Literature DB >> 34843073

Does admission acetylsalicylic acid uptake in hospitalized COVID-19 patients have a protective role? Data from the Spanish SEMI-COVID-19 Registry.

Francesc Formiga1, Manuel Rubio-Rivas2, José María Mora-Luján2, Samara Campos Escudero3, Rosa Fernandez Madera Martinez4, Manuel Mendez-Bailón5, Pedro Durán-Del Campo6, Andrea Riaño Pérez7, Francisco-Javier García-Sánchez8, José Nicolás Alcalá-Pedrajas9, Sergio Arnedo Hernández10, Almudena Hernández Milian11, Ana Latorre Díez12, Ricardo Gil Sánchez13, Ramon Boixeda14, Julio Vicente15, Begoña Cortes16, Carmen Mella Pérez17, María Esther Guisado Espartero18, José López Castro19, Santiago Rodríguez Suárez20, Jose F Varona21, Ricardo Gomez-Huelgas22, Jose Manuel Ramos-Rincón23.   

Abstract

Acetylsalicylic acid (ASA) is widely used in the treatment and prevention of cardiovascular disorders. Our objective is to evaluate its possible protective role, not only in mortality but also in other aspects such as inflammation, symptomatic thrombosis, and intensive care unit (ICU) admission in hospitalized COVID-19 patients. We realized an observational retrospective cohort study of 20,641 patients with COVID-19 pneumonia collected and followed-up from Mar 1st, 2020 to May 1st, 2021, from the nationwide Spanish SEMI-COVID-19 Registry. Propensity score matching (PSM) was performed to determine whether treatment with ASA affected outcomes in COVID-19 patients. On hospital admission, 3291 (15.9%) patients were receiving ASA. After PSM, 3291 patients exposed to ASA and 2885 not-exposed patients were analyzed. In-hospital mortality was higher in the ASA group (30.4 vs. 16.9%, p < 0.001) in the global sample. After PSM, no differences were found between groups (30.4 vs. 30.3%, p = 0.938). There were no differences in inflammation, symptomatic thrombosis, or ICU admission. In conclusion, ASA intake is not associated with in-hospital mortality or any other health outcome evaluated after applying PSM analysis in a real-world large sample of hospitalized COVID-19 patients.
© 2021. Società Italiana di Medicina Interna (SIMI).

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Keywords:  Acetylsalicylic acid; COVID-19; Coronavirus; Mortality

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Year:  2021        PMID: 34843073      PMCID: PMC8628049          DOI: 10.1007/s11739-021-02870-1

Source DB:  PubMed          Journal:  Intern Emerg Med        ISSN: 1828-0447            Impact factor:   5.472


Introduction

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), produces severe respiratory symptoms such as bilateral pneumonia associated with high morbidity and mortality, especially in patients of advanced age [1]. At this time, there is no known active treatment to fight this virus. Corticosteroids and biological immunosuppressants are being used to treat the inflammatory phase of the disease [1]. As severe COVID-19 infection is mainly a multisystem inflammatory process with an increased risk of hypercoagulability, the use of acetylsalicylic acid (ASA) can theoretically provide positive outcomes [2, 3]. It inhibits platelet aggregation triggered by the release of arachidonic acid from platelet cells [4]. Thus, the possible mechanism of the protective effects of ASA may be related to its antithrombotic and anti-inflammatory effects and also to its possible immunomodulatory effects (antiviral activity against DNA and RNA viruses, including different human coronaviruses) [5]. The role of ASA in patients with COVID-19 is not studied in depth. A first meta-analysis, including three studies evaluating the association between ASA at admission use and mortality in COVID-19 hospitalized patients, suggested no association between the use of ASA and mortality in patients with COVID-19 [6]. Although patients on ASA tend to have more risk factors for severe COVID-19 infection (older age, high cardiovascular risk, pre-existing coronary artery disease, etc.), the low heterogeneity in this analysis despite differences in characteristics of the population of the included studies [7-9] likely suggests no protective effect of ASA among different groups of patients [6]. As ASA was widely used in the treatment and prevention in the real world in cardiovascular disorders, our study aimed to check its possible protective role, not only in mortality but in other aspects such as inflammation, symptomatic thrombosis, and intensive care unit (ICU) admission.

Materials and methods

Study design, patient selection, and data collection

The analysis was performed in the large cohort of consecutive patients included in the Spanish SEMI-COVID-19 Registry, created by the Spanish Society of Internal Medicine (SEMI). This is a multicenter, nationwide registry with over 150 hospitals registered so far. From March 1st, 2020 to May 1st, 2021, 21,962 hospitalized patients were included in the Registry. Methods of the study have been previously described [10]. In brief, all included patients were diagnosed by polymerase chain reaction (PCR) test or rapid antigenic test for SARS-CoV-2 taken from a nasopharyngeal sample, sputum, or bronchoalveolar lavage. The collection of data from each patient in terms of sociodemographic data, comorbidities, laboratory data, treatments, and outcomes was verified by the principal investigator of each center through the review of clinical records. All participating centers in the register received confirmation from the relevant Ethics Committees, including Bellvitge University Hospital (PR 128/20). The inclusion criteria were all patients in the registry with a community (non-nosocomial) SARS-CoV-2 infection. We included all patients with valid information on whether or not they were taking ASA at the time of hospital admission. The patient sample was divided into 2 groups: patients with ASA admission intake and patients without. The treatments received were in accordance with the medical guidelines available at the time of the pandemic [10]. In the absence of clinical evidence of any of the treatments at the initial time of the pandemic, their use was allowed off-label.

Outcomes definition

The primary outcome of the study was in-hospital mortality. Secondary outcomes were the development of symptomatic deep venous thrombosis (DVT) or pulmonary embolism (PE), the requirement of high-flow nasal cannula (HFNC), non-invasive mechanical ventilation (NIMV), invasive mechanical ventilation (IMV), ICU admission, and the combined variable of in-hospital mortality, the requirement of HFNC, NIMV, IMV, or ICU admission. Also, the development of inflammation in the high-risk category according to the categories previously defined by our group [10]. This was defined when the patient met 1 of the following criteria: lymphocyte count < 760 × 106/L, C-reactive protein (CRP) > 101.5 mg/L, lactate dehydrogenase (LDH) > 394 U/L, ferritin > 1359.9 mcg/L, or d-dimer > 1580 ng/mL.

Statistical analysis

Multiple imputations of missing data were performed. To minimize differences between groups and improve comparability, logistic-regression propensity score nearest neighbor matching (PSM) with replacement and caliper 0.2 was performed. The PSM included sociodemographic variables (age and sex), days from symptom onset to hospital admission, smoking behavior, body mass index (BMI), comorbidities as arterial hypertension, diabetes mellitus, dyslipidemia, chronic liver disease, severe chronic renal failure, chronic obstructive pulmonary disease (COPD), asthma, obstructive sleep apnea syndrome (OSAS), chronic heart failure, ischemic heart disease, cerebrovascular disease, cancer, dementia, degree of dependency, and Charlson index, tachypnea and laboratory variables on admission as PaO2/FiO2, ferritin, lactate dehydrogenase (LDH), C-reactive protein (CRP), lymphocyte count, D-dimer, albumin, creatinine, platelets count, and hemoglobin), and treatments during admission (corticosteroids, tocilizumab, and remdesivir). Categorical variables were expressed as absolute numbers and percentages. Continuous variables are expressed as mean plus standard deviation (SD) in the case of parametric distribution or median [IQR] in the case of non-parametric distribution. Differences among groups were assessed using the chi-square test for categorical variables and T-test or Mann–Whitney test as appropriate for continuous variables. p values < 0.05 indicated statistical significance. Statistical analysis was performed by IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY, USA: IBM Corp.

Results

We included 20,641 patients in the study. There were 11,879 men (57%). On hospital admission, 3291 (15.9%) patients were detected as receiving ASA. In an attempt to differentiate the ASA effect from other effects, 3,291 exposed to ASA and 2885 not-exposed patients were matched.

General baseline data between groups

In the unadjusted analysis, patients on admission ASA were significantly older, predominantly male, and with fewer days between the start of symptoms at admission. Furthermore, patients on ASA were more frequently former smokers and had higher dependence, more comorbidities (arterial hypertension, dyslipidemia, diabetes mellitus, ischemic cardiopathy, cerebrovascular disease, peripheral arterial disease, dementia, chronic heart failure, severe chronic renal failure, cancer, COPD, and OSAS), and higher score in the Charlson Index. In contrast, the percentage of patients with atrial fibrillation and asthma was lower in patients with admission ASA use (Table 1).
Table 1

Patient characteristics before and after propensity score matching

All cohortPropensity Score Matched Cohort
ASANo ASA% or mean differencep valueASANo ASA% or mean differencep value
N329117,35032912885
Age, median [IQR]77.6 [70–85.2]66.9 [54.4–78.4] + 10.7< 0.00177.6 [70–85.2]79 [70.6–86.1]− 1.40.003
Gender (males), n (%)2053 (62.4)9826 (56.6) + 5.8%< 0.0012053 (62.4)1704 (59.1) + 3.3%0.008

Race, n (%)

Caucasian

Black

Hispanic

Asian

Others

3174 (96.4)

10 (0.3)

71 (2.2)

7 (0.2)

29 (0.9)

15,292 (88.1)

105 (0.6)

1629 (9.4)

95 (0.5)

229 (1.3)

 + 8.3%

− 0.3%

− 7.2%

− 0.3%

− 0.4%

< 0.001

3174 (96.4)

10 (0.3)

71 (2.2)

7 (0.2)

29 (0.9)

2782 (96.4)

9 (0.3)

68 (2.4)

7 (0.2)

29 (0.9)

0

0

 + 0.2%

0

0

0.859
Days from onset to admission, median [IQR]5 [3–8]7 [4–9]− 2< 0.0015 [3–8]5 [3–8]00.647
BMI, median [IQR]28.6 [25.4–32]28.5 [25.3–32.1] + 0.10.79328.6 [25.4–32]28.5 [25.3–32] + 0.10.653

Smoking behavior, n (%)

Never smoker

Former smoker

Current smoker

1912 (58.1)

1220 (37.1)

159 (4.8)

12,460 (71.8)

4055 (23.4)

834 (4.8)

− 13.7%

 + 13.7%

0

< 0.001

1912 (58.1)

1220 (37.1)

159 (4.8)

1805 (62.6)

925 (32.1)

155 (5.4)

− 4.5%

 + 5%

− 0.6%

< 0.001

Degree of dependency, n (%)

None or mild

Moderate

Severe

2340 (71.1)

532 (16.2)

419 (12.7)

14,847 (85.6)

1419 (8.2)

1084 (6.2)

− 14.5%

 + 8%

 + 6.5%

< 0.001

2340 (71.1)

532 (16.2)

419 (12.7)

2021 (70.1)

468 (16.2)

396 (13.7)

 + 1%

0

− 1%

0.498
Arterial hypertension, n (%)2599 (79)8109 (46.7) + 32.3%< 0.0012599 (79)2260 (78.3) + 0.7%0.542
Dyslipidemia, n (%)2140 (65)6046 (34.8) + 30.2%< 0.0012140 (65)1790 (62) + 3%0.015
Diabetes mellitus, n (%)1235 (37.5)3000 (17.3) + 20.2%< 0.0011235 (37.5)1021 (35.4) + 2.1%0.082
Atrial fibrillation, n (%)283 (8.6)1941 (11.2)− 2.6%< 0.001283 (8.6)322 (11.2)− 2.6%0.001
Ischemic cardiopathy, n (%)953 (29)665 (3.8) + 25.2%< 0.001953 (29)538 (18.6) + 10.4%< 0.001
Cerebrovascular disease, n (%)662 (20.1)847 (4.9) + 15.2%< 0.001662 (20.1)524 (18.2) + 1.9%0.052
Peripheral arterial disease, n (%)402 (12.2)471 (2.7) + 9.5%< 0.001402 (12.2)275 (9.5) + 2.7%0.001
Dementia, n (%)567 (17.2)1,459 (8.4) + 8.8%< 0.001567 (17.2)521 (18.1)− 0.9%0.393
Chronic heart failure, n (%)434 (13.2)946 (5.5) + 7.7%< 0.001434 (13.2)338 (11.7) + 1.5%0.081
Chronic liver disease, n (%)124 (3.8)578 (3.3) + 0.5%0.205124 (3.8)133 (4.6)− 0.8%0.098
Severe chronic renal failure, n (%)390 (11.9)816 (4.7) + 7.2%< 0.001390 (11.9)312 (10.8) + 1.1%0.201
Cancer, n (%)372 (11.3)1566 (9) + 2.3%< 0.001372 (11.3)353 (12.2)− 0.9%0.256
COPD, n (%)371 (11.3)1029 (5.9) + 5.4%< 0.001371 (11.3)317 (11) + 0.3%0.722
Asthma, n (%)195 (5.9)1257 (7.2)− 1.3%0.007195 (5.9)188 (6.5)− 0.6%0.336
OSAS, n (%)271 (8.2)966 (5.6) + 2.6%< 0.001271 (8.2)222 (7.7) + 0.5%0.435
Charlson index median [IQR]2 [1–3]0 [0–2] + 2< 0.0012 [1–3]1 [1–3] + 1< 0.001

ASA Acetylsalicylic acid, BMI body mass index, IQR interquartile range, COPD chronic obstructive pulmonary disease, OSAS obstructive sleep apnea syndrome, Severe chronic renal failure: Creatinine > 300 mg/dl or dialysis

Patient characteristics before and after propensity score matching Race, n (%) Caucasian Black Hispanic Asian Others 3174 (96.4) 10 (0.3) 71 (2.2) 7 (0.2) 29 (0.9) 15,292 (88.1) 105 (0.6) 1629 (9.4) 95 (0.5) 229 (1.3) + 8.3% − 0.3% − 7.2% − 0.3% − 0.4% 3174 (96.4) 10 (0.3) 71 (2.2) 7 (0.2) 29 (0.9) 2782 (96.4) 9 (0.3) 68 (2.4) 7 (0.2) 29 (0.9) 0 0 + 0.2% 0 0 Smoking behavior, n (%) Never smoker Former smoker Current smoker 1912 (58.1) 1220 (37.1) 159 (4.8) 12,460 (71.8) 4055 (23.4) 834 (4.8) − 13.7% + 13.7% 0 1912 (58.1) 1220 (37.1) 159 (4.8) 1805 (62.6) 925 (32.1) 155 (5.4) − 4.5% + 5% − 0.6% Degree of dependency, n (%) None or mild Moderate Severe 2340 (71.1) 532 (16.2) 419 (12.7) 14,847 (85.6) 1419 (8.2) 1084 (6.2) − 14.5% + 8% + 6.5% 2340 (71.1) 532 (16.2) 419 (12.7) 2021 (70.1) 468 (16.2) 396 (13.7) + 1% 0 − 1% ASA Acetylsalicylic acid, BMI body mass index, IQR interquartile range, COPD chronic obstructive pulmonary disease, OSAS obstructive sleep apnea syndrome, Severe chronic renal failure: Creatinine > 300 mg/dl or dialysis The differences regarding days from onset to admission, degree of dependency, arterial hypertension, diabetes mellitus, cerebrovascular disease, dementia, and chronic heart failure disappeared after PSM analysis. Regarding symptoms, ASA patients had a lower percentage of cough, arthromyalgias, ageusia, anosmia, sore throat, headache, fever, diarrhea, and abdominal pain with a similar percentage of dyspnea and vomiting. Heart rate was lower in ASA patients on admission, although in this group there was a higher percentage of patients with respiratory rate > 20 bpm (Table 2). All symptoms and physical examination differences lost the statistical association after PSM.
Table 2

Symptoms and physical examination upon admission between groups before and after propensity score matching

All cohortPropensity score matched cohort
ASANo ASA% or mean differencep valueASANo ASA% or mean differencep value
Cough, n (%)2148 (65.3)12,534 (72.2)− 6.9%< 0.0012148 (65.3)1864 (64.6) + 0.7%0.588
Arthromyalgias, n (%)736 (22.4)5375 (31)− 8.6%< 0.001736 (22.4)637 (22.1) + 0.3%0.789
Ageusia, n (%)184 (5.6)1730 (10)− 4.4%< 0.001184 (5.6)164 (5.7)− 0.1%0.874
Anosmia, n (%)151 (4.6)1535 (8.8)− 4.2%< 0.001151 (4.6)146 (5.1)− 0.5%0.387
Sore throat, n (%)230 (7)1683 (9.7)− 2.7%< 0.001230 (7)209 (7.2)− 0.2%0.697
Headache, n (%)230 (7)2264 (13)− 6%< 0.001230 (7)196 (6.8) + 0.2%0.763
Fever, n (%)2487 (75.6)14,261 (82.2)− 6.6%< 0.0012487 (75.6)2168 (75.1) + 0.5%0.701
Dyspnea, n (%)1928 (58.6)10,200 (58.8)− 0.2%0.8261928 (58.6)1685 (58.4) + 0.2%0.887
Diarrhea, n (%)692 (21)4257 (24.5)− 3.5%< 0.001692 (21)588 (20.4) + 0.6%0.532
Vomiting, n (%)246 (7.5)1367 (7.9)− 0.4%0.429246 (7.5)210 (7.3) + 0.2%0.769
Abdominal pain, n (%)179 (5.4)1128 (6.5)− 1.1%0.022179 (5.4)188 (6.5)− 1.1%0.074
Heart rate, bpm median [IQR]83 [73–95]88 [77–100]− 5< 0.00183 [73–95]84 [74–95]− 10.077
Respiratory rate > 20 bpm, n (%)1142 (34.7)5429 (31.3) + 3.4%< 0.0011142 (34.7)1037 (35.9)− 1.2%0.307

ASA Acetylsalicylic acid, IQR interquartile range

Symptoms and physical examination upon admission between groups before and after propensity score matching ASA Acetylsalicylic acid, IQR interquartile range

Laboratory tests between groups

Concerning to the analytical values, the group with ASA admission use had lower PaO2/FiO2, lymphocyte count, platelet figures, and albumin. In contrast, they presented with higher values of CRP, LDH, D-dimer, and creatinine. In the group without ASA, they presented higher values of ferritin and alanine transferase (ALT) (Table 3). Except for the Ddimer, all variables lost their association after PSM.
Table 3

Laboratory tests upon admission between groups before and after propensity score matching

All cohortPropensity score matched cohort
ASANo ASAMean differencep valueASANo ASAMean differencep value
PaO2/FiO2, median [IQR]290.7 [235–347.6]300 [242.9–358.5]− 9.3< 0.001290.7 [235–347.6]289.5 [233–347.2] + 1.20.595
Lymphocytes × 106/l, median [IQR]900 [600–1232]950 [690–1300]− 50< 0.001900 [600–1232]900 [610–1280]00.195
CRP mg/l, median [IQR]72 [27.7–139]64 [21.5–130] + 8< 0.00172 [27.7–139]69.2 [23.8–138] + 2.80.151
LDH U/l, median [IQR]335 [251–463]325 [248–440.9] + 100.005335 [251–463]331 [248.5–454] + 40.602
Ferritin mcg/l, median [IQR]630 [222–1328.1]751.1 [273.5–1450.2]− 121.1< 0.001630 [222–1328.1]653.8 [221.5–1331.8]− 23.80.883
Ddimer ng/ml, median [IQR]920 [454–2200]631 [315–1400] + 289< 0.001920 [454–2200]846 [411–2072] + 740.034
Hemoglobin g/dl, median [IQR]13.2 [11.9–14.6]13.9 [12.7–15]− 0.7< 0.00113.2 [11.9–14.6]13.3 [12–14.6]− 0.10.077
Platelets × 109/l, median [IQR]184 [142–246]192 [149–250]− 8< 0.001184 [142–246]187 [145–244]− 30.332
Creatinine mg/dl, median [IQR]1.06 [0.82–1.45]0.9 [0.72–1.13] + 0.7< 0.0011.06 [0.82–1.45]1.03 [0.81–1.45] + 0.30.179
Albumin g/dl, median [IQR]3.6 [3.17–4]3.7 [3.3–4.1]− 0.1< 0.0013.6 [3.2–4]3.6 [3.2–3.9]00.676
ALT U/l, median [IQR]26 [17–42]30 [19–49]− 4< 0.00126 [17–42]26 [17–42]00.568

ASA Acetylsalicylic acid, ALT alanine transferase. CRP C-reactive protein, LDH lactate dehydrogenase, IQR interquartile range

Laboratory tests upon admission between groups before and after propensity score matching ASA Acetylsalicylic acid, ALT alanine transferase. CRP C-reactive protein, LDH lactate dehydrogenase, IQR interquartile range

Treatments during admission

During admission (Table 4), patients with ASA use were treated less frequently with oral anticoagulants, tocilizumab, and remdesivir. In contrast, they were treated more often with prophylactic doses of low-molecular-weight heparin (LMWH) and corticosteroids. Only treatment with LMWH retained significance when applying PSM.
Table 4

Treatments during admission between groups before and after propensity score matching

All cohortPropensity score matched cohort
ASANo ASA% differencep valueASANo ASA%differencep value

Oral anticoagulants, n (%)

Anti vitamin k

DOAC

33 (1)

46 (1.4)

293 (1.7)

402 (2.3)

− 0.7%

− 0.9%

< 0.001

33 (1)

46 (1.4)

46 (1.6)

52 (1.8)

− 0.6%

− 0.4%

0.051

LMWH, n (%)

None

Prophylactic doses

Intermediate doses

Full doses

371 (12.3)

2208 (67.1)

315 (9.6)

364 (11.1)

2737 (16.3)

10,991 (63.3)

1493 (8.6)

2032 (11.7)

− 4%

 + 3.8%

 + 1%

− 0.6%

< 0.001

404 (12.3)

2208 (67.1)

364 (11.1)

315 (9.6)

406 (14.1)

1812 (62.8)

403 (14)

264 (9.2)

− 1.8%

 + 4.3%

− 2.9%

 + 0.4%

< 0.001
Steroids, n (%)1663 (50.9)7817 (45.3) + 5.6%< 0.0011663 (50.5)1439 (49.9) + 0.6%0.609
Tocilizumab, n (%)272 (8.3)1748 (10.1)− 1.8%0.001272 (8.3)236 (8.2) + 0.1%0.904
Remdesivir, n (%)126 (3.8)823 (4.7)− 0.9%0.022126 (3.8)106 (3.7) + 0.1%0.750

ASA Acetylsalicylic acid, DOACs direct oral anticoagulants, LMWH low-mollecular-weight heparin

Treatments during admission between groups before and after propensity score matching Oral anticoagulants, n (%) Anti vitamin k DOAC 33 (1) 46 (1.4) 293 (1.7) 402 (2.3) − 0.7% − 0.9% 33 (1) 46 (1.4) 46 (1.6) 52 (1.8) − 0.6% − 0.4% LMWH, n (%) None Prophylactic doses Intermediate doses Full doses 371 (12.3) 2208 (67.1) 315 (9.6) 364 (11.1) 2737 (16.3) 10,991 (63.3) 1493 (8.6) 2032 (11.7) − 4% + 3.8% + 1% − 0.6% 404 (12.3) 2208 (67.1) 364 (11.1) 315 (9.6) 406 (14.1) 1812 (62.8) 403 (14) 264 (9.2) − 1.8% + 4.3% − 2.9% + 0.4% ASA Acetylsalicylic acid, DOACs direct oral anticoagulants, LMWH low-mollecular-weight heparin Outcomes between groups after propensity score matching. ASA Acetylsalicylic acid, HFNC high Flow nasal cannula, NIMV non-invasive mechanical ventilation, IMV invasive mechanical ventilation, ICU intensive care unit, DVT deep venous thrombosis, PE pulmonary embolism

Outcomes between groups (Fig. 1)

In-hospital mortality was higher in the ASA group (30.4 vs. 16.9%, p < 0.001). ASA patients presented also more frequently with high-risk-inflammatory categories (80.1 vs. 75.3%, p < 0.001), the requirement of NIMV (6.7 vs. 5.7%, p = 0.028), and the combined variable (38.1 vs. 27.4%, p < 0.001). In contrast, ASA patients required less frequent IMV (6.5 vs. 7.7%, p = 0.014) and ICU admission (8.6 vs. 9.9%, p = 0.018). There were no differences in the number of DVT (0.5 vs. 0.6%, p = 0.851), PE (1.7 vs. 1.7%, p = 0.851), DVT + PE (0.1 vs. 0.2%, p = 0.851), or HFNC use (9.7 vs. 9.5%, p = 0.720). As shown in Table 5, none of the outcomes assessed remained associated with admission ASA use after PSM. In-depth, in-hospital mortality was practically identical in the two groups after matching (30.4 vs. 30.3%, p = 0.938), same as DVT (0.5 vs 0.8%, p = 0.508), PE (1.7 vs. 1.4%, p = 0.508), DVT + PE (0.1 vs 0.2%, p = 0.508), high-risk inflammation category (80.1 vs. 79.1%, p = 0.316), HFNC (9.7 vs. 9.1%, p = 0.411), NIMV (6.7 vs. 6.3%, p = 0.518), IMV (6.5 vs. 6.3%, p = 0.750), ICU (8.6 vs. 8.2%, p = 0.622), and the combined variable (38.1 vs. 38%, p = 0.946).
Table 5

Outcomes between groups before and after propensity score matching

All cohortPropensity score matched cohort
ASANo ASA%differencep valueASANo ASA% differencep value

Primary outcome n (%)

In-hospital mortality

1000 (30.4)2929 (16.9) + 13.5%< 0.0011000 (30.4)874 (30.3) + 0.1%0.938

Secondary outcomes n (%)

DVT

PE

DVT + PE

High-risk inflammatory category

HFNC

NIMV

IMV

ICU admission

Combined variable

18 (0.5)

57 (1.7)

4 (0.1)

2637 (80.1)

319 (9.7)

221 (6.7)

213 (6.5)

283 (8.6)

1253 (38.1)

105 (0.6)

303 (1.7)

32 (0.2)

13,058 (75.3)

1647 (9.5)

994 (5.7)

1337 (7.7)

1723 (9.9)

4752 (27.4)

− 0.1%

0

− 0.1%

 + 4.8%

 + 0.2%

 + 1%

− 1.2%

− 1.3%

 + 10.7%

0.851

0.851

0.851

< 0.001

0.720

0.028

0.014

0.018

< 0.001

18 (0.5)

57 (1.7)

4 (0.1)

2637 (80.1)

319 (9.7)

221 (6.7)

213 (6.5)

283 (8.6)

1253 (38.1)

22 (0.8)

41 (1.4)

5 (0.2)

2282 (79.1)

262 (9.1)

182 (6.3)

181 (6.3)

238 (8.2)

1096 (38)

− 0.3%

 + 0.3%

− 0.1%

 + 1%

 + 0.6%

 + 0.4%

 + 0.2%

 + 0.4%

 + 0.1%

0.508

0.508

0.508

0.316

0.411

0.518

0.750

0.622

0.946

ASA Acetylsalicylic acid, HFNC High Flow nasal cannula, NIMV non-invasive mechanical ventilation, IMV invasive mechanical ventilation, ICU intensive care unit, DVT Deep venous thrombosis, PE Pulmonary embolism

Outcomes between groups before and after propensity score matching Primary outcome n (%) In-hospital mortality Secondary outcomes n (%) DVT PE DVT + PE High-risk inflammatory category HFNC NIMV IMV ICU admission Combined variable 18 (0.5) 57 (1.7) 4 (0.1) 2637 (80.1) 319 (9.7) 221 (6.7) 213 (6.5) 283 (8.6) 1253 (38.1) 105 (0.6) 303 (1.7) 32 (0.2) 13,058 (75.3) 1647 (9.5) 994 (5.7) 1337 (7.7) 1723 (9.9) 4752 (27.4) − 0.1% 0 − 0.1% + 4.8% + 0.2% + 1% − 1.2% − 1.3% + 10.7% 0.851 0.851 0.851 < 0.001 0.720 0.028 0.014 0.018 < 0.001 18 (0.5) 57 (1.7) 4 (0.1) 2637 (80.1) 319 (9.7) 221 (6.7) 213 (6.5) 283 (8.6) 1253 (38.1) 22 (0.8) 41 (1.4) 5 (0.2) 2282 (79.1) 262 (9.1) 182 (6.3) 181 (6.3) 238 (8.2) 1096 (38) − 0.3% + 0.3% − 0.1% + 1% + 0.6% + 0.4% + 0.2% + 0.4% + 0.1% 0.508 0.508 0.508 0.316 0.411 0.518 0.750 0.622 0.946 ASA Acetylsalicylic acid, HFNC High Flow nasal cannula, NIMV non-invasive mechanical ventilation, IMV invasive mechanical ventilation, ICU intensive care unit, DVT Deep venous thrombosis, PE Pulmonary embolism Risk factors for in-hospital mortality in the matched-cohort Smoking behavior Never (ref.) Former smoker Current smoker 1 1.19 (1.07–1.34) 0.83 (0.64–1.08) 0.002 0.161 Degree of dependency Mild (ref.) Moderate Severe 1 2.47 (2.14–2.85) 3.03 (2.60–3.53) < 0.001 < 0.001 1 1.54 (1.29–1.84) 2 (1.65–2.42) < 0.001 < 0.001 LMWH None (ref.) Prophylactic doses Intermediate doses Full doses 1 0.48 (0.41–0.56) 0.57 (0.46–0.72) 0.79 (0.65–0.97) < 0.001< 0.001 0.025 1 0.44 (0.37–0.54) 0.41 (0.31–0.53) 0.52 (0.41–0.67) < 0.001 < 0.001 < 0.001 BMI body mass index, NS not significant, COPD chronic obstructive pulmonary disease, CRP C-reactive protein, LDH lactate dehydrogenase, LMWH low-molecular-weight heparin, ASA acetylsalicylic acid

Risk factors for in-hospital mortality (Table 6)

Despite PSM some variables were not correctly matched so we performed a logistic regression to really investigate the possible effectiveness of ASA. The factors that were related to higher in-hospital mortality were older age, male sex, higher degree of dependency, chronic heart failure, higher Charlson index, tachypnea on admission, higher CRP, LDH, and ferritin levels. Lower PaO2/FiO2 and lymphocyte count levels were also associated with higher in-hospital mortality. The use of ASA was not related to in-hospital mortality.

Discussion

The main result of our study in a very large sample of patients (more than 20,000 patients) is the fact that there is no relationship between the intake of ASA at admission and the main outcome (in-hospital mortality), nor the secondary outcomes (inflammation, symptomatic thrombosis, and ICU admission) in Spanish hospitalized patients with COVID-19 infection after the correcting impact of PSM analysis. ASA-related antiplatelet and anti-inflammatory effects could lead to better health outcomes in patients hospitalized for COVID-19 but our study failed to demonstrate that. When evaluating the data globally, the percentage of in-hospital mortality was much higher in the ASA group (30.4 vs. 16.9%, p < 0.001). The most obvious hypothesis is that occurs because the ASA patients were older and with more comorbidities. When applied PSM, we found identical rates of 30% of in-hospital mortality irrespective of whether or not they had previously taken ASA. ASA is inexpensive, widely available, and with clear indications of prescription and a well-known risk profile. Of all the patients admitted for COVID-19 in Spain, 15.9% were under ASA before hospital admission. The percentage of patients admitted for COVID-19 who were under ASA is slightly lower than the 19.2% reported in a recent meta-analysis [6] and the 24% reported in a Veterans Health Administration study in patients with COVID-19 infection [11]. Our results confirm, as previously reported in COVID-19 patients, that ASA users tend to have more risk factors for severe COVID-19 infection (older age, diabetes mellitus, ischemic cardiopathy, etc.,)[6]. In-hospital mortality among ASA users in the meta-analysis by Salah et al.[6] was 22.6 vs. 18.3% among non-ASA users (RR = 1.12, 95% CI 0.84–1.50). It is important to take into account the few patients included in the 3 studies, and none of them assessing a European population. So, in the study by Alamdari et al. [7] they evaluated 459 patients (53 under ASA) from Iran, Chow et al. [9] included 419 USA patients (98 under ASA), and Yuan et al. [8] 183 Chinese patients, all with coronary artery disease (52 under ASA). We evaluated higher figures of patients (20,641 patients) of whom 3291 were treated with ASA before hospital admission. Sahai et al. [12] concluded in 248 USA-matched patients with COVID-19 that ASA had no overall mortality benefit in a retrospective observational study. A recent study from Iran assessing 991 patients (336 with prior ASA intake or having started ASA on the first day of hospital admission) demonstrated a significant independent association between ASA and lower in-hospital mortality (RR = 0.75, 95% CI 0.56–0.99) [13]. Although the study was not carried out with PSM correction, it is worth highlighting the results taking into account that patients with ASA were older and had more comorbidities. Finally, Chow et al. [9] reported that ASA use was independently associated with decreased risk of MV and ICU admission. Neither Yuan et al. [8] nor our results after PSM could confirm this association. In a different scenario from our study, ASA has shown good health outcomes. Liu et al. [14] enrolled 24 pairs of patients (after PSM) and reported that among adults (with arterial hypertension and cardiovascular diseases) infected with SARS-CoV-2, low-dose ASA (100 mg/day) was associated with a lower risk of mortality compared with non-ASA users. Among more than 30,000 COVID-19 positive USA Veterans, prior ASA intake was associated with a statistically and clinically significant decrease in overall mortality at 14-days (OR = 0.38, 95% CI 0.32–0.46) and 30-days (OR = 0.38, 95% CI 0.33–0.45) [13]. One possible interpretation of these results is that ASA is beneficial due to its possible antithrombotic, anti-inflammatory, and immunomodulation effects in community cases of COVID-19, but no longer when patients have a severe condition requiring hospital admission. A USA study [15] evaluating 1,956 patients according to the antiplatelet therapy prior to and during admission found lower in-hospital mortality in the group with ASA during admission after applying PSM (HR = 0.52, 95% CI 0.34–0.81). A recent meta-analysis [16] reported that ASA intake (prior or initiated during hospitalization) was independently associated with lower mortality in patients with COVID-19. When analyzing the results of the study, it is important to take into account the possible favorable effects of other important cardiovascular drug classes, especially renin–angiotensin–aldosterone system inhibitors and statins [17, 18]. The main strength of the study is a large number of patients evaluated, which makes it the largest study on the subject to our knowledge. Secondly, its multicentre hospital nature spans a diverse geographic range, from an integrated longitudinal database. This study has several limitations. First, it was a retrospective study. Second, the intake of ASA before admission was collected and confirmed but neither the dose nor the reason for its prescription was recorded. Third, as this study was focused on in-patients, it was difficult to reflect the effect of ASA in an outpatient setting. Fourth, our sample is mostly Caucasian with a low representation of other ethnic groups. Fifth, we did not record the presence of other medications that are associated with hypercoagulabilities, such as oral contraceptives and hormone replacement. Sixth, we not explore if there was any difference in bleeding events Seventh, among the two groups, in-hospital mortality compared to patients who have undergone the same treatments for COVID was not evaluated. Finally, it is always concerning which variables to include in a PSM model. Including variables that are related to the exposure but not the outcome will decrease the precision of the estimated exposure effect without decreasing bias [20]. In our study, we have included a wide variety of comorbidities, some of them strongly related to ASA use but not so clearly related to the outcomes we describe. This could result in a loss of precision and, therefore, a limitation of the study.

Conclusions

To date, no consensus guidelines are available regarding ASA use in COVID-19, reflecting a paucity of data in this regard. Awaiting results from powered and randomized studies [19], our results, from a real-world large sample of hospitalized COVID-19 patients, provides information along with the idea that ASA intake at admission is not associated with lower in-hospital mortality or any other health outcome evaluated after applying PSM analysis.
Table 6

Risk factors for in-hospital mortality in the matched-cohort

Univariate analysisMultivariate analysis
OR (95% CI)p valueOR (95% CI)p value
Age1.06 (1.05–1.07)< 0.0011.19 (1.02–1.38)0.030
Gender (female)0.85 (0.76–0.95)0.0050.73 (0.63–0.83)< 0.001
BMI1.02 (1.01–1.03)0.003NS

Smoking behavior

Never (ref.)

Former smoker

Current smoker

1

1.19 (1.07–1.34)

0.83 (0.64–1.08)

0.002

0.161

NS

Degree of dependency

Mild (ref.)

Moderate

Severe

1

2.47 (2.14–2.85)

3.03 (2.60–3.53)

< 0.001

< 0.001

1

1.54 (1.29–1.84)

2 (1.65–2.42)

< 0.001

< 0.001

Arterial hypertension1.45 (1.26–1.67)< 0.001NS
Dyslipidemia1.04 (0.93–1.16)0.545
Diabetes mellitus1.17 (1.04–1.30)0.008NS
Ischaemic cardiopathy1.36 (1.20–1.54)< 0.001NS
Chronic heart failure2.14 (1.83–2.49)< 0.0011.21 (1.01–1.47)0.049
Atrial fibrillation1.96 (1.66–2.33)< 0.001NS
Cerebrovascular disease1.41 (1.23–1.61)< 0.001NS
Peripheral arterial disease1.53 (1.30–1.81)< 0.001NS
Dementia2.26 (1.97–2.58)< 0.001NS
COPD1.46 (1.24–1.72)< 0.001NS
Chronic liver disease1.04 (0.79–1.36)0.780
Severe chronic renal failure1.85 (1.58–2.17)< 0.001NS
Charlson index1.19 (1.16–1.22)< 0.0011.12 (1.08–1.16)< 0.001
Respiratory rate > 20 rpm3.65 (3.26–4.10)< 0.0012.49 (2.19–2.84)< 0.001
PaO2/FiO20.99 (0.99–0.99)< 0.0010.99 (0.99–0.99)< 0.001
Lymphocyte count × 106/L0.99 (0.99–0.99)< 0.0010.99 (0.99–0.99)< 0.001
CRP (mg/L)1.01 (1.01–1,01)< 0.0011.01 (1.01–1.01)< 0.001
LDH (U/L)1.01 (1.01–1,01)< 0.0011.01 (1.01–1.01)< 0.001
Ferritin (mcg/L)1.01 (1.01–1,01)< 0.0011.01 (1.01–1.01)0.001
d-dimer (ng/mL)1.01 (1.01–1.01)< 0.001NS

LMWH

None (ref.)

Prophylactic doses

Intermediate doses

Full doses

1

0.48 (0.41–0.56)

0.57 (0.46–0.72)

0.79 (0.65–0.97)

< 0.001< 0.001

0.025

1

0.44 (0.37–0.54)

0.41 (0.31–0.53)

0.52 (0.41–0.67)

< 0.001

< 0.001

< 0.001

Steroids1.46 (1.31–1.63)< 0.0011.22 (1.07–1.4)0.003
Tocilizumab1.29 (1.06–1.56)0.0091.71 (1.36–2.16)< 0.001
ASA1.01 (0.90–1.12)0.9381.05 (0.92–1.19)0.476

BMI body mass index, NS not significant, COPD chronic obstructive pulmonary disease, CRP C-reactive protein, LDH lactate dehydrogenase, LMWH low-molecular-weight heparin, ASA acetylsalicylic acid

  20 in total

1.  Variable selection for propensity score models.

Authors:  M Alan Brookhart; Sebastian Schneeweiss; Kenneth J Rothman; Robert J Glynn; Jerry Avorn; Til Stürmer
Journal:  Am J Epidemiol       Date:  2006-04-19       Impact factor: 4.897

2.  Cyclooxygenase inhibitors and the antiplatelet effects of aspirin.

Authors:  F Catella-Lawson; M P Reilly; S C Kapoor; A J Cucchiara; S DeMarco; B Tournier; S N Vyas; G A FitzGerald
Journal:  N Engl J Med       Date:  2001-12-20       Impact factor: 91.245

3.  Mortality Risk Factors among Hospitalized COVID-19 Patients in a Major Referral Center in Iran.

Authors:  Nasser Malekpour Alamdari; Siamak Afaghi; Fatemeh Sadat Rahimi; Farzad Esmaeili Tarki; Sasan Tavana; Alireza Zali; Mohammad Fathi; Sara Besharat; Leyla Bagheri; Fatemeh Pourmotahari; Seyed Sina Naghibi Irvani; Ali Dabbagh; Seyed Ali Mousavi
Journal:  Tohoku J Exp Med       Date:  2020-09       Impact factor: 1.848

4.  Antagonizing the renin-angiotensin-aldosterone system in the era of COVID-19.

Authors:  Riccardo Sarzani; Federico Giulietti; Chiara Di Pentima; Andrea Filipponi; Francesco Spannella
Journal:  Intern Emerg Med       Date:  2020-05-18       Impact factor: 3.397

5.  Effect of aspirin on short-term outcomes in hospitalized patients with COVID-19.

Authors:  Aditya Sahai; Rohan Bhandari; Matthew Godwin; Thomas McIntyre; Mina K Chung; Jean-Pierre Iskandar; Hayaan Kamran; Essa Hariri; Anu Aggarwal; Robert Burton; Ankur Kalra; John R Bartholomew; Keith R McCrae; Ayman Elbadawi; James Bena; Lars G Svensson; Samir Kapadia; Scott J Cameron
Journal:  Vasc Med       Date:  2021-05-19       Impact factor: 4.739

6.  Decreased in-hospital mortality associated with aspirin administration in hospitalized patients due to severe COVID-19.

Authors:  Mohammad Haji Aghajani; Omid Moradi; Hossein Amini; Hamed Azhdari Tehrani; Elham Pourheidar; Mohammad M Rabiei; Mohammad Sistanizad
Journal:  J Med Virol       Date:  2021-05-08       Impact factor: 20.693

Review 7.  Is Acetylsalicylic Acid a Safe and Potentially Useful Choice for Adult Patients with COVID-19 ?

Authors:  Vanessa Bianconi; Francesco Violi; Francesca Fallarino; Pasquale Pignatelli; Amirhossein Sahebkar; Matteo Pirro
Journal:  Drugs       Date:  2020-09       Impact factor: 9.546

8.  Meta-Analysis of the Effect of Aspirin on Mortality in COVID-19.

Authors:  Husam M Salah; Jawahar L Mehta
Journal:  Am J Cardiol       Date:  2021-01-06       Impact factor: 2.778

9.  Mortality and pre-hospitalization use of low-dose aspirin in COVID-19 patients with coronary artery disease.

Authors:  Shuai Yuan; Peng Chen; Huaping Li; Chen Chen; Feng Wang; Dao Wen Wang
Journal:  J Cell Mol Med       Date:  2020-12-18       Impact factor: 5.295

10.  Should aspirin be used for prophylaxis of COVID-19-induced coagulopathy?

Authors:  Aliae A R Mohamed-Hussein; Karim M E Aly; Mohamed-Eltaher A A Ibrahim
Journal:  Med Hypotheses       Date:  2020-06-08       Impact factor: 1.538

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1.  Effect of low dose acetylsalicylic acid and anticoagulant on clinical outcomes in COVID-19, analytical cross-sectional study.

Authors:  Muhammad B Malik; Samar A Amer; Eric Merrell; Ronald Russo; Jeffrey B Riley; Austin Scro; Elizabeth James; Anderson Anuforo; Soumya Adhikari; Rosalie Siciliano; Philip Chebaya; Edward Darling; Michael Kuhn; Gary Nieman; Ahmed Shawkat; Hani Aiash
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