Short Term Home Oxygen Therapy for COVID-19 patients: The COVID-HOT algorithm.
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ABSTRACT:
SUBMITTER: Sardesai I
PROVIDER: S-EPMC7567238 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Publications
Short Term Home Oxygen Therapy for COVID-19 patients: The COVID-HOT algorithm.
Sardesai Indrani I Grover Joydeep J Garg Manish M Nanayakkara P W B PWB Di Somma Salvatore S Paladino Lorenzo L Anderson Harry L HL Gaieski David D Galwankar Sagar C SC Stawicki Stanislaw P SP
Journal of family medicine and primary care 20200730 7
Innovative solutions are required to effectively address the unprecedented surge of demand on our healthcare systems created by the COVID-19 pandemic. Home treatment and monitoring of patients who are asymptomatic or mildly symptomatic can be readily implemented to ameliorate the health system burden while maintaining safety and effectiveness of care. Such endeavor requires careful triage and coordination, telemedicine and technology support, workforce and education, as well as robust infrastruc ...[more]
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Project description:Introduction: The COVID-19 pandemic created challenges to healthcare systems worldwide. To allow overwhelmed hospitals to focus on the most fragile and severely ill patients, new types of management had to be set up. During the pandemic, patients with COVID-19 from greater Paris area were monitored at home using a web-based remote system called COVIDOM™, using self-administered questionnaires, which triggered alerts to a regional control center. To ease hospital discharge and to prevent hospital from being overwhelmed, patients still requiring low-flow oxygen therapy discharged home were also included in this telemedicine solution. We aim to evaluate the safety of this original management. Methods: We conducted a retrospective multicenter cohort of patients discharged home from hospital after COVID-19 and still requiring nasal oxygen therapy, who were monitored by questionnaire and trained physicians using COVIDOM. During late follow-up, the status of the patients using a Euro-Qol (EQ-5D-5L) questionnaire, and the Medical Research Council (MRC) Dyspnea scale was collected. Results: From March 21st to June 21st 2020, 73 COVID-19 patients still receiving nasal oxygen at hospital discharge were included. Median [Inter-Quartile Range (IQR)] age was 62.0 [52.5-69.0] years, 64.4% were male. Altogether, risk factors were observed in 49/73 (67%) patients, mainly hypertension (35.6%), diabetes mellitus (15.1%) and active neoplasia (11.0%). Among the cohort, 26% of patients were previously managed in ICU. Oxygen therapy was required for a median [IQR] of 20 [16-31] days. No death or urgent unplanned hospitalization were observed during the COVIDOM telemonitoring. During the late follow-up evaluation (6 months after inclusion), the mean EQ-5D-5L questionnaire score was 7.0 ± 1.6, and the mean MRC dyspnea scale was 0.8 ± 1.0, indicating absence of dyspnea. Five patients have died from non-COVID causes. Conclusions: In this preliminary study, early discharge home of patients with severe COVID-19 disease who still required low-oxygen therapy seems to be safe.
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Project description:BackgroundEffective home treatment algorithms implemented based on a pathophysiologic and pharmacologic rationale to accelerate recovery and prevent hospitalisation of patients with early coronavirus disease 2019 (COVID-19) would have major implications for patients and health system.MethodsThis academic, matched-cohort study compared outcomes of 90 consecutive consenting patients with mild COVID-19 treated at home by their family physicians between October 2020 and January 2021 in Northern and Central Italy, according to the proposed recommendation algorithm, with outcomes for 90 age-, sex-, and comorbidities-matched patients who received other therapeutic regimens. Primary outcome was time to resolution of major symptoms. Secondary outcomes included prevention of hospitalisation. Analyses were by intention-to-treat.FindingsAll patients achieved complete remission. The median [IQR] time to resolution of major symptoms was 18 [14-23] days in the 'recommended schedule' cohort and 14 [7-30] days in the matched 'control' cohort (p = 0·033). Other symptoms persisted in a lower percentage of patients in the 'recommended' than in the 'control' cohort (23·3% versus 73·3%, respectively, p<0·0001) and for a shorter period (p = 0·0107). Two patients in the 'recommended' cohort were hospitalised compared to 13 (14·4%) controls (p = 0·0103). The prevention algorithm reduced the days and cumulative costs of hospitalisation by >90%.InterpretationImplementation of an early home treatment algorithm failed to accelerate recovery from major symptoms of COVID-19, but reduced the risk of hospitalisation and related treatment costs. Given the study design, additional research would be required to consolidate the proposed treatment recommendations.FundingFondazione Cav.Lav. Carlo Pesenti.
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Project description:BackgroundWith the growing stress on hospitals caused by the COVID-19 pandemic, the need for home-based solutions has become a necessity to support these overwhelmed hospitals.ObjectiveThe goal of this study was to compare two nonpharmacological respiratory treatment methods for home-isolated COVID-19 patients using a newly developed telemanagement health care system.MethodsIn this single-blinded randomized clinical trial, 60 patients with stage 1 pneumonia caused by SARS-CoV-2 infection were treated. Group A (n=30) received oxygen therapy with bilevel positive airway pressure (BiPAP) ventilation, and Group B (n=30) received osteopathic manipulative respiratory and physical therapy techniques. Arterial blood gases of PaO2 and PaCO2, pH, vital signs (ie, temperature, respiratory rate, oxygen saturation, heart rate, and blood pressure), and chest computed tomography scans were used for follow-up and for assessment of the course and duration of recovery.ResultsAnalysis of the results showed a significant difference between the two groups (P<.05), with Group A showing shorter recovery periods than Group B (mean 14.9, SD 1.7 days, and mean 23.9, SD 2.3 days, respectively). Significant differences were also observed between baseline and final readings in all of the outcome measures in both groups (P<.05). Regarding posttreatment satisfaction with our proposed telemanagement health care system, positive responses were given by most of the patients in both groups.ConclusionsIt was found that home-based oxygen therapy with BiPAP can be a more effective prophylactic treatment approach than osteopathic manipulative respiratory and physical therapy techniques, as it can impede exacerbation of early-stage COVID-19 pneumonia. Telemanagement health care systems are promising methods to help in the pandemic-related shortage of hospital beds, as they showed reasonable effectiveness and reliability in the monitoring and management of patients with early-stage COVID-19 pneumonia.Trial registrationClinicalTrials.gov NCT04368923; https://clinicaltrials.gov/ct2/show/NCT04368923.
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Project description: Not available
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Project description:The lack of available biomarkers for diagnosing and predicting different stages of coronavirus disease 2019 (COVID-19) is currently one of the main challenges that clinicians are facing. Recent evidence indicates that the plasma levels of specific miRNAs may be significantly modified in COVID-19 patients. Large-scale deep sequencing analysis of small RNA expression was performed on plasma samples from 40 patients hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (between March and May 2020) (median 13.50 [IQR 9–24] days since symptoms initiation) and 21 healthy noninfected individuals. Patients were categorized as hospitalized not requiring oxygen therapy (n = 6), hospitalized requiring low-flow oxygen (n = 23), and hospitalized requiring high-flow oxygen support (n = 11). A total of 1218 different micro(mi)RNAs were identified. When compared with healthy noninfected donors, SARS-CoV-2 infected patients showed significantly (fold change [FC] >1.2 and adjusted p [padj] <0.05) altered expression of 190 miRNAs. The top 10 differentially expressed (DE) miRNAs were miR-122-5p, let-7b-5p, miR-146a-5p, miR-342-3p, miR-146b-5p, miR-629-5p, miR-24-3p, miR-12136, let-7a-5p, and miR-191-5p, which displayed FC and padj values ranging from 153 to 5 and 2.51 × 10-32 to 2.21 × 10-21, respectively, which unequivocally diagnosed SARS-CoV-2 infection. No differences in blood cell counts and biochemical plasma parameters, including interleukin 6, ferritin and D-dimer, were observed between COVID-19 patients on high-flow oxygen therapy, low-flow oxygen therapy, or not requiring oxygen therapy. Notably, 31 significantly deregulated miRNAs were found when patients on high- and low-flow oxygen therapy were compared. Similarly, 6 DE miRNAs were identified between patients on high flow and those not requiring oxygen therapy. SARS-CoV-2 infection generates a specific miRNA signature in hospitalized patients. Furthermore, specific miRNA profiles are associated with COVID-19 prognosis in severe patients.
2024-04-03 | GSE230092 | GEO
Project description:BackgroundShort-term follow-up of COVID-19 patients reveals pulmonary dysfunction, myocardial damage and severe psychological distress. Little is known of the burden of these sequelae, and there are no clear recommendations for follow-up of COVID-19 patients.In this multi-disciplinary evaluation, cardiopulmonary function and psychological impairment after hospitalization for COVID-19 are mapped.MethodsWe evaluated patients at our outpatient clinic 6 weeks after discharge. Cardiopulmonary function was measured by echocardiography, 24-hours ECG monitoring and pulmonary function testing. Psychological adjustment was measured using questionnaires and semi-structured clinical interviews. A comparison was made between patients admitted to the general ward and Intensive care unit (ICU), and between patients with a high versus low functional status.FindingsEighty-one patients were included of whom 34 (41%) had been admitted to the ICU. New York Heart Association class II-III was present in 62% of the patients. Left ventricular function was normal in 78% of patients. ICU patients had a lower diffusion capacity (mean difference 12,5% P = 0.01), lower forced expiratory volume in one second and forced vital capacity (mean difference 14.9%; P<0.001; 15.4%; P<0.001; respectively). Risk of depression, anxiety and PTSD were 17%, 5% and 10% respectively and similar for both ICU and non-ICU patients.InterpretationOverall, most patients suffered from functional limitations. Dyspnea on exertion was most frequently reported, possibly related to decreased DLCOc. This could be caused by pulmonary fibrosis, which should be investigated in long-term follow-up. In addition, mechanical ventilation, deconditioning, or pulmonary embolism may play an important role.
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Project description:BackgroundPatients with severe Coronavirus disease 19 (COVID-19) typically require supplemental oxygen as an essential treatment. We developed a machine learning algorithm, based on deep Reinforcement Learning (RL), for continuous management of oxygen flow rate for critically ill patients under intensive care, which can identify the optimal personalized oxygen flow rate with strong potentials to reduce mortality rate relative to the current clinical practice.MethodsWe modeled the oxygen flow trajectory of COVID-19 patients and their health outcomes as a Markov decision process. Based on individual patient characteristics and health status, an optimal oxygen control policy is learned by using deep deterministic policy gradient (DDPG) and real-time recommends the oxygen flow rate to reduce the mortality rate. We assessed the performance of proposed methods through cross validation by using a retrospective cohort of 1372 critically ill patients with COVID-19 from New York University Langone Health ambulatory care with electronic health records from April 2020 to January 2021.ResultsThe mean mortality rate under the RL algorithm is lower than the standard of care by 2.57% (95% CI: 2.08-3.06) reduction (P < 0.001) from 7.94% under the standard of care to 5.37% under our proposed algorithm. The averaged recommended oxygen flow rate is 1.28 L/min (95% CI: 1.14-1.42) lower than the rate delivered to patients. Thus, the RL algorithm could potentially lead to better intensive care treatment that can reduce the mortality rate, while saving the oxygen scarce resources. It can reduce the oxygen shortage issue and improve public health during the COVID-19 pandemic.ConclusionsA personalized reinforcement learning oxygen flow control algorithm for COVID-19 patients under intensive care showed a substantial reduction in 7-day mortality rate as compared to the standard of care. In the overall cross validation cohort independent of the training data, mortality was lowest in patients for whom intensivists' actual flow rate matched the RL decisions.
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Project description:Current smokers who are prescribed home oxygen may not benefit from the therapy. In addition to being an obvious fire hazard, there is some evidence that the physiological mechanisms by which home oxygen is believed to operate are inhibited by smoking. Although their effectiveness is yet to be demonstrated, electronic cigarettes (e-cigarettes) are often regarded as an aid to smoking cessation. However, several burn accidents in e-cigarette smokers receiving home oxygen therapy have also been reported, leading Health Canada to release a warning of fire risk to oxygen therapy patients from e-cigarettes. It is the authors' position that patients receiving oxygen should definitely not use e-cigarettes. The authors provide suggestions for addressing the delicate issue of home oxygen therapy in current cigarette and?or e-cigarette smokers.
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