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Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 4  |  Issue : 3  |  Page : 258-266

Clinical outcomes of patients attending a flu clinic at a tertiary health-care facility in india during the COVID-19 pandemic


Department of Community and Family Medicine, All India Institute of Medical Sciences, Patna, Bihar, India

Date of Submission24-Oct-2020
Date of Decision22-Jan-2021
Date of Acceptance14-Feb-2021
Date of Web Publication26-Jul-2021

Correspondence Address:
Bijit Biswas
Department of Community and Family Medicine, All India Institute of Medical Sciences, Phulwarisharif, Patna: 801507, Bihar
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jnsm.jnsm_135_20

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  Abstract 


Purpose: In response to ongoing coronavirus disease (COVID)-19 pandemic, flu clinics were set by most of the hospitals all over India to screen patients for the disease. The study aimed to find out treatment outcome of patients attending a flu clinic at a tertiary health-care facility. Methods: It is an observational study, cross-sectional in design. The study used data routinely collected at the flu clinic of a selected tertiary health-care facility of a selected state of India. Data collected between March 22, 2020, and May 31, 2020 were used for the study. Results: Among 3873 study participants, 364 (9.4%) required admission in COVID-19 isolation ward for testing, while 1536 (39.6%) were referred for further management and the rest being symptomatically managed or home quarantined. In multivariate multinomial logistic regression analysis, females, lockdown phases, symptomatic, severe acute respiratory illness patients, those with contact history with a COVID-19 case, chronic comorbidities, and health worker had significantly higher odds of being admitted in COVID-19 isolation ward compared to others. Those who belonged to the age group of 16–30 years had significantly lower odds of admission. On the other hand, age, sex, lockdown phases, native district COVID-19 risk category, symptom status, chronic comorbidity, contact history, travel history. and profession were significant predictors of referral for further management. Conclusion: Half of the study participants were home quarantined or symptomatically managed. Age, sex, symptom status, contact history, travel history, chronic comorbidity, and profession were significant predictors for their treatment outcome.

Keywords: Comorbidity, coronavirus disease-19 pandemic, health-care personnel, outpatient clinic, treatment outcome


How to cite this article:
Agarwal N, Pandey S, Mishra A, Biswas B, Lohani P. Clinical outcomes of patients attending a flu clinic at a tertiary health-care facility in india during the COVID-19 pandemic. J Nat Sci Med 2021;4:258-66

How to cite this URL:
Agarwal N, Pandey S, Mishra A, Biswas B, Lohani P. Clinical outcomes of patients attending a flu clinic at a tertiary health-care facility in india during the COVID-19 pandemic. J Nat Sci Med [serial online] 2021 [cited 2021 Oct 19];4:258-66. Available from: https://www.jnsmonline.org/text.asp?2021/4/3/258/322319




  Introduction Top


Coronavirus disease (COVID)-19 is an ongoing pandemic, imposing a severe challenge to humankind.[1],[2] The pandemic had affected millions and claimed nearly half a million lives till date.[3] The health-care system is one of the worst affected areas during the ongoing pandemic. The rising trend of COVID-19 cases has forced affected countries to deliver essential health-care services holding the elective ones.[2],[4],[5]

In India, the first case of COVID-19 reported from Kerala was an immigrant medical student from Wuhan, China, on January 30, 2020.[6] From the very initial stage of the pandemic, the government had taken stringent steps (i.e., thermal screening at airports, contact tracing of cases, isolation/quarantine of contacts, etc.) to control it.[7],[8] Advisory on the establishment of flu clinics at every hospital and medical education institutions to screen patients with flu-like symptoms was one of the essential early steps to curb the pandemic in the country.[9] When the number of cases started to rise, the country implemented the most extensive lockdown in human history from March 25, 2020, to April 14, 2020. Later on, the lockdown was further extended in five phases until June 30, 2020.[10] For more effective control over the pandemic and enforcement of lockdown measures, the country stratified its districts in three zones, namely red, orange, and green based on the number of active cases, doubling rate, extent of testing, and the risk of transmission (surveillance) in a particular area on April 15, 2020.[11]

Selected state is the third most populous state of India.[12] The state reported its first COVID-19 case and death on March 22, 2020, at the selected tertiary health-care facility.[13] Till May 31, 2020, the state has reported 3692 COVID-19 cases after conduction of 75,737 tests with overall positivity rate of 4.9%.[14] The institute is a tertiary health-care facility of national importance situated in the capital city of the selected state. As per government directives, the institute had also established a flu clinic to screen persons with flu-like symptoms and who are at higher risk of acquiring COVID-19 infection from March 22, 2020. Till the study period, it had screened about 4000 patients for COVID-19.

In the era of COVID-19, most of the hospitals and medical education institutes in India and all over the world are running separate outpatient departments (OPDs) to screen persons at higher risk of infection and to determine the need for COVID-19 testing.[15],[16] Treatment outcomes decided by these OPDs help to ensure the safety of the health-care workers, patients, and their communities at large from COVID-19.[17] As per the authors' knowledge, there was no prior evidence on background characteristics and treatment outcome of the patients attending this flu OPDs. Thus, the current research was planned to bring about a better understanding on the treatment outcome of the patients attending the flu clinic of the selected tertiary health-care facility and their predictors. The findings of the study will give more insights about patients attending flu OPDs which may further help in the formulation of suitable strategies to curb this ongoing pandemic.


  Methods Top


It was an observational study, cross-sectional in design. The study used data routinely collected using Google® form at the flu clinic of a selected tertiary health-care facility of a selected state of India. Data collected between March 22, 2020, and May 31, 2020, were used for the study. Google Form is a tool by Google Limited Liability Company that allows collecting information from users through a personalized survey or quiz. The information is then collected and automatically synced to a connected dynamic Google® excel sheet. The flu clinic was managed by a resident doctor and a medical intern. Screening of the attending patients was done using the Indian Council of Medical Research (ICMR) strategy for COVID-19 testing, which has been updated from time to time during the pandemic.[18],[19],[20],[21] All patients visiting the flu clinic get themselves registered at the registration counter where he/she receives a unique case registration (CR) number. This was followed by an assessment by an on-duty resident doctor to decide further management for the patient. This includes the assessment of the presenting symptoms with duration, history of travel, contact, quarantine, chronic comorbidities, and whether health-care personnel by profession. In the end, thermal screening by an infrared thermometer, pulse, and oxygen saturation measurement by a pulse oximeter was done. If a person was found to be a COVID-19 suspect based on the testing strategy laid by ICMR, he/she was advised for admission in the COVID-19 isolation ward for testing using the real-time reverse transcription-polymerase chain reaction method. Patients with no symptoms or mild-to-moderate symptoms were admitted in a general COVID-19 isolation ward, while sick patients were admitted in the critical care unit COVID-19 isolation ward. If screened patient found to be a non-COVID-19 suspect with minor complaints were symptomatically managed/home quarantined by the resident doctor at the flu clinic. Non-COVID-19 suspects who required specialist care were referred to various specialist department emergency OPDs of the institute based on their presenting complaints. Notably, non-COVID-19 suspects were not subjected to COVID-19 testing. All the COVID-19 and non-COVID-19 patients were managed using “standard operating procedure (SOP) and handbook for COVID-19 management” by the selected tertiary health-care facility.[22] There were 4034 entries available in the Google dynamic excel sheet linked with the Google Form for data entry of the patients attending the flu clinic. We scanned the data using the CR number of the patients to find out duplicate entries of patients who were likely to have visited the flu clinic multiple times during the study period. We found that 32 patients had visited thrice and 97 patients visited twice during the study period. In these cases, data of their last visit was only considered for analysis. In this way, 3873 data of unique patients were identified and included for the analysis using the complete enumeration method. Out of 3873 data, entries for all the variables were available for 2350 entries. Hence, for multinomial logistic regression analysis, these 2350 data entries were used [Figure 1].
Figure 1: Flow diagram showing selection, management and treatment outcome of the study subjects

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Outcome variable

It was the treatment outcome of the study participants. The three possible treatment outcomes were symptomatic management or home quarantine, referral for further management, and admission in the COVID-19 isolation ward for testing.

Attributable variables

The attributes used in the analysis were age in completed years, sex (male and female), presenting symptoms (asymptomatic, fever, cough, breathing difficulty, sore throat, throat pain, cold, headache, myalgia, fatigue, sputum, rhinorrhea, hemoptysis, nausea, vomiting, loose stool, abdominal pain, unconsciousness, altered sensorium, and chest pain), severe acute respiratory illness (SARI) (yes and no), history of international travel (yes and no), history of domestic travel (yes and no), history of contact with a COVID-19-positive case (yes and no), history of quarantine for COVID-19 (yes and no), suffering from chronic comorbidities (yes and no; hypertension, diabetes, cancer, tuberculosis, cardiovascular disease, chronic obstructive pulmonary disease or asthma, other chronic liver, kidney, lung, thyroid, and hematological disorders causing immunodeficiency), and whether a health-care worker by profession (yes and no). The operational definition used for some variables used in the study was as following:

Severe acute respiratory illness

Individuals with acute respiratory infection with a history of fever or measured temperature ≥38°C and cough, onset within the last ~10 days, and requiring hospitalization.[23]

District category

Native districts of the study participants were categorized to red, orange, and green based on the risk of infection spread and control measures as per government guidelines issued from April 15, 2020, onward.[11],[24],[25],[26]

Lockdown phases

In India, Lockdown Had Four Phases Till May 31, 2020. The Duration Of Different Phases Of Lockdown With Duration Was Phase 1 (From March 25 To April 14: 21 Days), Phase 2 (From April 15 To May 3: 19 Days), Phase 3 (From May 4 To May 17: 14 Days), And Phase 4 (From May 18 To May 31: 17 Days).[10]

Ethical statement

The study was based on routinely collected data at flu clinic of All India Institute of Medical Sciences (AIIMS)-Patna. Therefore, ethical clearance for the study was exempted by the institutional ethical committee (IEC) of AIIMS-Patna. Informed written consent of the study participants could not be taken due to retrospective nature of the study. Although during analysis and drafting of the manuscript their anonymity were assured. The study was conducted abiding by all the principles of Declaration of Helsinki.

Statistical analysis

Data were analyzed using IBM SPSS (Chicago, USA) (version 16). At first, bivariate analysis was performed using the Chi-square test in between attributable variables and outcome variables to find out associates of treatment outcome of the study participants. This was followed by univariate multinomial logistic regression analysis to find out the strength of the association between treatment outcome and their attributes. Finally, statistically associated variables in univariate analysis were entered into the multivariate multinomial logistic regression model using the forced entry method to find out multivariate predictors of treatment outcome of the study participants. The minimum acceptable confidence level was α = 0.95 for all statistics, and the maximum acceptable significance level was P < 0.05.


  Results Top


In total, 3873 patients attended the flu clinic in the designated study period to get themselves screened for COVID-19. The trend of total patients attending the clinic had an increasing pattern which was similar to the trend of referral and admission, while symptomatic treatment/home quarantine had a decreasing trend. Week wise, the total number of patients who attended flu clinic along with their treatment outcome is depicted in [Figure 2].
Figure 2: Line diagram showing week wise trend of the patients attending flu clinic along with their treatment outcome: n = 3873

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[Table 1] depicts presenting symptoms of the study participants as per their age. Study participants of 16–60 years of age group were mostly asymptomatic while attending the flu clinic. Those who were aged ≤15 and >60 years, fever was the most common presenting symptom, followed by breathing difficulty and cough.
Table 1: Distribution of the study participants as per age and presenting symptoms (n=3873*)

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Among the study participants, 1973 (50.9%) were managed symptomatically or home quarantined based on their presenting symptoms, contact and travel history, while 1536 (39.6%) needed further management, therefore referred. Notably, out of total 364 patients admitted in the COVID-19 isolation ward, 20 (5.5%) were eventually tested positive for COVID-19. The mean age of the study participants was 31.8 ± 17.7 years, while 275 (7.1%) of them were elderly (aged >60 years). The majority of the patients were males 2757 (71.2%), while most of them visited the flu clinic during phase 2 of the lockdown (35.0%). Considering the native district COVID-19 risk category, most of the patients belonged to the green districts (45.3%), whereas 17.9% of them belonged to the orange districts. More than one-third of the study participants were asymptomatic (36.2%). Fever (64.0%) was the most common presenting symptom among those who were admitted, followed by cough (47.2%) and breathing difficulty (47.2%). Those who were symptomatically managed/home quarantined, cough (16.5%) was the most common presenting complaint, followed by fever (13.7%) and breathing difficulty (6.2%). Only a few patients (2.4%) had a SARI during attending the clinic with the majority of them (56.2%) were decided to be admitted in the COVID-19 isolation ward. A similar trend was also observed for those who had a history of contact with a confirmed COVID-19 case. One-sixth (16.6%) of the study participants had domestic travel history, while 27 (0.7%) of them had a history of international travel in the preceding 14 days of attending the flu clinic. History of quarantine was present in the case of 52 (2.1%) of the study participants. One-tenth (11.5) of them were suffering from chronic comorbidities with hypertension (31.3%) being the most commonly reported chronic comorbidity, followed by diabetes (27.2%) and cancer (20.8%). In univariate analysis, age, sex, lockdown phase, native district COVID-19 risk category, presenting symptoms, SARI, history of travel, contact, and quarantine, chronic comorbidity, and profession were significantly associated with the treatment outcome of the study participants [Table 2].
Table 2: Distribution of the study participants as per their treatment outcome (n=3873)

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In multivariate multinomial logistic regression analysis, females, lockdown phases, symptomatic, SARI patients, contact history with a confirmed COVID-19 case, those with chronic comorbidities, and health-care personnel by profession had significantly higher odds of being admitted in COVID-19 isolation ward compared to others. Those who belonged to the age group of 16–30 years had a significantly lower odds of admission compared to others. Considering predictors of referral for further management, females, lockdown phases, symptomatic, patients with chronic comorbidities, and no travel history had significantly higher odds of being referred for further management compared to others. Those who belonged to the age group of 16–60, red category district, had contact history with a COVID-19-positive case and health worker by profession had lower odds for referral compared to others. Overall, the model predicted 67.6% variability of the outcome variables with a predictive accuracy rate of 79.6% with a nonsignificant deviance Chi-square test (P = 0.997) indicating model fit [Table 3].
Table 3: Univariate and multivariate multinomial logistic regression analysis showing predictors of treatment outcome among the study subjects (n=2350)

Click here to view



  Discussion Top


This was a record-based observational study, cross-sectional in design which explored the predictors of treatment outcome of the patients attending flu clinic in a tertiary health-care facility.

We found that study participants aged between 16 and 60 years were less likely to be referred for further management and admitted in the isolation ward for COVID-19 testing compared to others although the odds of protection declined with increasing age. This may be because those who belong to extremes of age are at more risk of developing any infection. Although as per previous reports, the elderly were more at risk of developing severe COVID-19 symptoms, whereas children mostly had a milder course of illness.[27],[28],[29] We found that females were more likely to be referred and admitted as compared to males. It may be since in the selected state, females are not that empowered to seek health care for minor ailments, and to some extent, they are negligent to their health too. They usually do not seek health care unless it is required.[30],[31],[32],[33] In addition, lockdown may have impacted their mobility further. Thus, those females who attended the flu clinic may have more severe health issues compared to males; thus, they were more likely to be referred or admitted.

It is being observed that with the progress of the lockdown the odds of referral and admission have increased. It may be because with each phase of lockdown extension relaxation in population movement was given, which had enabled persons with even minor ailments to attend the selected tertiary health-care facility for seeking health care.[34],[35],[36] The other possible reason could be with the progression of the pandemic more and more people became susceptible to infection with the rising number of cases in the state; thus, they had voluntarily subjected themselves for COVID-19 screening. Similarly, those who belonged to the district classified as red based on the risk of COVID-19 infection transmission were less likely to be referred for further management, while those belonged to orange districts were more likely to be admitted. This may be because on 4th May, the government of the selected state transferred then existing 13 green districts as orange to more effectively control the COVID-19 situation in those districts.[25] Hence, literally no green district existed in the selected state after May 4, 2020. The majority of the study participants belonged to different districts of the selected state. That may be the possible reason for such discordant findings in our study.

We found that those who were symptomatic were more likely to be referred or admitted. Although symptomatic patients had higher odds for admission than a referral, this may be because the testing strategy of ICMR right from the very beginning of the pandemic emphasized on testing symptomatic individuals compared to asymptomatic.[18],[19],[20],[21] Similarly, patients with SARI were more likely to be admitted and less likely to be referred. This was as per the testing strategy laid by the ICMR. The selected tertiary health-care facility is a referral institute for most of the hospitals in the region. Patients with complicated diseases in the region are usually referred to the institute to seek specialist health care. Patients from the whole state and some of the neighboring states usually travel hundreds of kilometers to seek health care from the selected tertiary health-care facility. That may be why those who had a history of domestic travel were more likely to be referred than admitted. In the present study, those who had contact history with a positive COVID-19 case were more likely to be admitted than referred or symptomatically managed. It may be so because they are at higher risk of acquiring infection compared to others. ICMR testing strategy also advocates for testing contacts of positive cases irrespective of symptoms in between 5 and 14 days of contact.[18],[19],[20],[21]

In the current study, we found that those who had chronic comorbidities were more likely to be admitted than referred. This may be because they are at higher risk of acquiring COVID-19 infection compared to others.[27],[36] Similarly, health-care workers who were screened at the flu clinic were more likely to be admitted than referred. It may be due to their higher chance of exposure to a positive case due to their profession.[37],[38],[39]

In limitations, most of the data were self-reported by the study participants, so there may be reporting and social desirability-related biases. Second, as it was an institute-based study and a complete enumeration method was followed for inclusion, so chances of Berksonian bias were there, and generalizability of the findings of the study to other tertiary health-care facilities is limited. Finally, different resident doctors were posted at flu clinic during the study period to screen patients. However, SOPs were issued by the institute for COVID-19 management[22] from time to time abiding by the government directives to govern decision-making. The chances of individual variability (due to difference in areas of expertise, experience, clinical judgment, etc.) in the decision of treatment outcomes for the attending patients cannot be ruled out which also may have influenced the study results.


  Conclusion Top


Half of the study participants were home quarantined or symptomatically managed with only one-tenth requiring admission at the COVID-19 isolation ward for testing. Age, sex, symptom status, contact history, travel history, chronic comorbidity, and profession were significant predictors of their treatment outcome. Evaluation of treatment outcome of the attending patients of flu corners may serve as a useful tool to track the progress and formulation of strategies to curb the ongoing COVID-19 pandemic.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

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