Community-acquired pneumonia in the emergency department: an algorithm to facilitate diagnosis and guide chest CT scan indication.


Journal

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
ISSN: 1469-0691
Titre abrégé: Clin Microbiol Infect
Pays: England
ID NLM: 9516420

Informations de publication

Date de publication:
Mar 2020
Historique:
received: 25 03 2019
revised: 12 06 2019
accepted: 17 06 2019
pubmed: 10 7 2019
medline: 2 10 2020
entrez: 9 7 2019
Statut: ppublish

Résumé

The aim was to create and validate a community-acquired pneumonia (CAP) diagnostic algorithm to facilitate diagnosis and guide chest computed tomography (CT) scan indication in patients with CAP suspicion in Emergency Departments (ED). We performed an analysis of CAP suspected patients enrolled in the ESCAPED study who had undergone chest CT scan and detection of respiratory pathogens through nasopharyngeal PCRs. An adjudication committee assigned the final CAP probability (reference standard). Variables associated with confirmed CAP were used to create weighted CAP diagnostic scores. We estimated the score values for which CT scans helped correctly identify CAP, therefore creating a CAP diagnosis algorithm. Algorithms were externally validated in an independent cohort of 200 patients consecutively admitted in a Swiss hospital for CAP suspicion. Among the 319 patients included, 51% (163/319) were classified as confirmed CAP and 49% (156/319) as excluded CAP. Cough (weight = 1), chest pain (1), fever (1), positive PCR (except for rhinovirus) (1), C-reactive protein ≥50 mg/L (2) and chest X-ray parenchymal infiltrate (2) were associated with CAP. Patients with a score below 3 had a low probability of CAP (17%, 14/84), whereas those above 5 had a high probability (88%, 51/58). The algorithm (score calculation + CT scan in patients with score between 3 and 5) showed sensitivity 73% (95% CI 66-80), specificity 89% (95% CI 83-94), positive predictive value (PPV) 88% (95% CI 81-93), negative predictive value (NPV) 76% (95% CI 69-82) and area under the curve (AUC) 0.81 (95% CI 0.77-0.85). The algorithm displayed similar performance in the validation cohort (sensitivity 88% (95% CI 81-92), specificity 72% (95% CI 60-81), PPV 86% (95% CI 79-91), NPV 75% (95% CI 63-84) and AUC 0.80 (95% CI 0.73-0.87). Our CAP diagnostic algorithm may help reduce CAP misdiagnosis and optimize the use of chest CT scan.

Identifiants

pubmed: 31284034
pii: S1198-743X(19)30377-5
doi: 10.1016/j.cmi.2019.06.026
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

382.e1-382.e7

Investigateurs

Y E Claessens (YE)
X Duval (X)
E Bouvard (E)
M F Carette (MF)
M P Debray (MP)
C Mayaud (C)
C Leport (C)
N Houhou (N)
S Tubiana (S)
M Benjoar (M)
F X Blanc (FX)
A L Brun (AL)
L Epelboin (L)
C Ficko (C)
A Khalil (A)
H Lefloch (H)
J M Naccache (JM)
B Rammaert (B)
A Abry (A)
J C Allo (JC)
S Andre (S)
C Andreotti (C)
N Baarir (N)
M Bendahou (M)
L Benlafia (L)
J Bernard (J)
A Berthoumieu (A)
M E Billemont (ME)
J Bokobza (J)
A L Brun (AL)
E Burggraff (E)
P Canavaggio (P)
M F Carette (MF)
E Casalino (E)
S Castro (S)
C Choquet (C)
H Clément (H)
L Colosi (L)
A Dabreteau (A)
S Damelincourt (S)
S Dautheville (S)
M P Debray (MP)
M Delay (M)
S Delerme (S)
L Depierre (L)
F Djamouri (F)
F Dumas (F)
M R S Fadel (MRS)
A Feydey (A)
Y Freund (Y)
L Garcia (L)
H Goulet (H)
P Hausfater (P)
E Ilic-Habensus (E)
M O Josse (MO)
J Kansao (J)
Y Kieffer (Y)
F Lecomte (F)
K Lemkarane (K)
P Madonna (P)
O Meyniard (O)
L Mzabi (L)
D Pariente (D)
J Pernet (J)
F Perruche (F)
J M Piquet (JM)
R Ranerison (R)
P Ray (P)
F Renai (F)
E Rouff (E)
D Saget (D)
K Saïdi (K)
G Sauvin (G)
E Trabattoni (E)
N Trimech (N)
C Auger (C)
B Pasquet (B)
S Tamazirt (S)
J M Treluyer (JM)
F Tubach (F)
J Wang (J)
O Chassany (O)
C Misse (C)

Informations de copyright

Copyright © 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Auteurs

P Loubet (P)

INSERM, IAME, UMR 1137, Paris, France; AP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris, France. Electronic address: paul.loubet@aphp.fr.

S Tubiana (S)

INSERM, IAME, UMR 1137, Paris, France.

Y E Claessens (YE)

Service des urgences, Hôpital Princesse Grace, Monaco.

L Epelboin (L)

Unité des Maladies Infectieuses et Tropicales, Centre Hospitalier Andrée Rosemon, Cayenne, French Guiana; Ecosystèmes Amazoniens et Pathologie Tropicale (EPaT) EA3593, Université de la Guyane, Cayenne, French Guiana; Service des Maladies Infectieuses et Tropicales, Groupe Hospitalier Pitié-Salpêtrière, 47-83 bd de l'hôpital, Paris, France.

C Ficko (C)

Service de Maladies Infectieuses et Tropicales, Hôpital Inter-armées de Bégin, Saint-Mandé, France.

J Le Bel (J)

INSERM, IAME, UMR 1137, Paris, France; Département de Médecine Générale, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.

B Rammaert (B)

Service de Maladies Infectieuses et Tropicales, CHU de Poitiers, Poitiers, France; Université de Poitiers, Poitiers, France; Inserm U1070, Poitiers, France.

N Garin (N)

Service de Médecine Interne Générale, Hôpitaux Universitaires de Genève, Genève, Switzerland.

V Prendki (V)

Service de Médecine Interne de l'âgé, Hôpitaux Universitaires de Genève, Genève, Switzerland.

J Stirnemann (J)

Service de Médecine Interne Générale, Hôpitaux Universitaires de Genève, Genève, Switzerland.

C Leport (C)

INSERM, IAME, UMR 1137, Paris, France; Université Paris-Diderot, Paris, France; AP-HP, Unité de Coordination du Risque Épidémique et biologique, Paris, France.

Y Yazdanpanah (Y)

INSERM, IAME, UMR 1137, Paris, France; AP-HP, Hôpital Bichat-Claude Bernard, Service de Maladies Infectieuses et Tropicales, Paris, France.

E Varon (E)

Centre National de Référence des Pneumocoques, Centre Hospitalier Intercommunal de Créteil, Créteil, France.

X Duval (X)

INSERM, IAME, UMR 1137, Paris, France; Université Paris-Diderot, Paris, France; Inserm CIC 1425, Hôpital Bichat-Claude Bernard, Paris, France.

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Classifications MeSH