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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 27  |  Issue : 4  |  Page : 285-292

Clinical characteristics, predictors of symptomatic coronavirus disease 2019 and duration of hospitalisation in a cohort of 632 Patients in Lagos State, Nigeria


1 Department of Oral and Maxillofacial Surgery, Lagos State University Teaching Hospital, Lagos State, Lagos, Nigeria
2 Department of Community Health and Primary Health Care, Lagos State University Teaching Hospital, Lagos State, Lagos, Nigeria
3 Research Unit, Directorate of Health Planning Research and Statistics Lagos State Ministry of Health, Lagos State, Lagos, Nigeria
4 Infectious Disease Unit, Mainland Hospital, Lagos State, Lagos, Nigeria
5 Lagos State Blood Transfusion Services, Lagos State, Lagos, Nigeria
6 Lagos State Bio-Security Laboratory, Mainland Hospital Yaba, Lagos State, Lagos, Nigeria
7 Department of Medicine, Infectious Disease Unit, Lagos University Teaching Hospital, Lagos State, Lagos, Nigeria
8 Directorate of Research, Institute of Medical Research, Lagos State, Lagos, Nigeria
9 Ministry of Health, Lagos State, Lagos, Nigeria
10 Department of Community and Primary Health, College of Medicine, University of Lagos, Lagos, Nigeria

Date of Submission20-Aug-2020
Date of Decision27-Aug-2020
Date of Acceptance29-Sep-2020
Date of Web Publication04-Nov-2020

Correspondence Address:
Dr. Kikelomo Ololade Wright
Department of Community Health and Primary Health Care, Lagos State University Teaching Hospital/ Lagos State University College of Medicine, Lagos
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/npmj.npmj_272_20

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  Abstract 


Objective: The clinical spectrum of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still evolving. This study describes the clinical characteristics and investigates factors that predict symptomatic presentation and duration of hospitalisation in a cohort of coronavirus disease 2019 (COVID-19) patients managed in Lagos, Nigeria. Methodology: This was a retrospective assessment of patients hospitalised with COVID-19 disease in six dedicated facilities in Lagos, Nigeria, between April 1st and May 31st 2020. Participants were individuals with laboratory-confirmed SARS-CoV-2 infection. The outcome measures were presence of symptoms and duration of hospitalisation. Demographic and comorbidity data were also obtained. Statistical analysis was done using STATA 15.0 software, with P < 0.05 being considered statistically significant. Results: A total of 632 cases were analysed. The median age was 40 years (IQR: 30.5–49); male patients accounted for 60.1%. About 63% of patients were asymptomatic at presentation. Among the symptomatic, the most common symptoms were cough (47.4%) and fever (39.7%). The most common comorbidities were hypertension (16.8%) and diabetes (5.2%). The median duration of hospitalisation was 10 days (IQR: 8–14). Comorbidities increased the odds of presenting with symptoms 1.6-fold (P = 0.025) for one comorbidity and 3.2-fold (P = 0.005) for ≥2 comorbidities. Individuals aged ≥50 years were twice as likely to be hospitalised for more than 14 days compared to individuals aged <50 years (P = 0.016). Conclusion: Most individuals had no symptoms with comorbidities increasing the likelihood of symptoms. Older age was associated with longer duration of hospitalisation. Age and comorbidities should be used for COVID-19 triaging for efficient resource allocation.

Keywords: Clinical profile, coronavirus disease 2019, duration of hospitalisation


How to cite this article:
Erinoso OA, Wright KO, Anya S, Bowale A, Adejumo O, Adesola S, Osikomaiya B, Mutiu B, Saka B, Falana A, Ola-Ayinde D, Akase EI, Owuna H, Abdur-Razzaq H, Lajide D, Ezechi O, Ogboye O, Osibogun A, Abayomi A. Clinical characteristics, predictors of symptomatic coronavirus disease 2019 and duration of hospitalisation in a cohort of 632 Patients in Lagos State, Nigeria. Niger Postgrad Med J 2020;27:285-92

How to cite this URL:
Erinoso OA, Wright KO, Anya S, Bowale A, Adejumo O, Adesola S, Osikomaiya B, Mutiu B, Saka B, Falana A, Ola-Ayinde D, Akase EI, Owuna H, Abdur-Razzaq H, Lajide D, Ezechi O, Ogboye O, Osibogun A, Abayomi A. Clinical characteristics, predictors of symptomatic coronavirus disease 2019 and duration of hospitalisation in a cohort of 632 Patients in Lagos State, Nigeria. Niger Postgrad Med J [serial online] 2020 [cited 2020 Nov 30];27:285-92. Available from: https://www.npmj.org/text.asp?2020/27/4/285/299915




  Introduction Top


According to the data from the Johns Hopkins University, coronavirus disease 2019 (COVID-19) which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly to 188 countries/regions since first identified in Wuhan, China.[1] The index case in Nigeria was identified in February 2020, and the country has since recorded a rise in the number of cases.[2],[3] According to the data from the Nigeria Centre for Disease Control (NCDC), as at August 2nd, there were 43,537 confirmed cases, of which 15,238 (35%) were laboratory-confirmed cases from Lagos State, the epicentre of the pandemic in Nigeria.[2]

The clinical spectrum of SARS-CoV-2 infection is still evolving. Current evidence suggests that carriers of SARS-CoV-2 can present clinically with or without symptoms. Symptomatic patients usually present with one or more of the common symptoms: fever, dry cough, fatigue, shortness of breath, anosmia, myalgia and other less common symptoms such as diarrhoea, nausea and vomiting.[4] On the other hand, asymptomatic cases do not have the cardinal symptoms of COVID-19 disease, but are laboratory positive based on real-time reverse transcriptase-polymerase chain reaction (RT-PCR) or antibody tests.[5] One immediate challenge in case ascertainment is that asymptomatic carriers may be in the virus incubation period and could still develop symptoms. Hence, the term presymptomatic may apply to a significant proportion of cases identified as asymptomatic. The significance of making this distinction is important in breaking the cycle of transmission, as epidemiologic data suggest that COVID-19 can be transmitted by individuals who are asymptomatic or presymptomatic.[6],[7]

Studies from the United States, Italy and China indicate that about a quarter of patients infected with SARS-CoV-2 have underlying comorbidities.[8],[9],[10],[11] Common comorbidities include diabetes, hypertension and other cardiovascular diseases,[8],[9],[10] with some increasing the risk of mortality in infected patients.[12] Older age and male gender have also been identified as risk factors for COVID-19.[4],[13],[14]

There is a dearth of literature describing the spectrum of clinical characteristics of COVID-19 disease in patients from Nigeria. A preliminary study of the first 32 patients managed in Lagos State detailed fever, dry cough and anosmia as the most common symptoms and 16% of cases as asymptomatic.[3] However, the sample size of this study was rather small, hence the current gap in the literature on the broad spectrum of COVID-19 symptomatology in Nigeria. As the COVID-19 pandemic spreads rapidly, many unanswered questions about the epidemiology and clinical characteristics of the disease limit local and global public health response. For example, what factors may predict symptomatic versus asymptomatic presentation? And what factors predict the duration of hospitalisation in COVID-19 patients?

As cases surge, a description of the clinical characteristics, symptomatology and predictors of symptomatic presentation is crucial in Lagos State, to support evidence-based regulatory measures for triaging suspected cases and targeted testing. The importance of these regulations cannot be overemphasised for Lagos and Nigeria, because testing capacity is limited, most of the population reside in crowded communities and are unable to adopt measures such as physical distancing.

Therefore, this study describes the clinical characteristics of a cohort of COVID-19 patients managed at isolation and treatment facilities in Lagos State, Nigeria, between April and May 2020. The study also investigates the factors that predict symptomatic presentation and duration of hospitalisation in this cohort of patients.


  Methodology Top


Study design

A retrospective study of cases from six Lagos State COVID-19 Isolation and treatment facilities seen between 1 April and 31 May 2020. This study forms part of the Lagos State COVID-19 Clinicopathologic Profile Project, which investigates the clinical, laboratory, radiologic and pathologic presentation of COVID-19 patients in Lagos State, Nigeria, during treatment and follow-up for a period of 1 year.

Ethics

Ethical approval was obtained from the Lagos State University Teaching Hospital Health Research Ethics Committee, at the Lagos State University Teaching Hospital, Ikeja, Lagos State; the protocol number assigned by the ethics committee was: LREC/06/10/1345; the date of approval was 21st April 2020.

Study settings

The study was conducted using de-identified data from six COVID-19 isolation centres in Lagos State, Nigeria. Lagos State is located in south-western Nigeria, and at the time of study was the epi-centre of the COVID-19 disease in Nigeria.[3] At the time of the study data collection, the State was operating six isolation and treatment facilities. The overall bed capacity for all six isolation centres was 424 beds during the period of the study data collection. The process for admission entailed identification of laboratory-confirmed SARS-CoV-2 individuals by a remote triage team, followed by transportation of the confirmed individuals to the facility in a COVID-19 evacuation ambulance. On arrival at the isolation facility, consent was obtained, and baseline clinical assessments were conducted after which a bedspace was allocated to individuals who accepted inpatient care. Discharge from the isolation facilities during the period of the study was based on the World Health Organization criteria: (a) three days after resolution of symptoms and (b) two negative RT-PCR SARS-CoV-2 results, at least 24 h apart.

Study data

Case records of hospitalised and outpatient laboratory-confirmed COVID-19 cases seen between 1 April 2020 and 31 May 2020 were obtained. Inclusion criterion for the selected records was a laboratory-confirmed SARS-CoV-2 infection. A laboratory-confirmed case of the SARS-CoV-2 virus was defined as a positive result on high-throughput sequencing or real-time RT-PCR assay of a nasopharyngeal swab, and sputum specimens based on the World Health Organization guidelines.[15]

Data collection tool

Patient demographic information, clinical symptoms and signs, comorbidities and information on the duration of hospitalisation (for admitted inpatient cases only) were recorded. A team of experienced clinicians reviewed the medical records and abstracted data of cases seen during the study period. The abstracted data were collected from paper-based medical records and entered into a Microsoft Excel sheet (2007) under the coordination of the Research Unit of the Lagos State Ministry of Health. Double entry was required for all variables and the data were reconciled by a third party. When missing data were encountered, requests for clarification were sent to the site coordinator at the COVID-19 health facilities who subsequently contacted the attending clinicians or used the source documents. Of a total of 825 discharged cases as at May 31st (NCDC update week 14),[2] cases with missing or incomplete records (n = 139) on demographic and/or clinical information were excluded. Furthermore, cases that ended with mortality (n = 54) were excluded from the study, as complete data on deceased cases were not accessible during data abstraction.

Study variables

The study primary endpoints were the duration of hospitalisation (measured in days) and self-reported presence of symptoms from time of exposure to the laboratory diagnosis of COVID-19 and subsequent isolation at a health facility. Furthermore, the self-reported presence of comorbidities was assessed categorically: no comorbidity, one comorbidity and two or more comorbidities.

Statistical analysis

Statistical analysis was done using STATA 15.0 software (StataCorp LLC Lakeway Drive, College Station, Texas, USA). Demographic information, medical history and COVID-19 symptoms were analysed using descriptive statistics. Pearson's Chi-square test was used to determine an association between the categorical data. Bivariate and multivariate logistic regression models were used to investigate the association between demographic information, comorbidities (self-reported and determined following clinical assessment) and the presence or absence of COVID-19 symptoms. A logistic regression model was used to investigate the association between demographic information, number of comorbidities (none, 1 comorbidity and ≥ 2 comorbidities) and duration of hospitalisation (≤14 days vs. > 14 days). Tests of normality were used to assess continuous variables. P < 0.05 was considered statistically significant, and tests were 2-tailed and the confidence levels were 95%.


  Results Top


Demographic and clinical characteristics of patients

A total of 632 cases were analysed for this study. The mean age of patients was 40.1 years (SD ± 13.9), with 60.1% (n = 385) being male [Table 1]. Less than one-third of the patients (27.2%) presented with associated comorbidities. The most common comorbidities were hypertension (16.8%) and diabetes mellitus (4.1%). Other less common comorbidities were psoriasis and hypothyroidism [Table 1]. About 63% of the patients were asymptomatic on presentation for admission, and among the symptomatic patients, most presented with one or two symptoms [Table 1]. Furthermore, among symptomatic patients, the most common symptoms were cough (47.4%), fever (39.4%) and shortness of breath (18.8%). On the other hand, the least common symptoms were nausea (1.3%) and insomnia (0.8%) [Table 2].
Table 1: Clinical characteristic of cases

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Table 2: Self-reported symptoms of coronavirus disease 2019 patients

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Association between demographic factors and symptomatic coronavirus disease 2019 presentation

[Table 3] demonstrates the association between demographic, comorbidities and a symptomatic COVID-19 presentation. Older age (P = 0.029) and the presence of comorbidities (P = 0.001) were significantly associated with symptomatic COVID-19 presentation. [Table 4] shows using a logistic regression model and factors predictive of symptomatic COVID-19 presentation. Patients with one comorbidity had significantly higher odds of presenting with COVID-19 symptoms (odds ratio [OR]: 1.59; 95% confidence interval [CI]: 1.06–2.39; P = 0.025) compared to patients with no comorbidities. Similarly, patients with two comorbidities also had significantly higher odds of presenting with COVID-19 symptoms compared to patients with no comorbidities (OR: 3.17; 95% CI: 1.42–7.07; P = 0.005). Age and sex were not significantly associated with symptomatic COVID-19 presentation in both bivariate and multivariate logistic regression.
Table 3: Chi-square analysis demonstrating the association between patient demographic factors and symptomatic coronavirus disease 2019 presentation

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Table 4: Bivariate and multivariate regression demonstrating the association between patient demographic factors and symptomatic coronavirus disease 2019 presentation

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Association between clinical characteristics and duration of hospitalisation

A subset analysis was done for 302 patients for whom exact duration of hospitalisation (in days) could be ascertained from their clinical records. Using a multivariate logistic regression, [Table 5] demonstrates that patients aged 50 years and above have 2.08 times higher odds of being hospitalised for longer than 14 days compared to patients aged <50 years (95% CI: 1.14–3.80; P = 0.016). Conversely, using a Poisson regression [Appendix: Table A], for every increase in age by 1 year, the difference in the logs of duration of hospitalisation decreased by 0.005, while holding sex and number of underlying comorbidities were constant (95% CI: 0.002–0.007; P = 0.000). On both models, sex and number of comorbidities were not significant predictors of duration of hospitalisation.
Table 5: Logistic regression model demonstrating the association between clinical characteristics and duration of hospitalisation in a subset of the study population (n=302)

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Participant treatment

The standard of care administered to participants at the time of the study was lopinavir 200 mg/ritonavir 50 mg combination tablet orally twice a day (12 h/24 h) for 14 days, zinc sulphate tablets 100 mg daily, calcium tablets 300 mg daily and Vitamin C tablets 1 g daily [Appendix: Table B].


  Discussion Top


This study aimed to describe the clinical characteristics of a cohort of COVID-19 patients managed at six isolation and treatment facilities in Lagos State, Nigeria. The findings suggest that six out of every ten hospitalised patients presented asymptomatically during the study period, and less than a third of patients presented with comorbidities. Further, the presence of comorbidity was significantly associated with symptomatic presentation; likewise, older age was a significant predictor of increased duration of hospitalisation. The Lagos State Government policy of isolating asymptomatic and mild-to-moderate cases of COVID-19 disease, early in the pandemic, provided a unique opportunity for assessing the clinical characteristics of these patients. The proportion of asymptomatic cases seen in this study was quite large compared to prior studies in China, the United States and Italy.[5],[16],[17] The prevalence of asymptomatic cases has been reported to range between 1% and 56%.[7],[18] Further, a preliminary study on the first 32 cases of SARS-CoV-2 cases in Nigeria identified only 16% of these cases as asymptomatic.[3] The relatively larger proportion of asymptomatic cases in this study compared to the earlier preliminary study in Nigeria could be attributed to the larger study population reviewed and the rigorously implemented policy of testing and isolating contacts of SARS-CoV-2 laboratory-positive individuals in Lagos State.[3] Identifying the actual prevalence of asymptomatic cases usually poses a challenge as presymptomatic cases may be recorded as asymptomatic, and others without contact with laboratory-confirmed individuals may not be tested.[5] However, this is unlikely in this study, because the patients assessed were on admission and monitored for symptoms. The high fraction of asymptomatic patients in this study provides evidence in support of the need for physical distancing measures enacted in the country to prevent community transmission and curb SARS-CoV-2 spread.[4]

The most common COVID-19 symptoms identified in the study were cough, fever and shortness of breath. This finding aligns with reports from multiple countries and reviews of COVID-19 symptomatology based on diverse population groups.[4],[10],[13] In comparison with a local preliminary report, a higher proportion of cases presented with cough rather than fever.[3] This underlines the role of the cardinal symptoms, cough and fever, in the early detection of COVID-19 disease. It also highlights the need for continuing study of the clinical profile of COVID-19 to enhance our understanding of the disease.

Our findings suggest that comorbidities are associated with symptomatic clinical presentation. Patients with one comorbidity had almost two times higher odds of presenting with COVID-19 symptoms, while those with two comorbidities had more than three times higher odds of presenting with COVID-19 symptoms compared to patients without comorbidities. These findings correspond with prior studies which detail the association between comorbidities and increased disease severity and risk of mortality.[8],[9],[10],[11],[14] The most common comorbidities seen in our study were hypertension and diabetes. Multiple studies, notably in China, the United States, United Kingdom and Italy, report similar rates of hypertension and diabetes in COVID-19 patients and generally detail a high rate of COVID-19 risk, hospitalisation and mortality in patients with underlying comorbid conditions.[8],[9],[10],[11],[12],[14],[19] Based on this evidence, individuals with comorbidities, particularly hypertension and diabetes, may benefit from targeted COVID-19 messaging, routine screening and social incentives [free provision of face masks and hand sanitisers] to enhance compliance with preventive measures.

Older age (50 years and above) is associated with increased duration of hospitalisation. This pattern is widely reported globally, as well as the link between older age and increased severity, critical care and mortality.[8],[10],[12],[20],[21],[22] Asides demographic factors such as age, other factors such as therapeutic agents have been reported to influence the duration of hospitalisation or time to recovery. For example, a study has demonstrated that patients receiving remdesivir had a shorter time to recovery,[23] likewise hydroxychloroquine,[24] compared to patients who did not receive these therapeutic agents. However, the participants in this study received lopinavir/ritonavir, with the standard of care based on the NCDC guideline for managing COVID-19,[25] and the design of the current study is unable to ascertain the effect of this treatment.

Strengths and limitations

The present study provides information on a relatively large cohort of COVID-19 cases seen in the early stage of the pandemic in Nigeria and provides evidence to support preventive measures and policies. Another strength of this study is the information on factors that may be related to duration of hospitalisation of COVID-19 cases in Nigeria. However, there are several limitations. This study uses only data of hospitalised patients in Lagos State and may not be generalisable to the entire country. There may be recall bias for symptoms and comorbidities and missed comorbidities in the absence of clinical and laboratory test results. In addition, the study excludes data of mortality cases, and a review of this subset of cases would provide useful information for policy and practice. Furthermore, the incomplete data for duration of hospitalisation in some cases means the subset analysis may not be generalisable to the entire cohort.


  Conclusion and Policy Implications Top


The current study describes the clinical characteristics of a cohort of patients managed at six isolation facilities in Lagos State, Nigeria. The majority of patients seen during the study period presented without symptoms, while the most common presentations in symptomatic patients were cough, fever and shortness of breath. Hypertension and diabetes were the most common comorbidities, and the presence of a comorbidity and older age were significantly associated with symptomatic presentation and increased duration of hospitalisation, respectively. These findings support the current recommendations that encourage physical distancing despite the absence of symptoms and a high index of COVID-19 suspicion in individuals presenting with respiratory symptoms. Continued study of the clinical profile of individuals with COVID-19 is also necessary to further characterise the disease, its evolution and outcomes, particularly on mortality, in our clime.

Data availability statement

The datasets are available from the corresponding author on reasonable request.

Financial support and sponsorship

This work was supported by funding from the Lagos State Government. The funders had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript and decision to submit the manuscript for publication.

Conflicts of interest

There are no conflicts of interest.


  Appendix Top




Logistic model for symptomatology, goodness-of-fit test [Table 4]

number of observations = 632

number of covariate patterns = 20

Pearson chi2 (13) = 4.93

Prob > chi2 = 0.9768

And using the Homer-Lemeshow test;

number of observations = 632

number of groups = 7

Hosmer-Lemeshow chi2 (5) = 0.70

Prob > chi2 = 0.9830 (demonstrates no evidence of lack of fit)

Logistic model for Duration of Hospitalisation, goodness-of-fit test [Table 5]

number of observations = 302

number of covariate patterns = 8

Pearson chi2 (4) = 2.93

Prob > chi2 = 0.5691

And using the Homer-Lemeshow test;

number of observations = 302

number of groups = 6

Hosmer-Lemeshow chi2 (4) = 1.42

Prob > chi2 = 0.8414 (demonstrates no evidence of lack of fit)





 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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