I have read the journal's policy and the authors of this manuscript have the following competing interests: All authors, including those employed by AstraZeneca, participated in the data interpretation, decision to publish, and preparation of the manuscript. All authors had full access to study results and had final responsibility for the decision to submit for publication. MK is an employee of the Observational and Pragmatic Research Institute Pte LTD, which conducted this study and which has conducted paid research in respiratory disease on behalf of the following other organizations in the past 5 years: Aerocrine; AKL Ltd.; Almirall; AstraZeneca; British Lung Foundation; Boehringer Ingelheim; Chiesi; GlaxoSmithKline; Mylan; Mundipharma; Napp; Novartis; Orion; Respiratory Effectiveness Group; Takeda; Teva; and Zentiva, a Sanofi company. JN is an employee, and TNT, GG, and SR are employees and shareholders of AstraZeneca, which supplied the funding for this study. MvdB has, within the last 5 years, received research grants paid to the University of Groningen from AstraZeneca, GlaxoSmithKline, Teva, and Chiesi. GB has, within the last 5 years, received honoraria for lectures from AstraZeneca, Boehringer-Ingelheim, Chiesi, GlaxoSmithKline, Novartis, Pfizer, and Teva; he is a member of advisory boards for AstraZeneca, Boehringer-Ingelheim, GlaxoSmithKline, Novartis, Sanofi/Regeneron, and Teva. RJ reports grants, personal fees and non-financial support from Astra Zeneca, personal fees from Boehringer Ingelheim, personal fees from Chiesi, personal fees and non-financial support from GSK, grants and personal fees from Novartis, non-financial support from Nutricia, personal fees from Pfizer, outside the submitted work.JWHK reports grants and personal fees from AstraZeneca, grants and personal fees from Boehringer Ingelheim, grants from Chiesi, grants and personal fees from GSK, grants and personal fees from Novartis, grants from Mundi Pharma, grants from TEVA, outside the submitted work. AMG has attended advisory boards for Glaxo SmithKline, Novartis, AstraZeneca, Boehringer Ingelheim andTeva. He has received speaker fees from Novartis, AstraZeneca, Vectura, Boehringer Ingelheim and Teva. He has participated in research with Hoffman La Roche, GlaxoSmithKline and Boehringer Ingelheim. He has attended international conferences sponsored by AstraZeneca and Boehringer Ingelheim. He has consultancy agreements with AstraZeneca and Vectura. IDP has received speaker’s honoraria for speaking at sponsored meetings from AstraZeneca, Boehringer Inglehiem, Aerocrine, Almirall, Novartis, and GSK and a payment for organising an educational event for SPRs from AZ. He has received honoraria for attending advisory panels with Almirall, Genentech, Regeneron, AstraZeneca, Boehringer Ingelheim, GSK, MSD, Schering-Plough, Novartis, Dey, Napp and Respivert. He has received sponsorship to attend international scientific meetings from Boehringer Ingelheim, GSK, AstraZeneca and Napp. DBP has board membership with Aerocrine, Amgen, AstraZeneca, Boehringer Ingelheim, Chiesi, Mylan, Mundipharma, Napp, Novartis, and Teva Pharmaceuticals; consultancy agreements with Almirall, Amgen, AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, Mylan, Mundipharma, Napp, Novartis, Pfizer, Teva Pharmaceuticals, and Theravance; grants and unrestricted funding for investigator-initiated studies (conducted through Observational and Pragmatic Research Institute Pte Ltd) from Aerocrine, AKL Research and Development Ltd, AstraZeneca, Boehringer Ingelheim, British Lung Foundation, Chiesi, Mylan, Mundipharma, Napp, Novartis, Pfizer, Respiratory Effectiveness Group, Teva Pharmaceuticals, Theravance, UK National Health Service, Zentiva; payment for lectures/speaking engagements from Almirall, AstraZeneca, Boehringer Ingelheim, Chiesi, Cipla, GlaxoSmithKline, Kyorin, Mylan, Merck, Mundipharma, Novartis, Pfizer, Skyepharma, and Teva Pharmaceuticals; payment for manuscript preparation from Mundipharma and Teva Pharmaceuticals; payment for the development of educational materials from Mundipharma and Novartis; payment for travel/accommodation/meeting expenses from Aerocrine, AstraZeneca, Boehringer Ingelheim, Mundipharma, Napp, Novartis, and Teva Pharmaceuticals; funding for patient enrolment or completion of research from Chiesi, Novartis, Teva Pharmaceuticals, and Zentiva; stock/stock options from AKL Research and Development Ltd which produces phytopharmaceuticals; owns 74% of the social enterprise Optimum Patient Care Ltd (Australia and UK) and 74% of Observational and Pragmatic Research Institute Pte Ltd (Singapore); and is peer reviewer for grant committees of the Efficacy and Mechanism Evaluation programme, and Health Technology Assessment. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Recent studies have demonstrated an association between high blood eosinophil counts and greater risk of asthma exacerbations. We sought to determine whether patients hospitalized for an asthma exacerbation were at greater risk of readmission if they had a high blood eosinophil count documented before the first hospitalization.
This historical cohort study drew on 2 years of medical record data (Clinical Practice Research Datalink with Hospital Episode Statistics linkage) of patients (aged ≥5 years) admitted to hospital in England for asthma, with recorded blood eosinophil count within 1 baseline year before admission. We analyzed the association between high blood eosinophil count (≥0.35x109 cells/L) and readmission risk during 1 year of follow-up after hospital discharge, with adjustment for predefined, relevant confounders using forward selection.
We identified 2,613 eligible patients with asthma-related admission, of median age 51 years (interquartile range, 36–69) and 76% women (1,997/2,613). Overall, 835/2,613 (32.0%) had a preadmission high blood eosinophil count. During the follow-up year, 130/2,613 patients (5.0%) were readmitted for asthma, including 55/835 (6.6%) with vs. 75/1,778 (4.2%) without high blood eosinophil count at baseline (adjusted hazard ratio [HR] 1.49; 95% CI 1.04–2.13, p = 0.029). The association was strongest in never-smokers (n = 1,296; HR 2.16, 95% CI 1.27–3.68, p = 0.005) and absent in current smokers (n = 547; HR 1.00, 95% CI 0.49–2.04, p = 0.997).
A high blood eosinophil count in the year before an asthma-related hospitalization is associated with increased risk of readmission within the following year. These findings suggest that patients with asthma and preadmission high blood eosinophil count require careful follow-up, with treatment optimization, after discharge.
Severe asthma exacerbations may result in hospital admissions, relatively rare but important events with adverse implications for patients’ quality of life, health care resource use, and related costs. Approximately 83,000 hospital episodes (including inpatient, day-case, and intensive care episodes) were recorded as related to asthma in England in 2011–2012, representing approximately 3.3 million patients with clinician-reported, diagnosed-and-treated asthma in England during that time [
Recent studies have demonstrated an association between high blood eosinophil counts and greater risk of asthma exacerbations, especially in patients with asthma that is not well-controlled [
Patients who are admitted to hospital for asthma-related reasons, such as a severe exacerbation, may be at risk of short-term readmission to hospital. For example, some patients with persistent airways inflammation are at risk of readmission after discharge despite treatment with corticosteroids [
The aim of this study was to determine if patients hospitalized for an asthma exacerbation were more likely to be readmitted if their preadmission blood eosinophil count was elevated. Our hypothesis was that standard management of asthma exacerbations is insufficient to prevent readmissions for patients who have high blood eosinophil counts in the year preceding a hospitalization.
We used primary and secondary care data from the Clinical Practice Research Datalink (CPRD) and linked Hospital Episode Statistics (HES) for this historical cohort study of patients with asthma who had been admitted to hospital in England. The CPRD is a large well-validated database, frequently used for medical and health research, that contains de-identified, longitudinal medical records of 5 million patients from >600 UK practices [
The study dataset spanned the period from April 1997 through February 2016.
Eligible patients were 5 years or older at the time of their most recent asthma diagnosis and had active asthma, which we defined as (1) a diagnostic Read code for asthma qualifying for inclusion in the asthma registry, which general practices in the UK maintain for the Quality Outcomes Framework (QOF) [
Eligible patients had to have available, continuous data throughout the study period (
The study was performed in compliance with all applicable local and international laws and regulations and to standards suggested for observational studies, including an independent advisory group, use of an
The exposure of interest was the most recent blood eosinophil count measured within 1 year before hospital admission. For patients who had multiple tests in the baseline year, we used the blood eosinophil count (with no oral corticosteroid prescription within 2 weeks prior) that was closest to the admission. A high blood eosinophil count was defined as ≥0.35x109 cells/L (or ≥0.4x109 cells/L when counts were recorded to only 1 decimal place). This value was chosen based on our findings in a prior study in which patients with blood eosinophil counts >0.3x109 cells/L experienced more severe exacerbations and poorer asthma control [
The primary outcome was readmission to hospital with asthma as primary diagnosis (ICD-10 code J45/J46) over a 4-week outcome period and over a 1-year outcome period after discharge from the hospital (
Patients’ baseline characteristics and hospital readmissions were compared between patients with high and normal blood eosinophil counts using Pearson's χ2 test of independent categories for categorical variables, and the Mann-Whitney test for continuous variables.
Kaplan-Meier curves were constructed for patients with and without high blood eosinophil count for the maximum follow-up period of 1 year after hospital discharge. Comparisons were made with log-rank analyses, and patients were censored if they died.
Cox proportional hazard regression, with the time from hospital discharge date to the first readmission date as the “survival” time, was performed to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) for the association between high blood eosinophil count and time to readmission, adjusted for potential confounders. The following variables were evaluated for their potential confounding effect on the effect estimate: sex, age, body mass index (BMI), smoking habits, timing of blood eosinophil count relative to the first hospitalization, Charlson comorbidity index (categorical as 0, 1−4, ≥5), comorbidities, and Global Initiative for Asthma [
Potential effect modification of smoking status was tested for significance by including an interaction term into the full model. We conducted several sensitivity analyses, repeating the outcome analyses using alternative definitions of high blood eosinophil counts (≥0.25x109 cells/L or ≥0.3x109 cells/L if rounded, and ≥0.45x109 cells/L or ≥0.5x109 cells/L if rounded) and examining outcomes in two subsets of patients: (1) after exclusion of those who initiated inhaled corticosteroids (ICS) after their first asthma-related hospital admission and (2) after exclusion of patients with a concomitant diagnosis of COPD.
Statistical analyses were conducted using IBM SPSS Statistics version 23 (IBM SPSS Statistics, Feltham, Middlesex, UK) and R version 3.0.2 (The R Project for Statistical Computing;
Of 146,485 patients in the CPRD with HES data linkage, 22,940 (16%) patients had at least one hospital admission for asthma and ≥2 years of medical record data, and 3,611 patients (16%) of those hospitalized had an eosinophil count recorded within 1 year before the hospitalization (and no oral corticosteroid prescription within 2 weeks prior). Of these 3,611 patients, 2,613 patients (72%) were ≥5 years old, had active asthma, and were eligible for the study (
CPRD = Clinical Practice Research Database. HES = Hospital Episode Statistics. OCS = oral corticosteroid. QOF = Quality Outcomes Framework.
In the study population, 482 of 2,613 patients (18%) were discharged from hospital on the same day. Six patients died (one patient died 31 weeks after readmission for asthma and was not censored; others were censored) during 1 year of follow up.
Characteristics of the total population with blood eosinophil count (n = 2,613) and 13,016 patients with asthma who met all eligibility criteria except availability of blood eosinophil count during baseline are presented in
A high blood eosinophil count (≥0.35x109 cells/L) was recorded during the year before the hospital admission for 835 of 2,613 patients (32%). The high blood eosinophil cohort had a median age of 45 (vs. 54 years in the cohort with eosinophil count of <0.35x109 cells/L) and included proportionately fewer women and fewer overweight and obese patients (
All patients |
Blood eosinophil cohort | |||
---|---|---|---|---|
Variable | <0.35x109 cells/L |
≥0.35x109 cells/L |
P value |
|
Age | ||||
Median (IQR) | 51.0 (36.0–69.0) | 54.0 (39.0–70.3) | 45.0 (30.0–65.0) | <0.0001 |
5–12 years | 56 (2.1) | 17 (1.0) | 39 (4.7) | <0.0001 |
13–17 years | 77 (2.9) | 31 (1.7) | 46 (5.5) | |
18–64 years | 1,681 (64.3) | 1,141 (64.2) | 540 (64.7) | |
≥65 years | 799 (30.6) | 589 (33.1) | 210 (25.1) | |
Female sex | 1,997 (75.7) | 1,392 (78.3) | 585 (70.1) | <0.0001 |
Smoking status |
||||
Data available | 2,597 (99.4) | 1,771 (99.6) | 826 (98.9) | |
Current smoker | 547 (21.1) | 378 (21.3) | 169 (20.5) | 0.007 |
Ex-smoker | 754 (29.0) | 544 (30.7) | 210 (25.4) | |
Never smoker | 1,296 (49.9) | 849 (47.9) | 447 (54.1) | |
Body mass index |
||||
Data available | 2,260 (86.5) | 1,551 (87.2) | 709 (84.9) | |
Mean (SD) | 29.2 (7.0) | 29.6 (7.0) | 28.4 (7.0) | <0.0001 |
<18.5 kg/m2 | 78 (3.5) | 38 (2.5) | 40 (5.6) | <0.0001 |
≥18.5 kg/m2 to <25 kg/m2 | 625 (27.7) | 393 (25.3) | 232 (32.7) | |
≥25 kg/m2 to <30 kg/m2 | 625 (27.7) | 450 (29.0) | 175 (24.7) | |
≥30 kg/m2 | 932 (41.2) | 670 (43.2) | 262 (37.0) | |
Allergic/non-allergic rhinitis |
876 (33.5) | 545 (30.7) | 331 (39.6) | <0.0001 |
Atopic eczema |
927 (35.5) | 595 (33.5) | 332 (39.8) | <0.0001 |
Nasal polyps |
83 (3.2) | 39 (2.2) | 44 (5.3) | <0.0001 |
Chronic rhinosinusitis |
579 (22.2) | 400 (22.5) | 179 (21.4) | 0.54 |
COPDc | 284 (10.9) | 192 (10.8) | 92 (11.0) | 0.87 |
GERDc | 474 (18.1) | 355 (20.0) | 119 (14.3) | <0.001 |
Cardiovascular disease |
654 (25.0) | 491 (27.6) | 163 (19.5) | <0.0001 |
Charlson comorbidity index | ||||
0 | 611 (23.4) | 429 (24.1) | 182 (21.8) | 0.028 |
1–4 | 1,661 (63.6) | 1,101 (61.9) | 560 (67.1) | |
≥5 | 341 (13.1) | 248 (13.9) | 93 (11.1) | |
GINA step of asthma treatment |
||||
1 | 124 (4.7) | 78 (4.4) | 46 (5.5) | 0.009 |
2 | 493 (18.9) | 357 (20.1) | 136 (16.3) | |
3 | 468 (17.9) | 298 (16.8) | 170 (20.4) | |
4 | 1,220 (46.7) | 848 (47.7) | 372 (44.6) | |
5 | 308 (11.8) | 197 (11.1) | 111 (13.3) | |
≥1 ICS inhaler prescribed | 2,444 (93.5) | 1,671 (94.0) | 773 (92.6) | 0.173 |
Daily dose of ICS (μg/day), median (IQR) |
262 (110–521) | 263 (110–534) | 247 (99–492) | 0.041 |
≥1 SABA inhaler prescribed | 2,432 (93.1) | 1,646 (92.6) | 786 (94.1) | 0.144 |
Daily SABA dose, median (IQR) |
1.64 (0.82–3.55) | 1.64 (0.66–3.29) | 2.04 (0.82–4.11) | <0.0001 |
OCS daily dose (g), median (IQR) | 0.55 (0–1.64) | 0.55 (0–1.56) | 0.55 (0–1.75) | 0.139 |
No. severe asthma exacerbations | ||||
0 | 747 (28.6) | 516 (29.0) | 231 (27.7) | 0.25 |
1 | 848 (32.5) | 589 (33.1) | 259 (31.0) | |
2 | 506 (19.4) | 345 (19.4) | 161 (19.3) | |
3 | 266 (10.2) | 174 (9.8) | 92 (11.0) | |
≥4 | 246 (9.4) | 154 (8.7) | 92 (11.0) |
Data expressed as No. (%) unless otherwise noted. COPD = chronic obstructive pulmonary disease. GERD = gastroesophageal reflux disease. GINA = Global Initiative for Asthma; ICS = inhaled corticosteroid; OCS = oral corticosteroid; SABA = short-acting β-agonist.
aP-value comparing blood eosinophil cohorts, computed from χ2 test for categorical variables, or Mann-Whitney test, for continuous variables. Where variables are presented as both continuous and categorical, the p-value is from the Mann-Whitney test.
bThe closest BMI within 10 years of hospital discharge, and the smoking status closest to and within 5 years before hospital discharge, were included. The GINA treatment step was determined based on the last prescription before the hospitalization (
cComorbidities were those with diagnostic Read code ever-recorded in the available data before hospital discharge.
dICS dose expressed as fluticasone propionate equivalent (μg/day), and one SABA dose defined as 200 μg in albuterol equivalents.
The likelihood of a blood eosinophil count being recorded was greater at dates closer to the hospital admission (
The median duration of hospitalization (2 nights) was the same in patients with and without a high blood eosinophil count; however, there were fewer patients with a high blood eosinophil count who had a long hospital stay (
All patients |
Blood eosinophil cohort | |||
---|---|---|---|---|
Variable | <0.35x109 cells/L |
≥0.35x109 cells/L |
P value |
|
Nights in hospital, median (IQR) | 2 (1–5) | 2 (1–4) | ||
No. nights in hospital, n (%) | ||||
0 | 482 (18.4) | 323 (18.2) | 159 (19.0) | 0.006 |
1 | 529 (20.2) | 349 (19.6) | 180 (21.6) | |
2 | 356 (13.6) | 230 (12.9) | 126 (15.1) | |
3 | 281 (10.8) | 182 (10.2) | 99 (11.9) | |
4 | 243 (9.3) | 162 (9.1) | 81 (9.7) | |
5 | 149 (5.7) | 99 (5.6) | 50 (6.0) | |
6 | 142 (5.4) | 106 (6.0) | 36 (4.3) | |
≥7 | 431 (16.5) | 327 (18.4) | 104 (12.5) |
aP-value comparing blood eosinophil cohorts computed from χ2 test.
Only 6 patients were readmitted to the hospital within 4 weeks of the first admission, with no significant difference between blood eosinophil cohorts (
Eosinophil cohort | |||||
---|---|---|---|---|---|
Readmission | <0.35x109 cells/L |
≥0.35x109 cells/L |
P value |
Adjusted HR (95% CI) for blood eosinophil count ≥0.35x109/L |
P value |
With asthma as primary diagnosis (n = 2,613) | |||||
Within 4 weeks | 4 (0.2) | 2 (0.2) | 0.94 | — | — |
Within 1 year | 75 (4.2) | 55 (6.6) | 0.009 | 1.49 (1.04–2.13) | 0.029 |
By known smoking status (n = 2,597) |
|||||
Never-smokers (n = 1,296) | 29 (3.4) | 30 (6.7) | 0.007 | 2.16 (1.27–3.68) | 0.005 |
Ex-smokers (n = 754) | 19 (3.5) | 13 (6.2) | 0.010 | 1.49 (0.73–3.06) | 0.27 |
Current smokers (n = 547) | 27 (7.1) | 12 (7.1) | 0.99 | 1.00 (0.49–2.04) | 0.997 |
Never/ex-smokers pooled (n = 2,050) | 48 (3.4) | 43 (6.5) | 0.002 | 1.78 (1.17–2.73) | 0.007 |
With respiratory condition other than asthma, and asthma as subsidiary diagnosis (n = 2,613) | |||||
Within 4 weeks | 22 (1.2) | 8 (1.0) | 0.53 | — | — |
Within 1 year | 81 (4.6) | 39 (4.7) | 0.90 | 1.12 (0.76–1.65) | 0.57 |
aP-value computed using χ2 test.
bAdjusted for sex, age, smoking status, timing of blood eosinophil count measurement, duration of index hospitalization.
c16 patients with no recent record of smoking status were excluded from the analyses by smoking status.
The effect of current smoking was non-significant (p = 0.073) when tested by including an interaction term for current smoking (yes/no) and high blood eosinophil count (yes/no) into the model. The increased readmission rate with a high blood eosinophil count was found only in non-smokers (HR 1.84; 1.20–2.80; p = 0.005) and not in current smokers (HR 0.88; 0.44–1.76; p = 0.73). In this analysis of all 2,613 patients, 16 patients without recent, recorded smoking status were included as non-smokers (never-smokers plus ex-smokers).
Results were similar for patients with known smoking status, with a significant 216% higher adjusted risk of readmission for never-smokers with high blood eosinophil count, and no additional risk for current smokers with high blood eosinophil count (
A high blood eosinophil count was recorded for 1,328 patients (51%) when defined as ≥0.25x109 cells/L, and for 588 patients (23%) when defined as ≥0.45x109 cells/L. The association between a high blood eosinophil count and readmission to hospital for asthma was less pronounced and not significant for patients with blood eosinophil count of either ≥0.25x109 cells/L (HR = 1.17; 0.82−1.66; p = 0.39) or ≥0.45x109 cells/L (HR = 1.15; 0.77−1.72; p = 0.50;
A total of 169 of the 2,613 patients (6%) had no prescription for ICS in the baseline year before being hospitalized for asthma; of the 169, 115 (68%) had ICS prescribed in the outcome year. After exclusion of these 115 patients, HRs for the association with blood eosinophil count of ≥0.35x109 cells/L slightly increased as compared with those for the full population (
Results of an additional subanalysis excluding patients with a concomitant diagnosis of COPD showed no relevant difference in association for the remaining 2,329 patients (HR = 1.48; 95% CI 1.01–2.17, p = 0.045; see
In this large, historical cohort study, we found that patients who had a blood eosinophil count of ≥0.35x109 cells/L recorded in the year preceding an asthma-related hospitalization had a significantly greater risk of readmission for asthma during the year after they were discharged. Few patients (n = 6) were readmitted to hospital for asthma within 4 weeks after discharge, while by 1 year after discharge, 5% (130 of 2,613) patients were readmitted for asthma. The greater risk of readmission during 1 year follow-up was present only for patients with high blood eosinophil count who were never- or ex-smokers (not for current smokers).
Our study is one of few studies examining hospital readmissions for asthma in a general asthma population and in the real-life setting. Readmissions in the present study were comparatively infrequent relative to results in other studies: for example, in one US study, approximately 4% of patients were readmitted for an asthma exacerbation within 30 days [
Other recent studies of hospital readmissions have been limited to patients on systemic corticosteroids [
An interesting finding in the present study that requires further investigation is the effect of smoking status on association of readmissions with eosinophil count. Cigarette smoking increases levels of oxidative stress, alters airway immune responses, and increases risk of hospitalization in patients with asthma [
The median duration of hospitalization (2 nights) was the same in both normal and high blood eosinophil cohorts; however, patients with a high blood eosinophil count were less likely to have a hospital stay longer than 5 nights (17% vs. 24% of those without high eosinophil count). This finding illustrates the conundrum of eosinophilic asthma: while it tends to be more severe in terms of exacerbations and asthma control, eosinophilic asthma is also potentially more responsive to therapies targeting type 2 inflammation, including ICS and biologics.
We speculated that the association between eosinophil count and readmission could be diluted for patients with eosinophil count performed several months before the first admission; therefore, we re-examined outcomes including only patients with eosinophil counts measured close to the initial hospitalization to see if the association were stronger. However, when selecting those with eosinophil count recorded within 4 months before hospitalization, the numbers became small and associations non-significant, although the direction of the effect was the same: for never- and ex-smokers pooled (n = 915), the risk of readmission was 51% greater but non-significant (adjusted HR 1.69;0.60–4.76; p = 0.32).
A strength of this study is that we included a broad patient population with asthma, not limited to those with severe asthma. We selected inclusion criteria to ensure that patients’ asthma was actively managed in advance of the hospital admission, thereby excluding patients experiencing a first episode of asthma diagnosed at the time of admission. Moreover, we required that patients had not received an oral corticosteroid prescription within 2 weeks before the eosinophil count to obviate the eosinopenic effects of systemic corticosteroids [
Nevertheless, a limitation is that the study dataset comprised information collected for clinical and routine use rather than specifically for research purposes. Moreover, prescriptions for drugs prescribed by specialists are not reliably recorded in the CPRD. Therefore, we could not evaluate treatment prescribed immediately after hospital discharge. However, the daily dose of ICS prescribed by GPs in the year after admission was not significantly different between patients with and without high eosinophil counts (median for both: 329 vs. 329 μg/day fluticasone-equivalent, p = 0.70, Mann-Whitney test). Finally, as for all observational studies, there is the possibility of residual confounding from unrecognized and/or unmeasured factors.
A “count-response” association of blood eosinophil levels with risk of asthma exacerbations has been reported in both an observational study [
We did not exclude patients with a concomitant diagnosis of COPD; therefore, approximately one-tenth of the study population appeared to have some form of physician-diagnosed asthma-COPD overlap [
By necessity we were able to include only patients who had a recorded blood eosinophil count, which is not routinely measured in clinical practice, a factor serving as a possible source of selection bias and thereby limiting the generalizability of our findings. There were large differences in baseline characteristics between the patients with available eosinophil count and those without, who tended to be younger; more likely female, a current smoker, and of normal weight; and less likely having comorbidities such as rhinitis, chronic sinusitis, gastroesophageal reflux disease, and cardiovascular disease. The age differences were expected because older people more frequently have full blood counts available. Further work is needed to examine the use of blood eosinophil count in the clinical assessment of the full spectrum of patients with asthma.
Tailoring asthma therapy using sputum eosinophil counts appears to be effective in reducing exacerbations, particularly for adults with frequent exacerbations [
A high blood eosinophil count in the year before an asthma-related hospitalization is associated with increased risk of readmission within the following year. This risk was slightly greater in the subset of patients who were not new initiators of ICS treatment after their index hospital admission, suggesting that this trait is only partially treatable with anti-inflammatory therapy. This association was present only in non-smoking patients with high blood eosinophil count. Our findings support the benefit of including a full blood count with differential as a routine assessment in clinical practice for patients with not well-controlled asthma. Moreover, our findings support the need for careful follow-up, with treatment optimization, after hospital discharge for patients with asthma and preadmission high blood eosinophil count.
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Writing and editorial support was provided by Elizabeth V. Hillyer, DVM, supported by the Observational and Pragmatic Research Institute Pte Ltd (OPRI).