A novel scale based on biomarkers associated with COVID-19 severity can predict the need for hospitalization and intensive care, as well as enhanced probabilities for mortality.

Prognostic scales may help to optimize the use of hospital resources, which may be of prime interest in the context of a fast spreading pandemics. Nonetheless, such tools are underdeveloped in the context of COVID-19. In the present article we asked whether accurate prognostic scales could be developed to optimize the use of hospital resources. We retrospectively studied 467 files of hospitalized patients after COVID-19. The odds ratios for 16 different biomarkers were calculated, those that were significantly associated were screened by a Pearson's correlation, and such index was used to establish the mathematical function for each marker. The scales to predict the need for hospitalization, intensive-care requirement and mortality had enhanced sensitivities (0.91 CI 0.87-0.94; 0.96 CI 0.94-0.98; 0.96 CI 0.94-0.98; all with p < 0.0001) and specificities (0.74 CI 0.62-0.83; 0.92 CI 0.87-0.96 and 0.91 CI 0.86-0.94; all with p < 0.0001). Interestingly, when a different population was assayed, these parameters did not change considerably. These results show a novel approach to establish the mathematical function of a marker in the development of highly sensitive prognostic tools, which in this case, may aid in the optimization of hospital resources. An online version of the three algorithms can be found at: http://benepachuca.no-ip.org/covid/index.php.

Yoga Therapy in Cancer Care via Telehealth During the COVID-19 Pandemic.

BACKGROUND: Yoga is an evidence-based mind-body practice known to improve physical and mental health in cancer patients. We report on the processes and patient-reported outcomes of one-on-one yoga therapy (YT) consultations delivered via telehealth. METHODS: For patients completing a YT consultation between March 2020 and October 2021, we examined demographics, reasons for referral, and self-reported symptom burden before and after one YT session using the Edmonton Symptom Assessment Scale (ESAS). Changes in ESAS symptom and subscale scores [physical distress (PHS), psychological distress (PSS), and global distress (GDS)] were evaluated by Wilcoxon signed-rank test. Descriptive statistics summarized the data. RESULTS: Ninety-seven initial YT consults were completed, with data evaluated for 95 patient encounters. The majority were women (83.2%) and white (75.8%), The mean age for females was 54.0 and for males was 53.4; the most common diagnosis was breast cancer (48%), 32.6% had metastatic disease, and nearly half (48.4%) were employed full-time. Mental health (43.0%) was the most common reason for referral, followed by fatigue (13.2%) and sleep disturbances (11.7%). The highest symptoms at baseline were sleep disturbance (4.3), followed by anxiety (3.7) and fatigue (3.5). YT lead to clinically and statistically significant reductions in PHS (mean change = -3.1, P < .001) and GDS (mean change = -5.1, P < .001) and significant reductions in PSS (mean change = -1.6, P < .001). Examination of specific symptom scores revealed clinically and statistically significant reductions in anxiety (mean change score -1.34, P < .001) and fatigue (mean change score -1.22, P < .001). Exploratory analyses of patients scoring ≥1 for specific symptoms pre-YT revealed clinically and statistically significant improvements in almost all symptoms and those scoring ≥4 pre-YT. CONCLUSIONS: As part of an integrative oncology outpatient consultation service, a single YT intervention delivered via telehealth contributed to a significant improvement in global, physical, and psychosocial distress. Additional research is warranted to explore the long-term sustainability of the improvement in symptoms.

Building a community to engineer synthetic cells and organelles from the bottom-up.

Employing concepts from physics, chemistry and bioengineering, 'learning-by-building' approaches are becoming increasingly popular in the life sciences, especially with researchers who are attempting to engineer cellular life from scratch. The SynCell2020/21 conference brought together researchers from different disciplines to highlight progress in this field, including areas where synthetic cells are having socioeconomic and technological impact. Conference participants also identified the challenges involved in designing, manipulating and creating synthetic cells with hierarchical organization and function. A key conclusion is the need to build an international and interdisciplinary research community through enhanced communication, resource-sharing, and educational initiatives.

Implementing Telehealth Music Therapy Services in an Integrative Oncology Setting: A Case Series.

Providing music therapy in a medical setting has necessarily undergone major changes during the COVID-19 world pandemic. Many programs had to discontinue while others were able to transition to a telehealth model. This paper describes the process of conducting telehealth-based music therapy sessions within an integrative oncology setting in a large cancer hospital. Patients provide feedback regarding benefits and challenges of inpatient, outpatient, and group music therapy using a telehealth model. Benefits include anxiety reduction, increased coping skills, and increased social support. Unique challenges include technology limitations. We share examples of how we successfully adapted our workflows to provide telehealth-based music therapy in inpatient, outpatient, and group settings.

Beach carrying capacity management under Covid-19 era on the Basque Coast by means of automated coastal videometry.

This paper describes the methodology followed to implement social distancing recommendations in the COVID-19 context along the beaches of the coast of Gipuzkoa (Basque Country, Northern Spain) by means of automated coastal videometry. The coastal videometry network of Gipuzkoa, based on the KostaSystem technology, covers 14 beaches, with 12 stations, along 50 km of coastline. A beach user detection algorithm based on a machine learning approach has been developed allowing for automatic assessment of beach attendance in real time at regional scale. For each beach, a simple classification of occupancy (low, medium, high, and full) was estimated as a function of the beach user density (BUD), obtained in real time from the images and the maximum beach carrying capacity (BCC), estimated based on the minimal social distance recommended by the authorities. This information was displayed in real time via a web/mobile app and was simultaneously sent to beach managers who controlled the beach access. The results showed a strong receptivity from beach users (more than 50.000 app downloads) and that real time information of beach occupation can help in short-term/daily beach management. In the longer term, the analysis of this information provides the necessary data for beach carrying capacity management and can help the authorities in controlling and in determining their maximum capacity.

Integrative Oncology Consultations Delivered via Telehealth in 2020 and In-Person in 2019: Paradigm Shift During the COVID-19 World Pandemic.

BACKGROUND: The COVID-19 pandemic has catalyzed the use of mobile technologies to deliver health care. This new medical model has benefited integrative oncology (IO) consultations, where cancer patients are counseled about healthy lifestyle, non-pharmacological approaches for symptom management, and addressing questions around natural products and other integrative modalities. Here we report the feasibility of conducting IO physician consultations via telehealth in 2020 and compare patient characteristics to prior in-person consultations conducted in 2019. METHODS: An integrated EHR-telemedicine platform was used for IO physician consultations. As in the prior in-person visits, patients completed pre-visit patient-reported outcome (PRO) assessments about common cancer symptoms [modified Edmonton Symptom Assessment Scale, (ESAS)], Measure Yourself Concerns and Wellbeing (MYCaW), and the PROMIS-10 to assess quality of life (QOL). Patient demographics, clinical characteristics, and PROs for new telehealth consultation in 2020 were compared to new in-person consultations in 2019 using t-tests, chi-squared tests, and -Wilcoxon rank-sum test. RESULTS: We provided telehealth IO consultations to 509 new patients from April 21, 2020, to October 21, 2020, versus 842 new patients in-person during the same period in 2019. Most were female (77 % vs 73%); median age (56 vs 58), and the most frequent cancer type was breast (48% vs 39%). More patients were seeking counseling on herbs and supplements (12.9 vs 6.8%) and lifestyle (diet 22.7 vs 16.9% and exercise 5.2 vs 1.8%) in the 2020 cohort than 2019, respectively. The 2020 telehealth cohort had lower symptom management concerns compared to the 2019 in-person cohort (19.5 vs 33.1%). CONCLUSIONS: Delivering IO consultations using telehealth is feasible and meets patients' needs. Compared to patients seen in-person during 2019, patients having telehealth IO consultations in 2020 reported lower symptom burden and more concerns about lifestyle and herbs and supplements. Additional research is warranted to explore the satisfaction and challenges among patients receiving telehealth IO care.

The Use of Mobile-technologies to Deliver Integrative Medicine During and Beyond the COVID-19 World Pandemic.

COVID-19 Pandemic has catalyzed the use of tele-medicine technologies in health care, especially in cancer. The recent relaxation of guidelines has enabled rapid expansion of these platforms many have been seeking for years. We review the advantages and challenges of delivering integrative oncology care using telemedicine. The article concludes with recommendations for areas that need to be addressed so that future practice can consider a hybrid model.

Diagnostic groups and short-term outcomes in suspected COVID-19 cases treated in an emergency department. / Categorías diagnósticas y resultados a corto plazo en los pacientes con sospecha de COVID-19 atendidos en un servicio de urgencias.

OBJECTIVES: The primary objective was to describe the clinical characteristics and 30-day mortality rates in emergency department patients with coronavirus disease 2019 (COVID-19) in different diagnostic groupings. MATERIAL AND METHODS: Secondary analysis of the COVID-19 registry compiled by the emergency department of Hospital Clínico San Carlos in Madrid, Spain. We selected suspected COVID-19 cases treated in the emergency department between February 28 and March 31, 2020. The cases were grouped as follows: 1) suspected, no polymerase chain reaction (PCR) test (S/no-PCR); 2) suspected, negative PCR (S/PCR-); 3) suspected, positive PCR (S/PCR+); 4) highly suspected, no PCR, or negative PCR (HS/no or PCR-); and 5) highly suspected, positive PCR (HS/PCR+). We collected clinical, radiologic, and microbiologic data related to the emergency visit. The main outcome was 30-day all-cause mortality. Secondary outcomes were hospitalization and clinical severity of the episode. RESULTS: A total of 1993 cases (90.9%) were included as follows: S/no-PCR, 17.2%; S/PCR-, 11.4%; S/PCR+, 22.1%; HS/no PCR or PCR-, 11.7%; and HS/PCR+, 37.6%. Short-term outcomes differed significantly in the different groups according to demographic characteristics; comorbidity and clinical, radiographic, analytical, and therapeutic variables. Thirty-day mortality was 11.5% (56.5% in hospitalized cases and 19.6% in cases classified as severe). The 2 HS categories and the S/PCR+ category had a greater adjusted risk for 30-day mortality and for having a clinically severe episode during hospitalization in comparison with S/PCR- cases. Only the 2 HS categories showed greater risk for hospitalization than the S/PCR- cases. CONCLUSION: COVID-19 diagnostic groups differ according to clinical and laboratory characteristics, and the differences are associated with the 30-day prognosis.

OBJETIVO: El objetivo principal fue describir el perfil clínico y la mortalidad a los 30 días de diferentes categorías diagnósticas en los casos de COVID-19 atendidos en un servicio de urgencias (SU). METODO: Análisis secundario del registro COVID-19_URG-HCSC. Se seleccionaron los casos sospechosos de COVID-19 atendidos en un SU de Madrid desde el 28 de febrero hasta el 31 de marzo de 2020. La muestra se dividió: 1) sospecha con PCR no realizada (S/PCR NR); 2) sospecha con PCR negativa (S/PCR­); 3) sospecha con PCR positiva (S/ PCR+); 4) alta sospecha con PCR negativa o no realizada (AS/PCR­ o NR); y 5) alta sospecha con PCR positiva (AS/ PCR+). Se recogieron variables clínicas, radiológicas y microbiológicas del episodio de urgencias. La variable de resultado principal fue la mortalidad por cualquier causa a los 30 días. Las variables secundarias fueron el ingreso y la gravedad del episodio. RESULTADOS: Se incluyeron 1.993 pacientes; 17,2% S/PCR NR, 11,4% S/PCR­, 22,1% S/PCR+, 11,7% AS/PCR­ o NR y 37,6% AS/PCR+. Se hallaron diferencias estadísticamente significativas respecto a las variables demográficas, comorbilidad, clínicas, radiográficas, analíticas y terapéuticas y de resultados a corto plazo en función las categorías diagnósticas. La mortalidad global a los 30 días fue de un 11,5%, 56,5% casos fueron hospitalizados y 19,6% casos sufrieron un episodio grave. Las categorías de AS y de S/PCR+ tuvieron un incremento del riesgo ajustado de mortalidad a los 30 días y de sufrir un episodio grave durante el ingreso hospitalario respecto a S/PCR­. En relación al ingreso, solo las categorías de AS tuvieron un incremento del riesgo ajustado de hospitalización respecto a la categoría de S/PCR­. CONCLUSIONES: Existen diferentes categorías diagnósticas de la enfermedad COVID-19 en función del perfil clínico y microbiológico que tienen correlato con el pronóstico a 30 días.

Categorías diagnósticas y resultados a corto plazo en los pacientes con sospecha de COVID-19 atendidos en un servicio de urgencias

OBJETIVO: EL objetivo principal fue describir el perfil clínico y la mortalidad a los 30 días de diferentes categorías diagnósticas en los casos de COVID-19 atendidos en un servicio de urgencias (SU). MÉTODO: Análisis secundario del registro COVID-19_URG-HCSC. Se seleccionaron los casos sospechosos de COVID-19 atendidos en un SU de Madrid desde el 28 de febrero hasta el 31 de marzo de 2020. La muestra se dividió: 1) sospecha con PCR no realizada (S/PCR NR);2) sospecha con PCR negativa (S/PCR-);3) sospecha con PCR positiva (S/PCR+);4) alta sospecha con PCR negativa o no realizada (AS/PCR- o NR);y 5) alta sospecha con PCR positiva (AS/PCR+). Se recogieron variables clínicas, radiológicas y microbiológicas del episodio de urgencias. La variable de resultado principal fue la mortalidad por cualquier causa a los 30 días. Las variables secundarias fueron el ingreso y la gravedad del episodio. RESULTADOS: Se incluyeron 1.993 pacientes;17,2% S/PCR NR, 11,4% S/PCR-, 22,1% S/PCR+, 11,7% AS/PCR- o NR y 37,6% AS/PCR+. Se hallaron diferencias estadísticamente significativas respecto a las variables demográficas, comorbilidad, clínicas, radiográficas, analíticas y terapéuticas y de resultados a corto plazo en función las categorías diagnósticas. La mortalidad global a los 30 días fue de un 11,5%, 56,5% casos fueron hospitalizados y 19,6% casos sufrieron un episodio grave. Las categorías de AS y de S/PCR+ tuvieron un incremento del riesgo ajustado de mortalidad a los 30 días y de sufrir un episodio grave durante el ingreso hospitalario respecto a S/PCR-. En relación al ingreso, solo las categorías de AS tuvieron un incremento del riesgo ajustado de hospitalización respecto a la categoría de S/PCR-. CONCLUSIONES: Existen diferentes categorías diagnósticas de la enfermedad COVID-19 en función del perfil clínico y microbiológico que tienen correlato con el pronóstico a 30 días OBJECTIVE: The primary objective was to describe the clinical characteristics and 30-day mortality rates in emergency department patients with coronavirus disease 2019 (COVID-19) in different diagnostic groupings. METHODS: Secondary analysis of the COVID-19 registry compiled by the emergency department of Hospital Clínico San Carlos in Madrid, Spain. We selected suspected COVID-19 cases treated in the emergency department between February 28 and March 31, 2020. The cases were grouped as follows: 1) suspected, no polymerase chain reaction (PCR) test (S/no-PCR);2) suspected, negative PCR (S/PCR-);3) suspected, positive PCR (S/PCR+);4) highly suspected, no PCR, or negative PCR (HS/no or PCR-);and 5) highly suspected, positive PCR (HS/PCR+). We collected clinical, radiologic, and microbiologic data related to the emergency visit. The main outcome was 30-day all-cause mortality. Secondary outcomes were hospitalization and clinical severity of the episode. RESULTS: A total of 1993 cases (90.9%) were included as follows: S/no-PCR, 17.2%;S/PCR-, 11.4%;S/PCR+, 22.1%;HS/no PCR or PCR-, 11.7%;and HS/PCR+, 37.6%. Short-term outcomes differed significantly in the different groups according to demographic characteristics;comorbidity and clinical, radiographic, analytical, and therapeutic variables. Thirty-day mortality was 11.5% (56.5% in hospitalized cases and 19.6% in cases classified as severe). The 2 HS categories and the S/PCR+ category had a greater adjusted risk for 30-day mortality and for having a clinically severe episode during hospitalization in comparison with S/PCR- cases. Only the 2 HS categories showed greater risk for hospitalization than the S/PCR- cases

Clinical presentation and outcome across age categories among patients with COVID-19 admitted to a Spanish Emergency Department.

PURPOSE: To determine the differences by age-dependent categories in the clinical profile, presentation, management, and short-term outcomes of patients with laboratory-confirmed COVID-19 admitted to a Spanish Emergency Department (ED). METHODS: Secondary analysis of COVID-19_URG-HCSC registry. We included all consecutive patients with laboratory-confirmed COVID-19 admitted to the ED of the University Hospital Clinico San Carlos (Madrid, Spain). The population was divided into six age groups. Demographic, baseline and acute clinical data, and in-hospital and 30-day outcomes were collected. RESULTS: 1379 confirmed COVID-19 cases (mean age 62 (SD 18) years old; 53.5% male) were included (18.1% < 45 years; 17.8% 45-54 years; 17.9% 55-64 years; 17.2% 65-74 years; 17.0% 75-84 years; and 11.9% ≥ 85 years). A statistically significant association was found between demographic, comorbidity, clinical, radiographic, analytical, and therapeutic variables and short-term results according to age-dependent categories. There were less COVID-specific symptoms and more atypical symptoms among older people. Age was a prognostic factor for hospital admission (aOR = 1.04; 95% CI 1.02-1.05) and in-hospital (aOR = 1.08; 95% CI 1.05-1.10) and 30-day mortality (aOR = 1.07; 95% CI 1.04-1.09), and was associated with not being admitted to intensive care (aOR = 0.95; 95% CI 0.93-0.98). CONCLUSIONS: Older age is associated with less COVID-specific symptoms and more atypical symptoms, and poor short-term outcomes. Age has independent prognostic value and may help in shared decision-making in patients with confirmed COVID-19 infection.