<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.126635.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>COVID-19 associated acute neurological manifestations in patients admitted to a tertiary care hospital</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: awaiting peer review]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Pallempati</surname>
                        <given-names>Bhanu Thejaswi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-1932-0082</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>BB</surname>
                        <given-names>Darshan</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Jha</surname>
                        <given-names>Abhavya</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-9084-4068</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Jinugu</surname>
                        <given-names>Vishnu Teja</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Ramapuram</surname>
                        <given-names>John T</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Chowta</surname>
                        <given-names>Nithyananda K</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Holla</surname>
                        <given-names>Ramesh</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-2296-3719</uri>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Dsouza</surname>
                        <given-names>Nikhil Victor</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-6627-1987</uri>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Achappa</surname>
                        <given-names>Basavaprabhu</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>MBBS, Kasturba Medical College, Mangalore, Karnataka, 575001, India</aff>
                <aff id="a2">
                    <label>2</label>Department of Community Medicine, Kasturba Medical College, Mangalore, Karnataka, 575001, India</aff>
                <aff id="a3">
                    <label>3</label>Department of General Medicine, Kasturba Medical College, Mangalore, Karnataka, 575001, India</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:basavaprabhu.a@manipal.edu">basavaprabhu.a@manipal.edu</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>16</day>
                <month>11</month>
                <year>2022</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2022</year>
            </pub-date>
            <volume>11</volume>
            <elocation-id>1332</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>17</day>
                    <month>10</month>
                    <year>2022</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Pallempati BT et al.</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/11-1332/pdf"/>
            <abstract>
                <p>BACKGROUND</p>
                <p>COVID-19 has become a major cause of concern globally for the past couple of years considering the number of lives it has claimed. The spectrum of clinical manifestations related to nervous system ranged from ageusia, anosmia to stroke and encephalopathies. The burden of follow-up and review currently lies in front of us, considering the rise of post COVID manifestations in patients.</p>
                <p>The objective of this research is to determine the neurological complications of the COVID-19 pandemic in India.</p>
                <p>METHODS</p>
                <p>The current study is a record-based retrospective study conducted in a tertiary care hospital. The records of patients admitted to the hospital between January 2021 and July 2021 were reviewed. The information was assessed and analyzed using SPSS 25.0. The results are expressed in the form of mean, standard deviation and proportions.</p>
                <p>RESULTS</p>
                <p>1,000 patients admitted with coronavirus were assessed, and 36 patients with a neurological diagnosis available were found. The mean age was 57.1&#x00b1;1.6 years. Most of the neurological diagnosis included cerebrovascular accidents in 44.4% patients followed by hypokalaemia in 25% of patients. Diabetes mellitus (58.3%) and hypertension (47.2%) were found to be the major contributing co-morbidities. There was a significant association seen between the final diagnosis and the age groups (p=0.039).</p>
                <p>CONCLUSIONS</p>
                <p>This research would aid in adapting to better management guidelines as well as an integrated approach to neurovascular complications of the same in future. This is vital considering the increase in various short-term and long-terms effects being reported in the hospitals.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>India</kwd>
                <kwd>Hospital</kwd>
                <kwd>COVID 19</kwd>
                <kwd>Neurological manifestation</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>1. Introduction</title>
            <p>SARS-CoV-2, announced a global pandemic by the World Health Organization (WHO) in March 2020, has more than 130 million confirmed cases and has recorded over 2.8 million deaths globally. The existing studies indicate that over 33% of hospitalized patients developed acute respiratory distress syndrome (ARDS) with 45% concomitant mortality.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> The crude fatality rate of India lied below 2% during the first wave.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
            </p>
            <p>Primarily a respiratory illness, its manifestations on other organ systems have taken a predominant part in the severity and mortality of the disease. The pervasive occurrence of angiotensin converting enzyme-2 (ACE-2) receptors, the functional receptors for pathogenesis of COVID-19 explains multiorgan involvement. Neurological manifestations of this disease are a cause of concern mainly due to their debilitating nature as well as their surge. One standing theory that explains its neuropathogenesis is that the virus attaches to the ACE-2 receptors. Innate immunity gets activated with the generation of cytokines like IL-10, CCL4, IL-6, neutrophils, 
                <italic toggle="yes">etc.</italic> This leads to endothelial dysfunction and inflammation promoting interference with blood&#x2013;brain barrier, creating an entry point for the cytokines to pass through and further the cytokine cascade, generating a hypercoagulable state that results in neurological manifestations.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>
            </p>
            <p>The neurotropism of SARS-CoV-2 has been attributed to not only peripheral nervous system (PNS) symptoms like ageusia and anosmia but also manifestations of CNS that include stroke, encephalitis, encephalopathies (acute disseminated encephalomyelitis (ADEM), posterior reversible encephalopathy syndrome (PRES), acute necrotizing encephalopathy (ANE), etc.), haemorrhages, meningitis, vasculitis, neuritis, fibrosis, acute demyelination, movement disorders.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> According to available data, between 60%&#x2013;80% of hospitalized patients presented with neurological symptoms.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> 20% of patients admitted to the intensive care unit (ICU) with the infection have shown neurovascular complications.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> Investigations around the world into neurological manifestations revealed that about 46% of them were attributed to ischaemic stroke, 7% to cerebral haemorrhage and almost 62% to other cerebrovascular events.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> Upper motor neuron (UMN) signs and dysexecutive syndrome were also reported in ICU patients.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>When the trends of previous pandemics, epidemics and outbreaks are taken into perspective, a similar array of complications was noticed, where the neurological aspects were often overlooked. Apart from acute complications, a myriad of post infectious Guillain-Barr&#x00e9; syndrome (GBS), myositis, transverse myelitis, motor and peripheral neuropathies, neurocognitive disorders and progressive neurodegenerative disorders like Alzheimer&#x2019;s, Parkinson&#x2019;s and multiple sclerosis were witnessed. With the novel coronavirus following a similar trail as claimed by the initial reports, it is imperative on the part of the medical community to ascertain the pattern.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>The reason that neurological complications take a backseat globally is due to a lack of neuro diagnosticians, diagnostic equipment, treatment options as well a delay in diagnosis and excessive financial burden. Over 30% patients in tertiary care centres in developed nations do not get a diagnosis about neurological manifestations.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> In the context of developing countries like India, where the resources are constrained along with financial burden, it is further augmented.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
            </p>
            <p>There is a paucity in the literature available in the Indian setting regarding the acute neurological manifestations of COVID-19 and their consequences. Our study aims to fill in the gaps regarding neurological complications of the novel coronavirus in the Indian milieu.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>2. Methods</title>
            <p>After the approval from the Institutional Ethics Committee (IEC) of the investigators&#x2019; medical college, the Medical Superintendents of the respective hospitals were approached, and their permission was taken to access records from the hospital records section. Records of all the patients diagnosed with SARS-CoV-2 positive from 01-Jan-21 to 31-July-21 were assessed and relevant information was recorded in the proforma. This proforma included three sections: Section I consisted of the socio-demographic details. Section II included the covid category (A, B or C category), clinical features, co-morbidities, and diagnosis of the patients at the time of admission. Section III included the investigations undergone, management, final diagnosis, and clinical outcome of SARS-CoV-2 patients. All cases of patients with SARS-CoV-2 positive without prior neurological conditions were included and cases of patients with prior neurological conditions were excluded. Collected data were entered into MS Excel. IBM SPSS for Windows version 25.0, Armonk, New York. 25.0 was used for statistical analysis. Descriptive statistics like mean, proportions and standard deviation were used for expressing the results. The association among the baseline characteristic, clinical signs and symptoms and outcomes was analyzed by the Chi-squared test. P value &lt;0.05 was considered statistically significant.</p>
        </sec>
        <sec id="sec3" sec-type="results">
            <title>3. Results</title>
            <p>A total of 1000 medical records of COVID-19 patients were accessed and analyzed. 36 of them (0.036%) had neurological complications of COVID-19, stemming from reasons other than previously diagnosed neurological conditions. The mean age of these patients was 57.1&#x00b1;1.6 years that had a range of 1 to 77 years (IQR: 50&#x2013;59 years). 
                <xref ref-type="table" rid="T1">Table 1</xref> represents the baseline characteristics, including the pre-existing or newly diagnosed comorbidities and the category of COVID. Most participants were diabetic (N=21, 58.3%), while 22.2% of them were free of co-morbidities (N=8).</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Baseline characteristics (N=36).</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Characteristics</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variable</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">N (%)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Gender</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Male</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">27 (75.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Female</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">09 (25.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="6" valign="middle">Age</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2264;30</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (02.8)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31&#x2013;40</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (11.1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">41&#x2013;50</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">06 (16.7)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">51&#x2013;60</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">08 (22.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">61&#x2013;70</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">08 (22.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&gt;70</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">09 (25.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="middle">Category of COVID</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">A</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">20 (55.6)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">B</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13 (36.1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">C</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (08.3)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="5" valign="middle">Comorbidities
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Diabetes mellitus</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">21 (58.3)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Hypertension</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">17 (47.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Kidney disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (11.1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Ischaemic heart disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (08.3)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Others</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">07 (19.4)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>*</label>
                            <p>Multiple response.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>The chief presenting symptoms of patients are described in 
                <xref ref-type="table" rid="T2">Table 2</xref>. Other than symptoms presented in the table, patients also presented with symptoms like anosmia, ageusia, dyskinesia, akinesia, incontinence, aphasia, dysarthria, anxiety, sinus tenderness, symptoms of focal neuritis and blindness.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Chief presenting neurological symptoms (N=36).</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Neurological symptoms
                                <xref ref-type="table-fn" rid="tfn2">*</xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">N (%)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Dizziness</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10 (27.8)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Altered sensorium</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">09 (25.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Excessive vomiting</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">08 (22.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Headache</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">08 (22.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Fever</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">08 (22.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Seizures</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">07 (19.4)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Myalgia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">05 (13.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Weakness</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">05 (13.9)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <fn-group content-type="footnotes">
                        <fn id="tfn2">
                            <label>*</label>
                            <p>Multiple responses.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>
                <xref ref-type="table" rid="T3">Table 3</xref> shows that a large percentage of patients manifested with a cerebrovascular accident (N=16, 44.4%) and a few (N=6, 16.7%) were diagnosed with other conditions like mucormycosis, toxoplasmosis, GBS, MISA and PRES. Though the frequency of patients treated symptomatically and discharged was high (N=27, 75%), a small number of patients (N=2, 5.6%) chose to be discharged against medical advice.</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>Final neurological diagnosis and outcome (N=36).</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Final neurological diagnosis</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">N (%)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cerebrovascular accident (CVA)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16 (44.4)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Hypokalaemia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">09 (25.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Seizure disorder</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">05 (13.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">06 (16.7)</td>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Outcome</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">N (%)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Symptomatic treatment and discharge</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27 (75.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Death</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">07 (19.4)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Discharge against medical advice</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">02 (05.6)</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Most of the patients were treated according to the standard COVID-19 protocol (N= 30, 83.3%), and a minority were given remdesivir injection (N=3, 8.3%) in addition to the standard protocol.</p>
            <p>The association between the baseline characteristics with the final neurological diagnosis and outcome are depicted in 
                <xref ref-type="table" rid="T4">Table 4</xref>. Most of the patients more than 50 years of age were diagnosed to exhibit neurological symptoms due to cerebrovascular accidents (N=16, 60%), while younger patients, less than 50 years of age exhibited neurological complications associated with hypokalaemia (N=5, 45.5%). A meaningful association was observed between age groups and the final neurological diagnosis (N=27, 75%). Majority of the patients with category A COVID were diagnosed to have a cerebrovascular accident (N=9, 45%) but no association was seen between the COVID category and the final neurological diagnosis of the patients. Similarly, though cerebrovascular accident was the final neurological diagnosis for most patients with co-morbidities (N=14, 50%), no association was established. In terms of outcome, most of the patients of category A (N=16, 80%) and category B (N=10, 76.9%) were treated symptomatically and discharged, but 2 out of 3 (N=2, 66.7%) patients succumbed to the disease and died. Patients with (N=21, 75%) and without (N=6, 25%) co-morbidities were also mostly given symptomatic treatment and discharged. However, no association was seen between the outcome and category of COVID or presence/absence of comorbidities.</p>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>Table 4. </label>
                <caption>
                    <title>Association between baseline characters and final neurological diagnosis and outcome (N=36).</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">Category</th>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">Variable</th>
                            <th align="left" colspan="4" rowspan="1" valign="top">Final neurological diagnosis</th>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">Total N (%)</th>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">P value</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Cerebrovascular accident N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Seizure Disorder N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Hypokalaemia N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Others N (%)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Age (years)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;50</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (09.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (18.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">05 (45.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (27.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">11 (100.0)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.039</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2265;50</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">15 (60.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (12.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (16.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (12.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">25 (100.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="middle">COVID category</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">A</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">09 (45.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (20.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (20.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (15.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">20 (100.0)</td>
                            <td align="left" colspan="1" rowspan="3" valign="middle">0.202</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">B</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">07 (53.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (07.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (30.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (07.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13 (100.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">C</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">00 (00.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">00 (00.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (33.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (66.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (100.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Comorbidities</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Present</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">14 (50.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (14.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">06 (21.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (14.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">28 (100.0)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.581</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Absent</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (25.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (12.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (37.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (25.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">08 (100.0)</td>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">Category</th>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">Variable</th>
                            <th align="left" colspan="3" rowspan="1" valign="top">Outcome</th>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">Total N (%)</th>
                            <th align="left" colspan="1" rowspan="2" valign="bottom">P value</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Symptomatic treatment and discharge N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Deaths N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Discharge against medical advice N (%)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Age (years)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;50</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">08 (72.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (27.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">00 (00.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">11 (100.0)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.499</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2265;50</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">19 (76.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">04 (16.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (08.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">25 (100.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="middle">COVID category</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">A</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">16 (80.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (15.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (05.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">20 (100.0)</td>
                            <td align="left" colspan="1" rowspan="3" valign="middle">0.308</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">B</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (76.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (15.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (07.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13 (100.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">C</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">01 (33.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (66.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">00 (00.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">03 (100.0)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Comorbidities</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Present</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">21 (75.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">05 (17.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (07.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">28 (100.0)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.693</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Absent</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">06 (75.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">02 (25.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">00 (00.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">08 (100.0)</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
        </sec>
        <sec id="sec4" sec-type="discussion">
            <title>4. Discussion</title>
            <p>To our knowledge, this is one of the very few studies on acute neurological complications of COVID-19 in India. The ages affected by the disease were varied depending on the countries and a meta-analysis done in the US showed the mean age of 59.9&#x00b1;0.6 years.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> The mean age in our study is similar, being 57.1&#x00b1;1.6 years.</p>
            <p>Complications like Acute Ischemic Stroke came into picture when focused on extrapulmonary complications due to activation of pathways for coagulation and inflammation.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> We observed cerebrovascular accidents in 44% (N=16) of our patients, which included Ischemic Stroke, Haemorrhagic stroke and UMN palsies. This corroborates with other studies done globally.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> There were elevated biomarkers in all these patients, which included D dimer, ferritin, creatine kinase (CK) and lactate dehydrogenase LDH. 25% (N=9) of the patients were diagnosed with hypokalaemia, which is primarily due to elevated aldosterone. The virus activates glial cells, increases pro- inflammatory cytokines in the brain and disrupts osmotic balance through breakdown of blood&#x2014;brain barrier (BBB) leading to an increase in seizures. Along these lines, fever and state of hyperthermia lead to seizure inducing environment in the central nervous system (CNS).
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> We have observed that 13.9% (N=5) of our patients were diagnosed with seizure disorders post the diagnosis of COVID. A small number of rare cases of GBS, PRES, MISA and concurrent mucormycotic infections were found in our study. The most common neurological symptoms associated in a meta-analysis were anosmia, ageusia, headache, dizziness, vomiting and others,
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> and were homogenous with our results (
                <xref ref-type="table" rid="T2">Table 2</xref>).</p>
            <p>The ABC category was used to triage the patients in the tertiary care hospital our study was conducted in. Category A was used in mild, asymptomatic and pre-symptomatic patients. Category B was used in patients with pneumonia and comorbidities that required monitoring. Category C included extremely severe cases.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> Most of the cerebrovascular accident patients were primarily diagnosed as category A COVID (45%, N=9) and most Category A (N=16, 80%) and Category B (N=10, 76.9%) were treated symptomatically and discharged while Category C (N=2) 66.7% patients succumbed to the disease and died. The presence of comorbidities changes the path of prognosis and treatment of any disease. 58.3% (N=21) of our patients had diabetes mellitus as comorbidity and 47.2% (N=17) of them had hypertension. We found a significant association between age groups divided above and below 50, and their final neurological diagnosis that involves CVA, seizure disorders, hypokalaemia and others. (p=0.039, 
                <xref ref-type="table" rid="T4">Table 4</xref>).</p>
            <p>The investigations done included routine blood tests, urine analysis, liver function tests, HbA1C, chest radiographs, Magnetic resonance imaging (MRI) brain, CT brain and others. CT brain in some revealed infarcts in areas like corona radiata, parietal lobe, frontoparietal lobe and haemorrhagic bleed with oedema. MRI in some cases showed gliosis and subacute, lacunar infarcts and small vessel changes.</p>
            <p>The treatment modalities included standard treatment of the hospital with antibiotics, dexamethasone, paracetamol, antihistamines vitamin C and zinc supplements. Comorbidities were treated with their standard medication. Ischemic stroke was treated with anticoagulants like enoxaparin, atorvastatin and citicoline. Potassium chloride oral solution was given to patients with hypokalaemia. Other complications were treated with appropriate symptomatic treatment.</p>
            <p>Our findings in this study corroborate with that seen internationally. However, the lack of diagnosticians and lack of affordability of healthcare among low socioeconomic population is where our concern lies.</p>
        </sec>
        <sec id="sec5" sec-type="conclusions">
            <title>5. Conclusions</title>
            <p>This study was done to help unfold and assess the pattern of acute neurological complications of COVID-19 infection in the Indian population. This would aid in adapting to better management guidelines as well as an integrated approach to neurovascular complications of the same in future. This has become vital considering the increase in various short-term and long-terms effects being reported in the hospitals. The recognition of common complications in Indian population would serve as genesis to mitigate them in the country and further contribute to forming new therapeutic approach especially with the looming threat of long-term post COVID complications.</p>
        </sec>
    </body>
    <back>
        <sec id="sec8" sec-type="data-availability">
            <title>Data availability</title>
            <p>All data underlying the results are available as part of the article and no additional source data are required.</p>
            <sec id="sec9">
                <title>Underlying data</title>
                <p>Figshare: Underlying data for &#x2018;COVID-19 associated acute neurological manifestations in patients admitted to a tertiary care hospital&#x2019;, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.21201640">https://doi.org/10.6084/m9.figshare.21201640</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref16">16</xref>
</sup>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgements</title>
            <p>The authors thank the support provided by Manipal Academy of Higher Education.</p>
        </ack>
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