Background <p>Circulating eosinophils can be measured inexpensively and reproducibly in routine care. Beyond their role in parasite defense and allergy, blood eosinophilia is now a key biomarker in respiratory medicine: prognostic, predictive, and recognized as a “treatable trait.” Its role as a marker of susceptibility, however, is not well defined.</p> Methods <p>We conducted a monocentric retrospective hospital-based cohort study at Montpellier University Hospital (France), including all adults hospitalized in 2018 with a complete blood count and without prior respiratory disease. Eosinophil counts were stratified as &lt; 150/mm³, 150–299/mm³, and ≥ 300/mm³. The primary outcome was incident respiratory disease, defined by hospitalization with a respiratory diagnosis (ICD-10 J00–J99) or initiation of inhaled therapy (ATC R03). Follow-up extended to December 2024; secondary outcomes included diagnostic subcategories and ICU admission.</p> Results <p>Among 24,405 patients, 6,173 (25.3%) developed incident respiratory disease. Event rates followed a dose-response pattern across eosinophil strata: 21.7% (&lt; 150/mm³), 26.0% (150–299/mm³), and 32.9% (≥ 300/mm³; <i>p</i> &lt; 0.001 pairwise comparisons across all groups). After multivariable adjustment, eosinophilia remained independently associated with higher risk of developing respiratory disease (HR 1.45, 95% CI 1.35–1.55). Baseline eosinophilia was also associated to increased ICU admissions and greater disease severity during the follow-up.</p> Conclusion <p>Blood eosinophilia was strongly associated with both increased risk of developing incident respiratory disease and in-hospital severity, in a clear dose–response manner. However, most patients with high counts (&gt; 300/mm3) did not develop respiratory events, underscoring the need to integrate blood eosinophil counts with complementary clinical and biological data for risk stratification.</p>

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Blood eosinophilia as a susceptibility biomarker for incident respiratory disease in hospitalized adults: a retrospective cohort study

  • Charles Roure,
  • Jeremy Charriot,
  • Dany Jaffuel,
  • Erika Nogue,
  • Manal Ahikki,
  • Edouard Tuaillon,
  • Nicolas Molinari,
  • Arnaud Bourdin,
  • Engi Ahmed

摘要

Background

Circulating eosinophils can be measured inexpensively and reproducibly in routine care. Beyond their role in parasite defense and allergy, blood eosinophilia is now a key biomarker in respiratory medicine: prognostic, predictive, and recognized as a “treatable trait.” Its role as a marker of susceptibility, however, is not well defined.

Methods

We conducted a monocentric retrospective hospital-based cohort study at Montpellier University Hospital (France), including all adults hospitalized in 2018 with a complete blood count and without prior respiratory disease. Eosinophil counts were stratified as < 150/mm³, 150–299/mm³, and ≥ 300/mm³. The primary outcome was incident respiratory disease, defined by hospitalization with a respiratory diagnosis (ICD-10 J00–J99) or initiation of inhaled therapy (ATC R03). Follow-up extended to December 2024; secondary outcomes included diagnostic subcategories and ICU admission.

Results

Among 24,405 patients, 6,173 (25.3%) developed incident respiratory disease. Event rates followed a dose-response pattern across eosinophil strata: 21.7% (< 150/mm³), 26.0% (150–299/mm³), and 32.9% (≥ 300/mm³; p < 0.001 pairwise comparisons across all groups). After multivariable adjustment, eosinophilia remained independently associated with higher risk of developing respiratory disease (HR 1.45, 95% CI 1.35–1.55). Baseline eosinophilia was also associated to increased ICU admissions and greater disease severity during the follow-up.

Conclusion

Blood eosinophilia was strongly associated with both increased risk of developing incident respiratory disease and in-hospital severity, in a clear dose–response manner. However, most patients with high counts (> 300/mm3) did not develop respiratory events, underscoring the need to integrate blood eosinophil counts with complementary clinical and biological data for risk stratification.