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Article

Factors Associated with SARS-CoV-2 Positivity in Patients Treated at the Lambayeque Regional Hospital, Peru during a Pandemic Period

by
Mario J. Valladares-Garrido
1,2,
Aldo Alvarez-Risco
3,
Annel B. Rojas-Alvarado
4,
José A. Zuniga-Cáceres
5,6,
Naylamp A. Estrella Izarra
2,7,8,9,
Christopher Ichiro Peralta
10,
David Astudillo
11,
Cristian Díaz-Vélez
12,13,
Virgilio E. Failoc Rojas
14,*,
Shyla Del-Aguila-Arcentales
14,
Neal M. Davies
15,16,
Andrés Garcia Guerra
15,16 and
Jaime A. Yáñez
17,*
1
South American Center for Education and Research in Public Health, Universidad Norbert Wiener, Lima 15046, Peru
2
Oficina de Epidemiología, Hospital Regional Lambayeque, Chiclayo 14012, Peru
3
Carrera de Negocios Internacionales, Facultad de Ciencias Empresariales y Económicas, Universidad de Lima, Lima 15023, Peru
4
Escuela de Medicina, Universidad Privada Antenor Orrego, Piura 13008, Peru
5
Facultad de Medicina, Universidad Nacional Pedro Ruiz Gallo, Lambayeque 14013, Peru
6
Servicio de Traumatología, Hospital Referencial de Ferreñafe, Chiclayo 14311, Peru
7
Escuela de Medicina, Universidad Señor de Sipán, Chiclayo 14000, Peru
8
Faculty of Medicine in Hradec Králové, Charles University, 500 03 Hradec Králové, Czech Republic
9
Escuela de Medicina, Universidad de Chiclayo, Chiclayo 14012, Peru
10
Facultad de Medicina, Universidad Nacional Federico Villareal, Lima 15088, Peru
11
Escuela de Medicina, Universidad Cesar Vallejo, Piura 20001, Peru
12
Facultad de Medicina, Universidad Cesar Vallejo, Trujillo 13001, Peru
13
Hospital Nacional Almanzor Aguinaga Asenjo, EsSalud, Chiclayo 14001, Peru
14
Escuela de Posgrado, Universidad San Ignacio de Loyola, Lima 02002, Peru
15
Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB T6G 2H1, Canada
16
Asociación Médica de Investigación y Servicios en Salud, Lima 15063, Peru
17
Escuela Profesional de Medicina Humana, Universidad Privada San Juan Bautista, Filial de Ica, Ica 11004, Peru
 
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*
Authors to whom correspondence should be addressed.
Sustainability 2022, 14(22), 14785; https://doi.org/10.3390/su142214785
Submission received: 3 September 2022 / Revised: 11 October 2022 / Accepted: 18 October 2022 / Published: 9 November 2022
(This article belongs to the Special Issue Achieving Sustainable Development Goals in COVID-19 Pandemic Times)
Review Reports Versions Notes

Abstract

:
The aim of this study was to provide additional data on mortality from COVID-19 with particular attention to the factors associated with the positivity of patients admitted to the Lambayeque Hospital in Peru. A retrospective cohort analysis was carried out to determine the clinical-epidemiological factors associated with positivity for SARS-CoV-2 in patients treated at the Lambayeque Regional Hospital during the health emergency period in the context of the COVID-19 pandemic. It was observed that, as the demographic age group increased, the percentage of seropositivity increased, with 66.8% of elderly adults testing positive, compared to 37.4% of children (p < 0.001). More seropositive men than women were evident (61.1% vs. 54.1%; p < 0.001). The most frequent symptom of patients with suspected COVID-19 was cough (65.0%). However, the symptoms with the greatest frequency of seropositive patients were ageusia (78.6%) and fever (77.6%); cough was one of the symptoms with the lowest (63.9%) (p-value < 0.001). The comorbidities with the most seropositive patients were obesity (80.7%) and diabetes mellitus (73.6%) (p-value < 0.001), different from the top comorbidity of heart disease (12.7%) in suspected COVID-19 patients. In terms of disease signs, abnormal findings on MRI (98.11%) and dyspnea (28.7%) were the most common in suspected COVID-19 patients, similar to those in seropositive patients, which were dyspnea (81.4%) and abnormal tomography findings (75.3%) (p-value < 0.001).

1. Introduction

At the end of December 2019, the appearance of a novel viral respiratory infection caused by the coronavirus (COVID-19) was reported in China [1,2]. During the initial wave of the disease in Peru, Lambayeque reached COVID-19 seroprevalences of 30% [3]. Peru implemented a strict quarantine [2,4,5,6,7] and social distancing [8,9,10] measure, but still became the country with the highest mortality rate [11], which caused significant detrimental mental effects [12,13,14,15,16,17,18,19,20,21,22,23,24]. The rapid dissemination of COVID-19 in Peru has been reported to have been aggravated by the fragile healthcare system [25,26,27,28], the spread of fake news [29], and conspiracy theories [30]. The detrimental mental health effects [31,32] affected students, causing technostress [33] and multitasking behavior [34]. The general population implemented self-care behaviors [35,36], such as self-medication [26,37,38] and preferential use of medicinal plants [26,38] because of their bioactive compounds content [39,40,41,42,43,44,45,46,47,48,49,50].
COVID-19 infections have varied during the first and second waves, becoming more severe, with particularly high mortality rates [51,52] among the elderly (>65 years) and comorbidities such as cardiovascular disease [53,54,55], chronic lung disease [56,57], kidney disease chronic [58,59,60,61], and other factors, such as diabetes [62,63,64,65,66], hypertension [67,68,69,70,71,72], and obesity [73,74,75,76,77]. As of May 2022, more than 3 million infected people (approximately 10% of the entire population) and 213,000 deaths caused by COVID-19 have been reported in Peru [78].
Previous studies have reported that age, obesity, and febrile response may be possible risk factors for the development of COVID-19 pneumonia [79]. Additionally, fever has been reported to have good sensitivity and specificity (64.0% and 63.9%), cough has high sensitivity but low specificity (79.6% and 15.5%), and dyspnea is the most specific symptom, but demonstrates low sensitivity [80]. In addition, previous studies have paid particular attention to evaluating the clinical characterization and severity of the disease [81]. However, few studies evaluated factors associated with positivity for COVID-19 [80]. Additionally, in Peru, there is no previous evidence of factors associated with the positivity of COVID-19. Therefore, it is necessary to generate local epidemiological evidence. To help guide clinicians and patients, the present study aims to provide further data on mortality from COVID-19, with special attention given to the factors associated with the positivity of patients admitted to the Lambayeque Regional Hospital in Peru.

2. Methodology

2.1. Study Design

A retrospective analytical cohort design study was carried out to determine the clinical-epidemiological factors associated with positivity for SARS-CoV-2 in patients treated at the Lambayeque Regional Hospital during the health emergency period in the context of the epidemic of COVID-19.

2.2. Population and Samples

The population consisted of patients diagnosed with COVID-19 in facilities belonging to the Regional Hospital of Lambayeque from March 2020 to September 2021. The sample consisted of patients with a suspected diagnosis of COVID-19 notified in the Notification System of the Ministry of Health (NotiWeb-MINSA). The sample included confirmed COVID-19 patients, new or continuing MINSA users, and those who had been treated and notified in the NotiWeb system in Lambayeque during the aforementioned period. Patients with incomplete clinical records and those with absent clinical records in the variables of interest were excluded.

2.3. Procedures

The database of the epidemiological notification sheets of patients treated at the Lambayeque Regional Hospital during the health emergency period due to COVID-19 was exported. The principal investigator enters and uses the records notified to the Epidemiological Surveillance System of the National Center for Epidemiology, Disease Prevention and Control (CDC, Peru). The general data of the notification and the patients were recorded, including the date of notification and the classification of the cases; general epidemiological variables: sex, age, and categorized age were recorded; clinical variables: symptoms were recorded, such as cough, sore throat, nasal congestion, shortness of breath, fever, chills, malaise, diarrhea, nausea/vomiting, headache, muscle pain, chest pain, abdominal pain, abnormal CT scan, abnormal X-ray findings, and comorbidities, such as cardiovascular disease, diabetes, obesity, tuberculosis, HIV, kidney disease, chronic lung disease, and cancer. The dependent variable was SARS-CoV-2 positivity, defined as detecting the SARS-CoV-2 virus utilizing molecular and serological tests in patients suspected of having COVID-19.

2.4. Statistical Processing and Analysis

Statistical analysis was performed with STATA v16.0 software (StataCorp LP, College Station, TX, USA). Numerical variables were estimated using means and standard deviations for variables with normal distributions. The Chi-square exact test (categorical variables) was used to compare clinical, epidemiological categorical variables among confirmed SARS-CoV-2 seropositive patients. In the case of numerical variables (age), the Student’s t-test was used after evaluating the assumption of normal distribution and homoscedasticity. The Mann-Whitney U test was also utilized. p values less than 0.05 were considered statistically significant.
Absolute and relative frequencies were estimated for categorical variables. Both simple and multiple regression analyses were performed to determine the factors associated with SARS-CoV-2 infection, estimating the prevalence ratio (PR) and the 95% confidence intervals (95% CI) using generalized linear models. The Poisson distribution family, the logarithmic link function, and the robust variance were employed. Nested models were built using the Log-Likelihood Ratio Test (LRTEST) to conclude which parsimonious model includes the variables that contribute to the final model. Additionally, the variables that do not contribute to the model were adjusted with the parsimonious model.

2.5. Ethics

The Ethics Committee approved the research protocol of the Lambayeque Regional Hospital. Additionally, the study was registered in the repository of health research projects (PRISA) of the National Institute of Health (INS, Lima, Peru) for its respective approval review. The privacy and confidentiality of the patient data used for the research was respected. Only anonymous codes were used as numerical inputs.

3. Results

A total of 8884 patients were evaluated; there was a predominance of adults and older adults (48% and 29%, respectively) with similarities in sex distribution. Of the total, 57.6% (5115 patients) were SARS-CoV-2 positive, 440 patients were confirmed positive based on antigen test, 1023 patients were confirmed positive based on PCR test, and 3652 were confirmed positive based on serological test. The most frequent symptom was cough (65%) and general malaise (48%), as well as fever (35.9%) and odynophagia (30%); while in 1.1% of patients, clinical abnormalities were observed in their tomography results. CVD and diabetes were the most frequent comorbidities. Further details are presented in Table 1.
It was observed that, as the age group increased, the percentage of seropositivity increased, with 66.8% of older adults testing positive, compared to 37.4% of children (p < 0.001). There were more seropositive men than women (61.1% vs. 54.1%; p < 0.001). Of the most frequent symptoms, those who had a cough 63.9%, general malaise (74.6%), as well as fever (77.6%), and sore throat (73%) were seropositive; all of them had a p-value < 0.001. Patients with CVD and diabetes with seropositivity were 71.3% and 73.6%. More clinical findings are presented in Table 2.
In the regression model (Table 3), we observed that an older age and being an adult over 21 were 79% and 56% more likely to be seropositive, respectively (p < 0.001 in both cases). In the parsimony model, this association was preserved.

4. Discussion

4.1. SARS-CoV-2 Positivity

A positivity rate for SARS-CoV-2 of 57.6% was estimated. Moreira-Soto et al. reported a similar positivity rate of 59% during the second wave of COVID-19 in the rural population of the San Martín region-Peru; considering that our study collected data from the first and second waves of viral sickness [82]. Similarly, studies carried out in Peru during the first wave reported a seroprevalence of 13% in Ancash between March and May 2020 [83], and 21% [84] and 29% in Lima and Lambayeque between June 2020 and July 2020, respectively [3]. On the other hand, Álvarez-Antonio, et al. [85] in Iquitos-Peru reported a seroprevalence of 70% between July and August of the same year when the first wave was declining in case numbers. A time-related increase in seroprevalence was observed, possibly due to the natural course of a pandemic and the high prevalence of viral variants with higher transmission and reinfection capacities, such as the alpha and delta variant, during the first and second waves in Lambayeque-Peru [86]. Globally, it has been estimated that approximately 45% of people worldwide had SARS-CoV-2 antibodies by July 2021, and 35% excluding vaccinated individuals [87].
The estimated seroprevalence is likely due to, as in other low-income countries, citizens not having sufficient resources to enable them to apply effective or sustained social distancing measures, including hand washing or the use of suitable masks. Likewise, there is high mobilization between urban and rural centers for commerce, which is related to a high geographic dispersion despite the low population density of these communities [88]; this leads to transmission.

4.2. Factors Associated with SARS-CoV-2 Positivity

Our study found that youth, adults, and older adults had a higher prevalence of SARS-CoV-2 positivity, similar to other hospitals in Loreto and San Martin [82,83]. However, other studies found that COVID-19 seroprevalence among children younger than 12 years in Iquitos was as high as that among adults older than 60 years, but these results were not statistically significant [84]. Additionally, another study found that participants between 21 and 50 presented with the highest frequencies of SARS-CoV-2 positivity [3]. This association could be explained by the high rate of transmissibility among young people [89] as a result of not optimally practicing social distancing and other methods to contain viral transmission.
Regarding symptoms, we found that the prevalence of positive cases increased in patients with fever, general discomfort, cough, sore throat, nasal congestion, and muscle pain, which is similar to that described by Díaz-Vélez [3], where patients reported fever (PR: 1.41), general discomfort (PR: 1.27), cough (PR: 1.44), dysosmia (PR: 1.69), chest pain (PR: 1.49), and back pain (PR: 1.45) were associated with a higher frequency of positivity [3]. This association corresponds with the international literature regarding the alpha and delta variants, and is widely described [90]. However, it contrasts with what was documented by Vera-Ponce et al., where cough, dyspnea, and diarrhea were the symptoms most associated with seropositivity [83]. While cough was the most common symptom reported in patients with suspected COVID-19 symptoms (65.0%), it was the symptom with the second least frequency (63.9%) of patients that were actually seropositive.
Patients who presented abnormal findings on lung auscultation had increased prevalence of SARS-CoV-2 positivity by 32%. Similarly, Wang, et al. [91] reported a sensitivity of 85% and specificity of 13% for the presence of fine and coarse lung crackles, and a sensitivity of 89% and specificity of 15% for patients with signs of pulmonary consolidation [92]. However, this differs from what was documented by Shi et al. and Guan et al., where most patients positive for SARS-CoV-2 had abnormal auscultation in their examination (34.8% vs. 17.5%). Only 37% were false negatives. This association could be explained by the pathophysiology of COVID-19, which produces a release of mucus in the pulmonary alveoli, producing audible sounds on auscultation when air is inspired [91]. Similarly, dyspnea was the sign with the highest prevalence of seropositive patients (81.4%) (p-Value < 0.001).
Diabetic disease increases the prevalence of SARS-CoV-2 positivity by 6%, as was reported by Alpesh Goyal et al. The seropositivity to SARS-CoV-2, evaluated before the administration of developed COVID-19 vaccines, was significantly higher in the controls between participants with DM1 (55.7% vs. 44.9%, p = 0.028) and DM2 (56.9% vs. 44.9%, p = 0.013). It was reported that this susceptibility rate does not differ between types of diabetes [93]. However, it contrasts with what was documented by Díaz-Vélez [3] and Moreira-Soto et al. [82] in populations of Lambayeque and San Martin, respectively, where no statistically significant association was observed. This association could be explained by the increased expression of angiotensin-converting enzyme 2, increased viral replication in a hyperglycemic environment, and the consequent dysregulation of the immune system and the augmented inflammatory response that occurs in patients with diabetes [94].
The prevalence of positive cases increased by 7% in obese patients; this was the comorbidity group with the most notable frequency of seropositive patients (80.7%). This is similar to that reported by Alpesh Goyal et al., where patients with preexisting overweight/obesity were 2.6 times (OR, 2.63 [95% CI, 1.54–4.47]; p < 0.001) more likely to be positive for SARS-CoV-2 (21). Similarly, obesity has been identified to be associated with an increased risk of severe COVID-19 disease (OR, 2.09 [95% CI, 1.67–2.62]) and mortality (OR, 1.49 [95% CI, %, 1.20–1.85]) [95]. This association could be explained by the chronic inflammation present in obese patients, coupled with respiratory compromise and impaired pulmonary perfusion due to excess body fat, and the high prevalence and presence of other comorbidities such as diabetes, hypertension, and cardiovascular disease that are associated with immune dysregulation [96].

Implications of Findings for Public Health-Epidemiology

Understanding the factors associated with a higher seroprevalence of SARS-CoV-2 is crucial to implementing effective epidemiological strategies for contact tracing, early detection, and isolation of cases. It is essential to develop genomic surveillance capabilities to define the distribution and appearance of new viral variants. Through this process, optimal preparedness of human and financial planning for sufficient health resources can be projected and predicted.

4.3. Limitations and Strengths

The strengths of this research include that it is a study carried out in a level 3 hospital of the Ministry of Health (MINSA) of Peru, and the only one in the Lambayeque region intended to care for COVID-19 patients. Additionally, it analyzes a broad and diverse sample of clinical-epidemiological data captured through a functional hospital epidemiological surveillance system from the first and second pandemic waves in this region of northern Peru, spanning age groups from children to older adults. However, all research has limitations. This study was carried out in a single hospital in the region, so the results might not be generalizable. However, the Lambayeque region is in the northern microregion of Peru. Therefore, the data analyzed came from patients residing in multiple regions. Due to the cross-sectional design, causality between the clinical-epidemiological variables associated with seropositivity for SARS-CoV-2 cannot be ascertained. There is potential measurement bias as it was not possible to measure other variables that could influence SARS-CoV-2 seropositivity, such as level of education, socioeconomic status, and housing conditions. Furthermore, in antibody dependent but PCR negative cases, there is the risk that these individuals attended the medical facility with a resolved infection, and their symptoms might be caused by another infection. Another limitation was the lack of genomic monitoring to evaluate the prevalence of SARS-CoV-2 variants, which could affect the management of the symptomatology and the dynamics of the routine of a hospital.

5. Conclusions

A SARS-CoV-2 positivity of 57.6% in patients treated at a hospital in the Lambayeque region in Peru was determined. Additionally, the factors associated with a higher prevalence of positivity were a young age, adult, older adult, and having systemic symptoms (fever, malaise, muscle pain), respiratory symptoms (sore throat, nasal congestion), dyspnea, and obesity and diabetes mellitus as comorbidities.

Author Contributions

Conceptualization, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V. and V.E.F.R.; methodology, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V. and V.E.F.R.; validation, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V. and V.E.F.R.; formal analysis, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V. and V.E.F.R.; investigation, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V. and V.E.F.R.; data curation, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V., N.M.D., V.E.F.R. and J.A.Y.; writing—original draft preparation, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V., V.E.F.R., A.A.-R., S.D.-A.-A., N.M.D., A.G.G. and J.A.Y.; writing—review and editing, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V., V.E.F.R., A.A.-R., S.D.-A.-A., N.M.D., A.G.G. and J.A.Y.; visualization, M.J.V.-G., A.B.R.-A., J.A.Z.-C., N.A.E.I., C.I.P., D.A., C.D.-V., V.E.F.R., A.A.-R., S.D.-A.-A., N.M.D., A.G.G. and J.A.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The Ethics Committee approved the research protocol of the Lambayeque Regional Hospital. Additionally, it was registered in the repository of health research projects (PRISA) of the National Institute of Health (INS, Peru) for its respective review. The privacy and confidentiality of the data used for the research were respected. Only anonymous codes were used.

Informed Consent Statement

All the survey participants were well versed on the study intentions and were required to consent before enrollment.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

M.J.V.-G. was supported by the Fogarty International Center of the National Institutes of Mental Health (NIMH) under Award Number D43TW009343 and the University of California Global Health Institute.

Conflicts of Interest

The authors declare no conflict of interest.

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Table
Table 1. Clinical-epidemiological characteristics of patients with suspected COVID-19 at Hospital Regional Lambayeque, 2020–2021 (n = 8884).
Table 1. Clinical-epidemiological characteristics of patients with suspected COVID-19 at Hospital Regional Lambayeque, 2020–2021 (n = 8884).
Characteristicsn (%)
Age (year) ‡ 45.0 ± 22.51
Age (categorized)
Children942 (10.6)
Teenager120 (1.4)
Young adult942 (10.6)
Adult4295 (48.4)
Elderly2585 (29.1)
Sex
Male4481 (50.4)
Female4403 (49.6)
Symptoms (Yes)
Fever2714 (35.9)
Chill604 (8.1)
General discomfort3748 (48.7)
Cough5030 (65.0)
Throat pain2260 (30.0)
Nasal congestion1116 (14.9)
Diarrhea643 (8.7)
Nausea411 (5.6)
Headache1314 (17.6)
Irritability165 (2.3)
Muscle pain1203 (16.2)
Abdominal pain263 (3.6)
Chest pain619 (8.4)
Joint pain448 (6.1)
Anosmia40 (0.6)
Ageusia28 (0.4)
Earache6 (0.1)
Signs (Yes)
Pharyngeal exudate154 (2.1)
Conjunctival injection/hyperemia59 (0.8)
Convulsion37 (0.5)
Dyspnea/tachypnea2182 (28.7)
Abnormal lung auscultation753 (10.1)
Abnormal findings on radiography238 (3.2)
Abnormal findings on ultrasound11 (0.2)
Abnormal findings on tomography77 (1.1)
Abnormal findings on MRI363 (98.11)
Comorbidity-risk factors
Heart disease953 (12.7)
Mellitus diabetes651 (8.8)
Cerebrovascular disease11 (0.2)
Down’s Syndrome2 (0.0)
Obesity228 (3.1)
Pregnancy348 (4.7)
HIV27 (0.4)
Chronic kidney disease362 (4.9)
Chronic lung disease64 (0.9)
Cancer267 (3.6)
Contact with COVID-19 case
No212 (78.9)
Yes57 (21.1)
Confirmed COVID-19
No3769 (42.4)
Yes5115 (57.6)
‡ Age expressed as mean ± standard deviation.
Table
Table 2. Clinical-epidemiological factors associated with seropositivity of SARS-CoV-2 presented in the Lambayeque Regional Hospital.
Table 2. Clinical-epidemiological factors associated with seropositivity of SARS-CoV-2 presented in the Lambayeque Regional Hospital.
CharacteristicsSeropositivityp-Value
Negative
(n = 379)		Positive
(n = 5115)
n (%)n (%)
Age (years) †40.16 ± 23.3648.55 ± 21.17<0.001
Age (category) <0.001
Children590 (62.6)352 (37.4)
Teenager69 (57.5)51 (42.5)
Young adult456 (48.4)486 (51.6)
Adult1796 (41.8)2499 (58.2)
Elderly858 (33.2)1727 (66.8)
Sex
Female2056 (45.9)2425 (54.1)<0.001
Male1713 (38.9)2690 (61.1)<0.001
Symptoms (Yes)
Fever609 (22.4)2105 (77.6)<0.001
Chills149 (24.7)455 (75.3)<0.001
General discomfort954 (25.5)2794 (74.6)<0.001
Cough1815 (36.1)3215 (63.9)<0.001
Sore throat610 (27.0)1650 (73.0)<0.001
Nasal congestion343 (30.7)773 (69.3)<0.001
Diarrhea208 (32.3)435 (67.7)0.001
Nausea161 (39.2)250 (60.8)0.814
Headache436 (33.2)878 (66.8)<0.001
Irritability73 (44.2)92 (55.8)0.127
Muscle pain344 (28.6)859 (71.4)<0.001
Abdominal pain93 (35.4)170 (64.6)0.305
Chest pain170 (27.5)449 (72.5)<0.001
Joint pain155 (34.6)293 (65.4)0.084
Anosmia12 (30.0)28 (70.0)0.275
Ageusia6 (21.4)22 (78.6)0.065
Earache2 (33.3)4 (66.7)0.799
Signs (Yes)
Pharyngeal exudate56 (36.4)98 (63.6)0.584
Conjunctival injection/hyperemia19 (32.2)40 (67.8)0.325
Convulsions15 (40.5)22 (59.5)0.784
Dyspnea/tachypnea406 (18.6)1776 (81.4)<0.001
Abnormal lung auscultation159 (21.1)594 (78.9)<0.001
Abnormal radiography findings74 (31.1)164 (68.9)0.017
Abnormal ultrasound findings4 (36.4)7 (63.6)0.891
Abnormal tomography findings19 (24.7)58 (75.3)0.013
Comorbidity—Risk factors
Heart disease274 (28.8)679 (71.3)<0.001
Diabetes mellitus172 (26.4)479 (73.6)<0.001
Cerebrovascular disease6 (54.6)5 (45.5)0.270
Down’s Syndrome0 (0.0)2 (100.0)0.265
Obesity44 (19.3)184 (80.7)<0.001
Pregnancy142 (40.8)206 (59.2)0.431
HIV18 (66.7)9 (33.3)0.003
Chronic kidney disease148 (40.9)214 (59.1)0.354
Chronic lung disease29 (45.3)35 (54.7)0.254
Cancer152 (56.9)115 (43.1)<0.001
Contact with COVID-19 case 0.079
No146 (68.5)67 (31.5)
Yes32 (56.1)25 (43.9)
† Age expressed as mean ± standard deviation.
Table
Table 3. Simple and multiple regression results of the clinical-epidemiological factors associated with seropositivity of SARS-CoV-2 presented in the Lambayeque Regional Hospital.
Table 3. Simple and multiple regression results of the clinical-epidemiological factors associated with seropositivity of SARS-CoV-2 presented in the Lambayeque Regional Hospital.
Seropositivity
CharacteristicsSimple Regression Multiple Regression
PR95% CIp-Value * PR95% CIp-Value *
Age (categorized)
ChildrenRef Ref
Teenager1.140.91–1.420.260 1.120.87–1.440.379
Young1.381.25–1.53<0.001 1.401.25–1.58<0.001
Adult1.561.43–1.70<0.001 1.361.26–1.54<0.001
Elderly1.791.64–1.95<0.001 1.381.30–1.60<0.001
Sex
FemaleRef Ref
Male1.131.09–1.17<0.001 0.990.97–1.040.857
Symptoms (Yes)
Fever1.471.42–1.52<0.001 1.201.16–1.24<0.001
Chill1.251.19–1.31<0.001 0.960.91–1.010.122
Discomfort1.521.46–1.58<0.001 1.211.17–1.27<0.001
Cough1.131.09–1.17<0.001 1.020.99–1.070.221
Throat pain1.291.25–1.33<0.001 1.091.04–1.12<0.001
Nasal congestion1.151.11–1.21<0.001 1.071.02–1.120.004
Diarrhea1.111.05–1.17<0.001 0.970.92–1.030.329
Nausea0.990.91–1.070.815
Headache1.111.06–1.16<0.001 0.970.93–1.020.186
Irritability0.910.79–1.040.154
Muscle pain1.201.15–1.25<0.001 1.051.01–1.100.040
Abdominal pain1.050.96–1.150.286
Chest pain1.201.14–1.26<0.001 0.990.94–1.050.909
Articulations pain1.070.99–1.140.070
Anosmia1.140.93–1.390.217
Ageusia1.281.05–1.550.014 0.980.80–1.210.853
Earache1.080.61–1.910.785
Signs (Yes)
Pharyngeal exudate1.040.92–1.170.574
Conjunctival injection1.100.92–1.310.283
Convulsion0.960.74–1.260.790
Dyspnea/tachypnea1.511.47–1.56<0.001 1.321.28–1.37<0.001
Abnormal lung auscultation1.321.27–1.38<0.001 1.040.99–1.090.080
Abnormal findings on radiography1.131.03–1.230.008 1.010.93–1.100.765
Abnormal findings on ultrasound1.030.66–1.620.888
Heart disease1.191.14–1.24<0.001 1.010.96–1.050.755
Mellitus diabetes1.221.16–1.28<0.001 1.060.96–1.050.033
cerebrovascular disease0.740.39–1.410.357
Obesity1.321.24–1.41<0.001 1.071.00–1.150.032
Pregnancy0.970.88–1.060.442
HIV0.540.32–0.920.024 0.550.28–1.070.080
Chronic kidney disease0.960.88–1.050.367
Chronic lung disease0.890.71–1.110.294
Cancer0.700.61–0.80<0.001 1.020.88–1.170.826
Contact with COVID-19 case
NoRef.
Yes1.390.98–1.990.066
* p-Values obtained using generalized linear models, Poisson family, log link function, and robust variance.
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Valladares-Garrido, M.J.; Alvarez-Risco, A.; Rojas-Alvarado, A.B.; Zuniga-Cáceres, J.A.; Estrella Izarra, N.A.; Peralta, C.I.; Astudillo, D.; Díaz-Vélez, C.; Failoc Rojas, V.E.; Del-Aguila-Arcentales, S.; et al. Factors Associated with SARS-CoV-2 Positivity in Patients Treated at the Lambayeque Regional Hospital, Peru during a Pandemic Period. Sustainability 2022, 14, 14785. https://doi.org/10.3390/su142214785

AMA Style

Valladares-Garrido MJ, Alvarez-Risco A, Rojas-Alvarado AB, Zuniga-Cáceres JA, Estrella Izarra NA, Peralta CI, Astudillo D, Díaz-Vélez C, Failoc Rojas VE, Del-Aguila-Arcentales S, et al. Factors Associated with SARS-CoV-2 Positivity in Patients Treated at the Lambayeque Regional Hospital, Peru during a Pandemic Period. Sustainability. 2022; 14(22):14785. https://doi.org/10.3390/su142214785

Chicago/Turabian Style

Valladares-Garrido, Mario J., Aldo Alvarez-Risco, Annel B. Rojas-Alvarado, José A. Zuniga-Cáceres, Naylamp A. Estrella Izarra, Christopher Ichiro Peralta, David Astudillo, Cristian Díaz-Vélez, Virgilio E. Failoc Rojas, Shyla Del-Aguila-Arcentales, and et al. 2022. "Factors Associated with SARS-CoV-2 Positivity in Patients Treated at the Lambayeque Regional Hospital, Peru during a Pandemic Period" Sustainability 14, no. 22: 14785. https://doi.org/10.3390/su142214785

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