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Predictors of infection, symptoms development, and mortality in people with SARS-CoV-2 living in retirement nursing homes

  • Andrea De Vito ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Writing – original draft, Writing – review & editing

    andreadevitoaho@gmail.com

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

  • Vito Fiore,

    Roles Formal analysis, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

  • Elija Princic,

    Roles Conceptualization, Data curation, Investigation, Writing – original draft

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

  • Nicholas Geremia,

    Roles Conceptualization, Data curation, Investigation, Writing – original draft

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

  • Catello Mario Panu Napodano,

    Roles Data curation, Investigation, Writing – review & editing

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

  • Alberto Augusto Muredda,

    Roles Data curation, Investigation, Writing – review & editing

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

  • Ivana Maida,

    Roles Investigation, Supervision, Writing – review & editing

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

  • Giordano Madeddu,

    Roles Conceptualization, Supervision, Validation, Writing – original draft, Writing – review & editing

    Affiliations Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy, Mediterranean Center for Disease Control, University of Sassari, Sassari, Italy

  • Sergio Babudieri

    Roles Conceptualization, Supervision, Validation, Writing – review & editing

    Affiliation Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy

Abstract

Introduction

Since the start of the pandemic, millions of people have been infected, with thousands of deaths. Many foci worldwide have been identified in retirement nursing homes, with a high number of deaths. Our study aims were to evaluate the spread of SARS-CoV-2 in the retirement nursing homes, the predictors to develop symptoms, and death.

Methods and findings

We conducted a retrospective study enrolling all people living in retirement nursing homes (PLRNH), where at least one SARS-CoV-2 infected person was present. Medical and clinical data were collected. Variables were compared with Student’s t-test or Pearson chi-square test as appropriate. Uni- and multivariate analyses were conducted to evaluate variables’ influence on infection and symptoms development. Cox proportional-hazards model was used to evaluate 30 days mortality predictors, considering death as the dependent variable. We enrolled 382 subjects. The mean age was 81.15±10.97 years, and males were 140(36.7%). At the multivariate analysis, mental disorders, malignancies, and angiotensin II receptor blockers were predictors of SARS-CoV-2 infection while having a neurological syndrome was associated with a lower risk. Only half of the people with SARS-CoV-2 infection developed symptoms. Chronic obstructive pulmonary disease and neurological syndrome were correlated with an increased risk of developing SARS-CoV-2 related symptoms. Fifty-six (21.2%) people with SARS-CoV-2 infection died; of these, 53 died in the first 30 days after the swab’s positivity. Significant factors associated with 30-days mortality were male gender, hypokinetic disease, and the presence of fever and dyspnea. Patients’ autonomy and early heparin treatment were related to lower mortality risk.

Conclusions

We evidenced factors associated with infection’s risk and death in a setting with high mortality such as retirement nursing homes, that should be carefully considered in the management of PLRNH.

Introduction

A new severe respiratory syndrome was identified in Wuhan [1] (Hubei Province, China) at the end of December 2019. On January 7, a new Coronavirus was detected and called SARS-CoV-2 [2].

The World Health Organization (WHO) declared SARS-CoV-2 disease (COVID-19) as a public health emergency of international concern and characterized the outbreak as a pandemic on March 12, 2020. Since the start of the pandemic, on October 30, 2020, the total number of SARS-CoV-2 infected people is 44,888,869, with 1,178,475 deaths [3].

The common COVID-19 symptoms are fever, cough, and dyspnea, while less common symptoms are fatigue, headache, anosmia, ageusia, cutaneous manifestation, and gastrointestinal symptoms [410]. Furthermore, it has been described as a complication, a higher risk of disseminated intravascular coagulation, and venous thromboembolism [1113]. The severity and mortality of elderly patients with COVID-19 are higher than those of young and middle-aged patients [14]. Several variables seem to be associated with worse outcomes, such as age > 65, pre-existing concurrent cardiological, and cerebrovascular disease [15].

Treatment with low molecular weight heparin (LMWH) in COVID-19 has been recommended by some expert consensus and is associated with a better prognosis in severe COVID-19 patients with markedly elevated D-dimer [16]. Hydroxychloroquine (HCQ) and azithromycin have been widely in the early treatment of COVID-19 patients. Several trials and metanalyses on HCQ and azithromycin showed a lack of mortality reduction, and now more than 30 countries do not recommend their use in clinical practice. However, the efficacy of HCQ is still debated in the literature [1724].

Our study aimed to evaluate all people living in Italian retirement homes and identify the risk factor for infection occurrence, symptoms development, and death.

Methods

Study conduction

We conducted an observational retrospective cohort study, collecting medical records of people living in retirement nursing homes (PLRNH), in Sassari, Italy, where at least one SARS-CoV-2 infected person was present. Our team evaluated all people present in the facilities from April 9, 2020, to May 31, 2020.

The diagnosis was based on real-time PCR on a nasopharyngeal swab. Medical history and clinical data were collected. Laboratory blood tests were performed when appropriate.

Fever was defined as body temperature > 37.5°C. Patient compliance was defined as the patient’s ability to adhere to medical advice on oral and intravenous treatment regimens and respiratory exercise. Autonomy was defined for a score of 5 or 6 [25], according to the Katz Index of Independence in Activities of Daily Living (ADL). Bedridden was defined as a condition causing inability to move or even sit upright for different medical conditions (e.g., stroke, cognitive impairment, fracture).

SARS-COV-2 infection treatments consisted of hydroxychloroquine 200 mg twice daily, azithromycin 500 mg once daily for five days, or LMWH adjusted by body weight, kidney failure, and HAS-BLED score. Treatment was started only in symptomatic patients. HCQ and azithromycin were not administered on patients with a previous diagnosis of cardiovascular disease, in people with G6PDH deficiency, and those who had a previous side effect to one of these drugs. According to the time of enrolment, the treatment prescription was based on national guidelines, and it was adjusted according to the disease’s clinical presentation and drug-drug interactions with patients’ chronic therapy.

From the medical records, we extracted the demographic data, medical history (including hypertension, chronic heart disease, chronic obstructive pulmonary disease (COPD), chronic renal disease, obesity, malignancy, diabetes, neurological syndromes, and mental disorders), clinical symptoms, and signs at first evaluation, treatment details, complications, and clinical outcome.

Five medical doctors have collected the medical records, Andrea De Vito, Nicholas Geremia, Elija Princic, Alberto A. Muredda, and Catello Panu Napodano, supervised by Professor Ivana Maida, Giordano Madeddu, and Sergio Babudieri.

Patients definition

Italian nursing homes are accommodations with extreme variability among accepted people. It follows that the population considered in our study included people requiring low-level support, support in some activities, or with high dependence degree. In all nursing homes included in the study, nurses and assistive personnel were present 24/7, whereas primary care doctors, and other specialists, were present only upon request.

Medical assessment

Patients’ history was collected by the available medical records. Medical assessment was conducted with clinical evaluation every three days, and electrocardiography at time zero and day three of treatment, with a portable device. Blood exams were performed according to the physician’s request. Nasopharyngeal swabs were repeated in positive patients every week until the first negative result and until the end of the outbreak among people who tested negative.

Statistical analysis

Before performing the statistical analysis, data distribution was evaluated with the Kolmogorov-Smirnov test. Data were elaborated as numbers on total (percentages), means ± standard deviation.

Continuous variables with parametric distribution were compared with Student’s t-test. Categorical variables were evaluated with the Pearson chi-squared test.

Bivariate analysis was conducted to evaluate variables’ influence on infection and symptoms development. The statistical significance level was established as p<0.05.

Regarding 30-days mortality, Cox proportional-hazards model was used for multivariate logistic regression. Independent variables resulting with a p<0.2 at bivariate analysis were included in the multivariate logistic regression. Death was considered as a dependent variable. The significance level was defined as p<0.05.

Ethical issues

This research has been part of the protocol “COVID-19-SS”, approved by the Local Ethical Committee of the University Hospital of Cagliari, with the protocol number PG/2020/9411.

Results

Since the start of the outbreak, in our province, people living in 63 different retirement nursing homes were tested for SARS-CoV-2 for a total of 1946 subjects. Only in five facilities, there was at least one positive nasopharyngeal swab for SARS-CoV-2. Overall, the positive patients were 264, while the negative patients were 118 (Table 1).

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Table 1. Comparison of characteristics of 382 people living in retirement nursing homes, divided into people with (264) and without (118) SARS-CoV-2 infection.

https://doi.org/10.1371/journal.pone.0248009.t001

Considering the 382 PLRNH included, 140 (36.7%) were male, with a mean age of 81.15 ± 10.97 years (Table 1). The most common comorbidity was hypertension, present in 223 (58.4%) people, followed by neurological syndromes and mental disorders with 185(48.4%) and 165 (43.2%) cases, respectively.

Comparing people with a positive swab for SARS-CoV-2 with people with a negative swab (Table 1), there was a significant difference in age (81.93 ± 10.11 vs. 79.4 ± 12.57 years, p = 0.037), having diabetes (21.2% vs. 12.7%, p = 0.048), mental disorders (47.7% vs. 33.1%, p = 0.007), neurological syndromes (44.7% vs. 56.8%), and malignancies (9.8% vs. 1.7%, p = 0.005). Mortality was significantly higher in people with SARS-CoV-2 infection (21.2% vs. 11%, p = 0.017).

At the multivariate analysis (S1 Table), people with mental disorders [Odds Ratio (OR) 1.81 (Confidence Interval (CI) 95% 1.13–2.91) p-value = 0.013] and cancer [OR 6.37 (95%CI 1.45–28.03] p-value = 0.014] had an increased risk of being infected, while having a neurological syndrome [OR 0.61 (95%CI 0.38–0.98] p-value = 0.041] was less associated with the infection. Besides, taking angiotensin II receptor blockers (ARBs) as a chronic treatment increased infection risk [OR 2.40 (95%CI 1.04–5.54) p-value 0.04] (Fig 1).

thumbnail
Fig 1. Forrest Plots of multivariate logistic regression estimates of factors associated with SARS-CoV-2 infection.

Multivariable model includes all variables selected by a backward selection that were retained with a p-value less than 0.2 level. OR: Odds Ratio; CI: Confidence Interval; COPD: chronic obstructive pulmonary disease; CHD: cardiovascular disease; ARBs: Angiotensin II receptor blockers.

https://doi.org/10.1371/journal.pone.0248009.g001

Characteristics of symptomatic patients

Between SARS-CoV-2 infected people 50% developed symptoms (Table 2). The mean age was not significantly different from the asymptomatic subjects (82.3 ± 9.7 vs. 81.5 ± 10.5 years, p = 0.52). Significant differences were present in people with COPD (28% vs. 15.2%, p = 0.011), CHD (43.9% vs. 31.1%, p = 0.031), and neurological syndrome (52.3% vs. 37.1%, p = 0.013). Mortality was higher in the symptomatic group (28% vs. 14.4%, p = 0.007).

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Table 2. Comparison of characteristics of 264 people living in retirement nursing homes with SARS-CoV-2 infection, divided into people with (132) and without (132) SARS-CoV-2 related symptoms.

https://doi.org/10.1371/journal.pone.0248009.t002

The most common symptoms were fever and dyspnea, present in 90 (68.2%), and 74 (56.1%) patients, respectively. Fifty-five (41.7%) people had both fever and dyspnea. Cough occurred in 27 (20.4%) cases, while 12 (9.1%) complained of severe asthenia.

At the multivariate analysis (S2 Table), having COPD [OR 1.96 (95%CI 1.04–3.70), p = 0.037], or a neurological syndrome [OR 1.8 (95%CI 1.07–3.01) p = .026] were correlated with an increased risk to develop SARS-CoV-2 related symptoms (S1 Fig).

Among symptomatic people, 124 (93.9%) started SARS-CoV-2 treatment. In particular, 59 (44.7%) received hydroxychloroquine, 48 (36.4%) azithromycin, and 105 (79.5%) heparin. Despite the drugs used, no adverse reactions such as QT prolongation were found.

Mortality

Fifty-six (21.2%) people with SARS-CoV-2 infection died; of them, 53 died in the first 30 days after the swab’s positivity. Dividing people by age, mortality was higher in people with 80 years and above (24.6%), while it was significantly lower in the other age ranges (Fig 2).

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Fig 2. Distribution of 264 patients with SARS-CoV-2 infection according to age groups and mortality rates.

https://doi.org/10.1371/journal.pone.0248009.g002

The deceased’s mean age was significantly higher than the survivors’ mean age (85.3 ± 6.3 vs. 81 ± 10.7 years, p = 0.005). Significant differences in the two groups were also the COPD (32.2% vs. 18.7%; p = 0.031), neurological syndrome (57.1% vs. 41.3%, p = 0.035), autonomy (3.6% vs. 38.9%, p<0.001), hypokinetic disease (55.4% vs. 19.2%), and presence of fever and dyspnea (42.9% vs. 14.9%, p<0.001) (Table 3).

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Table 3. Comparison of characteristics of 264 people living in retirement nursing homes with SARS-CoV-2 infection, divided into deceased and survival.

https://doi.org/10.1371/journal.pone.0248009.t003

At the multivariate Cox proportional-hazards model (S3 Table) the significant factors associated with 30-days mortality were male gender [Hazard Ratio (HR) 1.93 (95%CI 1.07–3.45), p = 0.028], hypokinetic disease [HR 1.91 (95%CI 1.05–3.48), p = 0.035], and the presence of fever and dyspnea [HR 3.99 (95%CI 2.05–7.79), p<0.001]. On the contrary, patients’ autonomy [HR 0.051 (95%CI 0.007–0.39), p = 0.004], and heparin treatment [HR 0.42 (95%CI 0.22–0.79), p = 0.008], were associated with a significantly lower mortality risk, according to our results’ (Fig 3).

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Fig 3. Forrest Plots of multivariate Cox proportional hazards model regression estimates of factors associated with mortality.

Multivariable model includes all variables selected by a backward selection that were retained with a p-value less than 0.2 level. HR: Hazard Ratio; CI: Confidence Interval; COPD: chronic obstructive pulmonary disease; LMWH: low molecular weight heparin.

https://doi.org/10.1371/journal.pone.0248009.g003

Discussion

To our knowledge, this report is one of the largest studies about the SARS-CoV-2 spread in retirement nursing homes.

Nursing homes play an important role as a significant clustering hotspot of the epidemic, as reported in the literature [26, 27]. However, few published official data regarding the infection rate in nursing homes, individual risk factors, and the residents’ outcome. For this reason, focused interventions should be realized in these settings.

In the facilities with at least one SARS-CoV-2 positive subject, 69.1% of the PLRNH resulted positive in our study, thus, confirming that retirement nursing homes have high transmission rates of SARS-CoV-2. We can hypothesize that this could be related to crowding, sharing of gathering areas, and inadequate infection prevention and control measures, which need to be quickly revised [28, 29]. One of the most critical issues in the authors’ experience was applying optimal protocols of isolation and social distancing in such challenging settings and difficulties in communication with elderly subjects, often with mental health and neurological disorders. Furthermore, as shown by Daoust, elderly people seem to have reduced adherence to preventive measures (e.g., wearing masks and social distancing) [30].

Wang et al., in their manuscript among 339 elderly patients with SARS-CoV-2 infection, found that the most common comorbidities were hypertension (40.8%), diabetes (16.0%), and CHD (15.7%) [31]. In our study, the percentage of people with these comorbidities was abundantly higher, and other comorbidities such as neurological syndromes and mental disorders were more common than diabetes and CHD. The older age of our cases could explain this difference (81.2±10.1 in our study vs. 71±8).

When considering factors that influenced infection occurrence, mental health disorders, malignancies, and use of ARBs were significantly associated with SARS-CoV-2 infection development at multivariate analysis.

Regarding ACE inhibitors, the interaction between SARS viruses and ACE 2 has been proposed as a potential risk factor of infectivity. For this reason, some concerns have been raised about their use, for a possible transmission increase, related to hosting susceptibility. Interestingly, our findings diverge from most common literature findings, and ACE inhibitors did not influence the risk, as described by most of the literature on SARS-CoV-2 infection and outcomes [3236].

On the contrary, our data seem to support the hypothesis that chronic treatment with ARBs can raise the possibility of contracting the disease.

Regarding asymptomatic patients, estimates among the elderly are debated. A recent meta-analysis, including 50,155 subjects, estimated the prevalence of asymptomatic SARS-CoV-2 infection between 15 and 16%. When analysing the elderly subgroup, the prevalence of asymptomatic patients was 28.3% [37]. Our data showed an even higher prevalence, with the involvement of 50% of PLRNH. The overestimation of asymptomatic cases could explain this high percentage. In fact, it was difficult to collect medical history regarding slight symptoms, giving the high presence of neurological syndromes, which represents a barrier between doctor and patient.

Mildly symptomatic and pre-symptomatic cases can be incorrectly diagnosed as asymptomatic, as showed by previously published data on long-term care facilities [38]. In any case, a high proportion of asymptomatic, mildly symptomatic, and pre-symptomatic patients support a possible important role of unrecognized carriers in SARS-CoV-2 diffusion and transmission in retirement nursing homes [3840].

At the multivariate logistic regression, COPD and neurological syndromes were associated with a higher risk of developing SARS-CoV-2-related symptoms. On the one hand, the ACE2 upregulation may have a protective effect on the lung epithelial cells against the chronic injury observed in smokers and COPD patients. On the other hand, it could be related to SARS-CoV-2 mucosal penetration, with a significant role in the clinical presentation [41].

Association between neurological syndromes and COVID-19 development is still debated. Stoessl et al. and Ferini-Strambi et al. aimed that Parkinson’s disease and parkinsonism are not related to a major infection vulnerability [42, 43]. However, old age and respiratory muscle rigidity associated with neurological disorders, as well as the presence of comorbidities, could explain our results.

To our knowledge, there are no data available about the risk of developing COVID-19 related symptoms in patients with dementia and Alzheimer’s disease. It is known how dementia, especially in its severe stages and independently by age, is associated with worse outcomes [13, 44]. Probably, elderly patients’ vulnerability may be associated with a more critical presentation of COVID-19.

The most common symptoms were fever and dyspnoea. As highlighted by other studies, fever represents the most common symptom among elderly patients. From this point of view, our data are concordant with the literature. However, cough, dyspnoea, or sputum have been reported with different frequencies in previous reports, suggesting that these symptoms may be extremely variable as presentation, compared to fever [14, 31, 45].

Regarding mortality, in our sample, it occurred both in symptomatic and asymptomatic patients. Overall, 56 (21.2%) people with SARS-CoV-2 died, while the negative group percentage was 11%.

Bonadad et al.[46] conducted a meta-analysis on 611,583 subjects to analyze the effect of age on mortality. Comparing the different samples, the mortality was lower in our study for all age groups (60–69 years: 5.3% vs. 9.5%; 70–79 years: 13.5% vs. 22.8%; ≥80 years: 24.6% vs. 29.6%).

The role of the male gender on mortality is still debated. Looking at the national report, in 54/64 (84%) countries, the male/female death ratio was>1 [47]. Data from different Countries highlighted a fatality ratio higher among men than in women. Although some authors explained this difference with higher rates of comorbidities among men [48], prior studies suggested a higher trend among females to follow hand hygiene [49] and preventive care [48, 50].

The hypokinetic disease has been identified as a mortality predictor, with an HR of 1.91. It could be explained by the fact that subjects with this condition are, generally, more vulnerable.

Even if having a malignancy was not associated with an increased risk of symptoms’ development and mortality, these results should be taken with caution, given the low number of cases.

Patients who started treatment with LMWH showed decreased mortality. The SARS-CoV-2 pathogenesis is still unclear. However, many reports associated COVID-19 and coagulopathies, such as pulmonary embolism and microvascular thrombosis [16, 51]. For these reasons, LMWH is used in the management of COVID-19 [52]. Different studies showed how LMWH has anti-inflammatory and, possibly, antiviral effects [5355]. In our study, 19 asymptomatic patients died suddenly. Post-mortem examinations were not performed, but the presence of coagulopathy was likely. Furthermore, different studies described the presence of undiagnosed cerebrovascular and cardiovascular complications in severe SARS-CoV-2 infections [56, 57]. We speculate that LMWH start could also be considered in asymptomatic patients, based on the patients’ comorbidities and the fall-risk evaluation.

The receipt of treatment with hydroxychloroquine and azithromycin did not modify the mortality, in accordance with previous studies [18, 23, 24].

The COVID-19 may have relatively high mortality rates among elderly patients. For this reason, focused interventions should be programmed by healthcare providers, with the provision of close monitoring in patients at high mortality risk due to their burden of comorbidities. More studies are needed to evaluate the advantages in the survival of an early LMWH start, particularly in such a challenging and frail population.

Limitations of the study

Our study has some limitations that should be addressed. Firstly, this is an observational, retrospective survey. Secondly, our experience is monocentric, and this could not entirely reflect the national situation. Given the timeline and the constant advice updates, treatments were extremely variable in time of staring after symptoms development, drug choice, and combination. This could cause a bias in our evaluation of hydroxychloroquine or azithromycin influence on mortality, as well as severe comorbidities presence.

Supporting information

S1 Table. Bivariate and multivariate logistic regression estimates of factors associated with SARS-CoV-2 infection.

https://doi.org/10.1371/journal.pone.0248009.s001

(DOCX)

S2 Table. Bivariate and multivariate logistic regression estimates of factors associated with SARS-CoV-2-related symptoms.

https://doi.org/10.1371/journal.pone.0248009.s002

(DOCX)

S3 Table. Bivariate and multivariate Cox proportional-hazards model estimates of factors associated with mortality.

https://doi.org/10.1371/journal.pone.0248009.s003

(DOCX)

S1 Fig. Forrest Plots of multivariate logistic regression estimates of factors associated with symptoms development.

Multivariable model includes all variables selected by a backward selection that were retained with a p-value less than 0.2 level. OR: Odds Ratio; CI: Confidence Interval; COPD: chronic obstructive pulmonary disease; CHD: cardiovascular disease; ARBs: Angiotensin II receptor blockers.

https://doi.org/10.1371/journal.pone.0248009.s004

(PDF)

References

  1. 1. Commission WMH. Report of clustering pneumonia of unknown etiology in Wuhan City. Published December 31, 2019. [cited 1 Mar 2020]. Available: http://wjw.wuhan.gov.cn/front/web/showDetail/2019123108989
  2. 2. New-type coronavirus causes pneumonia in Wuhan: expert—Xinhua | English.news.cn. [cited 1 Mar 2020]. Available: http://www.xinhuanet.com/english/2020-01/09/c_138690570.htm
  3. 3. WHO. Coronavirus disease (COVID-19), report 191. 2020. Available: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200729-covid-19-sitrep-191.pdf?sfvrsn=2c327e9e_2
  4. 4. Vaira LA, Hopkins C, Salzano G, Petrocelli M, Melis A, Cucurullo M, et al. Olfactory and gustatory function impairment in COVID ‐19 patients: Italian objective multicenter‐study. Head Neck. 2020;42: 1560–1569. pmid:32437022
  5. 5. Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020;382: 1708–1720. pmid:32109013
  6. 6. Vaira LA, Deiana G, Fois AG, Pirina P, Madeddu G, De Vito A, et al. Objective evaluation of anosmia and ageusia in COVID‐19 patients: a single‐center experience on 72 cases. Head Neck. 2020;42: 1252–1258. pmid:32342566
  7. 7. De Vito A, Geremia N, Fiore V, Princic E, Babudieri S, Madeddu G. Clinical features, laboratory findings and predictors of death in hospitalized patients with COVID-19 in Sardinia, Italy. Eur Rev Med Pharmacol Sci. 2020;24: 7861–7868. pmid:32744714
  8. 8. Zinellu A, Arru F, De Vito A, Sassu A, Valdes G, Scano V, et al. The De Ritis ratio as prognostic biomarker of in‐hospital mortality in COVID‐19 patients. Eur J Clin Invest. 2020; e13427. pmid:33043447
  9. 9. Guarneri C, Venanzi Rullo E, Gallizzi R, Ceccarelli M, Cannavò SP, Nunnari G. Diversity of clinical appearance of cutaneous manifestations in the course of COVID‐19. J Eur Acad Dermatology Venereol. 2020;34: e449–e450. pmid:32441830
  10. 10. Geremia N, De Vito A, Gunnella S, Fiore V, Princic E, Panu Napodano C, et al. A Case of Vasculitis-Like Skin Eruption Associated With COVID-19. Infect Dis Clin Pract. 2020;28: e30–e31.
  11. 11. Niu S, Tian S, Lou J, Kang X, Zhang L, Lian H, et al. Clinical characteristics of older patients infected with COVID-19: A descriptive study. Arch Gerontol Geriatr. 2020;89: 104058. pmid:32339960
  12. 12. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395: 1054–1062. pmid:32171076
  13. 13. Covino M, De Matteis G, Santoro M, Sabia L, Simeoni B, Candelli M, et al. Clinical characteristics and prognostic factors in COVID‐19 patients aged ≥80 years. Geriatr Gerontol Int. 2020;20: 704–708. pmid:32516861
  14. 14. Liu K, Chen Y, Lin R, Han K. Clinical features of COVID-19 in elderly patients: A comparison with young and middle-aged patients. J Infect. 2020;80: e14–e18. pmid:32171866
  15. 15. Du RH, Liang LR, Yang CQ, Wang W, Cao TZ, Li M, et al. Predictors of mortality for patients with COVID-19 pneumonia caused by SARSCoV- 2: A prospective cohort study. Eur Respir J. 2020;55: 2000524. pmid:32269088
  16. 16. Tang N, Bai H, Chen X, Gong J, Li D, Sun Z. Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thromb Haemost. 2020;18: epub. pmid:32220112
  17. 17. Rosenberg ES, Dufort EM, Udo T, Wilberschied LA, Kumar J, Tesoriero J, et al. Association of Treatment With Hydroxychloroquine or Azithromycin With In-Hospital Mortality in Patients With COVID-19 in New York State. JAMA. 2020. pmid:32392282
  18. 18. Molina JM, Delaugerre C, Le Goff J, Mela-Lima B, Ponscarme D, Goldwirt L, et al. No evidence of rapid antiviral clearance or clinical benefit with the combination of hydroxychloroquine and azithromycin in patients with severe COVID-19 infection. Med Mal Infect. 2020;50: 384. pmid:32240719
  19. 19. Castelnuovo A Di, Costanzo S, Antinori A, Berselli N, Blandi L, Bruno R, et al. Use of hydroxychloroquine in hospitalised COVID-19 patients is associated with reduced mortality: Findings from the observational multicentre Italian CORIST study. Eur J Intern Med. 2020;0. pmid:32859477
  20. 20. Million M, Gautret P, Colson P, Roussel Y, Dubourg G, Chabriere E, et al. Clinical efficacy of chloroquine derivatives in COVID-19 infection: comparative meta-analysis between the big data and the real world. New Microbes New Infect. 2020;38: 100709. pmid:33088574
  21. 21. d’Arminio Monforte A, Tavelli A, Bai F, Marchetti G, Cozzi-Lepri A. Effectiveness of hydroxychloroquine in COVID-19 disease: A done and dusted deal? Int J Infect Dis. 2020;99: 75–76. pmid:32738491
  22. 22. Lee TC, MacKenzie LJ, McDonald EG, Tong SYC. An observational cohort study of hydroxychloroquine and azithromycin for COVID-19: (Can’t Get No) Satisfaction. Int J Infect Dis. 2020;98: 216–217. pmid:32623080
  23. 23. Fiolet T, Guihur A, Rebeaud ME, Mulot M, Peiffer-Smadja N, Mahamat-Saleh Y. Effect of hydroxychloroquine with or without azithromycin on the mortality of coronavirus disease 2019 (COVID-19) patients: a systematic review and meta-analysis. Clin Microbiol Infect. 2021;27: 19–27. pmid:32860962
  24. 24. The RECOVERY Collaborative Group. Effect of Hydroxychloroquine in Hospitalized Patients with Covid-19. N Engl J Med. 2020;383: 2030–2040. pmid:33031652
  25. 25. Shelkey M, Wallace M. Katz Index of Independence in Activities of Daily Living: Home Healthcare Now. Home Healthc Nurse. 2001;19: 323–324.
  26. 26. Wang J, Yang W, Pan L, Ji JS, Shen J, Zhao K, et al. Prevention and control of COVID-19 in nursing homes, orphanages, and prisons. Environ Pollut. 2020;266: Online ahead of print. pmid:32645554
  27. 27. WHO. Infection prevention and control guidance for long-term care facilities in the context of COVID-19: interim guidance, 21 March 2020. Geneva PP—Geneva: World Health Organization; 2020. Available: https://apps.who.int/iris/handle/10665/331508
  28. 28. Adalja AA, Toner E, Inglesby T V. Priorities for the US Health Community Responding to COVID-19. JAMA—J Am Med Assoc. 2020;323: 1343–1344. pmid:32125355
  29. 29. Bedford J, Enria D, Giesecke J, Heymann DL, Ihekweazu C, Kobinger G, et al. COVID-19: towards controlling of a pandemic. Lancet. 2020;395: 1015–1018. pmid:32197103
  30. 30. Daoust J-F. Elderly people and responses to COVID-19 in 27 Countries. Tu W-J, editor. PLoS One. 2020;15: e0235590. pmid:32614889
  31. 31. Wang L, He W, Yu X, Hu D, Bao M, Liu H, et al. Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up. J Infect. 2020;80: 639–645. pmid:32240670
  32. 32. Watkins J. Preventing a covid-19 pandemic. The BMJ. BMJ Publishing Group; 2020. p. m810. pmid:32111649
  33. 33. Khan SH, Zaidi SK. Review of evidence on using ACEi and ARBs in patients with hypertension and COVID-19. Drugs Ther Perspect. 2020;36: 347–350. pmid:32837189
  34. 34. Fosbøl EL, Butt JH, Østergaard L, Andersson C, Selmer C, Kragholm K, et al. Association of Angiotensin-Converting Enzyme Inhibitor or Angiotensin Receptor Blocker Use with COVID-19 Diagnosis and Mortality. JAMA—J Am Med Assoc. 2020;324: 168–177. pmid:32558877
  35. 35. Li J, Wang X, Chen J, Zhang H, Deng A. Association of Renin-Angiotensin System Inhibitors with Severity or Risk of Death in Patients with Hypertension Hospitalized for Coronavirus Disease 2019 (COVID-19) Infection in Wuhan, China. JAMA Cardiol. 2020;5: 825–830. pmid:32324209
  36. 36. De Vito A, Geremia N, Princic E, Fanelli C, Panu Napodano CM, Muredda AA, et al. Does Angiotensin II receptor blockers increase the risk of SARS-CoV-2 infection? A real-life experience. Eur Rev Med Pharmacol Sci. 2021;25: 523–526. pmid:33506944
  37. 37. He J, Guo Y, Mao R, Zhang J. Proportion of asymptomatic coronavirus disease 2019 (COVID‐19): a systematic review and meta‐analysis. J Med Virol. 2020; jmv.26326. pmid:32691881
  38. 38. Louie JK, Scott HM, DuBois A, Sturtz N, Lu W, Stoltey J, et al. Lessons from Mass-Testing for COVID-19 in Long Term Care Facilities for the Elderly in San Francisco. Clin Infect Dis. 2020. pmid:32687150
  39. 39. Arons MM, Hatfield KM, Reddy SC, Kimball A, James A, Jacobs JR, et al. Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility. N Engl J Med. 2020;382: 2081–2090. pmid:32329971
  40. 40. Kimball A, Hatfield KM, Arons M, James A, Taylor J, Spicer K, et al. Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents of a Long-Term Care Skilled Nursing Facility—King County, Washington, March 2020. MMWR Morb Mortal Wkly Rep. 2020;69: 377–381. pmid:32240128
  41. 41. Leung JM, Yang CX, Tam A, Shaipanich T, Hackett TL, Singhera GK, et al. ACE-2 expression in the small airway epithelia of smokers and COPD patients: implications for COVID-19. Eur Respir J. 2020;55: 2000688. pmid:32269089
  42. 42. Stoessl AJ, Bhatia KP, Merello M. Movement Disorders in the World of COVID‐19. Mov Disord. 2020;35: 709–710. pmid:32250468
  43. 43. Ferini-Strambi L, Salsone M. COVID-19 and neurological disorders: are neurodegenerative or neuroimmunological diseases more vulnerable? J Neurol. 2020;1: 3. pmid:32696341
  44. 44. Bianchetti A, Rozzini R, Guerini F, Boffelli S, Ranieri P, Minelli G, et al. Clinical Presentation of COVID19 in Dementia Patients. J Nutr Heal Aging. 2020;24: 560–562. pmid:32510106
  45. 45. Guo T, Shen Q, Guo W, He W, Li J, Zhang Y, et al. Clinical Characteristics of Elderly Patients with COVID-19 in Hunan Province, China: A Multicenter, Retrospective Study. Gerontology. 2020; 1–9. pmid:32474561
  46. 46. Bonanad C, García-Blas S, Tarazona-Santabalbina F, Sanchis J, Bertomeu-González V, Fácila L, et al. The Effect of Age on Mortality in Patients With COVID-19: A Meta-Analysis With 611,583 Subjects. J Am Med Dir Assoc. 2020;21: 915–918. pmid:32674819
  47. 47. COVID-19 sex-disaggregated data tracker–Global Health 50/50. [cited 6 Aug 2020]. Available: https://globalhealth5050.org/covid19/sex-disaggregated-data-tracker/
  48. 48. Sharma G, Volgman AS, Michos ED. Sex Differences in Mortality From COVID-19 Pandemic. JACC Case Reports. 2020;2: 1407–1410. pmid:32373791
  49. 49. Johnson HD, Sholcosky D, Gabello K, Ragni R, Ogonosky N. Sex differences in public restroom handwashing behavior associated with visual behavior prompts. Percept Mot Skills. 2003;97: 805–810. pmid:14738345
  50. 50. Wu Z, McGoogan JM. Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases from the Chinese Center for Disease Control and Prevention. JAMA—J Am Med Assoc. 2020;323: 1239–1242. pmid:32091533
  51. 51. Kipshidze N, Dangas G, White CJ, Kipshidze N, Siddiqui F, Lattimer CR, et al. Viral Coagulopathy in Patients With COVID-19: Treatment and Care. Clin Appl Thromb. 2020;26: 1–7. pmid:32687449
  52. 52. Marietta M, Ageno W, Artoni A, De Candia E, Gresele P, Marchetti M, et al. COVID-19 and haemostasis: A position paper from Italian Society on Thrombosis and Haemostasis (SISET). Blood Transfus. 2020;18: 167–169. pmid:32281926
  53. 53. Seffer MT, Cottam D, Forni LG, Kielstein JT. Heparin 2.0: A New Approach to the Infection Crisis. Blood Purification. S. Karger AG; 2020. p. published online ahead of print. https://doi.org/10.1159/000508647 pmid:32615569
  54. 54. Poterucha TJ, Libby P, Goldhaber SZ. More than an anticoagulant: Do heparins have direct anti-inflammatory effects? Thromb Haemost. 2017;117: 437–444. pmid:27975101
  55. 55. Paar V, Wernly B, Zhou Z, Motloch LJ, Hoppe UC, Egle A, et al. Anti-coagulation for COVID-19 treatment: both anti-thrombotic and anti-inflammatory? J Thromb Thrombolysis. 2020; Online ahead of print. pmid:32632558
  56. 56. Fan H, Tang X, Song Y, Liu P, Chen Y. Influence of covid-19 on cerebrovascular disease and its possible mechanism. Neuropsychiatr Dis Treat. 2020;16: 1359–1367. pmid:32547039
  57. 57. Mishra AK, Sahu KK, George AA, Sargent J, Lal A. Cerebrovascular events in COVID-19 patients. Monaldi Arch chest Dis = Arch Monaldi per le Mal del torace. 2020;90. pmid:32527073