ABSTRACT
Introduction: Membranous nephropathy is one of the most common causes of nephrotic syndrome. Among the available treatment options, the tried and tested regimen is the modified Ponticelli regimen. Despite adequate therapy, studies have shown that close to one-quarter of patients fail to attain complete remission. However, data is limited regarding patients who are resistant to this regimen. Method(s): This was an ambispective, observational study conducted in Madras Medical College, Chennai, India between April 2021 to August 2022. All patients with biopsy-proven primary membranous nephropathy resistant to modified Ponticelli regimen were included. Complete remission was defined as proteinuria < 0.5g/day combined with a stable eGFR. Partial remission was defined as reduction of proteinuria by 50% to < 3.5g/day but >0.5g/day. Resistance to therapy was defined as the failure to attain at least partial remission, 12 months after completion of modified Ponticelli regimen. Result(s): A total of 13 patients were enrolled in the study. The median age was 41 years (IQR 38-49) with a male preponderance (n=9;69%). Serum MPLA2R antibody was positive for 9 patients. All patients were negative for ANA and serology for hepatitis B, hepatitis C and HIV were negative. The most common clinical presentation was with nephrotic syndrome, seen in nine patients (69.23%). Renal failure was seen at presentation in 4 patients (30.76%), with one patient warranting initiation of hemodialysis. At 12 months, post completion of modified Ponticelli regimen, the median quantum of proteinuria was 8.7 grams per day. Due to trend towards normalisation of serum albumin and immunological remission, 3 patients were managed with optimised RAS inhibition after modified Ponticelli regimen. Currently, they are in partial remission. Four patients were treated with a second course of modified Ponticelli regimen. Of them one patient is in partial remission, while two patients had progressed to end-stage renal disease and are currently on maintenance hemodialysis. One patient who was resistant to the second course, was managed with a trial of calcineurin inhibitors (CNI) therapy followed by 4 doses of Rituximab (500mg each) due to persistent proteinuria. However, he was lost to follow up during the COVID pandemic and presented with end stage renal disease warranting hemodialysis. A trial of CNI therapy was given to 6 patients. All patients had nephrotic-range proteinuria 12 months post CNI therapy initiation. Five patients were then given Rituximab, among whom, two patients attained complete remission, while three patients have attained immunological and clinical remission. One patient was given a second trial of modified Ponticelli regimen following CNI therapy and is currently in complete remission. Two of these patients developed thrombotic complications - one patient diagnosed with coronary artery disease and one patient with renal vein thrombosis. Conclusion(s): Rituximab is a promising option for patients with primary membranous nephropathy who do not respond to modified Ponticelli regimen. No conflict of interestCopyright © 2023
ABSTRACT
Background: SARS-CoV-2 antibody responses after COVID-19 vaccination are attenuated in people living with MS on high efficacy DMTs such as Fingolimod and Ocrelizumab. Uncertainties on how to manage vaccination schedule and DMT administration persist. Furthermore, data on effects of newer related DMTs like Siponimod and Ofatumumab are limited. Objective(s): We aimed to determine the seroprevalance of Spike antibody and the longevity of antibody mediatedimmune protection after COVID-19 vaccination in MS patients. Method(s): Spike IgG antibodies against Wuhan SARS CoV-2 were assessed in sera (n=520) of MS patients collected pre-vaccination (baseline n= 304), 1 month post second dose (n=172), 6 months post second dose (n=23) and 1 month post third dose (n=21). Demographic and clinical information including age, gender, DMT treatment and timing of COVID-19 vaccination were collected from 160 of these MS patients. Result(s): 151/172 sera at 1 month post second dose, 20/23 sera at 6 months post second dose, and 15/21 sera at 1 month post third dose were positive for Spike antibodies. Seropositive patients were treated on Alemtuzumab;n=3, Cladribine;n=32, Dimethyl fumarate;n=8, Fingolimod;n=16, IFN;n =4, Ocrelizumab;n=14, Ofatumumab;n=4, Natalizumab;n=11, Siponimod;n=1 and Teriflunomide;n=1. Out of the 21 patients who did not seroconvert at a month post second dose, treatment information was available in 12 patients. n=9 were treated by Ocrelizumab and n=2 were treated by Cladribine and n=1 was treated by Fingolimod, confirming certain DMTs prevent seroconversion. Out of the 151 patients that did seroconvert, 120 had titers that were comparable to controls (healthy general population) and 31 had reduced titres. Treatment information was available in 21/31 of these patients. Interestingly, 9/21 were on Ocrelizumab, 8/21 were on Fingolimod, 2/21 were on Ofatumumab, 1/21 was on Natalizumab and 1/21 was on Siponimod. This finding confirmed that certain DMTs such as Fingolimod, Ocrelizumab, Ofatumumab and Siponimod cause a reduction in post-vaccination Spike antibody titers in MS patients in comparison to general population. Expectedly, 304/304 sera were negative at baseline. Conclusion(s): Some High efficacy DMTs reduce Spike Ab titers or even prevent seroconversion. To maximize vaccine-mediated immune protection against COVID-19, timing of DMT administration and vaccine schedule may need intricate co-ordination in people living with MS.
ABSTRACT
Background: Current SARS-CoV-2 vaccines rely on protective immunity against early clade SARS-CoV-2 and have resulted in seroconversion in a subset of MS patients receiving immunosuppressive DMTs. However, it is unknown if SARS-CoV-2 spike antibodies afford immunity against emerging variants of concern, such as Delta and Omicron. Objective(s): To determine the binding of spike antibodies to early clade, Delta, and Omicron SARS-CoV-2 in patients with MS receiving different DMTs. Method(s): Spike antibody binding to early clade SARS-CoV-2, Delta and Omicron was assessed by flow cytometry using sera collected from 58 patients one month post second dose and one patient 1 month post third dose. All patients were previously determined to be seropositive against Wuhan (early clade spike). Clinical and demographic information including DMT treatment and vaccination timing was collected. Result(s): 53 patients were seropositive for Wuhan, Delta and Omicron spike antibodies. Wuhan Spike antibody titres were high at one month post second vaccination, whereas Delta and Omicron Spike antibody titres were significantly decreased. We observed a 70% and 93% decrease of in immunoreactivity to Delta and Omicron, respectively. Although ocrelizumab and fingolimod decrease Spike antibody titres after vaccination, they did not affect immunoreactivity to variants, in comparison to other DMTS. Conclusion(s): All 53 patients were able to generate a positive antibody response following vaccination. However, there was an observable decrease in the antibody titres and immunoreactivity to the Delta and Omicron variants, in comparison to Wuhan.
ABSTRACT
Background: COVID-19 vaccination induces protective Spike antibodies. Some responses are attenuated in people with multiple sclerosis (MS) on high efficacy disease-modifying therapies (DMT).Whether antibodies afford immunity against emerging SARS-CoV-2 Variants of Concern (VoC) such as Delta and Omicron is unknown. Aim(s): To assess the longevity and breadth of Spike antibody in MS patients after COVID-19 vaccination. Objective(s): To determine seroconversion and antibody binding toVoC Spike. Method(s): Spike antibodies to Clade A SARS-CoV-2 were assessed in 535 MS sera at baseline (n=292), 1 (n=141) and 6 month (n=67) post-second dose, and 1 month post-third dose (n=35), and 489 health worker controls. When known, COVID- 19 vaccines were BNT162b2 (n= 489 controls, n=108 MS patients) and ChAdOx1-S (n=37).Spike antibody binding to VoC Delta and Omicron BA1 was assessed in 68 sera 1 month post-second dose. Demographic and DMT information was available in 269 patients. Result(s): 123/141 sera at 1 month post-second dose, 66/67 at 6 months post-second dose, and 26/35 at 1 month post-third dose were positive for Spike antibodies.Patients who did not seroconvert at 1 and 6 month post-second and 1 month post-third dose (n=28) were treated with ocrelizumab (n=22), cladribine (n=1), fingolimod (n=4), and siponimod (n=1). At 1 month post-second dose, the median and IQR Spike antibody levels were 67,224+/- 101,251 in the seroconverted MS group compared to 145,510+/- 99,669 in controls (n=489). When patient sera were assessed for binding to Clade A Spike, and VoC Delta and Omicron BA1 Spikes, most sera were able to bind the three different Spike antigens (n=61). However, Spike antibody immunoreactivity was decreased by 70% against Delta Spike and 90% for Omicron BA1 Spike compared to the original clade A Spike.As observed for Clade A Spike antibody, DMTs, such as ocrelizumab, fingolimod, and ofatumumab, decreased the antibody binding to Delta and Omicron Spike. Still, the pattern of antibody recognition was similar between the three Spikes and all DMTs analysed, i.e. alemtuzumab, natalizumab, teriflunomide, and interferons. Our data suggest that, irrespectively of DMTs, antibodies generated after vaccination did not bind Spike from recent VoCs to the same extent as the original Spike used in COVID-19 vaccines. Conclusion(s): Some DMTs reduce Spike antibody titres or prevent seroconversion. The sequence of Spike used in the first generation of vaccines may need to be updated for emerging VoC.
ABSTRACT
Fungal lung co-infections associated with COVID-19 may occur in severely ill patients or those with underlying co-morbidities, and immunosuppression. The most common invasive fungal infections are caused by aspergillosis, mucormycosis, pneumocystis, cryptococcus, and candida. Radiologists integrate the clinical disease features with the CT pattern-based approach and play a crucial role in identifying these co-infections in COVID-19 to assist clinicians to make a confident diagnosis, initiate treatment and prevent complications.
ABSTRACT
Background: Severe acute respiratory syndrome (SARS-CoV-2), a zoonotic virus, is the pathogenic causal agent for the ongoing pandemic. Despite the lethality of the disease, there are no therapeutic agents available to combat the disease outbreak, and the vaccines currently accessible are insufficient to control the widespread, fast-mutating virus infection. Objective(s): This research study focuses on determining potential epitopes by examining the entire proteome of the SARS-CoV-2 virus using an in-silico approach. Method(s): To develop a vaccine for the deadly virus, researchers screened the whole proteome of the SARS-CoV-2 virus for potential epitopes in order to find a powerful peptide candidate that is both unique and fulfils the vaccine's objective. It is mandatory to identify the suitable B-cell and T-cell epitopes of the observed SARS-CoV-2 surface glycoprotein (QKN61229.1). These epitopes were subjected to various tests, including antigenicity, allergenicity, and other physicochemical proper-ties. The T-cell epitopes that met the criteria were subjected to population coverage analysis. It helped in better understanding epitope responses to the target population, computing peptide con-servancy, and clustering epitopes based on sequence match, MHC binding, and T-cell restriction sites. Lastly, the interactions between the T-cell receptor (TCR) and a peptide-MHC were studied to thoroughly understand MHC restriction to design a peptide-vaccine. Result(s): The findings revealed that four B-cell epitopes, two MHC-I epitopes, and four MHC-II epitopes qualified for all of the tests and so have antigen affinity. Conclusion(s): Based on the results obtained from this study, the estimated peptides are promising candidates for peptide-vaccine design and development. Copyright © 2022 Bentham Science Publishers.
ABSTRACT
Fungal lung co-infections associated with COVID-19 may occur in severely ill patients or those with underlying co-morbidities, and immunosuppression. The most common invasive fungal infections are caused by aspergillosis, mucormycosis, pneumocystis, cryptococcus, and candida. Radiologists integrate the clinical disease features with the CT pattern-based approach and play a crucial role in identifying these co-infections in COVID-19 to assist clinicians to make a confident diagnosis, initiate treatment and prevent complications.
Subject(s)
COVID-19 , Coinfection , Mycoses , Pneumonia , Humans , COVID-19/complications , Coinfection/diagnostic imaging , Coinfection/complications , Mycoses/etiology , Mycoses/microbiology , Lung/diagnostic imaging , RadiologistsABSTRACT
SESSION TITLE: Late Breaking Posters in Critical Care SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/18/2022 01:30 pm - 02:30 pm PURPOSE: This systematic review aims to better understand the clinical characteristics, comorbidities, diagnostic findings, and clinical outcomes associated with COVID-19 myocarditis. METHODS: A search for “COVID-19 OR SARS COV-2 OR Coronavirus AND Myocarditis” was performed on 1/4/2022. 2011 studies from Embase and 1165 studies from PubMed were identified. Selection criteria included studies on SARS COV-2 infection-related myocarditis. 142 PubMed and 104 Embase studies were identified. Studies were appraised per protocols and s, vaccine-related myocarditis, uncertain vaccine/infection-related myocarditis, and, systematic reviews. Duplicate studies were removed. A total of 53 articles from which 57 cases were selected to be part of this systematic review. Data on age, sex, days since diagnosis, comorbid conditions such as morbid obesity, hypertension, hyperlipidemia, CAD, preexisting CHF, ischemic heart disease, D- Dimer, ferritin, high sensitivity troponin, BNP, EKG, echocardiogram, cMRI findings, medications, ventilation requirements, and mortality were extracted from 57 studies and were analyzed using IBM SPSS v26. RESULTS: Mean EF was 32.65 ± 16.57 %. EKG findings of diffuse ST elevation were present in 22% of all cases. Echocardiogram findings of diffuse hypokinesis present in 42.1% and depressed EF in 31.6% of all cases. 21.1% required non-invasive ventilation while 26.3% of all cases ended up requiring mechanical ventilation. Ischemic cardiomyopathy was present in 1.7%, Hypertension in 24.5%, Hyperlipidemia in 7%, Morbid obesity, and a previous diagnosis of CHF was present in 0% of all cases. Overall mortality was seen in 5.3% of all cases. 50% of the cases reported using cardiac MRI (cMRI) and 58% with reported cMRI findings met the Lake Louis criteria for diagnosis of myocarditis. CONCLUSIONS: This systematic review presents findings of demographics, comorbidities, diagnostic findings, and clinical outcomes of adult COVID-19 patients with myocarditis. The mean days since COVID-19 diagnosis has a wide range due to varied presentations noted in case reports. The previously presumed high-risk factors for COVID-19-related myocarditis are not present in a significant percentage of the cases. SARS-CoV2 myocarditis-related mortality is lower in cases than expected. In the setting of the appropriate clinical context, acute/subacute chest pain, with elevated cardiac biomarkers, abnormal EKGs, and echocardiogram findings in patients with recent or /remote SARS-CoV2 infection/ vaccination, a clinical diagnosis of myocarditis can be made in absence of cMRI. CLINICAL IMPLICATIONS: Diagnosis of SARS-CoV2-related myocarditis can be made based on clinical presentation, abnormal EKG, and echocardiogram with or without the added benefit of cardiac MRI. This systematic review aims to update current knowledge on the characteristics of COVID-19 infection-related myocarditis. DISCLOSURES: No relevant relationships by Mubashir Ayaz Ahmed No relevant relationships by Hari Bhattarai No relevant relationships by shyam chalise No relevant relationships by Saral Desai No relevant relationships by Shayet Hossain Eshan No relevant relationships by Sudha Misra No relevant relationships by Zahin Islam Rafa No relevant relationships by Shrungavi Ramanathan No relevant relationships by Monica Sharma
ABSTRACT
Fungal lung co-infections associated with COVID-19 may occur in severely ill patients or those with underlying co-morbidities, and immunosuppression. The most common invasive fungal infections are caused by aspergillosis, mucormycosis, pneumocystis, cryptococcus, and candida. Radiologists integrate the clinical disease features with the CT pattern-based approach and play a crucial role in identifying these co-infections in COVID-19 to assist clinicians to make a confident diagnosis, initiate treatment and prevent complications.
ABSTRACT
Since 2019 November, an outbreak of COVID-19 arose and became a major public health emergency of international concern. A comprehensive case series from China was published by the New Coronavirus Pneumonia Emergency Response Epidemiology Team, which indicated an overall fatality rate of 2.3 percent, which climbed to 6.0 percent in persons with high blood pressure. The elderly and people with underlying medical problems, such as cardiovascular disease, diabetes, chronic respiratory diseases and cancer are more likely to develop serious illnesses. An electronic literature search was carried out by the search engines like PUBMED, Google scholar, etc. Comorbidities included in this study such as diabetes, hypertension, asthma, cardiovascular risk factors, cerebrovascular conditions. The result was the most of the comorbid caused was hypertension. By the above systemic review, it was concluded that the most comorbid condition hypertension followed by diabetes mellitus, hence the mortality rate also seems to be higher in these two cases. © 2022 Journal of Medical Pharmaceutical and Allied Sciences. All rights reserved.
ABSTRACT
TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: Viral Respiratory illnesses such as Covid-19 and Influenza pose significant health challenges worldwide. There are more than 150M confirmed cases of Covid-19 with a reported 3.15M deaths (as of April, 2021). The WHO reports there to be ~ 1 billion influenza cases and 290-650K influenza-associated deaths annually. A signature feature of these illnesses is an early infection period that, if insufficiently recognized and controlled early, can lead to viral spread and avoidable morbidity/mortality. The need for personalized, remote care tools that facilitate early detection and triage of viral illness has never been greater. To address this gap, we developed an institutional software, Vironix, that uses machine-learned (ML) prediction models to enable real-time risk stratification and decision support for global organizations. METHODS: ML models were trained on clinical characteristic data from East and South Asia, Western Europe, and USA. Algorithms take an input of symptom, profile, biometric, and exposure data and return an assessment of disease severity. Covid-19 algorithms were validated on computer generated patient vigenttes and deployed in the Vironix web app among 22 participants in a small business commercial pilot for member self-screening. Members conducted daily health assessments and received personalized decision support while organization managers received work-from-home recommendations and compliant symptom monitoring without seeing member health data. For influenza, Vironix ML algorithms were tested on a dataset (with a 90/10 train test split) collected from one academic and two community emergency rooms from March 2014 to July 2017 (Hong et al.). RESULTS: ML-predictions showed 87.6% accuracy, 85.5% sensitivity, and 87.8% specificity in identifying severe Covid-19 presentations in an out-of-sample validation set of 5,000 patient cases. After 4-months pilot use, Vironix issued 14 stay-at-home and 10 healthcare escalation recommendations while maintaining 30-day and 7-day user retention of 66% and 72%, greatly exceeding common app adoption rates. ML predictions for the Influenza data set showed 67.8% accuracy, 71.7% sensitivity, and 65.4% specificity in identifying admissible or dischargeable presentations of influenza in an out-of-sample validation set of 56,000 patient cases. CONCLUSIONS: Covid-19 ML-severity assessments showed strong accuracy, sensitivity, and specificity in identifying severe clinical presentations. The deployed web-app showed high adoption with members receiving relevant decision support. Flu algorithm performance could be bolstered by inclusion of biometric features. Additional controlled trials could be conducted to establish validated markers of health improvement and early illness detection resulting from Vironix use. The overall methodology for mapping clinical characteristic data into patient scenarios for training ML classifiers of health deterioration is generalizable for a variety of potential software and hardware deployments across disease spaces. CLINICAL IMPLICATIONS: The technology detailed in this study represents a potential low cost, scalable, hardware/software agnostic, global solution for early detection and intervention on infectious respiratory illness. These solutions can be integrated into remote care and institutional wellness workflows to support public health initiatives. DISCLOSURES: No relevant relationships by Anna Berryman, source=Web Response No relevant relationships by Shreyas Iyer, source=Web Response No relevant relationships by Vinay Konda, source=Web Response Advisory Committee Member relationship with ABMRCC Please note: $1-$1000 by Chris Landon, source=Web Response, value=Consulting fee Removed 04/28/2021 by Chris Landon, source=Web Response Consultant relationship with ABM Respiratory Please note: 11/20 - date Added 04/30/2021 by Chris Landon, source=Web Response, value=Consulting fee no disclosure on file for Nicholas Mark;No relevant relationships by James Morrill, source=Web R sponse No relevant relationships by Sriram Ramanathan, source=Web Response Owner/Founder relationship with Vironix Health, Inc Please note: 05/2020 - Present Added 04/28/2021 by Sumanth Swaminathan, source=Web Response, value=Ownership interest Owner/Founder relationship with Vironix Health Please note: 04/2020-Now Added 05/10/2021 by Botros Toro, source=Web Response, value=Ownership interest Consultant relationship with Vironix Please note: 2019-present Added 04/28/2021 by Nicholas Wysham, source=Web Response, value=Ownership interest
ABSTRACT
Purpose : Minimizing healthcare-related exposures for patients and providers are paramount during the coronavirus (COVID-19) pandemic. We performed a retrospective cohort study to compare visual outcomes and patient satisfaction in senior residentperformed immediate sequential bilateral cataract surgery (ISBCS) versus delayed sequential bilateral cataract surgery (DSBCS). Methods : All ISBCS and DSBCS patients who underwent senior resident-performed cataract surgery in the Comprehensive Ophthalmology division of a single academic institution from May to September 2020 were included. Outcome measures were final corrected distance visual acuity (CDVA), final manifest refraction (MRx), incidence of intraoperative and postoperative complications, total number of clinical and surgical visits, and patient satisfaction, assessed postoperatively by telephone questionnaire. Results : Fourteen (22 eyes) and 28 (56 eyes) patients underwent senior residentperformed ISBCS and DSBCS, respectively. Final CDVA was 20/25 or better in 21 (95%) ISBCS eyes and 51 (91%) DSBCS eyes (p=0.670). The deviation of final MRx from target refraction was within 0.50 D in 17 (77%) ISBCS eyes and 47 (84%) DSBCS eyes (p=0.522). There was no significant difference in intraoperative (p=1.000) or postoperative (p=1.000) complications. ISBCS patients averaged 3.5 fewer visits than DSBCS patients (5.9 vs 9.5, p<0.001). All ISBCS and 20 DSBCS patients (87%) reported they were overall “very satisfied” or “satisfied” with their experience (p=0.701), and there was no significant difference in the overall visual function 7 score, where 0 indicates the worst possible functional impairment and 100 indicates no disability (p=0.561). Finally, five of the six senior residents who performed the ISBCS cases included in this study reported that they preferred performing ISBCS over DSBCS. Conclusions : This early experience demonstrates that senior resident-performed ISBCS is as safe and effective as DSBCS, with the added benefit of averaging fewer in-person visits for patients. Residency programs should consider offering senior resident-performed ISBCS to select patients during the COVID-19 pandemic.
ABSTRACT
Purpose : During the coronavirus (COVID-19) pandemic, reducing unnecessary clinic visits is critical to limit risk of exposure for patients and providers. We hypothesized that final visual outcomes and postoperative complication rates in patients with postoperative week 1 (POW1) telehealth visits would be similar to patients with in-person POW1 visits in this retrospective cohort study. Methods : All uncomplicated cataract surgeries performed by senior residents with routine postoperative day 1 (POD1) exams and POW1 telehealth visits conducted from July 1, 2020 to December 31, 2020 at a single academic institution were reviewed. Controls were drawn from uncomplicated surgeries performed by senior residents with in-office POW1 visits during the same period the year prior (7/1/19 - 12/31/19). Visual outcomes, including final corrected distance visual acuity (CDVA) and deviation of manifest refraction from the target refraction, were compared between the two groups, along with rates of significant postoperative complications. Results : Thirty-eight patients (51 eyes) with POW1 telehealth visits and 44 patients (57 eyes) with POW1 in-office visits were included in the study. There were no statistically significant differences in baseline demographics or preoperative CDVA and biometry measurements between the two groups. The average final postoperative month 1 (POM1) logMAR CDVA was 0.030 and 0.021 (p=0.284) in the telehealth and in-office groups, respectively, with 44 (86%) telehealth eyes and 51 (90%) in-office eyes within 0.50 D of the target refraction (p=0.610). Six eyes (12%) in the telehealth group and 3 eyes (5%) in the inoffice group developed complications noted at the POM1 visit (p=0.222), comprised of pseudophakic cystoid macular edema (CME) or mild persistent/recurrent postoperative iritis. In all instances, the CME and iritis resolved with topical steroids and/or NSAIDs, with final CDVA 20/30 or better. Conclusions : There was no statistically significant difference in final CDVA, refractive outcomes, or postoperative complication rates in eyes undergoing POW1 telehealth as compared to in-office visits. In uncomplicated cataract surgeries, POW1 telehealth visits can be a safe and effective alternative to in-office visits to minimize exposure risks during the COVID-19 pandemic.
ABSTRACT
Covid-19 pandemic has brought us to a new norm that spawn the world towards new way of working, communicating, and doing business. The evolution of globalization and digital technology with a rapid speed has position Fintech as one of the important innovations that would support millions of SMEs in the current economic situation. Based on the contribution and raising number of SMEs across the world, this paper illustrates the technical and managerial challenges of SMEs that lie ahead upon the emergence of Fintech. The finding is meant to create an awareness towards the potentials of innovative Fintech platforms in solving financial issues of SMEs. However, there is a need for substantial further research and development which should include ongoing assessments on emerging Fintech innovation. © 2021 Nova Science Publishers, Inc.
ABSTRACT
Introduction: The COVID-19 pandemic has disrupted healthcare systems worldwide. In addition to the direct impact of the virus on patient morbidity and mortality, the effect of lockdown strategies on health and healthcare utilization have become apparent. The effect of the pandemic on children on home mechanical ventilation is unknown. We examined the impact of the pandemic on pediatric healthcare utilization in children on home mechanical ventilation. Methods: Between March 11 and December 1, 2020, we conducted a single center, retrospective analysis of 81 children, younger than 18 years old, on home mechanical ventilation who are followed at the UT Physicians High Risk Children's Clinic. Using the same cohort of patients, we compared healthcare utilization during the pandemic in 2020 to the same period in 2019. Results: We observed a massive decline in pediatric healthcare utilization during the pandemic year compared with the previous year. Emergency department total visits decreased by 70% (33 vs 10) (p<0.01). Total number of hospital admissions declined by 38% (52 vs 32) (p=0.03). The mean length of stay (LOS) in hospital admission was 6.7 days in 2019 and 5.3 days in 2020 (p=0.3). Similarly, pediatric intensive care unit (PICU) admissions reduced by 57% (30 vs 13) (P=0.04), and the mean PICU LOS was 7.5 days in 2019 and 6.0 days in 2020 (p=0.5). Mortality did not change during 2020 period (1 vs 0). Conclusions: Our data illustrate a significant improvement in pediatric hospital utilization and outcomes for children on home mechanical ventilation during the COVID-19 pandemic. We speculate that fewer medical office visits, increase in telehealth follow ups, school closures, social distancing, massive mask utilization, and increased hand washing during the pandemic year were protective factors that contributed to a lower hospitalization rate. However, we cannot fully exclude the possibilities of natural history of disease fluctuation, or regression to the mean phenomenon. More studies are needed to confirm the etiology of these findings.
ABSTRACT
RATIONALE The Covid-19 pandemic has posed a serious, ongoing global health challenge. The United States has been the worst affected, with more than 11M confirmed cases and 246K deaths (as of November 2020). Two primary and persisting concerns are the continued necessity for shutdown/isolation and the possibility of singular waves of rapid virus spread that could overwhelm global healthcare systems, resulting in preventable mortality and substantial economic burden. While vaccines are being developed and disseminated, the need for remote patient care has never been more critical. To that end, we developed a Covid-19 remote triage software, Vironix, which uses machine-learning algorithms to enable real-time risk stratification and decision support for users. This remote management approach has significant potential to increase safety, improve health outcomes, and stem virus spread as organizations reopen. METHODS Vironix uses personalized machine-learning algorithms trained off clinical characteristic data from the EU, East Asia, and the USA in tandem with prescribed guidelines from the CDC, WHO, and Zhejiang University's handbook on Covid-19 prevention. Clinical characteristics of thousands of patients in the literature were mapped into patient vignettes using Bayesian inference. Subsequent stacked, ensemble decision tree classifiers were trained on these vignettes to classify severity of presenting symptoms and signs. Crucially, the algorithm continuously learns from ongoing use of the application, strengthening decisions, and adapting decision boundaries based on inputted information. Vironix was deployed using a user-friendly API, allowing users to easily screen themselves and obtain remote decision support through a variety of devices (mobile apps, computers, health monitors, etc).RESULTS Algorithm performance was assessed based on its binary classification performance in an out-of-sample test set including severe and nonsevere labels. Vironix correctly assigned the severity classes with an accuracy of 87.6%. Vironix further demonstrated superior specificity (87.8%) and sensitivity (85.5%) in identifying positive (severe) presentations of Covid-19. The algorithms, deployed behind the Vironix Web Application, have been invoked by tens of thousands of users around the world. CONCLUSION 1. The Vironix approach is a highly novel, generalizable methodology for mapping clinical characteristic data into patient scenarios for the purpose of training machine-learning prediction models to detect health deterioration due to viral illness. 2. Vironix exhibits excellent accuracy, sensitivity, and specificity in identifying and triaging clinical presentations of Covid-19 and the most appropriate level of medical urgency. 3. Algorithms continuously learn and improve decision boundaries as individual user input increases. .