Building a Prediction Model for Radiographically Confirmed Pneumonia in Peruvian Children: From Symptoms to Imaging

Farhan Pervaiz, Miguel A. Chavez, Laura E. Ellington, Matthew Grigsby, Robert H Gilman, Catherine H. Miele, Dante Figueroa-Quintanilla, Patricia Compen-Chang, Julio Marin-Concha, Eric McCollum, William Checkley

Research output: Contribution to journalArticle

Abstract

Background: Community-acquired pneumonia remains the leading cause of death in children worldwide, and current diagnostic guidelines in resource-poor settings are neither sensitive nor specific. We sought to determine the ability to correctly diagnose radiographically confirmed clinical pneumonia when diagnostics tools were added to clinical signs and symptoms in a cohort of children with acute respiratory illnesses in Peru. Methods: Children < 5 years of age with an acute respiratory illness presenting to a tertiary hospital in Lima, Peru, were enrolled. The ability to predict radiographically confirmed clinical pneumonia was assessed using logistic regression under four additive scenarios: clinical signs and symptoms only, addition of lung auscultation, addition of oxyhemoglobin saturation (SpO2), and addition of lung ultrasound. Results: Of 832 children (mean age, 21.3 months; 59% boys), 453 (54.6%) had clinical pneumonia and 221 (26.6%) were radiographically confirmed. Children with radiographically confirmed clinical pneumonia had lower average SpO2 than those without (95.9% vs 96.6%, respectively; P <.01). The ability to correctly identify radiographically confirmed clinical pneumonia using clinical signs and symptoms was limited (area under the curve [AUC] = 0.62; 95% CI, 0.58-0.67) with a sensitivity of 66% (95% CI, 59%-73%) and specificity of 53% (95% CI, 49%-57%). The addition of lung auscultation improved classification (AUC = 0.73; 95% CI, 0.69-0.77) with a sensitivity of 75% (95% CI, 69%-81%) and specificity of 53% (95% CI, 49%-57%) for the presence of crackles. In contrast, the addition of SpO2 did not improve classification (AUC = 0.73; 95% CI, 0.69-0.77) with a sensitivity of 40% (95% CI, 33%-47%) and specificity of 72% (95% CI, 68%-75%) for an SpO2 ≤ 92%. Adding consolidation on lung ultrasound was associated with the largest improvement in classification (AUC = 0.85; 95% CI, 0.82-0.89) with a sensitivity of 55% (95% CI, 48%-63%) and specificity of 95% (95% CI, 93%-97%). Conclusions: The addition of lung ultrasound and auscultation to clinical signs and symptoms improved the ability to correctly classify radiographically confirmed clinical pneumonia. Implementation of auscultation- and ultrasound-based diagnostic tools can be considered to improve diagnostic yield of pneumonia in resource-poor settings.

Original languageEnglish (US)
Pages (from-to)1385-1394
Number of pages10
JournalChest
Volume154
Issue number6
DOIs
StatePublished - Dec 1 2018

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Pneumonia
Auscultation
Signs and Symptoms
Area Under Curve
Lung
Peru
Oxyhemoglobins
Respiratory Sounds
Tertiary Care Centers
Cause of Death
Ultrasonography
Logistic Models
Guidelines

Keywords

  • auscultation
  • lung ultrasound
  • oxyhemoglobin saturation
  • pneumonia
  • prediction models

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine
  • Cardiology and Cardiovascular Medicine

Cite this

Building a Prediction Model for Radiographically Confirmed Pneumonia in Peruvian Children : From Symptoms to Imaging. / Pervaiz, Farhan; Chavez, Miguel A.; Ellington, Laura E.; Grigsby, Matthew; Gilman, Robert H; Miele, Catherine H.; Figueroa-Quintanilla, Dante; Compen-Chang, Patricia; Marin-Concha, Julio; McCollum, Eric; Checkley, William.

In: Chest, Vol. 154, No. 6, 01.12.2018, p. 1385-1394.

Research output: Contribution to journalArticle

Pervaiz, F, Chavez, MA, Ellington, LE, Grigsby, M, Gilman, RH, Miele, CH, Figueroa-Quintanilla, D, Compen-Chang, P, Marin-Concha, J, McCollum, E & Checkley, W 2018, 'Building a Prediction Model for Radiographically Confirmed Pneumonia in Peruvian Children: From Symptoms to Imaging', Chest, vol. 154, no. 6, pp. 1385-1394. https://doi.org/10.1016/j.chest.2018.09.006
Pervaiz, Farhan ; Chavez, Miguel A. ; Ellington, Laura E. ; Grigsby, Matthew ; Gilman, Robert H ; Miele, Catherine H. ; Figueroa-Quintanilla, Dante ; Compen-Chang, Patricia ; Marin-Concha, Julio ; McCollum, Eric ; Checkley, William. / Building a Prediction Model for Radiographically Confirmed Pneumonia in Peruvian Children : From Symptoms to Imaging. In: Chest. 2018 ; Vol. 154, No. 6. pp. 1385-1394.
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AU - Pervaiz, Farhan

AU - Chavez, Miguel A.

AU - Ellington, Laura E.

AU - Grigsby, Matthew

AU - Gilman, Robert H

AU - Miele, Catherine H.

AU - Figueroa-Quintanilla, Dante

AU - Compen-Chang, Patricia

AU - Marin-Concha, Julio

AU - McCollum, Eric

AU - Checkley, William

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N2 - Background: Community-acquired pneumonia remains the leading cause of death in children worldwide, and current diagnostic guidelines in resource-poor settings are neither sensitive nor specific. We sought to determine the ability to correctly diagnose radiographically confirmed clinical pneumonia when diagnostics tools were added to clinical signs and symptoms in a cohort of children with acute respiratory illnesses in Peru. Methods: Children < 5 years of age with an acute respiratory illness presenting to a tertiary hospital in Lima, Peru, were enrolled. The ability to predict radiographically confirmed clinical pneumonia was assessed using logistic regression under four additive scenarios: clinical signs and symptoms only, addition of lung auscultation, addition of oxyhemoglobin saturation (SpO2), and addition of lung ultrasound. Results: Of 832 children (mean age, 21.3 months; 59% boys), 453 (54.6%) had clinical pneumonia and 221 (26.6%) were radiographically confirmed. Children with radiographically confirmed clinical pneumonia had lower average SpO2 than those without (95.9% vs 96.6%, respectively; P <.01). The ability to correctly identify radiographically confirmed clinical pneumonia using clinical signs and symptoms was limited (area under the curve [AUC] = 0.62; 95% CI, 0.58-0.67) with a sensitivity of 66% (95% CI, 59%-73%) and specificity of 53% (95% CI, 49%-57%). The addition of lung auscultation improved classification (AUC = 0.73; 95% CI, 0.69-0.77) with a sensitivity of 75% (95% CI, 69%-81%) and specificity of 53% (95% CI, 49%-57%) for the presence of crackles. In contrast, the addition of SpO2 did not improve classification (AUC = 0.73; 95% CI, 0.69-0.77) with a sensitivity of 40% (95% CI, 33%-47%) and specificity of 72% (95% CI, 68%-75%) for an SpO2 ≤ 92%. Adding consolidation on lung ultrasound was associated with the largest improvement in classification (AUC = 0.85; 95% CI, 0.82-0.89) with a sensitivity of 55% (95% CI, 48%-63%) and specificity of 95% (95% CI, 93%-97%). Conclusions: The addition of lung ultrasound and auscultation to clinical signs and symptoms improved the ability to correctly classify radiographically confirmed clinical pneumonia. Implementation of auscultation- and ultrasound-based diagnostic tools can be considered to improve diagnostic yield of pneumonia in resource-poor settings.

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