Failure to achieve lupus low disease activity state (LLDAS) six months after diagnosis is associated with early damage accrual in Caucasian patients with systemic lupus erythematosus

Background: The aim was to assess the attainability and outcome of the lupus low disease activity state (LLDAS) in the early stages of systemic lupus erythematosus (SLE). Methods: LLDAS prevalence was evaluated at 6 (T1) and 18 (T2) months after diagnosis and treatment initiation (T0) in a monocentric cohort of 107 (median disease duration 9.7 months) prospectively followed Caucasian patients with SLE. Reasons for failure to achieve LLDAS were also investigated. Multivariate models were built to identify factors associated with lack of LLDAS achievement and to investigate the relationship between LLDAS and Systemic Lupus International Collaboration Clinics (SLICC)/Damage Index (SDI) accrual. Results: There were 47 (43.9%) patients in LLDAS at T1 and 48 (44.9%) at T2. The most frequent unmet LLDAS criterion was prednisolone dose >7.5 mg/day (83% of patients with no LLDAS at T1). Disease manifestations with the lowest remission rate during follow up were increased anti-double-stranded DNA (persistently present in 85.7% and 67.5% of cases at T1 and T2, respectively), low serum complement fractions (73.2% and 66.3%) and renal abnormalities (46.4% and 28.6%). Renal involvement at T0 was significantly associated with failure to achieve LLDAS both at T1 (OR 7.8, 95% CI 1.4-43.4; p = 0.019) and T2 (OR 3.9, 95% CI 1.4-10.6; p = 0.008). Presence of any organ damage (SDI â\u89¥1) at T2 was significantly associated with lack of LLDAS at T1 (OR 5.0, 95% CI 1.5-16.6; p = 0.009) and older age at diagnosis (OR 1.05 per year, 95% CI 1.01-1.09; p = 0.020). Conclusion: LLDAS is a promising treatment target in the early stages of SLE, being attainable and negatively associated with damage accrual, but it fit poorly to patients with renal involvement

Assessment of energetic, economic and environmental performance of ground-coupled heat pumps

Ground-coupled heat pumps (GCHPs) have a great potential for reducing the cost and climate change impact of building heating, cooling, and domestic hot water (DHW). The high installation cost is a major barrier to their diffusion but, under certain conditions (climate, building use, alternative fuels, etc.), the investment can be profitable in the long term. We present a comprehensive modeling study on GCHPs, performed with the dynamic energy simulation software TRNSYS, reproducing the operating conditions of three building types (residential, office, and hotel), with two insulation levels of the building envelope (poor/good), with the climate conditions of six European cities. Simulation results highlight the driving variables for heating/cooling peak loads and yearly demand, which are the input to assess economic performance and environmental benefits of GCHPs. We found that, in Italy, GCHPs are able to reduce CO2 emissions up to 216 g CO2/year per euro spent. However, payback times are still quite high, i.e., from 8 to 20 years. This performance can be improved by changing taxation on gas and electricity and using hybrid systems, adding a fossil-fuel boiler to cover peak heating loads, thus reducing the overall installation cost compared to full-load sized GCHP systems

Severe neuropsychiatric systemic lupus erythematosus successfully treated with rituximab: An alternative to standard of care

Demyelinating syndrome secondary to systemic lupus erythematosus (DS-SLE) is a rare encephalomyelitis burden with a high risk of disability and death. We report on a 49-year-old Caucasian woman with systemic lupus erythematosus (SLE) complicated by severe cognitive dysfunction, brainstem disease, cranial nerve palsies, weakness and numbness in limbs and multiple discrete magnetic resonance imaging (MRI) areas of damage within the white matter of semioval centers, temporal lobe, external capsule, claustrum, subinsular regions and midbrain. She also had multiple mononeuritis diagnosed through sensory and motor nerve conduction study. She was diagnosed with severe DS-SLE prominently involving the brain and was treated with 500 mg methylprednisolone (PRE) pulses for 3 consecutive days, followed by one single pulse of 500 mg cyclophosphamide, and 1 g rituximab, which was then repeated 14 days later. PRE 25 mg/day, rapidly tapered to 7.5 mg/day in 6 months, and mycophenolate mofetil 1 g/day were prescribed as maintenance therapy. She had progressive and sustained improvement in neurological symptoms with almost complete resolution of brain MRI lesions after 1 year. B-cell depleting therapy could be considered as a possible alternative to standard of care in the management of severe inflammatory neuropsychiatric SLE but it should be associated with a conventional immunosuppressant as maintenance treatment to reduce the risk of flare and reduce corticosteroids dose

Polymyalgia rheumatica: an autoinflammatory disorder?

Polymyalgia rheumatica: an autoinflammatory disorder

A convex optimization approach for automated water and energy end use disaggregation

A detailed knowledge of water consumption at an end-use level is an essential requirement to design and evaluate the efficiency of water saving policies. In the last years, this has led to the development of automated tools to disaggregate high resolution water consumption data at the household level into end use categories. In this work, a new disaggregation algorithm is presented. The proposed algorithm is based on the assumption that the disaggregated signals to be identified are piecewise constant over the time and it exploits the information on the time-of-day probability in which a specific water use event might occur. The disaggregation problem is formulated as a convex optimization problem, whose solution can be efficiently computed through numerical solvers. Specifically, the disaggregation problem is treated as a least-square error minimization problem, with an additional (convex) penalty term aiming at enforcing the disaggregate signals to be piece-wise constant over the time. The proposed disaggregation algorithm has been initially tested against household electricity data available in the literature. The obtained results look promising and similar results are expected to be obtained for water data

Benefits and challenges of using smart meters for advancing residential water demand modeling and management: a review

Over the last two decades, water smart metering programs have been launched in a number of medium to large cities worldwide to nearly continuously monitor water consumption at the single household level. The availability of data at such very high spatial and temporal resolution advanced the ability in characterizing, modeling, and, ultimately, designing user-oriented residential water demand management strategies. Research to date has been focusing on one or more of these aspects but with limited integration between the specialized methodologies developed so far. This manuscript is the first comprehensive review of the literature in this quickly evolving water research domain. The paper contributes a general framework for the classification of residential water demand modeling studies, which allows revising consolidated approaches, describing emerging trends, and identifying potential future developments. In particular, the future challenges posed by growing population demands, constrained sources of water supply and climate change impacts are expected to require more and more integrated procedures for effectively supporting residential water demand modeling and management in several countries across the world

Prognostic impact of coronary microcirculation abnormalities in systemic sclerosis: a prospective study to evaluate the role of non-invasive tests

INTRODUCTION: Microcirculation dysfunction is a typical feature of systemic sclerosis (SSc) and represents the earliest abnormality of primary myocardial involvement. We assessed coronary microcirculation status by combining two functional tests in SSc patients and estimating its impact on disease outcome. METHODS: Forty-one SSc patients, asymptomatic for coronary artery disease, were tested for coronary flow velocity reserve (CFR) by transthoracic-echo-Doppler with adenosine infusion (A-TTE) and for left ventricular wall motion abnormalities (WMA) by dobutamine stress echocardiography (DSE). Myocardial multi-detector computed tomography (MDCT) enabled the presence of epicardial stenosis, which could interfere with the accuracy of the tests, to be excluded. Patient survival rate was assessed over a 6.7- ± 3.5-year follow-up. RESULTS: Nineteen out of 41 (46%) SSc patients had a reduced CFR (≤2.5) and in 16/41 (39%) a WMA was observed during DSE. Furthermore, 13/41 (32%) patients showed pathological CFR and WMA. An inverse correlation between wall motion score index (WMSI) during DSE and CFR value (r = -0.57, P <0.0001) was observed; in addition, CFR was significantly reduced (2.21 ± 0.38) in patients with WMA as compared to those without (2.94 ± 0.60) (P <0.0001). In 12 patients with abnormal DSE, MDCT was used to exclude macrovasculopathy. During a 6.7- ± 3.5-year follow-up seven patients with abnormal coronary functional tests died of disease-related causes, compared to only one patient with normal tests. CONCLUSIONS: A-TTE and DSE tests are useful tools to detect non-invasively pre-clinical microcirculation abnormalities in SSc patients; moreover, abnormal CFR and WMA might be related to a worse disease outcome suggesting a prognostic value of these tests, similar to other myocardial diseases

Predictors of musculoskeletal flares and Jaccoud׳s arthropathy in patients with systemic lupus erythematosus: A 5-year prospective study

Objective To investigate the prognostic value of US in predicting musculoskeletal flares and Jaccoud׳s arthropathy (JA) in systemic lupus erythematosus (SLE). Methods A total of 80 out of 94 patients (76 female; age 45.5 ± 13.2 years) with non-deforming non-erosive (NDNE) arthritis and 48/60 healthy controls (42 female; age 49.6 ± 11.6 years) completed the 5-year follow-up study. Each patient was prospectively assessed for the occurrence of musculoskeletal flares using BILAG2004 and hand deformities according to Jaccoud׳s articular index. Baseline clinical, serological, semi-quantitative (0–3 scale) ultrasound (US) findings, PD-synovitis and PD-tenosynovitis scores were used as covariates to identify predictors of study outcomes. Short Form 36 v2 (SF36v2) health survey questionnaire was administered. Results Overall, 12 MS flares in 10 (12.5%) patients were recorded and the incidence rate was 3.0 per 100 patient-year. Baseline PD-synovitis score independently predicted MS flare (p < 0.001; RR = 2.0; 95% CI: 1.4–3.0) within 2 years since US examination. In all, 5 (6.2%) patients developed JA whose incidence rate was 1.25 per 100 patient-year. Independent risk factors for development of JA were higher longitudinal BILAG score in the musculoskeletal domain (p = 0.005; RR = 2.4; 95% CI: 1.3–4.6) and longer disease duration (p = 0.013; RR 1.2; 95% CI: 1.1–1.3). JA and active musculoskeletal inflammation (BILAG ≥ C), but not US erosions, were associated with lower results in SF36v2 physical and mental summary components. Conclusions Performing musculoskeletal US can be useful in order to predict MS flares. Jaccoud׳s deformities may arise in patients with long-standing SLE and prolonged, even subclinical, joint and tendon inflammation

Modelling residential water consumers’ behaviors by feature selection and feature weighting

Identifying the most relevant determinants of water consuming or saving behaviors at the household level is key to building mathematical models that predict urban water demand variability in space and time and to explore the effects of different Water Demand Management Strategies for the residential sector. This work contributes a novel approach based on feature selection and feature weighting to model the single-user consumption behavior at the household level. A two-step procedure consisting of the extraction of the most relevant determinants of users’ consumption and the identification of a predictive model of water consumers’ profile is proposed and tested on a real case study. Results show the effectiveness of the proposed method in capturing the influence of candidate determinants on residential water consumption, as well as in attaining sufficiently accurate predictions of users’ consumption profiles, which constitutes essential information to support residential water demand management