Functional and Clinical Characteristics of Individuals Attending Pulmonary Rehabilitation After Severe COVID-19.

BACKGROUND: A proportion of patients with COVID-19 need hospitalization due to severe respiratory symptoms. We sought to analyze characteristics of survivors of severe COVID-19 subsequently admitted to in-patient pulmonary rehabilitation and identify their rehabilitation needs. METHODS: From the COVID-19 Registry of Fondazione Don Gnocchi, we extracted 203 subjects admitted for in-patient pulmonary rehabilitation after severe COVID-19 from April 2020-September 2021. Specific information on acute-hospital stay and clinical and functional characteristics on admission to rehabilitation units were collected. RESULTS: During the acute phase of disease, 168 subjects received mechanical ventilation for 26 d; 85 experienced delirium during their stay in ICU. On admission to rehabilitation units, 20 subjects were still on mechanical ventilation; 57 had tracheostomy; 142 were on oxygen therapy; 49 were diagnosed critical illness neuropathy; 162 showed modified Barthel Index < 75; only 51 were able to perform a 6-min walk test; 32 of 90 scored abnormal at Montreal Cognitive Assessment; 43 of 88 scored abnormal at Hospital Anxiety and Depression Scale; 65 scored ≥ 2 at Malnutrition Universal Screening Tool, and 95 showed dysphagia needing logopedic treatment. CONCLUSIONS: Our analysis shows that subjects admitted for in-patient pulmonary rehabilitation after severe COVID-19 represent an extraordinarily multifaceted and clinically complex patient population who need customized, comprehensive rehabilitation programs carried out by teams with different professional skills. The need for step-down facilities, such as sub-intensive rehabilitation units, is also highlighted.

Effects of COVID-19 pandemic on intensive rehabilitation after severe acquired brain injuries.

PURPOSE: COVID-19 pandemic has affected most components of health systems including rehabilitation. The study aims to compare demographic and clinical data of patients admitted to an intensive rehabilitation unit (IRU) after severe acquired brain injuries (sABIs), before and during the pandemic. MATERIALS AND METHODS: In this observational retrospective study, all patients admitted to the IRU between 2017 and 2020 were included. Demographics were collected, as well as data from the clinical and functional assessment at admission and discharge from the IRU. Patients were grouped in years starting from March 2017, and the 2020/21 cohort was compared to those admitted between March 2017/18, 2018/19, and 2019/20. Lastly, the pooled cohort March 2017 to March 2020 was compared with the COVID-19 year alone. RESULTS: This study included 251 patients (F: 96 (38%): median age 68 years [IQR = 19.25], median time post-onset at admission: 42 days, [IQR = 23]). In comparison with the pre-pandemic years, a significant increase of hemorrhagic strokes (p < 0.001) and a decrease of traumatic brain injuries (p = 0.048), a reduction of the number of patients with a prolonged disorder of consciousness admitted to the IRU (p < 0.001) and a lower length of stay (p < 0.001) were observed in 2020/21. CONCLUSIONS: These differences in the case mix of sABI patients admitted to IRU may be considered another side-effect of the pandemic. Facing this health emergency, rehabilitation specialists need to adapt readily to the changing clinical and functional needs of patients' addressing the IRUs.

Predicting SARS-CoV-2 infection duration at hospital admission:a deep learning solution.

COVID-19 cases are increasing around the globe with almost 5 million of deaths. We propose here a deep learning model capable of predicting the duration of the infection by means of information available at hospital admission. A total of 222 patients were enrolled in our observational study. Anagraphical and anamnestic data, COVID-19 signs and symptoms, COVID-19 therapy, hematochemical test results, and prior therapies administered to patients are used as predictors. A set of 55 features, all of which can be taken in the first hours of the patient's hospitalization, was considered. Different solutions were compared achieving the best performance with a sequential convolutional neural network-based model merged in an ensemble with two different meta-learners linked in cascade. We obtained a median absolute error of 2.7 days (IQR = 3.0) in predicting the duration of the infection; the error was equally distributed in the infection duration range. This tool could preemptively give an outlook of the COVID-19 patients' expected path and the associated hospitalization effort. The proposed solution could be viable in tackling the huge burden and the logistics complexity of hospitals or rehabilitation centers during the pandemic waves. With data taken ad admission, entering a PCA-based feature selection, a k-fold cross-validated CNN-based model was implemented. After external texting, a median absolute error of 2.7 days [IQR = 3 days].

Quantitative Analysis of Performance Recovery in Semi-Professional Football Players after the COVID-19 Forced Rest Period.

This study proposes the instrumental analysis of the physiological and biomechanical adaptation of football players to a fatigue protocol during the month immediately after the COVID-19 lockdown, to get insights into fitness recovery. Eight male semi-professional football players took part in the study and filled a questionnaire about their activity during the lockdown. At the resumption of activities, the mean heart rate and covered distances during fatiguing exercises, the normalized variations of mean and maximum exerted power in the Wingate test and the Bosco test outcomes (i.e., maximum height, mean exerted power, relative strength index, leg stiffness, contact time, and flight time) were measured for one month. Questionnaires confirmed a light-intensity self-administered physical activity. A significant effect of fatigue (Wilcoxon signed-rank test p < 0.05) on measured variables was confirmed for the four weeks. The analysis of the normalized variations of the aforementioned parameters allowed the distinguishing of two behaviors: downfall in the first two weeks, and recovery in the last two weeks. Instrumental results suggest a physiological and ballistic (i.e., Bosco test outcomes) recovery after four weeks. As concerns the explosive skills, the observational data are insufficient to show complete recovery.

The methodology of a "living" COVID-19 registry development in a clinical context.

OBJECTIVE: The aim of this study was to describe an innovative methodology of a registry development, constantly updated for the scientific assessment and analysis of the health status of the population with COVID-19. STUDY DESIGN AND SETTING: A methodological study design to develop a multi-site, Living COVID-19 Registry of COVID-19 patients admitted in Fondazione Don Gnocchi centres started in March 2020. RESULTS: The integration of the living systematic reviews and focus group methodologies led to a development of a registry which includes 520 fields filled in for 748 COVID-19 patients recruited from 17 Fondazione Don Gnocchi centres. The result is an evidence and experience-based registry, according to the evolution of a new pathology which was not known before outbreak of March 2020 and with the aim of building knowledge to provide a better quality of care for COVID-19 patients. CONCLUSION: A Living COVID-19 Registry is an open, living and up to date access to large-scale patient-level data sets that could help identifying important factors and modulating variable for recognising risk profiles and predicting treatment success in COVID-19 patients hospitalized. This innovative methodology might be used for other registries, to be sure which the data collected is an appropriate means of accomplishing the scientific objectives planned. CLINICAL TRIAL REGISTRATION NUMBER: not applicable.

Mortality and characteristics of older people dying with COVID-19 in Lombardy nursing homes, Italy: An observational cohort study.

BACKGROUND: The aim of the study was to describe the epidemiological characteristics of Nursing Homes (NHs) residents infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and to compute the related case-fatality rate. MATERIALS AND METHODS: The outcomes were mortality and case-fatality rate with related epidemiological characteristics (age, sex, comorbidity, and frailty). RESULTS: During the COVID-19 outbreak lasted from March 1 to May 7, 2020, 330 residents died in Fondazione Don Gnocchi NHs bringing the mortality rate to 27% with a dramatic increase compared to the same period of 2019, when it was 7.5%. Naso/oropharyngeal swabs resulted positive for COVID-19 in 315 (71%) of the 441of the symptomatic/exposed residents tested. The COVID-19 population was 75% female, with a 17% overall fatality rate and sex-specific fatality rates of 19% and 13% for females and males, respectively. Fifty-six percent of deaths presented SARS-CoV-2-associated pneumonia, 15% cardiovascular, and 29% miscellaneous pathologies. CONCLUSION: Patients' complexity and frailty might influence SARS-CoV-2 infection case-fatality rate estimates. A COVID-19 register is needed to study COVID-19 frail patients' epidemiology and characteristics.