Since February 21 2020, when the Italian National Institute of Health (Istituto Superiore di Sanità–ISS) reported the first autochthonous case of infection, a dedicated surveillance system for ...SARS‐CoV‐2‐positive (COVID+) cases has been created in Italy. These data were cross‐referenced with those inside the Information Transplant System in order to assess the cumulative incidence (CI) and the outcome of SARS‐COV‐2 infection in solid organ transplant recipients (SOTRs) who are assumed to be most at risk. We compared our results with those of COVID+ nontransplanted patients (Non‐SOTRs) with follow‐up through September 30, 2020. The CI of SARS‐CoV‐2 infection in SOTRs was 1.02%, higher than in COVID+ Non‐SOTRs (0.4%, p < .05) with a greater risk in the Lombardy region (2.89%). The CI by type of organ transplant was higher for heart (CI 1.57%, incidence rate ratio IRR 1.36) and lower for liver (CI 0.63%, IRR 0.54). The 60‐day CI of mortality was 30.6%, twice as much that of COVID+ Non‐SOTRs (15.4%) with a 60‐day gender and age adjusted odds ratio (adjusted‐OR) of 3.83 for COVID+ SOTRs (95% confidence interval 3.03–4.85). The lowest 60‐day adjusted‐OR was observed in liver SOTRs (OR 0.46, 95% confidence interval 0.25–0.86). More detailed studies on disease management and evolution will be necessary in these patients at greater risk of COVID‐19.
In Italy, SARS‐CoV‐2 infection risk for solid organ recipients compared to the general population is two times higher and mortality risk is four times higher, with heart recipients at the highest risk of infection and liver recipients at the lowest risk of both infection and mortality.
To assess the role of body mass index (BMI) and of the rate of weight loss as prognostic factors in amyotrophic lateral sclerosis (ALS) and to explore the clinical correlates of weight loss in the ...early phases of the disease.
The study cohort included all ALS patients in Piemonte/Valle d'Aosta in the 2007-2011 period. Overall survival and the probability of death/tracheostomy at 18 months (logistic regression model) were calculated.
Of the 712 patients, 620 (87.1%) were included in the study. Patients ' survival was related to the mean monthly percentage of weight loss at diagnosis (p<0.0001), but not to pre-morbid BMI or BMI at diagnosis. Spinal onset patients with dysphagia at diagnosis had a median survival similar to bulbar onset patients. About 20% of spinal onset patients without dysphagia at diagnosis had severe weight loss and initial respiratory impairment, and had a median survival time similar to bulbar onset patients.
The rate of weight loss from onset to diagnosis was found to be a strong and independent prognostic factor in ALS. Weight loss was mainly due to the reduction of nutritional intake related to dysphagia, but a subgroup of spinal onset patients without dysphagia at diagnosis had a severe weight loss and an outcome similar to bulbar patients. According to our findings, we recommend that in clinical trials patients should be stratified according to the presence of dysphagia at the time of enrolment and not by site of onset of symptoms.
Objective
To employ Artificial Intelligence to model, predict and simulate the amyotrophic lateral sclerosis (ALS) progression over time in terms of variable interactions, functional impairments, and ...survival.
Methods
We employed demographic and clinical variables, including functional scores and the utilisation of support interventions, of 3940 ALS patients from four Italian and two Israeli registers to develop a new approach based on Dynamic Bayesian Networks (DBNs) that models the ALS evolution over time, in two distinct scenarios of variable availability. The method allows to simulate patients’ disease trajectories and predict the probability of functional impairment and survival at different time points.
Results
DBNs explicitly represent the relationships between the variables and the pathways along which they influence the disease progression. Several notable inter-dependencies were identified and validated by comparison with literature. Moreover, the implemented tool allows the assessment of the effect of different markers on the disease course, reproducing the probabilistically expected clinical progressions. The tool shows high concordance in terms of predicted and real prognosis, assessed as time to functional impairments and survival (integral of the AU-ROC in the first 36 months between 0.80–0.93 and 0.84–0.89 for the two scenarios, respectively).
Conclusions
Provided only with measurements commonly collected during the first visit, our models can predict time to the loss of independence in walking, breathing, swallowing, communicating, and survival and it can be used to generate in silico patient cohorts with specific characteristics. Our tool provides a comprehensive framework to support physicians in treatment planning and clinical decision-making.
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