Impact of Body Mass Index on the Use of Prone Vigil and High-Flow Nasal Cannula in Pattients with COVID-19

SUMMARY;The aim of the study was to determine whether body composition is a condition influencing the effect of awake prone positioning (APP) in patients with COVID-19 connected to high-flow nasal cannula (HFNC). We conducted a retrospective observational study and analyzed the therapeutic outcomes of 83 patients treated with HFNC in the medicine department of Hospital El Carmen (HEC), Santiago, Chile. The following information was obtained from the electronic clinical record (Florence clinical version 19.3) and the kinesic registry: i) patient history, ii) medical diagnosis, iii) body mass index (BMI), iv) characteristics of the APP and v) characteristics of the process of connection to CNAF. It was observed that there were significant differences in overweight and obese patients who used the PPV (p=0.001) through the ROX index (IROX) at the end of treatment with CNAF, occurring in the same way when evaluating the effects of the APP and in the PAFI in these same groups. In conclusion, BMI is a further aggravating factor that conditions the health of patients with COVID-19, and elevated BMI can negatively affect the treatment of these patients. On the other hand, the use of APP and CNAF proved to be effective in patients with COVID-19.

Remote mental health care interventions during the COVID-19 pandemic: An umbrella review.

Mitigating the COVID-19 related disruptions in mental health care services is crucial in a time of increased mental health disorders. Numerous reviews have been conducted on the process of implementing technology-based mental health care during the pandemic. The research question of this umbrella review was to examine what the impact of COVID-19 was on access and delivery of mental health services and how mental health services have changed during the pandemic. A systematic search for systematic reviews and meta-analyses was conducted up to August 12, 2022, and 38 systematic reviews were identified. Main disruptions during COVID-19 were reduced access to outpatient mental health care and reduced admissions and earlier discharge from inpatient care. In response, synchronous telemental health tools such as videoconferencing were used to provide remote care similar to pre-COVID care, and to a lesser extent asynchronous virtual mental health tools such as apps. Implementation of synchronous tools were facilitated by time-efficiency and flexibility during the pandemic but there was a lack of accessibility for specific vulnerable populations. Main barriers among practitioners and patients to use digital mental health tools were poor technological literacy, particularly when preexisting inequalities existed, and beliefs about reduced therapeutic alliance particularly in case of severe mental disorders. Absence of organizational support for technological implementation of digital mental health interventions due to inadequate IT infrastructure, lack of funding, as well as lack of privacy and safety, challenged implementation during COVID-19. Reviews were of low to moderate quality, covered heterogeneously designed primary studies and lacked findings of implementation in low- and middle-income countries. These gaps in the evidence were particularly prevalent in studies conducted early in the pandemic. This umbrella review shows that during the COVID-19 pandemic, practitioners and mental health care institutions mainly used synchronous telemental health tools, and to a lesser degree asynchronous tools to enable continued access to mental health care for patients. Numerous barriers to these tools were identified, and call for further improvements. In addition, more high quality research into comparative effectiveness and working mechanisms may improve scalability of mental health care in general and in future infectious disease outbreaks.

Analysis of the Satisfaction Degree of Students at Spain's Physiotherapy Universities in Relation to Online Teaching during the COVID-19 Pandemic

Student satisfaction is a crucial aspect in the quality assessment of higher education. The aim of the present study was to assess the degree of satisfaction among students in the Faculties of physiotherapy throughout Spain concerning online teaching during the State of Emergency due to the COVID-19 pandemic. This was a quantitative study with a cross-sectional observational design. The online questionnaire DISFISCOVID was distributed to 24 physiotherapy faculties across Spain. A sample of 348 physiotherapy students from 14 Spanish universities completed the questionnaire. It showed high reliability evidence, achieving Cronbach's alpha indices higher than 0.870, alongside a McDonald's omega H of 0.876. On the whole, students were not satisfied with online learning during the State of Emergency, considering it unsuitable for their learning in either the theoretical or practical field of subjects in the degree of physiotherapy. In conclusion, the perception of physiotherapy students concerning the teaching they received, as far as practical contents and assessment methods are concerned, was not very satisfactory in those Faculties in which online learning platforms were not being used beforehand, and was more satisfactory when teaching was carried out in-person in the classroom.

Predictors of mortality in kidney transplant patients infected by SARS-CoV-2 in south of Spain

BACKGROUND AND AIMS: Covid-19 pandemic has especially affected kidney transplant (KT) recipients, who are more vulnerable than the general population due to their immunosuppressive status and added comorbidities. The objetic of this study was to determine risk factors related to infection and mortality from Covid-19 in KT. METHOD: We included 53 KT who had PCR-confirmed COVID-19 infection between march 21st and november 24th, from a total of 2030 KT. Outcomes related to patient survival were analyzed. RESULTS: 39 (73%) patients were men, with a mean age of 56±15 years old. Median time after KT where the infection took place was 104 months (IQR: 55-160). One patient was infected 40 days after transplant. 90% were on Tacrolimus therapy and 79% on MMF. 81% of patients were hypertensive, 36% diabetic and 19% had ischemic heart disease. 65% were on ARAII treatment. Clinical presentation consisted on pneumonia (64%), fever (55%), cough (70%), dyspnoea (45%), lymphopenia (66%) and gastrointestinal symptoms (36%). 21% required intubation and admission in ICU. 8 patients were asymptomatic. 18% received Hydroxychloroquine therapy plus Azithromycin, 11% Tocilizumab, 11% Ritonavir-Lopinavir, 59% steroids, 7.7% Remdesivir and 13.5% convalescent plasma. Immunosuppression was reduced in all symptomatic patients. 10 patients (19%) died. Table 1 compares the characteristics of these patients with those who survived. CONCLUSION: We concluded that mortality in KT is very high, more than reported in general population. Risk factors are patient age, time after KT, baseline renal function, the presence of pneumonia, as well as higher CRP levels at the time of diagnosis. More experience is needed to optimize our protocols and therapy for Covid- 19 in KT.

Dealing with scarce labelled data: Semi-supervised deep learning with mix match for Covid-19 detection using chest X-ray images

Coronavirus (Covid-19) is spreading fast, infecting people through contact in various forms including droplets from sneezing and coughing. Therefore, the detection of infected subjects in an early, quick and cheap manner is urgent. Currently available tests are scarce and limited to people in danger of serious illness. The application of deep learning to chest X-ray images for Covid-19 detection is an attractive approach. However, this technology usually relies on the availability of large labelled datasets, a requirement hard to meet in the context of a virus outbreak. To overcome this challenge, a semi-supervised deep learning model using both labelled and unlabelled data is proposed. We develop and test a semi-supervised deep learning framework based on the Mix Match architecture to classify chest X-rays into Covid-19, pneumonia and healthy cases. The presented approach was calibrated using two publicly available datasets. The results show an accuracy increase of around 15% under low labelled / unlabelled data ratio. This indicates that our semi-supervised framework can help improve performance levels towards Covid-19 detection when the amount of high-quality labelled data is scarce. Also, we introduce a semi-supervised deep learning boost coefficient which is meant to ease the scalability of our approach and performance comparison. © 2020 IEEE

Elevated HScore is Associated with Poor Clinical Outcomes in COVID-19, Even in the Absence of Secondary Hemophagocytic Lymphohistiocytosis. (preprint)

Introduction: Patients with Coronavirus Disease 2019 (COVID-19) frequently experience a hyperinflammatory syndrome, that leads to unfavorable outcomes. This condition resembles Secondary Hemophagocytic Lymphohistiocytosis (sHLH) described in neoplastic, rheumatic and other infectious diseases. However, it has not been prospectively studied on these patients. A scoring system (HScore) has been validated for sHLH, and recently proposed to evaluate hyperinflammation in COVID-19. Methods: 143 patients aged [≥]18 years admitted because of COVID-19 were enrolled in a prospective, single-center, cohort study. HScore was calculated within the 72 hours since admission. The incidence of sHLH during hospitalization was evaluated. Additionally, the relationship between HScore [≥]130 points and either the requirement of mechanical ventilation or 60-days mortality was explored. Results: The median age of enrolled patients was 57 (21-100), and 63.6% were male. The median HScore was 96 (33-169). One patient was diagnosed with sHLH (incidence 0,7%), due to a HScore of 169. After adjusting for age, sex, comorbidities and obesity, HScore [≥]130 was independently associated with the composite clinical outcome (HR 2.13, p=0.022). Conclusion: sHLH is not frequent among COVID-19 patients. HScore can efficiently predict the risk for poor outcomes.

Impact of Body Mass Index on the Use of Prone Vigil and High-Flow Nasal Cannula in Pattients with COVID-19.

The aim of the study was to determine whether body composition is a condition influencing the effect of awake prone positioning (APP) in patients with COVID-19 connected to high-flow nasal cannula (HFNC). We conducted a retrospective observational study and analyzed the therapeutic outcomes of 83 patients treated with HFNC in the medicine department of Hospital El Carmen (HEC), Santiago, Chile. The following information was obtained from the electronic clinical record (Florence clinical version 19.3) and the kinesic registry: i) patient history, ii) medical diagnosis, iii) body mass index (BMI), iv) characteristics of the APP and v) characteristics of the process of connection to CNAF. It was observed that there were significant differences in overweight and obese patients who used the PPV (p=0.001) through the ROX index (IROX) at the end of treatment with CNAF, occurring in the same way when evaluating the effects of the APP and in the PAFI in these same groups. In conclusion, BMI is a further aggravating factor that conditions the health of patients with COVID-19, and elevated BMI can negatively affect the treatment of these patients. On the other hand, the use of APP and CNAF proved to be effective in patients with COVID-19. Copyright © 2022, Universidad de la Frontera. All rights reserved.