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Background and aim: Dengue a worldwide concern for public health has no effective vaccine or drug available for its prevention or treatment. There are billions of people who are at risk of contracting the dengue virus (DENV) infections with only anti-mosquito strategies to combat this disease. Based on the reports, particularly in vitro studies and small animal studies showing anti-viral activity of aqueous extract of Cocculus hirsutus (AQCH), studies were conducted on AQCH tablets as a potential for the treatment of dengue and COVID-19 infections. The current study was part of the research on AQCH tablet formulation and was aimed to evaluate safety and pharmacokinetics in healthy human subjects. Materials and methods: Sixty healthy adult human subjects were divided into 5 groups (cohorts: I to V; n = 12 per cohort) and randomized in the ratio of 3:1 to receive active treatment or placebo in a blinded manner. Five doses 100 mg, 200 mg, 400 mg, 600 mg and 800 mg tablets were administered three times daily at an interval of 8 h for days 01-09 under fasting conditions and a single dose in morning on day 10. Safety assessment was based on monitoring the occurrence, pattern, intensity, and severity of adverse events during study period. Blood samples were collected for measurement of the bio-active marker Sinococuline concentrations by a validated LC-MS/MS method followed by pharmacokinetic evaluation. Results and conclusion: The test formulation was well tolerated in all cohorts. Sinococuline peak plasma concentration (Cmax) and total exposure of plasma concentration (AUC) demonstrated linearity up to 600 mg and saturation kinetics at 800 mg dose. There was no difference observed in elimination half-life for all the cohorts, suggesting absence of saturation in rate of elimination. Dose accumulation was observed and steady state was achieved within 3 days. The information on human pharmacokinetics of AQCH tablets would assist in further dose optimization with defined pharmacokinetic-pharmacodynamic relationship.
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Objective: To demonstrate the benefits of teleneurology visits for a vulnerable epilepsy population served at the epilepsy clinic in Los Angeles County Medical Center servicing the greater Los Angeles metropolitan area Background: We are a large safety-net hospital in Los Angeles county, providing Level 4 epilepsy care to patients who are uninsured/under-insured. Most are drug-resistant and have physical, social, and/or economic factors that limit their ability to receive healthcare, including epilepsy care. One main factor is that none can drive, and many have difficulties arriving to their in-person appointments due to limited transportation means (i.e. walking, public transportation). The current COVID-19 pandemic further limits their access to healthcare with reduced public services. However, the recent expanded access to teleneurology has been a significant change for this population by improving their access to healthcare and follow up. Regular follow up infers improved compliance leading to better quality of care. We readily and aggressively implemented teleneurology services for our patients. Teleneurology appointments (including phone and video) for our patients began March 20, 2020 with all appointments prior to this date being in-person appointments only. Design/Methods: We compared the rates of no-show appointments 12 months before (no teleneurology) and 12 months after (with teleneurology) March 20, 2020 by assessing significance using a z-test. Results: The rate of no-show appointments significantly falls from 33.7% (of 1711 patients) before to 15.3% (of 1684 patients) after the implementation of teleneurology (p<0.05). Conclusions: Teleneurology is a critical and effective clinical tool for improving patient compliance with clinic visits and continuing therapy. Teleneurology ensures justice in distribution of medical care even for an underserved population of patients with epilepsy in Los Angeles County.
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The coronavirus (COVID-19) vaccine has become recently available, and to make vaccination campaigns successful, we should increase the acceptability of the COVID-19 vaccine within the public. Thus, this study has been conducted to provide insights into the factors affecting vaccine acceptance and pricing considerations. A both online and paperbased cross-sectional study was conducted from August 1 to August 30, 2020, among the general population of Pakistan. The health belief model (HBM) was used to assess predictors of the intent to receive the vaccine and the willingness to pay (WTP). Descriptive analysis was done, and a chi-squared test was used to assess the demographic association with HBM items. The majority (73.4%) showed a definite/probable intent to receive the vaccine, and marital status and education were significantly associated with getting the vaccine. WTP for a dose of the COVID-19 vaccine was highest for less than 1,000 Pakistani Rupees (PKR) and lowest for 10,001–20,000 PKR. This research indicates that the acceptability of the COVID-19 vaccine in the Pakistani community is satisfactory but the majority of the population want to spend less money to get immunized. © 2022. Ali Hassan Gillani et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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Background The second wave of the COVID-19 pandemic is anticipated to be worse than the initial one and will strain the healthcare systems even more during the winter months. Our aim was to develop a machine learning-based model to predict mortality using the deep learning Neo-V framework. We hypothesized this novel machine learning approach could be applied to COVID-19 patients to predict mortality successfully with high accuracy. Methods The current Deep-Neo-V model is built on our previously statistically rigorous machine learning framework [Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework] that evaluated statistically significant risk factors, generated new combined variables, and then supply these risk factors to the deep neural network to predict mortality in RT-PCR positive COVID-19 patients in the inpatient setting. We analyzed adult patients (≥18 years) admitted to the Aga Khan University Hospital, Pakistan with a working diagnosis of COVID-19 infection (n=1228). We excluded patients that were negative on COVID19 on RT-PCR, had incomplete or missing health records. The first phase selection of the risk factors was done using Cox-regression univariate and multivariate analyses. In the second phase, we generated new variables and tested those statistically significant for mortality and in the third and final phase, we applied deep neural networks and other traditional machine learning models like Decision Tree Model, k-nearest neighbor models, and others. Results A total of 1228 cases were diagnosed as COVID-19 infection, we excluded 14 patients after the exclusion criteria, and (n=)1214 patients were analyzed. We observed that several clinical and laboratory-based variables were statistically significant for both univariate and multivariate analyses while others were not. With most significant being septic shock (hazard ratio [HR], 4.30;95% confidence interval [CI], 2.91-6.37), supportive treatment (HR, 3.51;95% CI, 2.01-6.14), abnormal international normalized ratio (INR) (HR, 3.24;95% CI, 2.28-4.63), admission to the intensive care unit (ICU) (HR, 3.24;95% CI, 2.22-4.74), treatment with invasive ventilation (HR, 3.21;95% CI, 2.15-4.79) and laboratory lymphocytic derangement (HR, 2.79;95% CI, 1.6-4.86). Machine learning results showed our DNN (Neo-V) model outperformed all conventional machine learning models with test set accuracy of 99.53%, sensitivity of 89.87%, and specificity of 95.63%;positive predictive value, 50.00%;negative predictive value, 91.05%;and area under the curve of the receiver-operator curve of 88.5. Conclusion Our novel Deep-Neo-V model outperformed all other machine learning models. The model is easy to implement, user friendly, and with high accuracy.
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The goals of a health-care system are, to provide effective treatment with minimum cost and risk factors, delivery of medical services on time, and be ready to counter any emergency situation. To achieve these goals, a health-care system must be well prepared. The preparation is depending upon data, and the data scientists to analyze that data. Artificial Intelligence (AI) introduced a novelty in health-care, with its different tools which are built upon Machine Learning (ML) and Deep Learning (DL) algorithms. Besides clinical procedures and treatments, these algorithms are used for analyzing data and provides help in decision making. Similarly, to tackle this pandemic Novel Coronavirus disease 2019 (COVID-19) the computer scientists played their role individually and with the help of biological scientists to provide the solutions related to risk management (How much this pandemic can spread and affect the people), diagnosis of this disease with minimum time and cost, making vaccine and, suggesting that which medical treatment should adopt. © 2022 IEEE.
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The present study was carried out to assess the level of depressive symptoms among health-care professionals (HCPs) during the unprecedented time of COVID-19 using Beck Depression Inventory-II (BDI-II) in Karachi, Pakistan. This descriptive, cross-sectional study was conducted using BDI-II containing 21 questionnaires for the determination of depressive symptoms among HCPs including physi-cians, pharmacists, dentists, and other healthcare personnel working in a metropolitan city of Karachi, from February 2020 to May 2020. The survey forms were distributed electronically after obtaining written consent of respondents. One-way ANOVA test was used to evaluate the association between independents variables and BDI-II items. In the current research, out of 500 HCPs, only 328 completed the form. The mean age of the respondents was 36.32 ± 5.23 years. The outcomes revealed that the respondents stated mild levels of depression (mean = 10.69 ± 9.4). Cronbach’s alpha or internal consistency reliability coeffi-cients for depression score was 0.903. Corrected item-total correlations were satisfactory. It was observed that the majority of BDI-II items were found to be significantly associated with the experience and profes-sion of respondents. The HCPs showed mild to moderate depression symptoms during the COVID-19. To avoid the switching of the psychological impact from moderate to severe, strategies should be designed and implemented by the government and health care bodies to overcome psychological distress among HCPs.
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Objective: NA Background: The SARS-CoV2 (COVID-19) pandemic has caused a lot of stress and fear of contracting the illness. There have been few cases describing patients presenting with psychiatric manifestations associated with COVID19 infection. Design/Methods: NA Results: We describe the case of a 26-year-old female, health care professional who was diagnosed with COVID19 infection manifested as self-resolved mild body aches, low grade fever and cough for a few days. Patient was evaluated at which time she did not require treatment;therefore, she was advised to self-isolate, which she did in a hotel for 14 days. Patient returned to work after 2 weeks of self-quarantine and resolution of her symptoms. While at work, patient had difficulty with concentration, inappropriate laughing episodes and previously recurring insomnia. She also displayed extreme anxiety towards work, dealing with COVID-19 positive patients, feeling of inadequacy, feeling guilty of spreading corona virus, crying spells, and panic attacks evidenced by palpitations, shortness of breath and restlessness. Patient was initially treated with Alprazolam, Trazodone and Escitalopram. Subsequently, patient returned with auditory hallucinations where voices were telling her that she was killing patients and that her nurse license was fake. Patient also had persecutory delusions, therefore she was afraid she may kill someone and her license will be revoked. She displayed worsening symptoms of anxiety, rapid speech, and suicidal ideations;so an inpatient admission was warranted to rule out other organic causes of acute psychosis. Workup including infectious and metabolic panel, CTH, EEG and spinal tap to rule out encephalitis or other organic causes of her symptoms were unremarkable except for persisting positive COVID 19 PCR. Consequently, she was diagnosed with acute psychosis and was successfully treated with Quetiapine, Escitalopram and Clonazepam. Conclusions: Acute psychosis is a less known complication of COVID19 infection which should be anticipated and managed appropriately to reduce morbidity.
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Objective: NA Background: The Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2), also known as Corona Virus Disease 2019 (COVID-19), pandemic has started at the end of December 2019. Most of the infected patients have presented initially with respiratory symptoms. There is growing evidence of neurological complications with COVID-19 infection. Guillain-Barre Syndrome (GBS), which can exacerbate respiratory symptoms, is one of the neurological complications of COVID-19 infection. We describe here a case of GBS associated with COVID-19 infection. Design/Methods: We describe a case of a 48-year-old female who presented to our hospital with gradually worsening progressive symmetric lower extremities weakness along with numbness and burning pain in the distal lower extremities, 3 weeks after being diagnosed with COVID-19 in another facility. Neurological examination at presentation was significant for bilateral facial muscles weakness, symmetrical and proximal more than distal lower extremities weakness, and loss of deep tendon reflexes in the lower extremities bilaterally. Clinical picture was suspicious for GBS, possibly secondary to COVID-19 infection. Lumbar puncture showed albuminocytologic dissociation and negative PCR for common viral and bacterial pathogens. She was treated with Intravenous Immunoglobulin (IVIG) with significant improvement in her weakness and other symptoms. EMG/NCS was not done during the acute hospital setting in order to limit exposure to COVID-19. Results: NA Conclusions: Our case report presents a patient with GBS as evidence for increasingly recognized potentially disabling neurological complications from COVID-19 infection. The case highlights the importance of early recognition and management.
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Objective: To identify common neurological complications in COVID-19 patients. Background: The novel Sars-CoV-2 virus was declared a Pandemic by WHO on March 11, 2020. Majority of the data published at this time brings into light the profound respiratory distress and cardiovascular outcomes however much is left to be discovered as far as neurological outcomes are concerned as suggested by anecdotal evidence and limited data. Design/Methods: We conducted a retrospective observational study from January 1, 2020 to April 30, 2020 on data collected from a multicenter health system based in Kansas City Metro area in United States. Composite neurological outcomes from the data included seizures (new onset), delirium (requiring medications), hemorrhagic and ischemic strokes (new onset, diagnosed > 48-72 hours after hospitalization). Results: Of the 346 people who tested positive for COVID-19, 89 (25.7%) were admitted to the hospital with 27 (30%) of the admitted patients requiring ICU level of care at some point. Delirium was seen in 19 patients (21%) of the total admitted out of which 14 patients (51%) were in the ICU. We observed a total of 2 cases of stroke, one ischemic and one hemorrhagic (2.2% of admitted patients). Seizures were not observed in this cohort of patients. Conclusions: Contrary to anecdotal data, we did not observe significant number of patients experiencing seizures or strokes in this cohort of patients. COVID-19 patients admitted to the hospital were documented to have significant levels of delirium. It is unclear as to why delirium was highly prevalent, could this be due to underlying ARDS or attributable to the critical condition or can it be a primary neurological outcome of COVID-19 is yet to be established. It would however benefit clinicians to closely monitor for worsening mentation or neurologic examination in COVID-19 patients.
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BACKGROUND: Although COVID-19 is an acute disease that usually resolves rapidly in most cases, the disease can be fatal and has a mortality rate of about 1% to 56%. Alveolar injury and respiratory failure are the main causes of death in patients with COVID 19. In addition, the effect of the disease on other organs is not fully understood. Renal system affection has been reported in patients with COVID 19 and is associated with a higher rate of diverse outcomes, including mortality. Therefore, in the present work, we reported the clinical characteristics and laboratory data of hospitalized patients with COVID-19 and analyzed the manifestations that indicated renal system involvement and their impact on clinical outcomes. MATERIALS AND METHODS: This was an observational retrospective study conducted at King Fahd Specialist Hospital, Buraydah, Saudi Arabia. All patients with COVID-19 who were admitted to this Hospital from April to December 2020 were included in the study. The patients' findings at presentation were recorded. Demographic data and laboratory results (hematuria, proteinuria, urinary sediment cast and pus cell presence, and kidney function tests) were retrieved from electronic patient records. RESULTS: One hundred and ninety-three patients with confirmed COVID 19 were included in the study. Dipstick examinations of all urine samples showed proteinuria and hematuria in 53.9% and 22.3% of patients, respectively, whereas microscopic examination revealed the presence of pus and brown muddy granular casts in 33.7% and 12.4% of samples, respectively. Acute kidney injury was reported in 23.3% of patients. A multivariable analysis demonstrated that hematuria was associated with acute kidney injury (AKI) (OR, 2.4; 95% CI, 1.2-4.9; P = 0.001), ICU admission (OR, 3.789; 95% CI, 1.913-7.505; P = 0.003), and mortality (OR, 8.084; 95% CI, 3.756-17.397; P = 0.002). Conversely, proteinuria was less significantly associated with the risk of AKI (OR, 1.56; 95% CI, 1.91-7.50; P = 0.003), ICU admission (OR, 2.493; 95% CI, 1.25-4.72; P = 0.001), and mortality (OR, 2.764; 95% CI, 1.368-5.121; P = 0.003). Patients with AKI had a higher probability for mortality than did those without AKI (OR, 14.208; 95% CI, 6.434-31.375; P = 0.003). CONCLUSION: The manifestations of the involvement of the renal system are not uncommon in COVID-19. These manifestations included proteinuria, hematuria, and AKI and were usually associated with a poor prognosis, including high incidences of both ICU admission and mortality.
Subject(s)
Acute Kidney Injury/pathology , COVID-19/complications , Acute Kidney Injury/epidemiology , Acute Kidney Injury/etiology , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/pathology , Female , Humans , Inpatients/statistics & numerical data , Male , Middle Aged , Saudi ArabiaABSTRACT
INTRODUCTION: As the COVID-19 pandemic threatens to strain health care systems worldwide, the presence of gaps in the global critical care capacity has become glaringly obvious, particularly in less developed countries like Pakistan. To identify existing gaps, an assessment of the critical care units across Pakistan was carried out. METHODS: A novel checklist for assessing critical care units was developed based on the Partners in Health 4S Framework. Our checklist evaluated the following key components: Space/Infrastructure, Staffing, Stuff/Equipment, and Systems/Protocols. A series of surveys was conducted using telephonic and on-site interviews at hospitals identified by the Ministry of Health in Pakistan. RESULTS: Critical care facilities at 53 hospitals were surveyed. The majority were from the public sector (62%) and located in metropolitan cities (62%). In terms of infrastructure, the majority of units were adequate, with gaps primarily being identified for negative-pressure rooms (21%), donning-doffing areas (58%) and isolation rooms (64%). In terms of staffing, the majority of hospitals had trainee doctors (94%) and nursing staff (100%) available, with gaps being identified in terms of presence of qualified intensivists (47%) and ancillary staff (ethicists - 17%, dietitians - 45%). Furthermore, an adequate nurse-to-patient ratio of 1:2 or 1:3 was only present in 53% of the hospitals. Equipment was present in the majority of facilities including ventilators (96%, n=9.7±1.1) and BIPAP machines (85%, n=4.5±0.6), with a relative lack of high-flow nasal cannulas (64%, n=3.2±0.9). More than 80% of hospitals had protocols in place for COVID-19 management and staffing, but fewer had them for patient surge (60%), clinician credentialing (58%) and risk mitigation (49%). On chi-square analysis, statistically significant differences (p<0.05) were noted between public and private sectors as well as metropolitan and rural hospitals in terms of availability of negative pressure rooms, ancillary staff like dietitians, and optimal nurse-to-patient ratio. CONCLUSIONS: The results from this study will be pivotal to guide policy makers in devising strategies for improving the quality of critical care units across Pakistan during the COVID-19 pandemic and beyond.
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SESSION TITLE: Chest Infections Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: The novel Sars-CoV-2 virus causes a viral pneumonia (COVID-19) and corticosteroids have been shown to prolong viral shedding and may increase mortality in viral pneumonias(1). Patients with asthma typically require inhaled corticosteroids. It is unknown if asthmatics will therefore have worse outcomes as a result. METHODS: This is a retrospective cohort study of asthmatics compared to the general population diagnosed with COVID-19 pneumonia from a multicenter health system in Kansas City. The primary outcome is admission to a hospital. Secondary outcomes include mechanical ventilatory support and in-hospital all-cause mortality. RESULTS: In this cohort, asthmatics had an average BMI of 32.9 +- 3.2, as compared to 31.2+-0.8 in the general population. Mean age is 49.0 +- 6.0 vs 54+-1.79. As of 5/1/2020 there have been 345 patients positive for COVID 19. 24 have asthma. 7/24 with asthma (29.2%) vs 79/321 non-asthmatics (24.6%, OR 1.26, p=0.6) have required admission to a hospital. 2/24 (8.3%) asthmatics have required mechanical ventilation vs 17/321 (5.2%, OR 1.49, p=0.6) non-asthmatics. 0 asthmatics have died and 7/321 (2.8%, OR 0.8, p=0.9) non-asthmatics have died. CONCLUSIONS: In conclusion, based on this limited retrospective data, asthma does not appear to be a significant risk factor for hospital admission, mechanical ventilation, or death. CLINICAL IMPLICATIONS: Larger, prospective studies are needed to ensure asthmatics are not at increased risk of worse outcomes due to COVID-19. DISCLOSURES: No relevant relationships by Ibrahim Alakhras, source=Web Response No relevant relationships by Hashaam Arshad, source=Web Response No relevant relationships by Taylor Brinton, source=Web Response No relevant relationships by Ain Ejaz, source=Web Response no disclosure on file for Gregory Howell