COVID-19's Mortality for Elderly People: Comparison
Please note this is a comparison between Version 2 by Ron Wang and Version 1 by Vicente Paulo Alves.

A prevalência da pandemia COVID-19 (SARS-CoV-2) na população idosa, principalmente institucionalizada, ocorre por ser este o cenário em que o isolamento social é difícil em uma situação como a de uma pandemia. A vulnerabilidade dessa população está ligada aos aspectos fisiológicos do envelhecimento, que impactam na eficácia do sistema imunológico, desencadeando morbimortalidade por doenças infecciosas.

  • SARS-CoV-2
  • COVID-19
  • non-communicable chronic diseases (NCCDs)
  • clinical features
  • institutionalized or hospitalized elderly
  • meta-analysis

1. Introdução1. Introduction

In this way, aging has become a global phenomenon in full exponential growth, showing the success of public health and socioeconomic development policies. However, there are new challenges for society that this presents. Our society needs to adapt to this new scenario, maximize the functional capacity and health of the elderly and promote their social inclusion and safe participation. [1]. In view of this, there are social consequences of the aging population and new public health issues arising that affect European countries, such as Italy, in particular [2]. In Italy, the profile of the elderly population is of a group with a high prevalence of non-communicable chronic diseases (NCCDs) and associated comorbidities [1]. In Italy, aging is a common and growing phenomenon. Italy is considered the country with the second largest number of elderly people [2], along with a mortality rate that has decreased by more than 50% in the last 30 years, mainly due to the reduction in cardiovascular diseases [3].

The COVID-19 pandemic (SARS-CoV-2) has caused considerable mortality in populations considered at risk, such as the elderly population, especially those who are institutionalized, a scenario in which social isolation is difficult in a situation such as a pandemic. The vulnerability of this population is linked with the physiological aspects of aging, which impact the effectiveness of the immune system, triggering morbidity and mortality from infectious diseases [4].

Thus, it is necessary to investigate the main factors that make institutionalized elderly people more vulnerable to death. Fragility is a condition that worsens with advancing age and with COVID-19 infection, especially for the hospitalized elderly, who tend to develop a more accentuated presentation of the classic symptoms of the disease [5].

The objective of this study was to synthesize the factors associated with the mortality of elderly Italian people diagnosed with coronavirus who lived in institutions or who were hospitalized because of the disease.

2. MaCurrenterials and Method Findings

The systematic review format was chosen based on the recommendations of The Joanna Briggs Institute (JBI), following the nine steps for its development: (1) construction of the preliminary research protocol; (2) formulation of the review question; (3) definition of inclusion and exclusion criteria; (4) search strategy; (5) selection of studies for inclusion; (6) data extraction; (7) synthesis of the data; (8) narrative summary; (9) references [9].

The inclusion criteria for the selection of articles were: Primary studies on the mortality of elderly people diagnosed with coronavirus; Studies in English, Spanish or Italian.

Once the inclusion criteria were estain morblished, these were set as the exclusion criteria: Studies that were not of Italian elderly people; Studies on the elderly who were not institutionalized or hospitalized; Studies that did not answer the guiding question of the systematic review.

While developing the search and selection of articles, from searching the datadities presented bases to selecting studies by reading titles and abstracts or the full text, the PRISMA protocol was used [12] ( Figure 1 ) to guarantethe elde the rigor of the systematic review [11].

3. Results

The main morbidities presented by the elderly in the studies were: dementia [20][6], diabetes [19[7][8],21], chronic kidney disease [19][7] and hypertension [21][8], showing that NCCDs had a key role to play in these cases.

Table 2 shows the descriptive analysis of the quantitative variables according to the survivors and non-survivors, and Table 3 shows the effect size, in SDM and 95% CI, of the variables affecting mortality.

Table 2.

Descriptive analysis of quantitative variables, according to groups of survivors and non-survivors.
VariablesSMD (95% CI)I2IZp-Value
2Zp-Value
Age (years)3.10 (2.79; 3.40)
Male0.98 (0.67; 1.43)99.9%89.319.760.10<0.001
0.919Charlson Index1.74 (1.56; 1.92)-19.33<0.001
Chronic diseases1.20 (0.94; 1.54)-1.480.139
Cancer1.60 (0.60; 4.23)-0.920.356
Diabetes1.90 (1.53; 2.37)62.75.73<0.001
Cardiovascular diseases/coronary artery disease1.80 (0.85; 3.80)92.01.530.125
COPD 12.19 (1.54; 3.10)0.04.39<0.001
Immunodeficiencies5.28 (0.26; 108.12)-1.080.280
Chronic kidney disease3.96 (2.65; 5.91)0.06.73<0.001
Metabolic disease1.51 (0.60;3.75)-0.890.374
Obesity1.28 (0.78; 2.10)60.80.990.322
Hypertension1.37 (1.24; 1.51)69.36.25<0.001
FH 23.27 (2.49; 4.29)-8.55<0.001
Dementia3.67 (2.43; 5.55)-6.17<0.001
Smoking0.74 (0.32;1.71)-0.700.483
VariablesNon-SurvivorsSurvivors
NMeanSDNMeanSD
Age (years)      
Iacarinno et al. (2020)18879.60.8130464.70.4
Stroppa et al. (2020)974.447.211668.3810.16
Bonetti et al. (2020)7075.414.997462.6314.97
Charlson Index      
Iacarinno et al. (2020)1884.370.1414032.630.05
N, sample size in each group; SD, standard deviation. Table 3. Meta-analysis of factors (quantitative variables) associated with mortality.
SMD, standardized mean difference; Z, Z statistic of the meta-analysis; I2, I-square; 95% CI, 95% confidence interval. Table 5. Meta-analysis of factors associated (quantitative variables) with mortality.
VariablesRR (95% CI)
1 Chronic obstructive pulmonary disease (COPD). 2 Familial hypercholesterolemia (FH). RR, relative risk; Z, Z statistic of meta-analysis; I2, I-square; 95% CI, 95% confidence interval.

Table 4 shows the descriptive analysis of qualitative variables according to the survivors and non-survivors, and Table 5 shows the effect size, in RR and 95% CI, of the variables affecting mortality.

The analysis of quantitative variables showed that the risk of mortality was higher in individuals with diabetes (RR, 1.90; 95% CI, 1.53; 2.37), COPD (RR, 2.19; 95% CI, 1.54; 3.10), chronic kidney disease (RR, 3.96; 95% CI, 2.65; 5.91), hypertension (RR, 1.37; 95% CI, 1.24; 1.51), FH (RR, 3.27; 95% CI, 2.49; 4.29) or dementia (RR, 3.67; 95% CI, 2.43; 5.55) ( Table 4 ).

4. Conclusions

As DCNTs, quando associadas à SARS-CoV-2, são fatores de mortalidade de idosos. Os dados relativos às DCNT são, portanto, fundamentais para a elaboração de políticas públicas e práticas de promoção da saúde e prevenção de doenças crônicas ao longo do envelhecimento. Além disso, estratégias de prevenção do coronavírus para a população idosa com DCNT, como doença pulmonar obstrutiva crônica ou demência, devem ser planejadas com uma meta clara e precisa para evitar que tantas mortes ocorram entre os idosos.

Certamente, não devemos criar mais instituições que abriguem idosos sem levar em conta os maiores riscos que a vida em uma grande comunidade acarreta para a convivência e o contágio dessas doenças. Será preciso pensar criativamente em novos espaços de convivência e novas formas de lidar com o trabalho como profissionais e operadores de saúde nesses estabelecimentos.

Com a vacinação chegando aos poucos em cada país, à medida que a indústria farmacêutica trabalha para entregar as doses suficientes e os países se empenham em implementar uma logística eficiente de distribuição e aplicação do medicamento, espera-se que tudo isso passe, e que neste momento de grandes dores e o sofrimento para muitas famílias facilitará nosso aprendizado e o crescimento de autoridades e de novas políticas públicas voltadas para a proteção dos idosos.

A limitação mais importante desta pesquisa é o pequeno número de artigos encontrados na Itália, o que impediu uma análise mais aprofundada. Em estudos futuros, fatores relacionados às doenças crônicas devem ser considerados, uma vez que esses aspectos impactam na mortalidade de idosos com COVID-19.

References

  1. WHO. World Report on Ageing and Health; WHO: Geneva, Switzerland, 2015; p. 260.
  2. Piccininni, M.; Rohmann, J.L.; Foresti, L.; Lurani, C.; Kurth, T. Use of all cause mortality to quantify the consequences of covid-19 in Nembro, Lombardy: Descriptive study. BMJ 2020, 369, m1835.
  3. Istituto Superiore di Sanità. L’epidemiologia per la Sanità Pubblica—Malattie Cardiovascolari; Istituto Superiore di Sanità: Rome, Italy, 2020.
  4. Granda, E.C.; Cunha, S.G.S.; Silva Michele Fabiana da Campos, K.F.C. Covid-19 in elderly: Why are they more vulnerable to the new coronavirus? Braz. J. Dev. 2021, 7, 10.
  5. Knopp, P.; Miles, A.; Webb, T.E.; McLoughlin, B.C.; Mannan, I.; Raja, N.; Wan, B.; Davis, D. Presenting features of COVID-19 in older people: Relationships with frailty, inflammation and mortality. Eur. Geriatr. Med. 2020, 11, 1089–1094.
  6. Bianchetti, A.; Rozzini, R.; Guerini, F.; Boffelli, S.; Ranieri, P.; Minelli, G.; Bianchetti, L.; Trabucchi, M. Clinical Presentation of COVID19 in Dementia Patients. J. Nutr. Health Aging 2020, 24, 560–562.
  7. Iaccarino, G.; Grassi, G.; Borghi, C.; Ferri, C.; Salvetti, M.; Volpe, M. Age and Multimorbidity Predict Death among COVID-19 Patients: Results of the SARS-RAS Study of the Italian Society of Hypertension. Hypertension 2020, 76, 366–372.
  8. Deiana, G.; Azara, A.; Dettori, M.; Delogu, F.; Vargiu, G.; Gessa, I.; Stroscio, F.; Tidore, M.; Steri, G.; Castiglia, P. Deaths in SARS-CoV-2 positive patients in Italy: The influence of underlying health conditions on lethality. Int. J. Environ. Res. Public Health 2020, 17, 4450.
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