Crackles recorded on physical examination by MD 1.487(0.862–2.565) 0.5488(0.4819–0.6158) 0.1540
Wheeze recorded on physical examination by MD 0.608(0.288–1.284) 0.5404(0.4811–0.5998) 0.1921
Prolonged expiration recorded on physical examination by MD 0.986(0.476–2.041) 0.5010(0.4508–0.5511) 0.9694
Supracostal indrawing recorded on physical examination by MD 2.007(0.996–4.044) 0.5529(0.4996–0.6062) 0.0514
Nasal flaring recorded on physical examination by MD 3.813(1.439–10.099) 0.5606(0.5178–0.6035) 0.0071
Intercostal indrawing recorded on physical examination by MD 1.719(0.959–3.079) 0.5583(0.4955–0.6212) 0.0688
Grunting recorded on physical examination by MD 1.801(0.814–3.986) 0.5346(0.4876–0.5815) 0.1464
Decreased air entry recorded on physical examination by MD 1.513(0.878–2.607) 0.5511(0.4842–0.6180) 0.1359
White blood cell count < 4 versus 4–15 X 109/L 1.490(0.385–5.763) 0.5101(0.4739–0.5464) 0.5637
White blood cell count > 15 versus 4–15 X 10 9 /L 3.724(2.017–6.877) 0.6286(0.5704–0.6868) < .0001
ESR ≥ 47 mm/hr versus lower 7.093(3.189–15.773) 0.6401(0.5867–0.6935) < .0001
CRP ≥ 42 mg/L versus lower 4.115(2.296–7.375) 0.6523(0.5921–0.7124) < .0001
PCT ≥ 0.85 ng/mL versus lower 4.323(2.304–8.112) 0.6418(0.5835–0.7000) < .0001

CRP—C-reactive protein; CXR–chest radiograph; ED–Emergency Department; ESR–erythrocyte sedimentation rate; MD–medical doctor; RN–Registered Nurse; PCT–procalcitonin

Table 7. Demographic, clinical and laboratory features that predicted typical bacterial pneumonia versus other types of pneumonia or “not pneumonia” for children assessed in the ED with cough and fever who had a CXR performed.

OR with 95%CI Area under ROC with 95%CI Pr > Chi-Square
Male gender 1.633(0.833–3.201) 0.5596(0.4798–0.6393) 0.1532
Age 1–5 years (versus less than 1 year or 6–17 years) 0.811(0.417–1.579) 0.5247(0.4442–0.6053) 0.5377
Age 6–16 years (versus < 6 years) 1.897(0.946–3.802) 0.6420(0.5734–0.7106) 0.0712
Admission temperature ≥38˚Celsius 1.926(0.993–3.734) 0.5812(0.5002–0.6622) 0.0524
Fever for ≥ 5 days versus for a shorter duration 1.009(0.485–2.098) 0.5009(0.4276–0.5742) 0.9806
Cough for ≥ 5 days versus for a shorter duration 1.459(0.753–2.825) 0.5467(0.4655–0.6278) 0.2629
Oxygen saturation on room air < 93% versus higher 2.639(0.983–7.081) 0.5719(0.5134–0.6304) 0.0540
Crackles recorded on physical examination by RN 0.883(0.445–1.752) 0.5143(0.4360–0.5925) 0.7214
Wheeze recorded on physical examination by RN 0.275(0.063–1.195) 0.5512(0.5116–0.5908) 0.0850
Prolonged expiration recorded on physical examination by RN 0.498(0.144–1.726) 0.5299(0.4858–0.5741) 0.2716
Crackles recorded on physical examination by MD 0.737(0.367–1.477) 0.5380(0.4504–0.6257) 0.3894
Wheeze recorded on physical examination by MD 0.109(0.014–0.830) 0.6061(0.5577–0.6545) 0.0323
Prolonged expiration recorded on physical examination by MD 0.370(0.107–1.276) 0.5535(0.5022–0.6048) 0.1155
Supracostal indrawing recorded on physical examination by MD 0.749(0.290–1.930) 0.5208(0.4563–0.5853) 0.5493
Nasal flaring recorded on physical examination by MD 1.679(0.616–4.581) 0.5281(0.4666–0.5895) 0.3114
Intercostal indrawing recorded on physical examination by MD 0.828(0.385–1.782) 0.5199(0.4403–0.5995) 0.6290
Grunting recorded on physical examination by MD 1.880(0.764–4.630) 0.5422(0.4736–0.6108) 0.1697
Decreased air entry recorded on physical examination by MD 1.565(0.760–3.223) 0.5544(0.4684–0.6405) 0.2243
White blood cell count < 4 versus 4–15 X 109/L 1.471(0.171–12.688) 0.5109(0.4389–0.5829) 0.7255
White blood cell count > 15 versus 4–15 X 10 9 /L 10.038(4.731–21.302) 0.7543(0.6783–0.8303) < .0001
ESR ≥ = 47 mm/hr versus lower 18.778(8.142–43.307) 0.7825(0.7032–0.8618) < .0001
CRP ≥ 42 mg/L versus lower 23.722(8.721–64.529) 0.8254(0.7636–0.8872) < .0001
PCT ≥ 0.85 ng/mL versus lower 14.344(6.376–32.268) 0.7885(0.7153–0.8618) < .0001

CRP—C-reactive protein; CXR–chest radiograph; ED–Emergency Department; ESR–erythrocyte sedimentation rate; MD–medical doctor; RN–Registered Nurse; PCT–procalcitonin

Table 6. Demographic, clinical and laboratory features that predicted bacterial pneumonia versus other types of pneumonia or “not pneumonia” for children assessed in the ED with cough and fever who had a CXR performed.

OR with 95%CI Area under ROC with 95%CI Pr >Chi-Square
Male gender 1.641(0.909–2.962) 0.5605(0.4899–0.6310) 0.1000
Age 1–5 years (versus less than 1 year or 6–17 years) 0.367(0.203–0.661) 0.6201(0.5493–0.6909) 0.0009
Age 6–16 years (versus <6 years) 3.903(2.095–7.2720 0.6420(0.5734–0.7106) < .0001
Admission temperature ≥38˚Celsius 1.370(0.769–2.438) 0.5391(0.4669–0.6114) 0.2851
Fever for ≥ 5 days versus for a shorter duration 1.261(0.670–2.373) 0.5235(0.4575–0.5894) 0.4719
Cough for ≥ 5 days versus for a shorter duration 1.869(1.035–3.374) 0.5767(0.5061–0.6472) 0.0379
Oxygen saturation on room air < 93% versus higher 1.530(0.733–3.195) 0.5362(0.4772–0.5952) 0.2578
Crackles recorded on physical examination by RN 1.247(0.691–2.251) 0.5259(0.4554–0.5965) 0.4630
Wheeze recorded on physical examination by RN 0.274(0.080–0.932) 0.5542(0.5166–0.5918) 0.0382
Prolonged expiration recorded on physical examination by RN 0.441(0.147–1.323) 0.5353(0.4958–0.5748) 0.1441
Crackles recorded on physical examination by MD 1.034(0.556–1.925) 0.5042(0.4269–0.5815) 0.9149
Wheeze recorded on physical examination by MD 0.411(0.149–1.129) 0.5632(0.5027–0.6237) 0.0846
Prolonged expiration recorded on physical examination by MD 0.850(0.361–2.004) 0.5108(0.4548–0.5669) 0.7107
Supracostal indrawing recorded on physical examination by MD 0.977(0.442–2.161) 0.5017(0.4412–0.5623) 0.9549
Nasal flaring recorded on physical examination by MD 1.044(0.389–2.801) 0.5021(0.4534–0.5508) 0.9311
Intercostal indrawing recorded on physical examination by MD 0.791(0.400–1.564) 0.5246(0.4541–0.5952) 0.5011
Grunting recorded on physical examination by MD 1.143(0.474–2.755) 0.5080(0.4534–0.5627) 0.7662
Decreased air entry recorded on physical examination by MD 1.724(0.908–3.272) 0.5661(0.4903–0.6419) 0.0958
White blood cell count < 4 versus 4–15 X 109/L 0.591 (0.071–4.905) 0.5109(0.4733–0.5485) 0.6258
White blood cell count > 15 versus 4–15 X 10 9 /L 4.577(2.423–8.644) 0.6637(0.5934–0.7340) < .0001
ESR ≥ = 47 mm/hr versus lower 10.783(5.054–23.005) 0.7076(0.6381–0.7770) < .0001
CRP ≥ 42 mg/L versus lower 6.277(3.269–12.051) 0.7100(0.6395–0.7805) < .0001
PCT ≥ 0.85 ng/mL versus lower 4.722(2.473–9.019) 0.6679(0.5961–0.7398) < .0001

CRP—C-reactive protein; CXR–chest radiograph; ED–Emergency Department; ESR–erythrocyte sedimentation rate; MD–medical doctor; RN–Registered Nurse: PCT–procalcitonin

Discussion

For children seen in the ED with fever and cough for whom a diagnosis of pneumonia was suspected, a consensus panel concluded that only one quarter had bacterial pneumonia in contrast to ED physicians who diagnosed more than half with bacterial pneumonia. One potential explanation for the discrepancy would be that ED physicians most often made decisions prior to knowing microbiologic results or the radiologists’ opinion of the CXR. Their main goal is not to miss a diagnosis of typical bacterial pneumonia as this could result in harm, leading them to err on the side of making this diagnosis. ED physicians achieved this goal as they diagnosed bacterial pneumonia for all but one of 62 cases that the panelists considered to be bacterial pneumonia. The most common discordance was diagnosis of viral pneumonia by the ED physician when the panel consensus diagnosis was “not pneumonia”; this would have limited consequences as antibiotics are not beneficial for either diagnosis.

The individual clinical symptoms and examination findings that predicted bacterial pneumonia, albeit with low accuracy, were older age (6 to 16 years of age), cough for more than five days and absence of wheeze as assessed by the study nurse. However, it is of note that the majority of children with bacterial pneumonia were 5 years of age or younger. The significance of wheeze detected by the nurse versus the physician is unclear as wheeze can be intermittent. A systematic review of predictors of radiographic pneumonia in children found that presence of symptoms for more than 3 days (including cough) had a significant positive likelihood ratio, but absence of wheeze did not [5]; this review did not report on age as a predictor. Two studies which derived clinical scores for predicting bacterial or radiographic pneumonia found both age and absence of wheeze to be important predictors and included them in diagnostic algorithms [15, 16]. In contrast to two published studies and a systematic review [4, 5, 17], we found that neither the presence of fever in the ED nor history of persistent fever predicted bacterial pneumonia. It is important to note, however, that fever on admission just missed achieving statistical significance (p = 0.0524). The borderline significance of this finding may be due to our inclusion criteria requiring children to have either a history or presence of fever to be enrolled.

Laboratory tests, specifically elevated WBC, ESR, CRP and PCT, were significantly better at predicting bacterial pneumonia than were signs and symptoms, with area under ROC of between 0.60 and 0.65. A systematic review of studies which evaluated biomarkers as predictors of bacterial pneumonia found similar area under ROC for each of these tests to the current study [7]. While substantially more accurate than clinical findings, individual laboratory results were not sufficiently accurate to serve as a surrogate reference standard. Our data also show that detection of viruses does not exclude bacterial pneumonia as almost one-third of those with bacterial pneumonia had viral coinfection.

We used expert panel consensus as our reference standard as there is no non-invasive investigation that definitively proves the etiology of pediatric pneumonia [4]. Although it is novel to use expert panel consensus as a reference standard for pediatric bacterial pneumonia, expert panels have been used increasingly in psychiatric, cardiovascular, and other respiratory conditions [811]. For the diagnosis of dementia, the diagnostic accuracy of an expert panel has been shown to be superior to individual clinicians and validated as comparable to the reference standard of neuropathological based diagnosis [11]. Expert panel consensus has also been demonstrated to have high reproducibility in infectious diseases [8]. Our findings also provide face validity as panelists’ assessments made after the provision of more patient data showed increasingly better agreement with the panel’s Consensus Diagnosis, and panelists’ diagnostic certainty increased with achievement of consensus.

A strength of our study is the novel use of an expert panel for the diagnosis of pneumonia and that the expert panel represented a heterogenous group of subspecialists each with their unique expertise relevant to the diagnosis of pneumonia in children. Notwithstanding the proven utility of expert panels, the most important limitation is that the use of our panel’s Consensus Diagnosis cannot be directly validated, and it is at potential risk for incorporation bias. A second limitation is that our inclusion criteria required children to have fever and their ED physician to have ordered a chest radiograph to be enrolled. These requirements may have narrowed our cohort in ways that may have modified the predictive potential of clinical factors such as fever. A third limitation is that our focus on pediatric emergency departments restricts the applicability of our findings to care provided in general emergency departments. A fourth limitation is that because of the relatively small number of children enrolled and reported on (n = 247) as compared with those who met study eligibility (n = 1,294) and that we do not have demographic and clinical details of those not enrolled, it is possible that our cohort of children does not accurately represent the full range of all children suspected of having pneumonia.

In conclusion, using expert panel Consensus Diagnosis as a reference standard, we determined that pediatric ED physicians significantly over diagnosed bacterial pneumonia, and that the most accurate individual patient findings for diagnosing bacterial pneumonia were greater than five years of age and cough for 5 or more days. Further we also demonstrated that standard inflammatory biomarkers were substantially more accurate than were clinical findings in the diagnosis of pediatric bacterial pneumonia.

Supporting information

S1 File. Alberta Children’s Hospital ethics approval.

(PDF)

pone.0311201.s001.pdf (177.2KB, pdf)
S2 File. Hospital for Sick Children’s ethics approval.

(PDF)

pone.0311201.s002.pdf (114.7KB, pdf)
S3 File. Queen’s University ethics approval.

(PDF)

S4 File. Western University ethics approval.

(PDF)

pone.0311201.s004.pdf (51.5KB, pdf)
S5 File. Montreal Children’s Hospital ethics approval.

(PDF)

pone.0311201.s005.pdf (520.7KB, pdf)
S6 File. Centre Hospitalier Universitaire Sainte-Justine ethics approval.

(PDF)

pone.0311201.s006.pdf (1.5MB, pdf)
S7 File. Stollery Children’s Hospital ethics approval.

(PDF)

pone.0311201.s007.pdf (131.9KB, pdf)

Acknowledgments

This study was conducted with the assistance of Pediatric Emergency Research Canada (PERC).

Data Availability

The data underlying the results presented in the study are available from Biostatistical Support, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada. [r4k@ucalgary.ca].

Funding Statement

Funding for Pneumonia Prospective Cohort Study • Canadian Institutes for Health Research Team Grant, Funded from April 2006-March 2011, Grant title: ‘Improving outcomes for ill and injured children in emergency departments’. Principal Investigator – Terry Klassen; Co-Investigators (and pneumonia project leads) – David Johnson and Tim Lynch. Can$4.8 million funded seven large multi-centre projects, one of which focused on three distinct pneumonia studies (systematic review, practice variation study and prospective cohort study) • Alberta Children’s Hospital Foundation project grant, Funded from April 2009-April 2010, Grant title: ‘Accuracy of metabolomics for diagnosing pediatric pneumonia’. Principal Investigator – Jim Kellner; Co-Investigator – David Johnson. Can$50,000 • Alberta Lung Association project grant. Funded from April 2009-April 2010, Grant title: ‘Accuracy of metabolomics for diagnosing pediatric pneumonia’. Co-investigator. Principal Investigator – Jim Kellner; Co-Investigator – David Johnson. Can $30,000 The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

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31 May 2024

PONE-D-24-14952Accuracy of the diagnosis of pneumonia in the pediatric Emergency Department: a prospective cohort studyPLOS ONE

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• Canadian Institutes for Health Research Team Grant, Funded from April 2006-March 2011, Grant title: ‘Improving outcomes for ill and injured children in emergency departments’. Principal Investigator – Terry Klassen; Co-Investigators (and pneumonia project leads) – David Johnson and Tim Lynch. Can$4.8 million funded seven large multi-centre projects, one of which focused on three distinct pneumonia studies (systematic review, practice variation study and prospective cohort study)

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Reviewer #1: Thanks for asking me to review this interesting paper. I have some minor comments as below:

1. Title:

My understanding is the study focused on Paed ED in high income countries. Better to include that information in title since the approach in "low income", "middle income" is somewhat different.

2. Introduction

3. Method

I am not really clear how the Expert Consensus made decisions of "no pneumonia", "bacterial pneumonia", "atypical pneumonia", "viral pneumonia". Did they use any specific cut off for CBC, CRP, PCT, ESR? Also, what changes on CXR would suggest "atypical pneumonia", "typical pneumonia", "viral pneumonia".

A common practice in ED is children > 5 years old would be covered both "bacterial pneumonia" and "atypical bacterial pneumonia". Did you record these cases in your study?

4. Results

- Table 1: please document unit that belongs to each factor. Ex: O2 sat room air (%), HR (bpm), fever (>=38) (n)

- Table 2: what is the subgroup of "no pneumonia" + blood culture positive?

How many cases NPS positive + superimposed infection?

- Table 4:

Why to choose the cut off 4, 15 for WBC? 42 for CRP? 47 for ESR? 0.85 for PCT? Any references?

Please add a foot note for abbreviations: MD, EN

5. Discussion

My main concern is how to apply the "Expert consensus" in practice as children present to ED require an urgent approach and management. Dx of pneumonia is based on clinical findings.

Reviewer #2: Thank you for opportunity to review. Well executed project with large sample and good design. The manuscript is well written. No changes to suggest. Would recommend it is ready for publication in its current form

Reviewer #3: Line 52-54: requires a reference.

Line 117-123: Mentions the parental logs; it may be useful to include how completely these were filled. What training did the parents receive?

Methods: why not also stratify the consensus diagnosis into non pneumonia cases? It may have been useful to know how many of cases which were incorrectly diagnosed as pneumonia were bronchiolitis, asthma etc.

By limiting the consensus diagnosis certainty to >50% it removes the ability of experts who still disagreed to reflect that, or to show that they were very uncertain and it means that the certainty on the censuses diagnosis of 79 is not really comparable to the others where the experts could choose between 0 and 100. It artificially inflates this certainty.

Results:

Lines 218-222: Enrolling only 269 out of 1294 eligible patients means there is room that a lot of information was missed. Were there any trends to who which children were most likely to decline consent i.e. more unwell children, first nations children, those presenting at night etc. Could these be associated with worse clinically outcomes which limited the generally applicability of your results?

Table 1 and 2: These tables are a little bit difficult to know which statistics are the best representation of data spread for each variable. Most of these characteristics and results were given to us as both medians + IQR and means +SD. If a variable is parametric just report on Mean and SD and if it is non parametric then a median and IQR. By giving us both for every characteristic it makes it more difficult for a reader to know what information is actually the most appropriate descriptor of spread for that variable.

I also would have been very interested to see a table breaking down how the expert examples at different parts of the diagnosis process compared to the ED physicians.

Table 2: I found it interesting that 30% of the bacterial pneumonias had entero/rhino present. Is this worth commenting on. I often see junior doctors falsely reassured by the presence of entero/rhino virus on an NPA.

Table 3:

You mention that this table demonstrated discrepancies, but this table actually shows how often each group (ED or Consensus) make each diagnosis, but not how often they agree and disagree. Your Sankey diagram is what shows the actual discrepancies. For the table to do this this you would need to create a 5x5 table with one Axis listing the ED MD diagnosis and the other listing Consensus diagnosis so you can see how often they were in agreement.

Results and conclusion:

I think it would be worth a more nuanced approach to conclusions than p<0.05 = absolutely significant and p>0.05 means no significance. Clinical relevance could be discussed more. i.e. lines 323-325 you state that fever was not associated with a diagnosis. Whilst true in the most rigid sense, you actually did find a trend associating with fever and the presence of typical bacterial pneumonia, however it missed out on statistical significance by a narrow margin (p=0.0524). This would have been a reasonable part of the paper to mention that statistical significance is not the same as clinical relevance. A p of 0.0524 compared to a p of 0.0499 is completely arbitrary and fever is still likely a useful factor in discriminating typical bacterial pneumonia from other causes. The same is true of wheeze, the way you talked about it with it being significant for one type of pneumonia if heard by a nurse, but the other if heard by a physician is not very clinically relevant. For both typical and overall pneumonia, absence of wheeze from nurses and physicians either reached significance or was trending close to significance. I also wondered if it was worth grouping those two findings as just wheeze heard on examination by a either study nurse or physician, as I think both professionals findings are relevant and wheeze can be an intermittent finding.

The way the over/under 5 statement is framed feels a bit incomplete. I understand that you are saying that the pretest probability of pneumonia in an over 5 year old presenting to ED is higher, but I think it would be worth at least flagging that the majority of pneumonias were in children under 5 (and possibly higher for typical pneumonia, but we were not given that information). The way this was written feels like a junior doctor reading it could think that pneumonia is less common in 5 year old, rather than what this actually says which is that 5 year olds present much more often with these symptoms in general, but a similar number of them overall (32 v 30 in your findings) will have have pneumonia.

Lastly, I think you could give ED physicians a little bit more credit. I think it is probably worth giving them some credit for the fact that of the in indiscrepancies there were almost no missed cases of TBP. Looking at the Sankey I think maybe one misdiagnosed as NP and one misdiagnosed as ABP. This means there were almost no children placed at significant risk of adverse outcome due to undertreated pneumonia, but we could be better with our antimicrobial stewardship. I actually read that as the ED physicians doing pretty good job. I am not worried about the difference between viral pneumonia and no pneumonia, as the treatment is so similar for the most part.

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Reviewer #1: Yes: Dr Thi Kim Phuong Nguyen

Reviewer #2: No

Reviewer #3: No

**********

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PLoS One. 2024 Dec 11;19(12):e0311201. doi: 10.1371/journal.pone.0311201.r003

Author response to Decision Letter 0


16 Jul 2024

A detailed Response to Reviewers and Revised Manuscript with Tracked Changes have been submitted. We believe these will address all issues identified by the reviewers and the editor. If not, we are fully open to further revisions.

Attachment

Submitted filename: RESPONSE TO REVIEWERS.docx

pone.0311201.s009.docx (24.2KB, docx)

Decision Letter 1

Maurizio Balbi

27 Aug 2024

PONE-D-24-14952R1Accuracy of the diagnosis of pneumonia in Canadian pediatric emergency departments: a prospective cohort studyPLOS ONE

Dear Dr. Robinson,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Academic Editor

PLOS ONE

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Additional Editor Comments:

Please address the minor issues raised by Reviewers #4 and #5. 

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

**********

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Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

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Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: Thank you for addressing my concerns regarding the clarity of statistics and my concerns regarding the interpretation of how the ED clinicians were diagnosing. In particular i found the stats easier to interpret with less extraneous information.

Reviewer #4: Thanks to the Editorial Staff for the opportunity to review this revised article. It is an incredible piece of work. The scale of which was huge. I have read the article and I agree with the discussion. I see on Page 4 ( introduction) line 2 has an error in ' per 100,00 ') . Two words are underlined on page 22 ( results). As a PEM physician I found the article relatively easy to comprehend. This is testament to the adjustments made in lieu of the previous reviewers and the balanced discussion.

Reviewer #5: The authors have adequately addressed the reviewers' comments and queries.

The only additional comment I have is that I wonder about incorporation bias when looking at the values that diagnose pyogenic bacterial CAP, especially with regards to the inflammatory markers. If the members of the expert panel (i.e., the gold standard) believe that high inflammatory markers strongly point to a diagnosis of pyogenic bacterial CAP, and incorporate that into their evaluation, it would not be surprising that these markers predict what the reference standard considers pyogenic bacterial CAP. Perhaps a comment to that effect might be warranted in the limitations?

**********

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: Yes: Elliot Lyon

Reviewer #4: Yes: Michael Barrett

Reviewer #5: No

**********

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Dec 11;19(12):e0311201. doi: 10.1371/journal.pone.0311201.r005

Author response to Decision Letter 1


3 Sep 2024

We have made the minor changes requested by the Editor and reviewers 4 and 5.

Attachment

Submitted filename: Response to Reviewers,Sept3,2024.docx

pone.0311201.s010.docx (13.6KB, docx)

Decision Letter 2

Maurizio Balbi

8 Sep 2024

Accuracy of the diagnosis of pneumonia in Canadian pediatric emergency departments: a prospective cohort study

PONE-D-24-14952R2

Dear Dr. Robinson,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Maurizio Balbi

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Maurizio Balbi

2 Oct 2024

PONE-D-24-14952R2

PLOS ONE

Dear Dr. Robinson,

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on behalf of

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Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File. Alberta Children’s Hospital ethics approval.

    (PDF)

    pone.0311201.s001.pdf (177.2KB, pdf)
    S2 File. Hospital for Sick Children’s ethics approval.

    (PDF)

    pone.0311201.s002.pdf (114.7KB, pdf)
    S3 File. Queen’s University ethics approval.

    (PDF)

    S4 File. Western University ethics approval.

    (PDF)

    pone.0311201.s004.pdf (51.5KB, pdf)
    S5 File. Montreal Children’s Hospital ethics approval.

    (PDF)

    pone.0311201.s005.pdf (520.7KB, pdf)
    S6 File. Centre Hospitalier Universitaire Sainte-Justine ethics approval.

    (PDF)

    pone.0311201.s006.pdf (1.5MB, pdf)
    S7 File. Stollery Children’s Hospital ethics approval.

    (PDF)

    pone.0311201.s007.pdf (131.9KB, pdf)
    Attachment

    Submitted filename: RESPONSE TO EDITOR AND REVIEWERS.docx

    pone.0311201.s008.docx (14.7KB, docx)
    Attachment

    Submitted filename: RESPONSE TO REVIEWERS.docx

    pone.0311201.s009.docx (24.2KB, docx)
    Attachment

    Submitted filename: Response to Reviewers,Sept3,2024.docx

    pone.0311201.s010.docx (13.6KB, docx)

    Data Availability Statement

    The data underlying the results presented in the study are available from Biostatistical Support, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada. [r4k@ucalgary.ca].


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