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Risk Factors Associated with the Mortality of COVID-19 Patients Aged ≥60 Years Neither Intubated nor Treated with Mechanical Ventilation: A Multicentre Retrospective Cohort Study during the First Wave in Spain

Dante R. Culqui
Josep Ortega Segura
Elisabeth Da Costa-Venancio
Anna Renom-Guiteras
Esther Roquer
Sherly Melissa Muñoz Tejada
Patricia Rodriguez
Adilis L. Alba Travieso
Isis Medrano
Lizzeth Canchucaja-Gutarra
Marta Herrero-Torrus
Paula Jurado-Marín
Mónica Marín-Casino
Rosa Ana Sabaté-Garcia
Cristina Roqueta
María del Carmen Martinez
Gabriel De Febrer
José Antonio López-Bueno
MÁ Navas-Martín
Working Group about Survival in Old COVID-19 Patients
César Garriga
8,† and
Joan A. Cayla
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Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, 28023 Madrid, Spain
Centre Blauclínic Isabel Roig, Barcelona Hospital for the Elderly (Sociosanitary), 08030 Barcelona, Spain
University Hospital Parc de Salut Mar, 08003 Barcelona, Spain
Member of the Health Services Chronic Patient Research Network (REDISSEC), 08019 Barcelona, Spain
Geriatrician, Intermediate Care Unit, Hospital Universitari Sant Joan de Reus, 43204 Reus, Spain
School of Statistics, University of San Marcos, Lima 15081, Peru
Internal Medicine, Intermediate Care Unit, Hospital Universitari Sant Joan de Reus, 43204 Reus, Spain
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
Foundation of TB Research Unit, 08023 Barcelona, Spain
Authors to whom correspondence should be addressed.
They are joint senior authors.
BioMed 2022, 2(3), 341-358;
Submission received: 27 June 2022 / Revised: 24 July 2022 / Accepted: 3 August 2022 / Published: 11 August 2022


Background: To determine risk factors of death in diagnosed patients with COVID-19 who were aged ≥60 years and could not benefit from intubation and mechanical ventilation. Methods: Retrospective multicentre study including all patients with COVID-19 admitted to four medium-stay centres in Catalonia (March-June 2020). At the multivariate level, we calculated hazard ratios (HR) with 95% confidence intervals (CI) to determine risk factors associated with mortality. Results: 683 patients were included, of whom 227 died (case fatality rate of 33%, reaching 42% in patients of more than 90 years). Mean survival was 21.92 (20.98–22.86) days. Factors associated with death were fever (HR:1.5 (1.06–2.13)), malaise (HR:1.4 (1.04–1.99)), dyspnoea (HR:1.98 (1.41–2.79)) and atrial fibrillation (HR:1.45 (1.03–2.05)), while coughing (HR: 0.66 (0.46–0.94)), diarrhoea (HR:0.46 (0.23–0.92)), dyslipidaemia (HR:0.47 (0.28–0.82)), and receiving antithrombotic treatment (HR:0.56 (0.40–0.78)) had a protective effect. The analysis by age group showed that other factors were uniquely associated with each age group, such as chronic obstructive pulmonary disease at 60–74 years and polypharmacy at 75–90 years, among other factors. Conclusions: Case fatality in COVID-19 patients who could not benefit from intubation and mechanical ventilation was exceptional. Clinical manifestations such as fever, malaise, dyspnoea and atrial fibrillation helped to identify patients at higher risk of mortality, while antithrombotic treatment had a protective effect. Although some symptoms are very general regarding COVID-19, in the context of the first wave without vaccination, when not much was known about the disease, such symptoms could be useful.

1. Introduction

The first COVID-19 epidemic wave had a huge impact on a global scale. According to the World Health Organization (WHO) data, by March 2020, SARS-CoV-2 had infected more than 87,137 people, with more than 2977 deaths worldwide [1]. Globally, cases and deaths due COVID-19 have been increasing dramatically, and around of the world, there has been a varying number of epidemic waves.
The pandemic started in Europe with a significant increase in cases in Italy. In March 2020, Italy reported 101,739 cases and 11,591 deaths [1]. The average age of the deceased was 81 years, and more than two thirds of the patients had comorbidities such as diabetes, cardiovascular disease, cancer or a history of being ex-smokers [2].
Spain was one of the first European countries with the highest number of affected patients. By 18 May 2020, 231,350 PCR-positive cases had been detected in Spain, and despite the limited availability of these tests, 27,650 (11.95%) died. Eighty-seven per cent of the deceased were over 70 years of age, and 95 per cent had at least one previous illness. A total of 55,824 patients corresponded to the Autonomous Community of Catalonia where, in addition, a 71% excess in mortality was observed for all ages (March/April 2020), reaching 85.2% in those over 74 years of age [3].
In this first wave of the epidemic, the health system was overwhelmed by the increase in the number of patients, and unfortunately, some fragile patients could not be intubated to offer them mechanical ventilation. Furthermore, as orotracheal intubation and mechanical ventilation are futile and aggressive treatments for fragile patients at an advanced age and high comorbidity, which in some of these patients could make them more vulnerable to death, it was decided to offer them conservative non-invasive treatment in social healthcare centres (intermediate care centres/hospitals) [4]. These centres are an intermediate step between the hospital and the private home or residential centre. Intermediate-care hospitals mainly admit patients referred from acute hospitals for specific therapy with an interdisciplinary approach, as well as patients in need of palliative care and complex symptom management, many of them in the last days of life.
Despite several published studies on factors related to COVID-19 mortality [5,6] many factors have not yet been identified. Therefore, the aim of this study is to identify factors related to mortality in a cohort of COVID-19 patients aged 60 years and older who were neither intubated nor mechanically ventilated and who were admitted to intermediate care hospitals during the first wave of the COVID-19 epidemic.

2. Materials and Methods

2.1. Study Design

Retrospective cohort study.

2.2. Sample

COVID-19 was diagnosed in patients transferred to long-term care facilities from 3 acute hospitals and nursing homes affected by COVID-19 outbreaks in Catalonia, Spain. Between March and June 2020 (Figure 1), there were 683 patients of 60 years and over identified who were ruled out for intubation and mechanical ventilation. A survival analysis was carried out for those allowing for at least 15 days of follow up. Patients who missed the date of the Real-Time Reverse Transcriptase Polymerase Chain Reaction Assay (RT-PCR) or wrong dates of admission or discharge were discarded.
In the general registry, 683 patients were entered. Within the registry, there were cases of patients whose length of stay in the study was not considered, since these had negative or atypical PCR dates.
These patients were considered and evaluated in the general descriptive analysis but were not considered in the Kaplan–Meier survival analysis and Cox regression analysis, because these would produce a bias or error in the final analysis.

2.3. Long-Term Care Facilities

Centro Sociosanitario Isabel Roig. (IR), Centro Sociosanitario Dolors Aleu (DA), Centre Fòrum del Parc de Salut Mar (CF) and Centre Sociosanitari de l’Hospital Universitari Sant Joan de Reus (SJR).

2.4. Variables

According to the Laframboise Epidemiological Model [7].

2.4.1. Human Biology

Sex, Age Band (60–74 years, 75–90, >90) [8], and Comorbidities on Admission
  • Hypertension, auricular fibrillation, heart failure, ischemic heart disease, other cardiovascular diseases.
  • Asthma, bronchitis, chronic obstructive pulmonary disease (COPD), other respiratory diseases.
  • Diabetes, obesity, dyslipidaemia, other metabolic conditions.
  • The term dyslipidaemia indicates an elevated concentration of lipids in the blood. There are several categories of this disorder, depending on which lipids are altered. The two most important forms are hypercholesterolaemia and hypertriglyceridaemia, although other disorders can be common, such as hyperchylomicronaemia or decreased HDL-cholesterol [9].
  • Ictus, migraine, Parkinson’s disease, Alzheimer’s disease, cognitive impairment, other neurological diseases.
  • Other conditions:
    Chronic renal failure;
    Low-frequency digestive pathology;
  • Geriatric syndrome: immobility, recurrent falls, pressure ulcers, malnutrition, incontinence, constipation, dysphagia, polypharmacy (more than 5 drugs), cognitive impairment, depression/insomnia and sensory impairment.
  • Initial symptoms: fever, cough, malaise, dyspnoea, myalgia, fatigue, diarrhoea, nausea, other initial symptoms.
  • The authors confirmed that all information about the whole medical history of these patients to the time of admission to care was confirmed with the patients’ medical records.

2.4.2. Lifestyles

Smoking (non-ex-smoker, ex-smoker, light smoker (1–9/day), moderate smoker (10–19/day), heavy smoker (20+/day); alcohol intake: non-drinker, trivial <1 units/day, light 1–2 units/day, moderate 3–6 units/day, heavy 7–9 units/day, very heavy >9 units/day. Cocaine, cannabis, heroine and other illicit drugs.

2.4.3. COVID-19 Progression

Respiratory distress onset, PCR date, clinical exacerbation date, radiological confirmation date, time elapsed to negative PCR test, dates of either discharge or death.

2.4.4. Treatments:

  • Azithromycin, ceftriaxone, other antibiotics.
  • Corticoids and inhalers (INH): methylprednisolone, hydrocortisone, dexamethasone, salbutamol, ipratropium bromide, other inhalers.
  • Other treatments: hydroxychloroquine (antimalarial), oxygen, antithrombotics, anti-platelet agents, antiviral and ivermectin.

2.5. Data Analysis

Forms with missing values or with misinterpreted items were returned for completion/correction to health staff. Date consistency was also checked. Randomly, 10% of the completed forms were validated as a quality control.
Analyses were carried out using SPSS 27.0 for descriptive and Cox regressions, as well as R 4.0.4 for the survival plots. We followed the STROBE statement (Strengthening the Reporting of Observational Studies in Epidemiology) to report this study [10].
Descriptive analysis and lethality rates of the sample and by age bands were obtained. Mean and standard deviation was calculated for continuous variables.
The outcome was death. Patients were followed from their admission date for at least 15 days up until they were censored at the earliest date of either being lost to follow-up, death, or 30 June 2020. The survival function of the patients in the groups studied, the risk of occurrence of the COVID-19 death event, as well as the mean survival time were determined.
The probability distribution of survival times in COVID-19 patients was performed using the non-parametric Kaplan–Meier method, followed by Cox regression analysis by specific age groups and the final multivariate analysis in which the variables that were significant (hazard ratio (HR)) were entered, and both protective and risk factors were identified in the total population and in the age groups studied. Kaplan–Meier survival curves were drawn for the death incidence, and differences between age group exposures were compared using the log-rank test. Cox’s proportional hazards models were used to describe the association between death and comorbidities, geriatric syndrome, onset of symptoms and treatments. We assessed the proportional hazards assumption by using log minus log plots. Hazard ratios with 95% confidence intervals were calculated for the sample and by age band.
Ethics statements: Data were treated in a strictly confidential manner according to the ethical principles of the Helsinki Declaration. The study was approved by the statutory clinical research committee of Hospital del Mar (2020/9477) and l’Hospital Universitari Sant Joan de Reus (CEIC 203/2020).

3. Results

We studied 683 patients, of whom 227 died; we identified a 33% lethality rate, and by age group, we observed an upward gradient (60–74: 21%; 75–90: 32%; 90+: 42%). By sex, men showed a higher lethality (42%). By socio-health centres, lethality ranged from 27% to 43% (Table 1). The geriatric syndromes with the highest lethality were dysphagia (42%) and immobility (40%); among cardiovascular diseases, atrial fibrillation (43%) and heart failure (40%); among respiratory diseases, patients with COPD (35%); and among metabolic diseases, patients with hypothyroidism (36%) and diabetes (35%). Neurological diseases included Parkinson’s disease (48%). The initial symptoms associated with the highest lethality were dyspnoea (45%), fever (40%), malaise (40%) and fatigue (40%). In terms of treatment, the highest lethality was observed among patients treated with antiplatelet agents (68%) and salbutamol (51%) (Table 1).
We identified a survival time of 21.9 days. In women, it was 20.37 days (95% CI: 18.9–21.84) and in men 23.01 days (95% CI; 21.81–24.22). By age group, mean survival was 22.20 days for the 60–74 years group, 22.34 days in the 75–90 years group, and 20.63 days in those over 90 years of age (Table 2).
At the multivariate level, associated variables leading to death were fever HR:1.5 (1.06–2.13), general discomfort HR: 1.4 (1.04–1.99), dyspnoea HR:1.9 (1.41–2.79) and atrial fibrillation HR: 1.45 (1.03–2.05), while cough HR:0.7 (0.46–0.94), diarrhoea HR:0.45 (0.23–0.92), dyslipidaemia HR:0.47 (0.28–0.82) and receiving antithrombotic treatment HR:0.56 (0.40–0.78), had a protective effect. By age, no statistically significant effect was identified (Table 3).
When analysed by age group, in the 60–74 years age group, constipation, chronic obstructive pulmonary disease (COPD) and neoplasia were risk factors (RF). Incontinence and migraine presented a very wide CI. Ceftriaxone treatment did not show a protective effect.
In the 75 to 90 years group, RF identified were male sex, polypharmacy, atrial fibrillation, and symptoms such as general discomfort, dyspnoea, fever and methylprednisolone treatment. Protective factors (PF) identified were cough and diarrhoea.
Finally, in the 91 years or older group, dyslipidaemia was confirmed as the PF with a more adjusted HR, as well as the use of azithromycin and antithrombotic agents (See Table 3).

4. Discussion

To the best of our knowledge, this survival study is the first conducted in COVID-19 patients over 60 years of age admitted to social-health centres (HAI) and who could not be treated with intubation and mechanical ventilation for several reasons (saturation of ICU beds, major comorbidities).
A high case mortality rate was observed (33%), which increased as age increased, reaching 42% in the 91 years or more age group. No significant differences were observed between HAI. This lethality rate coincided at a time when in many countries there was a high mortality rate, which worldwide reached 541,310 deaths up to 30 June 2020, although it has been estimated that only a quarter of the deaths were reported. In Spain, the mortality excess was 58% with 120,768 deaths registered as of 29 June 2020 [3].
In order to facilitate reading, we have divided the discussion into several blocks of analysis, which we describe below.

4.1. Demographic Variables

In the survival analysis, it was evident that men had a mean survival time longer than that of women (Table 2). However, in the multivariate regression of the total population, we did not find a statistically significant difference. The only exception was in the 75–90 years age group where male sex was a risk factor; in this regard, a meta-analysis mentions male sex as a mortality RF in the general population [11]. These results are in line with other research in Mexico carried out in people over 50 years of age [12] and India [13], and other studies [14,15,16,17]; however, these studies were carried out in a different population than HAI. One study mentions that there are factors associated with sex, which could increase the higher mortality of the male sex [18], such as the X chromosome and sex hormones, which could play a key role in the innate and adaptive immunity of male patients to the COVID-19 virus [16,18].
It was observed that survival time tends to decrease with age (Figure 2). Although this same trend is observed in the central estimators of the adjusted HRs (Table 3), when the age was adjusted for other variables, it did not appear to play a statistically significant role. This may be related to confusion between age and comorbidity. Thus, we can differentiate between chronological age and “biological age”, and this difference would be the key to why age alone is not associated with mortality, but we must analyse the factors that condition “biological age” [19]. This “biological age” is reflected in the so-called frailty, i.e., the decrease in functional reserve and resistance to stressors [20,21].

4.2. Geriatric Syndromes

There are many scientific reports on the association between immobility and the risk of dying from COVID-19 [22,23]. A study carried out on 102 patients showed a tendency towards higher mortality at day 30 in patients with greater functional impairment/immobility, although no statistically significant differences were found [24]. Another study in a residential centre showed that there was a statistically significant relationship between immobility and higher mortality due to COVID-19 [25].
We observed that mortality in patients with immobility increases as age increases, 23% for the group of 60–74, 40% for the group of 75 to 90 and 50% for the group of 91 and over (Table 1). The lethality rate in relation to recurrent falls also increases as age increases; however, the recurrent falls/lethality rates are lower than immobility lethality rate. Recurrent falls could be an indicator of greater patient mobility and better health status compared to immobile patients [25,26]. Despite lethality rate being high among patients with immobility and patients with recurrent falls, none of the variables were associated with a risk of mortality due to COVID-19 in the multivariate analysis (Table 3).
Polypharmacy, however, was a statistically significant RF in the age group of 75 to 90 years, although it was not observed in the general population, as reported in the literature [24,27,28]. Nevertheless, polypharmacy has been found to be associated with a higher risk of mortality among older persons [29] and the reasons for these could be various. Polypharmacy could behave as a surrogate for multi-morbidity, which has been found to be associated with a higher risk of mortality [30]. Conversely, the use of multiple concomitant medications may outweigh individual benefits due to potential ensuing side effects [31].
Finally, the associations observed with incontinence with very large CI and constipation (which has no biological explanation) in the 60–74 age group could be spurious associations.

4.3. Cardiovascular, Respiratory, Metabolic and Neurologic Comorbidities

Dyslipidaemia was associated as PF with mortality. Contrarily, some studies have suggested that dyslipidaemia could be associated with a higher risk of severe COVID-19 infection and mortality [26,32,33,34]. Nevertheless, no relationship between dyslipidaemia and COVID-19 infection has been well established yet.
In this study, older persons with atrial fibrillation had a higher risk of mortality (total population and 75–90 years). Cardiac arrhythmias are among the most common comorbidities in patients with COVID-19 [35], and atrial fibrillation has been found to be associated with a higher 60-day mortality.
Chronic obstructive pulmonary disease (COPD) (Table 3) was associated with a higher risk of mortality in the 60 to 74 years group. A systematic review and meta-analysis found that among individuals with COVID-19, the presence of co-morbidities (both cardiometabolic, COPD and other) is associated with a higher risk of severe COVID-19 and mortality [36]. Furthermore, neoplasia could play a role as another comorbidity. However, migraine due to such a wide CI seems to be a spurious association.

4.4. Initial Symptoms

Fever and dyspnoea were identified as RF of mortality, especially in older subgroups. These findings coincide with several studies, both in the general population and in older age groups [14,15,25,37]. A systematic review found that fever was associated as a mortality RF in almost all the of the studies analysed [38].
Cough and diarrhoea were PF of mortality. A systematic review [17] mentions that digestive symptoms have been associated with the severity of the disease, but are not associated with increased mortality. Furthermore, digestive symptoms were not among the clusters of symptoms mostly associated with mortality risk among patients with COVID-19 as studied [39]. The result of cough as a PF for mortality could be related to the patient’s fragilities. In patients with associated immobility syndrome, the cough reflex is usually reduced or goes away. Therefore, in patients with a better overall status, cough may be associated with a higher survival, evidencing a better respiratory functional capacity (the use of antitussives was not recorded in the patients studied). General discomfort/malaise is a symptom present in most of the patients studied. Malaise was a RF of mortality in the present study. This symptom seems to be related to the response of the body’s immune system to infection. COVID-19 disease results in a massive cytokine storm which results in a variety of symptoms, including malaise [40]. Thus, the presence of general discomfort/malaise may be associated with a more massive cytokine reaction, resulting in a more severe disease with a higher mortality risk [41].

4.5. Treatment

Patients treated with antithrombotic therapy (including both oral anticoagulants and low-molecular-weight heparins (LMWH)) had a lower risk of mortality in this study. These results are in line with the current literature on this issue as well as with current COVID-19 guidelines [42]. Another study suggested that anticoagulation for 7 days or longer may improve outcomes in hospitalized patients [43]. Moreover, in another study, it was observed that a longer duration of anticoagulation was associated with a reduced risk of mortality [44]. Furthermore, another study demonstrated the preventive use of apixaban or enoxaparin with a significant decrease in mortality in patients with D-dimer levels >1 µg/mL. [45]. Several studies have associated greater benefit with therapeutic anticoagulation compared with prophylactic anticoagulation [46]. Similarly, pre-existing antithrombotic treatment with direct acting oral anticoagulants (DOAC) or vitamin K antagonists (VKA) was also associated with improved outcomes [47].
The severe inflammatory response to COVID-19 may predispose patients to thrombotic events [43,48]. Moreover, autopsy data suggest that thrombotic events are directly responsible for up to 30% of deaths [49]. Consequently, the use of anticoagulants with LMWH or oral anticoagulants may be of benefit to these patients [43].
Fewer studies have reported on the effects of anticoagulants specifically among older persons with regard to mortality. Other authors found anticoagulant treatment to be associated with a higher chance of survival among older persons [50], and in another study, the treatment with LMWH was associated with better survival [51].
Receiving a treatment with methylprednisolone did not affect mortality among the overall sample of older people. Similar results were reported in other studies [52].
In the subgroup analysis (75 to 90 years), a higher risk of mortality was observed among those who received treatment with methylprednisolone. In the same line, another study found that the administration of high doses of corticosteroids was associated with an increased risk of mortality [53].
Contrarily, several studies have reported different results [54,55]. In the subgroup analysis of patients over 60 years old, those patients in the methylprednisolone group had a lower mortality rate at day 28 [54]. Furthermore, intravenous methylprednisolone administration has been found to be associated with a reduced risk of death among patients with moderate to severe COVID-19 [56]. The fact that neither data on COVID-19 severity nor data on the dose and duration of treatment with methylprednisolone were analysed in the present study may limit the interpretation of our results.
The safety profile of azithromycin used as an antibacterial agent is well established [57]. However, in the case of COVID-19, its role is controversial; thus, the results should be assessed with caution.
Although treatment with ceftriaxone was identified as a probable RF, the CI in the total population is very low and as the 60–74 years age group is a very small population (n = 55), we believe that the association presented could be spurious.
This study is one of the few studies carried out in a population over 60 years of age who could not benefit from orotracheal intubation and mechanical ventilation due to ICU bed saturation and/or suffering from many comorbidities and who were admitted to intermediate care hospitals (social-health centres (HAI)) in Spain.

5. Limitations

In terms of limitations, the retrospective methodology of the study may have limited the quality of the information collected. As regards information on drug use, no information is available on treatment times or doses. At the same time, this study has the limitation of retrospective studies. This study does not allow us to identify cause–effect relationships such that the associations observed must be interpreted in terms of associations with the survival analysed.
In addition, as this is an exploratory analysis of field observations, the sample size is small, especially in the 60–74 age groups and in those over 91 years of age, which could affect the results, as it limits the statistical power. Therefore, results by age group should be treated with caution.
Regarding the selection of the study variables, some of the parameters studied are considered as generalised conditions that could hide a different disorder. General discomfort/malaise, for example, cannot be objectively defined, while many conditions can lead to this situation. In addition, the sensation of dyspnoea is a subjective response, while oxygen saturation or PaO 2, and even more, the ratio to inspired oxygen fraction (GiO 2) are considered as valuable and objective factors; thus, results related to symptoms should be taken with caution.

6. Conclusions

This study is one of the few studies describing the main characteristics and analysing factors potentially related to mortality in a sample of unvaccinated elderly persons admitted to intermediate care hospitals (social-health centres (HAI)) with COVID-19.
Mortality due to COVID-19 in this population was relevant. Clinical manifestations such as initial fever, malaise, dyspnoea and atrial fibrillation were associated with an increased risk of death. These findings may help identify those older patients with COVID-19 who may specially benefit from a closer surveillance by health care professionals, especially in countries that do not yet have good vaccination coverage and health infrastructure.
The use of antithrombotic agents (including both oral anticoagulants and low-molecular-weight heparins) was associated with a lower risk of mortality in this population, suggesting that treatment protocols for the management of COVID-19 in this population should consider their use.
This study may help to improve the prognosis of older COVID-19 patients in countries that do not yet have good vaccination coverage and health infrastructure as well as good monitoring programmes.

Author Contributions

Conceptualization, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R. and A.L.A.T.; data curation, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R., A.L.A.T., I.M., L.C.-G., M.H.-T., P.J.-M., M.M.-C., R.A.S.-G., C.R., M.d.C.M., G.D.F., J.A.L.-B., M.N.-M., C.G. and J.A.C.; formal analysis, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R., J.A.L.-B., M.N.-M., C.G. and J.A.C.; resources, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R. and A.L.A.T.; software, D.R.C., J.A.L.-B., M.N.-M., C.G. and J.A.C.; supervision, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R. and A.L.A.T.; validation, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R. and A.L.A.T.; visualization, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R., A.L.A.T., I.M., L.C.-G., M.H.-T., P.J.-M., M.M.-C., R.A.S.-G., C.R., M.d.C.M., G.D.F., J.A.L.-B., M.N.-M., C.G. and J.A.C.; writing—original draft, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R., A.L.A.T., I.M., L.C.-G., M.H.-T., P.J.-M., M.M.-C., R.A.S.-G., C.R., M.d.C.M., G.D.F., J.A.L.-B., M.N.-M., C.G. and J.A.C.; writing—review and editing, D.R.C., J.O.S., E.D.C.-V., A.R.-G., E.R., S.M.M.T., P.R., A.L.A.T., I.M., L.C.-G., M.H.-T., P.J.-M., M.M.-C., R.A.S.-G., C.R., M.d.C.M., G.D.F., J.A.L.-B., M.N.-M., C.G. and J.A.C. (WGSO). All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

All authors have endorsed the submitted version of this manuscript. Data were treated in a strictly confidential manner according to the ethical principles of the Helsinki Declaration. The study was approved by the statutory clinical research committee of Hospital del Mar (2020/9477) and l’Hospital Universitari Sant Joan de Reus (CEIC 203/2020). Due to the emergency situation, the researchers asked to exclude the patient consent, and this was authorised by the ethics committee of the Hospital del Mar.

Informed Consent Statement

This study was exempted from informed consent by the ethics committee due to the emergency situation during the first wave. The study was approved by the statutory clinical research committee of Hospital del Mar (2020/9477) and l’Hospital Universitari Sant Joan de Reus (CEIC 203/2020).

Data Availability Statement

The data of this study are not accessible in open access in order to preserve the confidentiality rights of the patients included in the study. Further enquiries can be directed to the corresponding author.


The authors acknowledge the support of the Centro Sociosanitario Isabel Roig, Centro Sociosanitario Dolors Aleu, Centre Fòrum del Parc de Salut Mar, and Centre Sociosanitari de l’Hospital Universitari Sant Joan de Reus. To the working Group about Survival in Old COVID-19 Patients: nurses: Montserrat Lago, Ruben Palacios, Zaraida Moreno, Mónica Ferreira, Celso Silva Fernandez, Zoila Alcalde, Geraldine Velez Vergara, Rene Flores Gonzales, María Elena Lopez Salguero, Sharalyn García, Noelia Hermoso, and Noelia Buitrago, and to the doctors: Victor Reyes, Sonia Fernandez, Luis A. Nania, Luis Arrarian, Cristina Garzón, Marita Saldarriaga, Jose Teixidor, and Andreu Garrigos. Staff of the Hospital Sant Joan de Reus Noemi Gamez Fernandez and Pilar Garcia. Staff of H.del Mar. To Alicia Padrón of the National School of Health—Carlos III Health Institute of Madrid.

Conflicts of Interest

All authors declare that they have no conflict of interest. Thus, the results and conclusions were freely arrived, and the authors’ views do not necessarily coincide with the official statements and declarations of their institutions. Regarding funding, this work has been carried out without grants or sponsors.


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Figure 1. Mortality study of COVID-19 patients of the Isabel Roig, Dolores Aleu Socio-Health Centres, Saint Joan de Reus Hospital, Centre Fòrum del Parc de Salut Mar, Barcelona; March to June 2020; first wave.
Figure 1. Mortality study of COVID-19 patients of the Isabel Roig, Dolores Aleu Socio-Health Centres, Saint Joan de Reus Hospital, Centre Fòrum del Parc de Salut Mar, Barcelona; March to June 2020; first wave.
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Figure 2. (a). Graph of survival function in COVID-19 patients from the Isabel Roig; (b). survival function in COVID-19 patients by sex; (c). survival function in COVID-19 patients by age group. Dolores Aleu Socio-Health Centres, Saint Joan de Reus Hospital, Centre Fòrum del Parc de Salut Mar, Barcelona; March to June 2020; first wave.
Figure 2. (a). Graph of survival function in COVID-19 patients from the Isabel Roig; (b). survival function in COVID-19 patients by sex; (c). survival function in COVID-19 patients by age group. Dolores Aleu Socio-Health Centres, Saint Joan de Reus Hospital, Centre Fòrum del Parc de Salut Mar, Barcelona; March to June 2020; first wave.
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Table 1. Description of patient mortality by age groups.
Table 1. Description of patient mortality by age groups.
FactorsVariablesMortality RateTotalLethality RateFrom 60–74 From 75 to 90 From 91 to More
DeathsTotalLethality RateDeathsTotalLethality RateDeathsTotalLethality Rate
n%N% n%N% n%N% n%N%
Total number of patients22733%683100%33%209%9514%21%13760%42362%32%7031%16524%42%
Intermediate care hospitals (social-health centers (HAI))Isabel Roig11517%31546%37%55%3840%13%6916%19346%36%4125%8451%49%
Dolors Aleu528%19529%27%77%3436%21%307%11828%25%159%4326%35%
Reus Hospital203%467%43%55%1112%45%123%317%39%32%42%75%
Centre Fòrum del Parc de Salut Mar.406%12719%31%33%1213%25%266%8119%32%117%3421%32%
Age group60–74203%9514%21%
91 to more7010%16524%42%
Geriatric SyndromesImmobility13119%32549%40%1011%4447%23%7919%19748%40%4225%8453%50%
Recurrent falls487%14522%33%33%1415%21%348%10425%33%117%2717%41%
Pressure ulcers365%12018%30%33%2224%14%256%7518%33%85%2315%35%
Polypharmacy (+5 drugs)17926%50375%36%1415%6267%23%11227%31976%35%5333%12275%43%
Cognitive impairment10716%32348%33%910%3133%29%6616%20248%33%3220%9056%36%
Sensory Alterations8813%26742%33%67%2629%23%5212%16842%31%3018%7347%41%
Cardiovascular DiseasesIschemic heart disease315%8312%37%44%910%44%143%4912%29%138%2515%52%
Atrial Fibrillation7211%16624%43%33%1112%27%4310%10826%40%2616%4729%55%
Heart failure568%14021%40%22%77%29%328%9322%34%2314%4226%55%
Other Cardiovascular Diseases254%11116%23%11%1112%9%164%7418%22%85%2616%31%
Peripheral Vascular Disease61%304%20%11%66%17%41%195%21%11%53%20%
Non-Coronary Heart Disease30%25100%12%22%33%67%21%154%13%00%74%0%
Coronary Cardiopathy61%193%32%11.1%22.1%50%41%132%31%11%42%25%
Electrical Conduction Disorder51%203%25%00.0%11.0%0%31%133%23%21%64%33%
Respiratory DiseasesAsthma102%325%31%00%22%0%82%246%33%21%64%33%
Chronic Obstructive Pulmonary Disease (COPD)396%11116%35%88%1920%42%235%7117%32%85%2113%38%
Other Respiratory Diseases152%507%30%22%77%29%102%338%30%32%106%30%
Metabolic DiseasesDiabetes599%17125%35%910%3638%25%358%10525%33%159%3018%50%
Other Metabolic Diseases386%18227%21%22%2526%8%276%11527%23%96%4226%21%
Neurological DiseasesIctus406%11116%36%33%1516%20%246%7017%34%138%2616%50%
Other dementias487%13720%35%11%1011%10%287%8821%32%1912%3924%49%
Other Neurological Diseases325%9214%35%33%2324%13%235%5313%43%64%1610%38%
Other Dementias 1a6810%19228%35%22%1415%14%4210%12830%33%2415%5030%48%
Other PathologiesOther Pathologies9614%38056%25%1011%5659%18%6415%23656%27%2213%8853%25%
Neoplasia b304%10716%28%66%1718%35%205%7017%29%42%2012%20%
Chronic renal failure213%8512%25%11%88%13%164%5313%30%42%2415%17%
Lower Frequency Digestive Pathology c30%284%11%00%55%0%31%184%17%00%53%0%
Initial SymptomsFever15723%39257%40%1718%6063%28%9723%24458%40%4326%8853%49%
General discomfort9514%24035%40%88%3335%24%6114%15938%38%2616%4829%54%
Nausea and vomiting71%294%24%00%22%0%41%225%18%32%53%60%
Other Symptoms132%406%33%22%66%33%102%256%40%11%96%11%
Administered TherapiesAntibiotics
Other Antibiotics7110%15923%45%44%2223%18%5012%9523%53%1710%4226%40%
Hydroxychloroquine-Azithromycin d14121%43363%33%910%5356%17%8821%26663%33%4427%11469%39%
Hydroxychloroquine and Azithromycin e8813%25037%35%66%2324%26%5613%16639%34%2616%6137%43%
Corticosteroids and inhalers
Dexamethasone f112%2822%39%00%18%0%67%1620%38%53%1132%45%
Ipratropium bromide7811%16825%46%77%2021%35%4711%10224%46%2415%4628%52%
Other inhalers152%639%24%00%1011%0%123%4611%26%32%74%43%
Use of Antinthrombotic and/or Antiplatelet10315%39157%26%1011%5457%19%6415%24859%26%2918%8954%33%
Antithrombotic Agent11116%37655%30%2021%95100%21%4010%16840%24%5131%11369%45%
Platelet Antiplatelet254%375%68%00%00%0%72%72%100%1811%3018%60%
a—Other Dementias1: corresponds to the number of patients with Alzheimer’s and Other Dementias. b—Neoplasia: Includes any types of neoplasia. c—Lower Frequency Digestive Pathology: Includes digestive pathologies most reported in this study. d—Hydroxychloroquine—Azithromycin: corresponds to the number of patients who consumed at least one of these antibiotics in their treatment. e—Hydroxychloroquine and Azithromycin: corresponds to the number of patients who consumed these two antibiotics in their treatment. f—Dexamethasone: corresponds to the number of patients who consumed Dexamethasone and were treated only at Hospital del Mar. Source: Isabel Roig Socio Health Centers, Dolores Aleu, Saint Joan de Reus Hospital, Hospital del Mar.
Table 2. The survival time by gender and age groups.
Table 2. The survival time by gender and age groups.
Limit Product Estimator
or Kaplan–Meier
95% Confidence Interval (CI)
Lower LimitUpper Limit
From 60 to 74551722.201.3719.5124.89
From 75 to 9029610722.340.6021.1523.52
From 91 to more1246220.630.9318.8022.45
Table 3. The multivariate level by sex, age, comorbidities and treatments by age group.
Table 3. The multivariate level by sex, age, comorbidities and treatments by age group.
FactorsVariablesTotal Population (N = 475) (adjusted)Population 60–74 (n = 55)Population 75–90 (n = 296)Population 91 to More (n = 124)
p. ValueHR* ICp. ValueHR* ICp. ValueHR* ICp. ValueHR* IC
91 to more NS1488(0.87–2.55)
Geriatric SyndromesUrinary incontinenceNSNSNS0.03417.15(1.25–236.0)NSNSNSNSNSNS
Cardiovascular DiseasesAtrial Fibrillation0.0351452(1.03–2.05)NSNSNS0.0061.86(1.20–2.89)NSNSNS
Respiratory DiseasesChronic Obstructive Pulmonary Disease (COPD)NSNSNS0.0293.08(1.12–8.44)NSNSNSNSNSNS
Metabolic DiseasesDyslipidemia0.0070.474(0.28–0.82)NSNSNSNSNSNS0.0480.16(0.03–0.99)
Neurological DiseasesMigraineNSNSNS0.01123.14(2.04–262.83)NSNSNSNSNSNS
Other PathologiesNeoplasiaNSNSNS0.0075768(1.62–20.52)NSNSNSNSNSNS
Initial SymptomsFever0.0241500(1.06–2.13)NSNSNS0.0032.00(1.27–3.13)NSNSNS
General discomfort0.0281437(1.04–1.99)NSNSNS0.0071.77(1.17–2.69)NSNSNS
Dyspnoeap < 0.0011984(1.41–2.79)0.0134.75(1.39–16.20)p < 0.0012.27(1.51–3.41)0.0022.52(1.40–4.57)
Antibiotic treatmentsAzithromycinNSNSNSNSNSNSNSNSNS0.0430.50(0.23–0.98)
Corticosteroid treatmentsMethylprednisoloneNSNSNSNSNSNS0.0341.60(1.04–2.53)NSNSNS
Other treatmentsAntithrombotic agent0.0010.559(0.40–0.78)NSNSNS0.0010.53(0.36–0.78)0.0070.488(0.29–0.82)
NS = Result is not statistically significant in the observed group; * IC = Confidence Interval at 95% // HR = Hazard Ratio // Source: Isabel Roig Socio-Health Centers, Dolores Aleu, Saint Joan de Reus Hospital, Hospital del Mar; REF = referential indicator variable as comparative in the group of variables an-alyzed.
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Culqui, D.R.; Ortega Segura, J.; Da Costa-Venancio, E.; Renom-Guiteras, A.; Roquer, E.; Muñoz Tejada, S.M.; Rodriguez, P.; Alba Travieso, A.L.; Medrano, I.; Canchucaja-Gutarra, L.; et al. Risk Factors Associated with the Mortality of COVID-19 Patients Aged ≥60 Years Neither Intubated nor Treated with Mechanical Ventilation: A Multicentre Retrospective Cohort Study during the First Wave in Spain. BioMed 2022, 2, 341-358.

AMA Style

Culqui DR, Ortega Segura J, Da Costa-Venancio E, Renom-Guiteras A, Roquer E, Muñoz Tejada SM, Rodriguez P, Alba Travieso AL, Medrano I, Canchucaja-Gutarra L, et al. Risk Factors Associated with the Mortality of COVID-19 Patients Aged ≥60 Years Neither Intubated nor Treated with Mechanical Ventilation: A Multicentre Retrospective Cohort Study during the First Wave in Spain. BioMed. 2022; 2(3):341-358.

Chicago/Turabian Style

Culqui, Dante R., Josep Ortega Segura, Elisabeth Da Costa-Venancio, Anna Renom-Guiteras, Esther Roquer, Sherly Melissa Muñoz Tejada, Patricia Rodriguez, Adilis L. Alba Travieso, Isis Medrano, Lizzeth Canchucaja-Gutarra, and et al. 2022. "Risk Factors Associated with the Mortality of COVID-19 Patients Aged ≥60 Years Neither Intubated nor Treated with Mechanical Ventilation: A Multicentre Retrospective Cohort Study during the First Wave in Spain" BioMed 2, no. 3: 341-358.

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