This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O₂ saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching an appreciable accuracy. Finally, interpretable decision rules for estimating the risk of mortality of patients can be obtained from the decision tree, which can be crucial in the prioritization of medical care and resources.

Knee osteoarthritis is a chronic joint disease which damages articular cartilage. In its severe stages, it results in impairments in balance and muscle strength loss, which affect daily life activities such as walking or climbing stairs. This study sought to investigate associated factors with stair-climbing ability in this population, with special interest in measuring the relevance of postural balance for this task. Forty-four patients scheduled to undergo unilateral total knee arthroplasty were assessed. Timed up and go test, stair ascent–descent test, three different isometric strength tests (knee flexion, knee extension and hip abduction), active knee extension and flexion range of movement and static postural balance assessment were evaluated. Spearman’s correlation coefficients and multiple linear regression analysis determined the strength of association between the different variables and stair-climbing time. No significant association between the stair-climbing time and static balance was found. Significant associations were found between stair-climbing time and timed up and go (r = 0.71; p < 0.0001) and maximal knee extensor strength (r = –0.52; p = 0.0003). One-year increase in age was associated with 0.15 s (95% CI 0.00 to 0.30) slower stair-climbing time. In conclusion, muscle strength is more important than postural balance for stair-climbing ability in this population.

Elbow tendinopathy is a common pathology of the upper extremity that impacts both athletes and workers. Some research has examined the genetic component as a risk factor for tendinopathy, mainly in the lower limbs. A case-control study was designed to test for a relationship between certain collagen gene single nucleotide polymorphisms (SNPs) and elbow tendon pathology. A sample of 137 young adult athletes whose sports participation involves loading of the upper limb were examined for the presence of structural abnormalities indicative of pathology in the tendons of the lateral and medial elbow using ultrasound imaging and genotyped for the following SNPs: COL5A1 rs12722, COL11A1 rs3753841, COL11A1 rs1676486, and COL11A2 rs1799907. Anthropometric measurements and data on participants’ elbow pain and dysfunction were collected using the Disabilities of the Arm, Shoulder and Hand and the Mayo Clinic Performance Index for the Elbow questionnaires. Results showed that participants in the structural abnormality group had significantly higher scores in pain and dysfunction. A significant relationship between COL11A1 rs3753841 genotype and elbow tendon pathology was found (p = 0.024), with the CT variant associated with increased risk of pathology.

Asthma is a chronic respiratory disease that significantly impacts quality of life. Pulmonary rehabilitation has been shown to improve lung function and symptoms in asthma, but its adoption is limited due to accessibility and patient engagement challenges. Virtual reality (VR) and videogaming technologies have emerged as potential tools to enhance pulmonary rehabilitation by providing an engaging and interactive environment. This systematic review aimed to evaluate the effectiveness, feasibility, safety, and patient engagement of VR and videogaming in pulmonary rehabilitation for individuals with asthma. A comprehensive search of seven electronic databases (PubMed, Embase, CINAHL, Cochrane, AMED, SPORTDiscus and PEDro) was conducted to identify studies that included VR and videogaming interventions. Studies included participants with asthma and used VR or videogaming as part of pulmonary rehabilitation. Data extraction focused on intervention types, clinical outcomes, patient engagement, and safety. Five studies were included in the final review and involved 104 participants. The studies implemented different digital tools, including the InSpire System, and games such as “Reflex Ridge” and “Serious Games”. VR and videogaming interventions improved asthma control, lung function, and exercise capacity. High levels of patient engagement and adherence were reported, with no adverse events across the trial. VR and videogaming show promise as effective, feasible, and safe tools to enhance pulmonary rehabilitation in individuals with asthma. However, the heterogeneity of studies limited the ability to draw definitive conclusions, with further research needed using standardized outcomes.

The basis of all clinical science developments is the analysis of the data obtained from a particular problem. In recent decades, however, the capacity of computers to process data has been increasing exponentially, which has created the possibility of applying more powerful methods of data analysis. Among these methods, the multidimensional visual data mining methods are outstanding. These methods show all the variables of one particular problem on the whole allowing to the clinical specialist to extract his own conclusions. In this chapter, a neural approximation to this kind of data mining is shown by means of the valuation analysis of the knee in athletes in the pre- and post-surgery of the anterior cruciate ligament, studying variables of force and measurements at different distances of the knee.