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THE IMPACT OF THE COVID-19 PANDEMIC ON HOSPITALIZATIONS
AND ADMISSION PROFILE OF PATIENTS WITH HEART FAILURE
DECOMPENSATION AT THE ALBERT EINSTEIN ISRAELITA HOSPITAL
Elisa Rampazo Prado1
Abstract: Introduction: The coronavirus disease 2019 (COVID-19) pandemic was ofcially declared
by the WHO on March 11, 2020, and the rst Brazilian case was registered on February 26, 2020.
Since then, health systems have been adapted to receive the emerging ow of patients requiring
hospitalization due to moderate to severe manifestations of COVID-19 infection. In this scenario,
patients with chronic comorbidities were advised to stay at home, as a way to minimize the chances
of infection. Thus, the current context determined that patients who presented decompensated Heart
Failure (HF) had their medical-hospital care altered, a fact already evidenced by an English study
from June 2020, which observed a reduction in the number of hospitalizations during the pandemic
due to exacerbation of HF and a worse clinical prole at the time of hospital admission2. In this
sense, a reduction in the number of hospitalizations due to HF decompensation was observed at
Hospital Israelita Albert Einstein (HIAE) from March to August 2020. In this study, we will evaluate
the impact of the COVID-19 pandemic on hospitalizations due to HF decompensation at HIAE,
through data on the clinical prole at the time of admission and the evolution of these patients
during hospitalization, comparing them with the period before the pandemic by the new coronavirus.
Objective: The objectives of the present study aim to quantify the reduction in hospitalizations,
evaluate the clinical prole at the time of admission and evaluate the morbidity and mortality of
these patients, comparing the current pandemic data with previous data. We do not aim to analyze
the relationship between COVID-19 infection and cardiovascular disease. Methods: Retrospective
observational cohort study, carried out in a database of patients who were admitted to HIAE with
1 Graduated in Medicine from the Albert Einstein Israelite College of Health Sciences
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decompensated Heart Failure, between the periods of October 2019 and August 2020. Inclusion
criteria were patients with reduced left ventricular ejection fraction (LVEF 45%) and age 18 years.
Patients were not tested for COVID-19 diagnosis. The sample was characterized based on the mean
and standard deviation, minimum and maximum, median and quartiles, for quantitative variables,
and by absolute and relative frequencies, for qualitative variables. Comparisons between periods
were veried using Chi-square or Fishers exact tests, and Student’s t-tests or Mann-Whitney tests,
according to the distribution characteristic. Data normality was veried using the Shapiro-Wilk test,
bloxplot graphs, histograms and quantile comparison graphs. Results: During the pandemic period,
we saw an increase in the number of hospitalizations due to decompensated heart failure, with these
patients being more severe, with rising creatinine levels during hospitalization and higher mortality
due to HF during the pandemic. However, these patients admitted to the service had a higher ejection
fraction compared to the previous period. The use of vasoconstrictor and inotropic drugs remained the
same. We had more female hospitalizations when compared to the pre-pandemic period. Conclusion:
The number of hospitalizations due to acute HF did not decrease during the pandemic period, which
differs from previous literature. However, we corroborate the idea that there is an increase in severity
and morbidity of hospitalized patients. More female patients were hospitalized, and the hospitalized
patients had a higher LVEF compared to the pre-pandemic period.
Keywords: Heart Failure; COVID-19; Coronavirus; Quarantine; Lockdown; Acute Heart Failure.
INTRODUCTION
March 11, 2020 was marked by the decree made ofcial bythe World Health Organization
(WHO) that classied the outbreak of the coronavirus disease2019 (COVID-19) as a pandemic.
According to the WHO, in 80% of patients COVID-19 manifests itself with mild symptoms and no
complications, in 15% requires hospitalizationand in 5% needs care in the intensive care unit (ICU).
(WHO, 2020)
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The rst Brazilian case of the new coronavirus (SARS-CoV) was registered on February 26,
2020 in the municipality of São Paulo, at the Hospital Israelita Albert Einstein. With the advanceof
the disease, the São Paulo government decreed a mandatory quarantine on March 22, following
recommendations from international bodies, such as the WHO and the federal government. The
measure was an attempt to slow the spread of COVID-19 and reduce contagion rates, as a way to gain
enough timeto reorganize the health systemand build eld hospitals, thus avoiding the overload of
health services and the lack of hospital beds.
Due to the recommendations and changes established in the context of the pandemic, the
medical and surgical treatment of hospitalized and outpatient patients was restricted to urgent cases,
and all emergency and Intensive Care Unit (ICU) departments were prepared to receive patients
infected by the new coronavirus. Telemedicine consultations were also recommended for patients
who did not have suspected disease and who were not symptomatic, as a way to reduce exposure and
the risk of contagion.
This new health contextdetermined that patients with chronic comorbidities, such as Heart
Failure(HF), changed their behavior in the search for hospital services in the minimal presence of
symptoms that indicated decompensation of their pathologies. Since these patients are considered
a risk group for COVID-19, this measure alsoaimed to avoid hospitalization and, consequently,
contamination by the disease. A June 2020 study analyzed the impact of the new coronaviruson
hospitalizations and clinical characteristics of patients with HF decompensationduring the pandemic
in England, comparing the results with hospital data from previous years. The conclusion obtained
was that there was a reduction of approximately 50% inthe number of hospitalizations due to HF
during the lockdown period, and the patients who were admitted to the English health service had a
worse and more severe clinical prole. (BROMAGE et al, 2020)
Heart Failure (HF) is a complex clinical syndromethat occurs when abnormalities in the
function and structure of the heartmake it unable to maintain an adequate heart ordecrease the
lling of its vents, resulting in an imbalancebetween the supply and demand of oxygen body tissues
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(BONOW et al, 2013). The term Chronic Heart Failure refers to permanent and progressive situations
of the established pathology, while Acute HeartFailure refers to the newly established pathologyor
that which presented worsening of the signs and symptoms of an already present HF. The main
symptoms reported in acute HF are dyspnea, lower limb edema, fatigue, orthopnea, and paroxysmal
nocturnal dyspnea, which may be accompanied by signs of jugular vengeal stasis, hepatojugular
reux, andpulmonary congestion (PONIKOWSKI, 2016). The onset and severity of symptoms
experienced and reported by patients withacute heart failure varies according to the underlying cause
ofheart failure.
Within the current pandemic scenariodue to the new coronavirus, it was observed that the
patients most affected in seeking care in hospital services were those who suffered an exacerbation of
the chronic formof the disease. (BROMAGE et al, 2020)
Acute HF is one of the main causes of hospitalizations in Brazil and in the world and, as
it is apotentially fatal condition, there is a need forrapid and effective therapeutic intervention. In
addition, acute HF is related to an increase in mortality and rehospitalizations in the short and long
term (GHEORGHIADE et al, 2013). In Brazil, DATASUS data from 2019 point to approximately
1 millionand 700 thousand hospitalizations due to diseases of the circulatory system, and among
these, 200 thousand hospitalizations were due to decompensation of Heart Failure (MINISTRY OF
HEALTH, 2023).
The rst study on acute HF in Brazil, the BREATHE, demonstrates that the main causes
of chronic HF decompensationare, in descending order of incidence: medication adherence to drug
treatment, infectionand inadequate controlof sodium and water intake. Other causes of decompensation
involve arrhythmias, pulmonary embolism, andacute valvular disease. (ALBUQUERQUE et al, 2015)
Also according to the BREATHE study, the main etiologies of HF in patients who were
hospitalized due to decompensationvary according to the Brazilian region studied: the South, Southeast
and Northeast have a predominance of ischemic causes (33.6%, 32.6%, 31.9%, respectively); and the
North region has 37.2% of patients with hypertensive etiology and 42.4% with chagasic etiology.
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A wide variety of classications for Acute Heart Failure have been proposed, based on
different criteria (PONIKOWSKI et al, 2015). The classicationby Stevenson (1989) divides HF
decompensation according to its clinical-hemodinic prole, basedon physical examination ndings
of pulmonary congestion (wetor dry, if present or absent, respectively) and periphery hypoperfusion
(cold or hot, if present or absent, respectively). The combinationof these proles identies 4 groups,
which include acute HF presentations:
Prole A: patients without signs of hypoperfusionand without pulmonary congestion (hot
and dry);
Prole B: patient with no signs of hypoperfusionand pulmonary congestion(hot and humid);
Prole C: patient with signs of hypoperfusionand no pulmonary congestion (cold and dry);
Prole D: patient with signs of hypoperfusionand pulmonary congestion(cold and wet).
The epidemiology of acute HF presentations in Brazil, according to the BREATHE study,
states that 67.4% of patients present to the hospital with a hot and humid prole; 17.8% with a cold and
humid prole; 9.6% with a hot and dry prole and 5.2% with a cold and dry prole.
The diagnosis of decompensation must be made immediately upon hospital admission, in
order to establish the correct therapy and initiate management in a timely manner, aiming to reduce
in-hospital mortality, hospitalization period and symptoms (MAISEL et al, 2008). It is recommended
that the diagnosis be made based on clinical ndings, personal cardiovascular history and potential
cardiac and non-cardiac precipitants, in addition to performing a complete physical examination
looking for signs of congestion and peripheral hypoperfusion. Additional tests should be requested
upon admission to complement the clinical evaluation of the patient, in order to establish the triggering
factor for the exacerbation and the possible differential diagnoses, thus being able to detect potential
aggravating factors of acute HF and assess the presence of pulmonary and systemic congestion.
These additional tests include chest X-ray, electrocardiogram, laboratory tests and echocardiogram
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(PONIKOWSKI et al, 2016). Subsequent to this evaluation, the ndings should be analyzed according
to the Framingham criteria (appendix 01) or Boston criteria (appendix 02) for the effective diagnosis
of HF.
After the diagnosis of HF decompensation, the patient’s risk of in-hospital mortality at
admission should be determined by the patient’s clinical presentation (COLLINS et al, 2015) and
by risk scores, the best validated being the ADHERE registry risk scale, which takes into account
the variables creatinine, systolic blood pressure and blood urea nitrogen (BUN). According to the
BREATHE study, in Brazil, 12.6% of hospital admissions due to HF decompensation result in death.
(YANCY et al, 2005)
The recommended treatment for acute chronic HF involves an approach that encompasses
the etiological management and its trigger and has a specic conduct for each admission prole,
taking into account systemic blood pressure (SBP) and the clinical-hemodynamic prole based on
Stevensons classication (1989). According to the Brazilian Guideline for Chronic and Acute Heart
Failure, the management of acute HF includes the use of Angiotensin Receptor Blockers (ARBs)
or Angiotensin Converting Enzyme Inhibitors (ACEIs), Beta-blockers (BBs), diuretics, vasodilators,
vasoconstrictors, inotropes and volume replacement. Therefore, it is possible to consider specic
treatment as follows:
SBP > 110 mmHg and hot and dry hemodinic prole: ACE inhibitor or ARB + BB +
suspensionof diuric use;
SBP > 110 mmHg and hot and humid hemodinic prole: vasodilator + diuretic+ BB + ACE/
ARB;
SBP between 85 and 110 mmHg and hot and humid hemodinic prole: vasodilator + diuretic+
BB + ACE/ARB;
SBP between 85 and 110 mmHg and cold and humid hemodemic prole: vasodilator +
inotropic+ diuric+ reductionof BB dose + ACE/ARB;
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SBP < 85 mmHg and cold and humid hemodermal prole: inotropics+ vasoconstrictors +
ethical diure+ suspend use of BB + suspend use of ACE/ARB;
SBP < 85 mmHg and cold and dry hemodermal prole:volume replacement + suspend use of
BB + suspend use of ACE/ARB.
According to the BREATHE study, the main medications used in the intra-hospital
environment in Brazil were: loop diuretics (89.8%), beta blockers (57.1%), vasodilators (6.6%) and
inotropes (13.6%).
Brazilian records indicate an intra-hospital mortality rate between 4 and 12% (YANCY et
al, 2005) for patients with acute decompensated HF. The ADHERE registry indicates that patients
remain hospitalized for an average of 4.4 days. After hospital discharge, patients with HF still have
a risk of being readmitted within 90 days and a 30% chance of death within 1 year. (PONIKOWSKI
et al, 2016) In addition, increases in serum creatinine levels associated with long hospitalization in
patients hospitalized for acute decompensated HF are observed and are related to a worse short- and
long-term prognosis for these patients.
Thus, given the above and the current Brazilian and global scenario, a reduction in hospital
admissions due to decompensation of chronic heart failure was observed at Hospital Israelita Albert
Einstein (HIAE) during the novel coronavirus pandemic (March-August/2020).
Therefore, the objective of this study is to evaluate the incidence of exacerbations of chronic
heart failure during the months of the pandemic and to evaluate the hemodynamic prole at the
time of hospital admission of these patients, comparing the results with data from HIAE prior to the
pandemic. In addition, we will also evaluate in-hospital morbidity and compare the creatinine value
at admission and the highest value reached during hospitalization.
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Study Objectives
To comparatively evaluate the incidenceof acute HF exacerbations during the months
beforeand during the pandemic, in patients not tested for COVID-19;
To analyze thediagnoses at hospital admissionand the use of vasoactive and inotropic
drugsbetween periods;
To compare in-hospital morbidity and mortality;
To evaluate the evolutionof creatinine with values at admissionand signicant changesduring
hospitalization;
Relevance of the Study
The new coronavirus disease and the side effects caused by the lockdown have not yet been
fully explained in the medical literature regarding their harmful effects on population health.
Previous studies have already suggested a decrease in hospitalizations and a decrease in the
care of chronic patients, which may worsen long-term care. Therefore, it is intriguing to assess the
severity of the immediate effects of the pandemic on the care of these patients, especially those with
Acute Heart Failure, the leading cause of death in the world according to the WHO (WHO, 2023).
Therefore, it is a challenge to cover a topic that still has little scientic basis to corroborate or
diverge from our data, so it is important to know the momentary impact on treatment so that future
studies can estimate the long-term effects.
To advance the study, patient data was collected and stored in a spreadsheet and analyzed
anonymously, making the data protected and, consequently, safe for patients.
Given the above, we propose as a hypothesis that during the rst wave of the pandemic
(March 2020 to August 2020) we had a decrease in hospital admissions for HF, but those admitted
were in greater severity, causing greater mortality and morbidity due to Acute Heart Failure.
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METHODS
Patients
This retrospective observational study included 327 patients diagnosed with Acute Heart
Failure upon admission to Hospital Israelita Albert Einstein between October 2019 and August 2020.
None of these patients were tested for COVID-19.
All patients were over 18 years of age and were also included based on documentation of
systolic ventricular dysfunction (LVEF 45% or description of moderate to severe systolic dysfunction
in the medical record).
No patients were tested for COVID-19.
Experimental design
The database was divided into two groups according to the time of admission hospital: group
A patients admitted between October 2019 and February 2020, with a total of 89 patients; and, group
B, patients admitted between March 2020 and August 2020, totaling n = 119.
The objective of the groups was an an comparative analysis contemplating the achievement
of the study objectives Throughyou are from the HIAE database.
We used a database from the Hospital Israelita Albert Einstein, in the city of São Paulo, for
analysis.
In the database, the main quantitative variables that will be analyzed are:
Number of patients admitted to the service;
Creatinine at the time of hospital admission and after 24 hours, 48 hours, 72 hours and at
the time of hospital discharge;
In-hospital mortality.
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In addition, the main qualitative variablesanalysed will be:
Reason for CI decompensation;
Systemic blood pressureclassied as hypotension, normotens,or hypertension;
Need for inotropic medications;
Need for vasopressor medications.
The database was subdivided according to the time of hospital admission of these patients,
with group A being considered patients admitted between October 2019 and February 2020; and
group B being patients admitted between March 2020 and August 2020.
The sample was characterized based on the mean and standard deviation, minimum and
maximum, median and quartiles, for quantitative variables, and by absolute and relative frequencies,
for qualitative variables.
Comparisons between periods were veried using Chi-square or Fisher’s exact tests, and
Student’s t-tests or Mann-Whitney tests, according to the distribution characteristic. Data normality
was veried using the Shapiro-Wilk test, bloxplot graphs, histograms and quantile comparison graphs.
The analyses were performed using the Statistical Package for the Social Sciences SPSS,
v.26.0 (2), considering a signicance level of 5%.
Data Anonymization and Ethics
The data was anonymized by Marina Barros de Melo, a nurse in the Cardiology program at
Hospital Israelita Albert Einstein, holder of ID number 42.947.457-x and CPF number 369.983.938-
90. The professional has no connection with the project and declared responsibility and commitment
to the use of the data, in order to guarantee the privacy of the individuals whose information will be
accessed.
The anonymization process occurred, rst of all, through an ordering of the medical records
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in an Excel spreadsheet according to the medical record number and the date of admission of the
patient to the service. In this way, patients who were readmitted will have subsequent rows in the
organization of the spreadsheet.
After this step, a conditional equation {=IF(D4=D3;C3;C3+1)} will be applied using the cells
in the spreadsheet as a basis. The purpose of the equation was to create an increasing number of
patients per admission, so that each patient would receive a unique admission number that corresponds
to that hospitalization. This process used a high-level Python programming language, at no cost to the
research or the researcher.
Finally, the medical record, travel, name and date of birth elds were excluded from the
spreadsheet. It was also certied that the deleted data was not stored on any device in the “cloud”.
The already anonymized spreadsheet was delivered to the researcher in charge via a Pen
Drive.
Budget
Any expense related to the project was the sole responsibility of the project team and will not
incur costs for SBIBAE.
RESULTS
Incidence Prole of Heart Failure Exacerbations
For the analysis of the desired objectives, 208 patients were included, 89 (42.8%) admitted
before the pandemic and 119 (57.2%) after the beginning of the pandemic (Table 01).
Regarding gender, we found a signicant difference between the periods compared, with a
higher prevalence of male hospitalizations in the pre-pandemic period (74.2% vs. 55.5%; p-value =
0.006) (Table 1A). We did not observe any difference in age between the periods (p-value = 0.311),
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with the mean age being 78 years in the pre-pandemic period and 80 years in the post-pandemic
period (Table 1B).
We did not observe any signicant difference between the periods for the characteristics of
the patients: weight (p-value = 0.310) (Table 1D); height (p-value = 0.672) (Table 1E); and, body mass
index (p-value = 0.286) (Table 1F).
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Diagnoses at admission, use of vasoactive and inotropic drugs
Regarding the diagnosis at admission, we found signicant evidence (p = 0.003) of a higher
prevalence of chronic HF cases in the pre-pandemic period (89.9% vs. 73.9%) and a higher prevalence
of acute HF in the post-pandemic period (16.8% vs. 3.4%) (Table 2B) (Figure 01).
Figure 1: Comparison of diagnoses between periods (p-value = 0.006).
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Some patients had more than one diagnosis: one with acute HF + APE, two with acute HF
+ Cardiogenic Shock, and one with chronic HF + APE, but these were not statistically signicant (p
= 0.310) (Table 2B).
Regarding the etiology, we also did not nd a signicant difference between the periods (p
value = 0.207), with ischemic diseases being the most frequent (pre-pandemic = 78.5% and post-
pandemic = 70.2%). Some patients had more than one etiology: two patients in the post-pandemic
period had Ischemic + Idiopathic etiology; four patients in each period had Valvular + Idiopathic
etiology (Table 2A).
Regarding the use of inotropic drugs during hospitalization, the prevalence was higher in
the pre-pandemic period (43.8% vs. 31.9%), but this difference was not signicant (p value = 0.079)
(Table 2C). Among the patients who used it, in both periods the most used was Dobutamine (31.5%
in the pre-pandemic period and 23.5% in the post-pandemic period) and again we did not observe a
signicant difference regarding the type of drug used between the periods (p-value = 0.793) (Table
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2D). In addition, some patients used more than one inotropic drug during hospitalization: six in
the pre-pandemic period and three in the post-pandemic period used Dobutamine + Levosimendan
(Sindax); one in the pre-pandemic period and two in the post-pandemic period used Dobutamine +
Milrinone (Table 2D).
Regarding the use of vasoconstrictor drugs during hospitalization, the prevalence was similar
in both periods (pre = 13.5% and post = 13.4%), with no signicant difference (p-value = 0.994) (Table
1E). Patients could use more than one drug at the same time, with norepinephrine being the most
commonly used drug in both periods (Table 2F).
In-hospital morbidity and mortality prole
The type of hospital discharge did not show a signicant difference between the periods
(p-value = 0.420), with discharge to home being the most prevalent (pre-pandemic = 83.1% and post-
pandemic = 84.9%) (Table 3A). The incidence of death was higher in the post-pandemic period (7.6%
vs. 4.5%) (Table 3A).
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The length of stay also did not show a signicant difference, with a median of eight days in
the pre-pandemic period and seven days in the post-pandemic period (p-value = 0.578) (Table 3B).
The left ventricular ejection fraction showed a signicant difference between the periods,
being higher in the post-pandemic period (median = 35 vs. median = 30; p-value = 0.023) (Figure 2)
(Table 3H).
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Figure 2: Comparison of LVEF between periods (p-value = 0.023).
We compared other patient characteristics between the periods, but they also did not show
statistical differences. They are: systolic blood pressure (pre-mean = 124 vs. post-mean = 128; p-value
= 0.250) (Table 3C); diastolic blood pressure (pre-mean = 75 vs. post-mean = 74; p-value = 0.870)
(Table 3D); urea on admission (pre-median = 64 vs. post-median = 76; p-value = 0.663) (Table 3E);
creatinine on admission (pre-median = 1.48 vs. post-median = 1.49; p-value = 0.996) (Table 3F).
Changes in creatinine value
We compared creatinine values on admission with the highest value observed during
hospitalization. Although we found no evidence of differences in creatinine values between the
periods, as seen in Tables 3F and 3G, in both periods we observed an increase in creatinine values
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compared to admission values, and this difference was signicant (p-values < 0.001). In the pre-
pandemic period, the median increased from 1.48 mg/dL to 1.57 mg/dL. In the post-pandemic period,
the median increased from 1.49 mg/dL to 1.68 mg/dL. The results are presented in Table 2 and Figure
6.
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Figure 3: Comparison of Creatinine at admission with the highest hospitalization value between the
periods (p-value < 0.001).
DISCUSSION
Exacerbations of Heart Failure
The benets of physical exercise and diet to compensate for HF and health are already well
documented in the literature (ROGERS et al, 2017). However, the change in life dynamics imposed
by quarantine created barriers to the practice of physical activities and the maintenance of a balanced
diet.
In an English study, there were records that 82% of patients showed an increase in sedentary
lifestyle, smoking and intake of ultra-processed foods (ROBINSON et al, 20221) during the lockdown,
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which can cause harm to health even in the short term (PRESSLER et al, 2013). In this study, an
increase in anginal symptoms was reported (CRANSAC-MIET et al, 2021). Such evidence mentioned
above may support our nding of greater hospitalizations for Acute Heart Failure during the period
of analysis.
Furthermore, during the analysis period during the pandemic, we found that patients had
higher left ventricular ejection fraction (LVEF) (30 vs. 35). Although the values are different, they
are still considered as HF with reduced ejection fraction (HFrEF) according to the current literature
(JESUS et al, 2024). According to GOMEZ-SOTO et al (2024), physical exercise is an important
predictor for the prognosis of patients with HFrEF, preventing decompensation and reducing mortality.
As mentioned above, data indicate that during the lockdown there was a decrease in the practice of
physical activities (ROBINSON et al, 2021).
However, there were no active questions in our study about eating habits, physical activity
and weight change during the period. Furthermore, as we started our analysis at an early stage of the
pandemic, when we did not have sufcient resources for abundant testing, we do not know how many
of these cases are correlated with COVID-19 infection. Therefore, further studies are needed to verify
the suggested correlations.
In both groups analyzed, pre- and post-pandemic, the BMI of admitted patients was
overweight, although the comparison between groups did not show statistical relevance.
Our nding of an increase in hospitalizations due to exacerbation of heart failure is
inconsistent with the literature already recorded. This fact can be explained by regional differences in
the penetrance and temporal severity of the pandemic (BOOTH et al, 2020).
In addition, we also recorded data on more hospitalizations of female patients. Previous data
indicate that women with HF are more likely to present psychological changes such as anxiety and
depression when compared to male patients (STEVENSON et al, 1989). Psychological exhaustion is
reported as a determining factor in self-care (CLELAND et al, 2006). In addition, they have lower
adherence to non-pharmacological treatment (YANCY et al, 2024). Quarantine has been described
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as a high-stress and anxiety-inducing factor, which may increase the reduction in self-care. However,
it is dangerous to generalize and assume psychiatric symptoms as the only factors for the worsening
of HF, therefore, more studies are needed to support our nding. Furthermore, the worsening of HF
in females may be correlated with the difference in treatment (CAMPBELL et al, 2024) provided in
outpatient care for symptomatic patients, being a catalyzing factor for decompensation during the
reduction in medical care during the lockdown. Still, more studies are needed to verify these ndings.
Morbidity and mortality
Considering the periods analyzed and the number of hospitalizations due to HF, we afrm
that there was an increase in hospitalizations during the pandemic (89 vs. 119). This data is discordant
with most of the literature already described, therefore more studies are needed for greater scientic
validation.
However, we can consider that the increase in this number may be correlated with patients
who presented with symptoms due to acute HF, acute pulmonary edema or cardiogenic shock. The
total number of patients with these diagnoses at admission during the pandemic results in n=30 (25%)
and, in the pre-pandemic period, we had a record of n=9 (10%), even though such ndings are not
statistically relevant. That said, we can
Even with the greater severity of patients at admission, we noted stability in relative numbers
in the use of vasoactive and inotropic drugs to stabilize these patients, corroborating previous studies
(TIWARI et al, 2022).
In contrast, we observed that post-pandemic patients presented a more severe condition,
associated with higher mortality (4.5% vs. 7.6%). The contrast between the periods can be explained,
for example, by the longer delay that patients may have taken to seek medical care when they presented
symptoms (SHARMA et al, 2020).
Thus, due to the higher mortality, we can note the increase in creatinine values during
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hospitalization. In the pre-pandemic period, the median creatinine values increased from 1.48 mg/dL
to 1.57 mg/dL. During the pandemic period, the median increased from 1.49 mg/dL to 1.60 mg/dL.
Study Limitations
Our study has limitations, since it was limited in time to the rst wave of coronavirus,
which had lower health service occupancy compared to subsequent ones; at this time, we still did not
have abundant testing for COVID-19, making it difcult to correlate the ndings with SARS-CoV-2
infection. Thus, it is difcult to validate such data for other time periods. In addition, we present a low
sample size and it is only representative of a single care service.
However, our study adds to the medical literature. We present data on a greater number
of hospitalizations due to acute HF and among women, which has not yet been presented in the
medical literature. We corroborate data on the amount of vasoconstrictor and inotropic drugs. There is
inconclusive data on morbidity and mortality due to HF during the period. Therefore, further studies
are needed to evaluate and provide more data for science and medical care.
CONCLUSIONS
The number of hospitalizations for acute HF did not decrease during the pandemic period,
which differs from previous literature. However, we corroborate the idea that there is an increase in
severity and morbidity of hospitalized patients.
More female patients were hospitalized, and hospitalized patients had higher LVEF compared
to the pre-pandemic period.
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