Usefulness of lung ultrasound for selecting asymptomatic older patients with COVID 19 pneumonia.

Clinical and prognostic differences between symptomatic and asymptomatic older patients with COVID-19 are of great interest since frail patients often show atypical presentation of illness. Lung Ultrasound (LUS) has been proven to be a reliable tool for detecting early-phase COVID-19 pneumonic alterations. The current prospective bicentric study aimed to compare LUS score and 3-month overall mortality between asymptomatic and symptomatic older patients with COVID-19, according to frailty status. Patients were stratified according to LUS score tertiles and Clinical Frailty Scale categories. Survival rate was assessed by telephone interviews 3 months after discharge. 64 symptomatic (24 women, aged 80.0 ± 10.8 years) and 46 asymptomatic (31 women, aged 84.3 ± 8.8 years) were consecutively enrolled. LUS score resulted an independent predictor of 3-month mortality [OR 2.27 (CI95% 1.09-4.8), p = 0.03], and the highest mortality rate was observed in symptomatic and asymptomatic pre-frail and frail patients (70.6% and 66.7%, respectively) with greater LUS abnormalities (3rd tertile). In conclusion, LUS identified an acute interstitial lung involvement in most of the older asymptomatic patients. Mortality rate progressively increased according to clinical frailty and LUS score degree, resulting a reliable prognostic tool in both symptomatic and asymptomatic patients.

A Bayesian approach for the identification of patient-specific parameters in a dialysis kinetic model.

Hemodialysis is the most common therapy to treat renal insufficiency. However, notwithstanding the recent improvements, hemodialysis is still associated with a non-negligible rate of comorbidities, which could be reduced by customizing the treatment. Many differential compartment models have been developed to describe the mass balance of blood electrolytes and catabolites during hemodialysis, with the goal of improving and controlling hemodialysis sessions. However, these models often refer to an average uremic patient, while on the contrary the clinical need for customization requires patient-specific models. In this work, we assume that the customization can be obtained by means of patient-specific model parameters. We propose and validate a Bayesian approach to estimate the patient-specific parameters of a multi-compartment model, and to predict the single patient's response to the treatment, in order to prevent intra-dialysis complications. The likelihood function is obtained by means of a discretized version of the multi-compartment model, where the discretization is in terms of a Runge-Kutta method to guarantee convergence, and the posterior densities of model parameters are obtained through Markov Chain Monte Carlo simulation. Results show fair estimations and the applicability in the clinical practice.

Assessment of intradialysis calcium mass balance by a single pool variable-volume calcium kinetic model.

INTRODUCTION: A reliable method of intradialysis calcium mass balance quantification is far from been established. We herein investigated the use of a single-pool variable-volume Calcium kinetic model to assess calcium mass balance in chronic and stable dialysis patients. METHODS: Thirty-four patients on thrice-weekly HD were studied during 240 dialysis sessions. All patients were dialyzed with a nominal total calcium concentration of 1.50 mmol/L. The main assumption of the model is that the calcium distribution volume is equal to the extracellular volume during dialysis. This hypothesis is assumed valid if measured and predicted end dialysis plasma water ionized calcium concentrations are equal. A difference between predicted and measured end-dialysis ionized plasma water calcium concentration is a deviation on our main hypothesis, meaning that a substantial amount of calcium is exchanged between the extracellular volume and a nonmodeled compartment. FINDINGS: The difference between predicted and measured values was 0.02 mmol/L (range -0.08:0.16 mmol/L). With a mean ionized dialysate calcium concentration of 1.25 mmol/L, calcium mass balance was on average negative (mean ± SD -0.84 ± 1.33 mmol, range -5.42:2.75). Predialysis ionized plasma water concentration and total ultrafiltrate were the most important predictors of calcium mass balance. A significant mobilization of calcium from the extracellular pool to a nonmodeled pool was calculated in a group of patients. DISCUSSION: The proposed single pool variable-volume Calcium kinetic model is adequate for prediction and quantification of intradialysis calcium mass balance, it can evaluate the eventual calcium transfer outside the extracellular pool in clinical practice.

Prediction models for exacerbations in patients with COPD.

Personalised medicine aims to tailor medical decisions to the individual patient. A possible approach is to stratify patients according to the risk of adverse outcomes such as exacerbations in chronic obstructive pulmonary disease (COPD). Risk-stratified approaches are particularly attractive for drugs like inhaled corticosteroids or phosphodiesterase-4 inhibitors that reduce exacerbations but are associated with harms. However, it is currently not clear which models are best to predict exacerbations in patients with COPD. Therefore, our aim was to identify and critically appraise studies on models that predict exacerbations in COPD patients. Out of 1382 studies, 25 studies with 27 prediction models were included. The prediction models showed great heterogeneity in terms of number and type of predictors, time horizon, statistical methods and measures of prediction model performance. Only two out of 25 studies validated the developed model, and only one out of 27 models provided estimates of individual exacerbation risk, only three out of 27 prediction models used high-quality statistical approaches for model development and evaluation. Overall, none of the existing models fulfilled the requirements for risk-stratified treatment to personalise COPD care. A more harmonised approach to develop and validate high- quality prediction models is needed to move personalised COPD medicine forward.

Patient-specific modeling of multicompartmental fluid and mass exchange during dialysis.

BACKGROUND: Dialysis is associated with a non-negligible rate of morbidity, requiring treatment customization. Many mathematical models have been developed describing solute kinetics during hemodialysis (HD) for an average uremic patient. The clinical need can be more adequately addressed by developing a patient-specific, multicompartmental model. MATERIALS AND METHODS: The data from 148 sessions (20 patients), recorded at the Regional Hospital of Lugano, Switzerland, were used to develop and validate the mathematical model. Diffusive and convective interactions among patient, dialysate and substitution fluid were considered. Three parameters, related to mass transfer efficiency at the cell membrane, at the dialyzer and at the capillary wall, were used to tune the model. The ability of the model to describe the clinical evolution of a specific HD session was evaluated by comparing model outputs with clinically acquired data on solutes and catabolite concentrations. RESULTS: The model developed in this study allows electrolyte and catabolite concentration trends during each HD session to be described. The errors obtained before the estimation of the patient-specific parameters drastically decrease after their identification. With the optimized model, plasmatic concentration trends can be described with an average percent error lower than 2.1% for Na+, Cl-, Ca2+ and HCO3-, lower than 5% for K+ and lower than 8% for urea. CONCLUSIONS: The peculiarity of the proposed model is the possibility it offers to perform a real-time simulation enabling quantitative appraisal of hematochemical quantities whose direct measurement is prohibitive. These will be beneficial to dialysis therapy planning, reducing intradialysis complications and improving patients' quality of life.

How to extract clinically useful information from large amount of dialysis related stored data.

The basic storage infrastructure used to gather data from the technological evolution also in the healthcare field was leading to the storing into public or private repository of even higher quantities of data related to patients and their pathological evolution. Big data techniques are spreading also in medical research. By these techniques is possible extract information from complex heterogeneous sources, realizing longitudinal studies focused to correlate the patient status with biometric parameters. In our work we develop a common data infrastructure involving 4 clinical dialysis centers between Lombardy and Switzerland. The common platform has been build to store large amount of clinical data related to 716 dialysis session of 70 patient. The platform is made up by a combination of a MySQL(®) database (Dialysis Database) and a MATLAB-based mining library (Dialysis MATlib). A statistical analysis of these data has been performed on the data gathered. These analyses led to the development of two clinical indexes, representing an example of transformation of big data into clinical information.

Water security in Uzbekistan: implication of return waters on the Amu Darya water quality.

GOAL, SCOPE AND BACKGROUND: Amu Darya river, one of the main water resources of Uzbekistan, shows a relevant longitudinal enrichment of soluble contents which strongly limits the human uses of its waters. Because of the low natural run-off processes, salts and pollutants are mainly driven to the river by the return waters used for washing and irrigating the surrounding lands. The influence of return waters on stream quality is dramatically relevant in the lower reaches of the river where almost all the flowing waters have been previously used for the agriculture practises. To provide analytical evidence on the potential effects of return waters on the quality of the Amu Darya river, the paper reports and comments data on salinity and metals contents of the waters flowing in the artificial channel network of Bukhara and in the Amu Darya river, from Bukhara up to the dam forming the Tuyamuyn Hydro Complex (THC). METHODS: A total of 15 sampling sites were selected for the analytical survey: Two sites were located on the Amu Darya river downstream from the inflow of the return waters from Bukhara, two in the river entering in the THC, and three downstream from the dam forming the reservoir complex. The waters entering and leaving the Bukhara agricultural area were sampled in two main collectors, while the waters flowing in the channel system were sampled in six distinct collectors. The following parameters were considered in the survey: pH, Oxygen, Hardness, Salinity, Conductivity, P-PO4(3-), P tot, N tot, N-NO3(2-), N-NO2-, COD, Ca2+, Mg2+, Fe, Mn, Zn, Cr, Cu, Ni, Cd, Pb. RESULTS AND DISCUSSION: Salt concentrations below 1000 mg/l were measured in the Amu Darya waters upstream to Bukhara. In the drainage system, salinity exceeds the palatability limit and reaches the maximum peak of 3200 mg/l in the outflow collector. Due to dilution effects, salinity returns to lower values (400-700 mg/l) along the Amu Darya river downstream from Bukhara; calcium and magnesium resulted the major constituents of the overall salinity. No serious metal contaminations were detected in the waters entering and leaving the examined channel system. Differently, the Amu Darya waters upstream to the THC showed a relevant metal contamination, with Cr, Ni, Fe concentrations exceeding the limits for human consumption. In the downstream sites, located in the Tuyamuyn Hydro Complex and in the Amu Darya river flowing out from this reservoir, excluding Fe, all the examined metals showed lover concentrations and values below the normative limits. CONCLUSION: The direct human consumption of the lower Amu Darya waters is strongly limited by salinity and by metal contamination. Although the salinity of the return waters from the Bukhara drainage system results in above normal limits, no corresponding increases were measured in the Amu Darya river downstream from the return water inflow at the time of the survey. As for the metal contamination of the Amu Darya river, the survey revealed the presence of relevant sources of metal contamination downstream from Bukhara external to the agricultural drainage system. This contamination resulted in reduced sedimentation processes taking place in the limnetic zones of the Amu Darya river upstream to the dam forming the Tuyamuyn Hydro Complex. RECOMMENDATION AND OUTLOOK: To fully understand the longitudinal increase of Amu Darya salinity, an evaluation of the cumulative effects of the loads from the main agricultural areas is required, also by using mass-balance models. As for the metals, an investigation should be addressed to identify the anthropogenic sources of contaminations present in the lower Amu Darya region and the metal loads should be diverted.