How can we reward you? A compliance and reward ontology (CaRO) for eliciting quantitative reward rules for engagement in mHealth app and healthy behaviors.

OBJECTIVE: When developing mHealth apps with point reward systems, knowledge engineers and domain experts should define app requirements capturing quantitative reward patterns that reflect patient compliance with health behaviors. This is a difficult task, and they could be aided by an ontology that defines systematically quantitative behavior goals that address more than merely the recommended behavior but also rewards for partial compliance or practicing the behavior more than recommended. No ontology and algorithm exist for defining point rewards systematically. METHODS: We developed an OWL ontology for point rewards that leverages the Basic Formal Ontology, the Behaviour Change Intervention Ontology and the Gamification Domain Ontology. This Compliance and Reward Ontology (CaRO) allows defining temporal elementary reward patterns for single and multiple sessions of practicing a behavior. These could be assembled to define more complex temporal patterns for persistence behavior over longer time intervals as well as logical combinations of simpler reward patterns. We also developed an algorithm for calculating the points that should be rewarded to users, given data regarding their actual performance. A natural language generation algorithm generates from ontology instances app requirements in the form of user stories. To assess the usefulness of the ontology and algorithms, information system students who are trained to be system analysts/knowledge engineers evaluated whether the ontology and algorithms can improve the requirement elicitation of point rewards for compliance patterns more completely and correctly. RESULTS: For single-session rewards, the ontology improved formulation of two of the six requirements as well as the total time for specifying them. For multi-session rewards, the ontology improved formulation of five of the 11 requirements. CONCLUSION: CaRO is a first attempt of its kind, and it covers all of the cases of compliance and reward pattern definitions that were needed for a full-scale system that was developed as part of a large European project. The ontology and algorithm are available at https://github.com/capable-project/rewards.

The role of basophil activation test and component-resolved diagnostics in the workup of egg allergy in children at low risk for severe allergic reactions: A real-life study.

BACKGROUND: The gold standard for diagnosing egg allergy in children is the oral food challenge (OFC). However, OFCs are time-consuming and risky procedures. Our study aimed to evaluate the utility of the basophil activation test (BAT) and component-resolved diagnostic in the diagnostic workup of children with egg allergy. METHODS: Overall, 86 children aged 6 months to 17 years, suspected of egg allergy, underwent OFC with boiled egg according to international standardized protocols. BAT and specific immunoglobulin E (sIgE) testing to component egg proteins (Gal d 1-4) were also performed. RESULTS: Of the 22 children who reacted to boiled egg, only one experienced anaphylaxis during the challenge. BAT was performed in samples obtained by 75 of the 86 patients of our cohort. Egg white and yolk protein extracts induced CD63 upregulation in the egg-allergic (EA) children compared with sensitized children that tolerated boiled egg (we registered an overall mean of CD63 expression in the EA population of 44.4% [SD 34.1] for egg white and 34.7% [SD 31.3] for egg yolk vs. 12.5% [SD 19.1] and 10.0% [SD 16.0] in sensitized children). BAT could discriminate between true egg allergy and egg sensitization in our population. As a second-line diagnostic step, the positivity of BAT for egg white or Gal d 1-sIgE resulted in a 40.9% OFC reduction, especially for those with a positive outcome. CONCLUSION: The BAT may be implemented in the diagnostic workup of egg allergy in children and, in a stepwise approach, separately or combined with Gal d 1-sIgE, may predict the allergic status and reduce the number of positive OFCs in children with egg allergy at low risk for severe reactions.

Process mining for healthcare: Characteristics and challenges.

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

Lack of EULAR/ERA-EDTA response at 1 year predicts poor long-term renal outcome in patients with lupus nephritis.

OBJECTIVES: Short-term predictive endpoints of chronic kidney disease (CKD) are needed in lupus nephritis (LN). We tested response to therapy at 1 year. METHODS: We considered patients with LN who underwent renal biopsy followed by induction therapy between January 1970 and December 2016. LN was assessed using the International Society of Nephrology/Renal Pathology Society (2003) criteria and the National Institute of Health (NIH) activity and chronicity index. The renal outcome was CKD. Response was defined according to EULAR/European League Against Rheumatism/European Renal Association-European Dialysis and Transplant Association (EULAR/ERA-EDTA) recommendations: complete: proteinuria <0.5 g/24 hours, (near) normal estimated glomerular filtration rate (eGFR); partial: ≥50% proteinuria reduction to subnephrotic levels, (near) normal eGFR; and no response: all the other cases. Logistic regression analysis was employed for 12-month response and Cox regression for CKD prediction. RESULTS: We studied 381 patients (90.5% Caucasians). After 12-month therapy, 58%, 26% and 16% of patients achieved complete, partial and no response, respectively, according to EULAR/ERA-EDTA. During a median follow-up of 10.7 (IQR: 4.97-18.80) years, 53 patients developed CKD. At 15 years, CKD-free survival rate was 95.2%, 87.6% and 55.4% in patients with complete, partial and no response at 12 months, respectively (p<0.0001). CKD-free survival rates did not differ between complete and partial responders (p=0.067). Serum creatinine (HR: 1.485, 95% CI 1.276 to 1.625), eGFR (HR 0.967, 95% CI 0.957 to 0.977) and proteinuria at 12 months (HR 1.234, 95% CI 1.111 to 1.379) were associated with CKD, yet no reliable cut-offs were identified on the receiver operating characteristic curve. In multivariable analysis, no EULAR/ERA-EDTA response at 12 months (HR 5.165, 95% CI 2.770 to 7.628), low C4 (HR 1.053, 95% CI 1.019 to 1.089) and persistent arterial hypertension (HR 3.154, 95% CI 1.500 to 4.547) independently predicted CKD. CONCLUSIONS: Lack of EULAR/ERA-EDTA response at 12 months predicts CKD.

Idiopathic Retroperitoneal Fibrosis: Long-term Risk and Predictors of Relapse.

RATIONALE & OBJECTIVE: Idiopathic retroperitoneal fibrosis (IRF) is a rare disorder of unknown cause. Medical therapy can induce remission, but disease relapses are common. This study sought to characterize long-term outcomes of IRF and the factors associated with disease recurrences. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Retrospective analysis of 50 patients with IRF prospectively followed up for 8.9 (IQR, 4.7-12.7) years at a tertiary-care referral center. EXPOSURES: Demographic, clinical, treatment, and laboratory parameters, including measures of autoimmunity. OUTCOME: Disease relapse. ANALYTICAL APPROACH: Proportional hazards analysis for the subdistribution of competing risks. RESULTS: 49 patients received medical treatment and 35 underwent interventional procedures. All patients experienced a clinical response (defined as regression of disease-related symptoms and hydronephrosis, and decrease in the maximal transverse diameter of the retroperitoneal mass on computed tomography of >50%), 44 of whom responded within 1 year. The remaining 6 responded over a median of 2.95 years after starting therapy. 40 patients were alive at last observation, 1 receiving maintenance dialysis and 15 with estimated glomerular filtration rate < 60mL/min/1.73m2. Patient survival at 5, 10, and 15 years was 95%, 84%, and 68%, respectively. 19 (38%) patients had at least 1 relapse (occurring a median of 5.19 years after starting therapy), defined as an increase in serum creatinine level of at least 30% or recurrence/development of hydronephrosis and ≥20% increase in the maximal transverse diameter of the retroperitoneal mass on computed tomography. Cumulative incidences of relapse at 5, 10, and 15 years were 21%, 41%, and 48%, respectively. Baseline antinuclear antibody positivity and male sex were associated with relapse (subdistribution hazard ratios [sHRs] of 5.35 [95% CI, 2.15-13.27] and 4.94 [95% CI, 1.32-18.57], respectively), while higher corticosteroid therapy dosage at 1 year (sHR for relapse per 1-mg/d greater dosage, 0.91 [95% CI, 0.84-0.98]) and treatment with prednisone alone or with tamoxifen (sHR for relapse of 0.25 [95% CI, 0.07-0.85] vs other therapies) were associated with lower rate of relapse. LIMITATIONS: Small sample size and variable approaches to therapy. CONCLUSIONS: IRF relapses were common and were experienced more frequently by male patients. Corticosteroids alone or with tamoxifen were associated with a lower rate of relapse. The strong association of antinuclear antibody positivity with relapse supports the hypothesis of an autoimmune pathogenesis of IRF.

Supervised methods to extract clinical events from cardiology reports in Italian.

Clinical narratives are a valuable source of information for both patient care and biomedical research. Given the unstructured nature of medical reports, specific automatic techniques are required to extract relevant entities from such texts. In the natural language processing (NLP) community, this task is often addressed by using supervised methods. To develop such methods, both reliably-annotated corpora and elaborately designed features are needed. Despite the recent advances on corpora collection and annotation, research on multiple domains and languages is still limited. In addition, to compute the features required for supervised classification, suitable language- and domain-specific tools are needed. In this work, we propose a novel application of recurrent neural networks (RNNs) for event extraction from medical reports written in Italian. To train and evaluate the proposed approach, we annotated a corpus of 75 cardiology reports for a total of 4365 mentions of relevant events and their attributes (e.g., the polarity). For the annotation task, we developed specific annotation guidelines, which are provided together with this paper. The RNN-based classifier was trained on a training set including 3335 events (60 documents). The resulting model was integrated into an NLP pipeline that uses a dictionary lookup approach to search for relevant concepts inside the text. A test set of 1030 events (15 documents) was used to evaluate and compare different pipeline configurations. As a main result, using the RNN-based classifier instead of the dictionary lookup approach allowed increasing recall from 52.4% to 88.9%, and precision from 81.1% to 88.2%. Further, using the two methods in combination, we obtained final recall, precision, and F1 score of 91.7%, 88.6%, and 90.1%, respectively. These experiments indicate that integrating a well-performing RNN-based classifier with a standard knowledge-based approach can be a good strategy to extract information from clinical text in non-English languages.

Causes of late transplant failure in cyclosporine-treated kidney allograft recipients.

BACKGROUND: There is little information about very long-term outcomes of kidney allograft recipients exposed to calcineurin inhibitors. METHODS: In this single-centre retrospective study with 20-year follow-up, we analyzed data from 644 patients who underwent primary renal transplantation between 1983 and 1993. Participants were treated with a cyclosporine-based immunosuppressive scheme and had allograft function at 1 year. RESULTS: After 20 years, 15.2% patients died, 39.7% experienced allograft loss, 26.8% were alive with a functioning transplant, and 18.2% were lost to follow-up. Cardiovascular disease (30.8%), malignancy (26.6%) and infection (17.0%) were the main causes of death. Age, new-onset proteinuria > 1 g/day, major acute cardiovascular event (MACE), and malignancy were independent predictors of mortality at time-dependent multivariate analysis. Chronic rejection (63.3%), recurrent glomerulonephritis (14.0%), and nonspecific interstitial fibrosis/tubular atrophy (13.2%) were the leading cause of allograft loss. Basal disease, hepatitis C, difference between 1 year and nadir serum creatinine, new-onset proteinuria > 1 g/day, and MACE were independent predictors of transplant failure. Among patients with 20-year allograft function, we recorded the following complications: hypertension (85%), malignancy (13%), diabetes (9%), and cardiovascular disease (9%). Median serum creatinine and proteinuria were 1.4 mg/dL and 0.6 g/day, respectively. CONCLUSIONS: Prolonged use of cyclosporine may expose to several dose-related adverse events and may contribute to the development of allograft dysfunction but it does not necessarily cause relentless, progressive transplant failure if patients are carefully and consistently monitored during the follow-up.

What do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project.

BACKGROUND: To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computerized risk models. METHODS: The holistic and evidence-based CEHRES Roadmap, used to create eHealth solutions through participatory development approach, persuasive design techniques and business modelling, was adopted in the MOSAIC project to define the sequence of multidisciplinary methods organized in three phases, user needs, implementation and evaluation. The research was qualitative, the total number of participants was ninety, about five-seventeen involved in each round of experiment. RESULTS: Prediction models for the onset of T2D are built on clinical studies, while for T2D care are derived from healthcare registries. Accordingly, two set of DSSs were defined: the first, T2D Screening, introduces a novel routine; in the second case, T2D Care, DSSs can support managers at population level, and daily practitioners at individual level. In the user needs phase, T2D Screening and solution T2D Care at population level share similar priorities, as both deal with risk-stratification. End-users of T2D Screening and solution T2D Care at individual level prioritize easiness of use and satisfaction, while managers prefer the tools to be available every time and everywhere. In the implementation phase, three Use Cases were defined for T2D Screening, adapting the tool to different settings and granularity of information. Two Use Cases were defined around solutions T2D Care at population and T2D Care at individual, to be used in primary or secondary care. Suitable filtering options were equipped with "attractive" visual analytics to focus the attention of end-users on specific parameters and events. In the evaluation phase, good levels of user experience versus bad level of usability suggest that end-users of T2D Screening perceived the potential, but they are worried about complexity. Usability and user experience were above acceptable thresholds for T2D Care at population and T2D Care at individual. CONCLUSIONS: By using a holistic approach, we have been able to understand user needs, behaviours and interactions and give new insights in the definition of effective Decision Support Systems to deal with the complexity of T2D care.

Patient-Generated Health Data Integration and Advanced Analytics for Diabetes Management: The AID-GM Platform.

Diabetes is a high-prevalence disease that leads to an alteration in the patient's blood glucose (BG) values. Several factors influence the subject's BG profile over the day, including meals, physical activity, and sleep. Wearable devices are available for monitoring the patient's BG value around the clock, while activity trackers can be used to record his/her sleep and physical activity. However, few tools are available to jointly analyze the collected data, and only a minority of them provide functionalities for performing advanced and personalized analyses. In this paper, we present AID-GM, a web application that enables the patient to share with his/her diabetologist both the raw BG data collected by a flash glucose monitoring device, and the information collected by activity trackers, including physical activity, heart rate, and sleep. AID-GM provides several data views for summarizing the subject's metabolic control over time, and for complementing the BG profile with the information given by the activity tracker. AID-GM also allows the identification of complex temporal patterns in the collected heterogeneous data. In this paper, we also present the results of a real-world pilot study aimed to assess the usability of the proposed system. The study involved 30 pediatric patients receiving care at the Fondazione IRCCS Policlinico San Matteo Hospital in Pavia, Italy.

Changing patterns in clinical-histological presentation and renal outcome over the last five decades in a cohort of 499 patients with lupus nephritis.

OBJECTIVES: To evaluate changes in demographic, clinical and histological presentation, and prognosis of lupus nephritis (LN) over time. PATIENTS AND METHODS: We studied a multicentre cohort of 499 patients diagnosed with LN from 1970 to 2016. The 46-year follow-up was subdivided into three periods (P): P1 1970-1985, P2 1986-2001 and P3 2002-2016, and patients accordingly grouped based on the year of LN diagnosis. Predictors of patient and renal survival were investigated by univariate and multivariate proportional hazards Cox regression analyses. Survival curves were compared using the log-rank test. RESULTS: A progressive increase in patient age at the time of LN diagnosis (p<0.0001) and a longer time between systemic lupus erythematosus onset and LN occurrence (p<0.0001) was observed from 1970 to 2016. During the same period, the frequency of renal insufficiency at the time of LN presentation progressively decreased (p<0.0001) and that of isolated urinary abnormalities increased (p<0.0001). No changes in histological class and activity index were observed, while chronicity index significantly decreased from 1970 to 2016 (p=0.023). Survival without end-stage renal disease (ESRD) was 87% in P1, 94% in P2% and 99% in P3 at 10 years, 80% in P1 and 90% in P2 at 20 years (p=0.0019). At multivariate analysis, male gender, arterial hypertension, absence of maintenance immunosuppressive therapy, increased serum creatinine, and high activity and chronicity index were independent predictors of ESRD. CONCLUSIONS: Clinical presentation of LN has become less severe in the last years, leading to a better long-term renal survival.

Incorporating repeating temporal association rules in Naïve Bayes classifiers for coronary heart disease diagnosis.

In this paper, we develop a Naïve Bayes classification model integrated with temporal association rules (TARs). A temporal pattern mining algorithm is used to detect TARs by identifying the most frequent temporal relationships among the derived basic temporal abstractions (TA). We develop and compare three classifiers that use as features the most frequent TARs as follows: (i) representing the most frequent TARs detected within the target class ('Disease = Present'), (ii) representing the most frequent TARs from both classes ('Disease = Present', 'Disease = Absent'), (iii) representing the most frequent TARs, after removing the ones that are low-risk predictors for the disease. These classifiers incorporate the horizontal support of TARs, which defines the number of times that a particular temporal pattern is found in some patient's record, as their features. All of the developed classifiers are applied for diagnosis of coronary heart disease (CHD) using a longitudinal dataset. We compare two ways of feature representation, using horizontal support or the mean duration of each TAR, on a single patient. The results obtained from this comparison show that the horizontal support representation outperforms the mean duration. The main effort of our research is to demonstrate that where long time periods are of significance in some medical domain, such as the CHD domain, the detection of the repeated occurrences of the most frequent TARs can yield better performances. We compared the classifier that uses the horizontal support representation and has the best performance with a Baseline Classifier which uses the binary representation of the most frequent TARs. The results obtained illustrate the comparatively high performance of the classifier representing the horizontal support, over the Baseline Classifier.

Ethnic analogies and differences in fetal heart rate variability signal: A retrospective study.

AIM: We aimed to analyze computerized cardiotocographic (cCTG) parameters (including fetal heart rate baseline, short-term variability, Delta, long-term irregularity [LTI], interval index [II], low frequency [LF], movement frequency [MF], high frequency [HF], and approximate entropy [ApEn]) in physiological term pregnancies in order to correlate them with ethnic differences. The clinical meaning of numerical parameters may explain physiological or paraphysiological phenomena that occur in fetuses of different ethnic origins. METHODS: A total of 696 pregnant women, including 384 from Europe, 246 from sub-Saharan Africa, 45 from South-East Asia, and 21 from South America, were monitored from the 37th to the 41st week of gestation. Statistical analysis was performed with the analysis of variance test, Pearson correlation test and receiver-operator curves (P < 0.05). RESULTS: Our results showed statistically significant differences (P < 0.05) between white and black women for Delta, LTI, LF, MF, HF, and ApEn; between white and Asian women for Delta, LTI, MF, and the LF/(HF + MF) ratio; and between white and Latina women for Delta, LTI, and ApEn. In particular, Delta and LTI performed better in the white group than in the black, Asian, and Latina groups. Instead, LF, MF, HF, and ApEn performed better in the black than in the white group. CONCLUSION: Our results confirmed the integrity and normal functionality of both central and autonomic nervous system components for all fetuses investigated. Therefore, CTG monitoring should include both linear and nonlinear components of fetal heart rate variability in order to avoid misinterpretations of the CTG trace among ethnic groups.

Safely Addressing Patients with Atrial Fibrillation to Early Anticoagulation after Acute Stroke.

BACKGROUND: It has been widely reported that anticoagulants (ACs) are underused for primary and secondary prevention of ischemic stroke in patients with atrial fibrillation (AFib). Furthermore, precise evidence-based guidelines about the best timing for AC initiation after acute stroke are currently lacking. METHODS AND RESULTS: In this retrospective, observational study, we analyzed prescription trends in AFib patients with acute ischemic stroke who were hospitalized in four neurologic stroke units of our region (Lombardia, Italy). In-hospital antithrombotic prescription was performed in highly heterogeneous patterns. A prestroke treatment with AC was the leading factor enhancing AC prescription during hospitalization. The other factors promoting AC were male gender, younger age, lower prestroke disability and stroke severity, and smaller stroke volumes. AFib subtype influenced AC prescription only in AC-naïve patients. Interestingly, Congestive heart failure, Hypertension, Age higher than 75 years, Diabetes, previous Stroke or TIA or thromboembolism, Vascular disease, Age 64-75 years, female Sex (CHA2DS2-VASc) and Hypertension, Abnormal renal and liver function, Stroke, Bleeding, Labile INRs, Elderly, Drugs and alcohol (HAS-BLED) scores were not associated with AC prescription. However, patients who were treated with AC, including early treatment (<48 hours), showed a low rate of bleeding. CONCLUSIONS: Our findings potentially suggest that, although apparently neglecting the common risk stratification tools, our neurologists were able to select the more suitable candidates for prompt AC treatment. Further studies are needed to develop new scoring systems to aid ischemic and hemorrhagic risk estimation in the secondary prevention of stroke.

CorrelaGenes: a new tool for the interpretation of the human transcriptome.

BACKGROUND: The amount of gene expression data available in public repositories has grown exponentially in the last years, now requiring new data mining tools to transform them in information easily accessible to biologists. RESULTS: By exploiting expression data publicly available in the Gene Expression Omnibus (GEO) database, we developed a new bioinformatics tool aimed at the identification of genes whose expression appeared simultaneously altered in different experimental conditions, thus suggesting co-regulation or coordinated action in the same biological process. To accomplish this task, we used the 978 human GEO Curated DataSets and we manually performed the selection of 2,109 pair-wise comparisons based on their biological rationale. The lists of differentially expressed genes, obtained from the selected comparisons, were stored in a PostgreSQL database and used as data source for the CorrelaGenes tool. Our application uses a customized Association Rule Mining (ARM) algorithm to identify sets of genes showing expression profiles correlated with a gene of interest. The significance of the correlation is measured coupling the Lift, a well-known standard ARM index, and the χ(2) p value. The manually curated selection of the comparisons and the developed algorithm constitute a new approach in the field of gene expression profiling studies. Simulation performed on 100 randomly selected target genes allowed us to evaluate the efficiency of the procedure and to obtain preliminary data demonstrating the consistency of the results. CONCLUSIONS: The preliminary results of the simulation showed how CorrelaGenes could contribute to the characterization of molecular pathways and biological processes integrating data obtained from other applications and available in public repositories.

Clinical factors associated with statins prescription in acute ischemic stroke patients: findings from the Lombardia Stroke Registry.

BACKGROUND: Statins, due to their well-established pleiotropic effects, have noteworthy benefits in stroke prevention. Despite this, a significant proportion of high-risk patients still do not receive the recommended therapeutic regimens, and many others discontinue treatment after being started on them. The causes of non-adherence to current guidelines are multifactorial, and depend on both physicians and patients. The aim of this study is to identify the factors influencing statin prescription at Stroke Unit (SU) discharge. METHODS: This study included 12,750 patients enrolled on the web-based Lombardia Stroke Registry (LRS) from July 2009 to April 2012 and discharged alive, with a diagnosis of ischemic stroke or transient ischemic attack (TIA) and without contra-indication to statin therapy. By logistic regression analysis and classification trees, we evaluated the impact of demographic data, risk factors, tPA treatment, in-hospital procedures and complications on statin prescription rate at discharge. RESULTS: We observed a slight increase in statins prescription during the study period (from 39.1 to 43.9%). Lower age, lower stroke severity and prestroke disability, the presence of atherothrombotic/lacunar risk factors, a diagnosis of non-cardioembolic stroke, tPA treatment, the absence of in-hospital complications, with the sole exception of hypertensive fits and hyperglycemia, were the patient-related predictors of adherence to guidelines by physicians. Overall, dyslipidemia appears as the leading factor, while TOAST classification does not reach statistical significance. CONCLUSIONS: In our region, Lombardia, adherence to guidelines in statin prescription at Stroke Unit discharge is very different from international goals. The presence of dyslipidemia remains the main factor influencing statin prescription, while the presence of well-defined atherosclerotic etiopathogenesis of stroke does not enhance statin prescription. Some uncertainties about the risk/benefit of statin therapy in stroke etiology subtypes (cardioembolism, other or undetermined causes) may partially justify the underuse of statin in ischemic stroke. The differences that exist between current international guidelines may prevent a more widespread use of statin and should be clarified in a consensus.

Education in Health Informatics: Perspectives from the Italian Society for Biomedical Informatics (SIBIM).

The evolution of socio-technological habits together with the widespread demand of post-acute and chronic treatments outside hospital boundaries drove the increased demand of medical informatics experts to develop tools for and support healthcare professionals. The recent COVID-19 pandemic further highlighted the need of physicians able to manage diseases virtually and remotely. Moreover, healthcare professionals need to access to innovative techniques and procedures to manage biomedical data, cloud-based communication, and data sharing procedures, often connected to innovative devices to support an effective precision in the health treatments. In this paper we report the experiences of the Italian Biomedical Informatics Society (SIBIM), in the definition and promotion of eHealth educational topics in medical and health professions teaching programs, as well as in bioengineering schools, showing how SIBIM members' efforts have been applied towards increasing the level of eHealth contents in medical schools.

Corrigendum to "Effect of Sustained Clinical Remission on the Risk of Lupus Flares and Impaired Kidney Function in Patients With Lupus Nephritis" [Kidney International Reports Volume 9, Issue 4, April 2024, Pages 1047-1056].

[This corrects the article DOI: 10.1016/j.ekir.2024.01.016.].

Effect of Sustained Clinical Remission on the Risk of Lupus Flares and Impaired Kidney Function in Patients With Lupus Nephritis.

Introduction: This retrospective study on patients with biopsy-proven lupus nephritis (LN) aimed to assess the probability of sustained clinical remission (sCR) and to investigate sCR effects on disease flares and impaired kidney function (IKF). Methods: sCR was defined as clinical-Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) = 0 and estimated glomerular filtration rate (eGFR) >60 ml/min per 1.73 m2 lasting ≥1 year; IKF: eGFR <60 ml/min per 1.73 m2 for >3 months. We analyzed the probability of achieving and maintaining sCR, and the yearly risk of flare. Cox models were used to identify predictors of sCR and IKF with variables analyzed as time-dependent covariates when appropriate. Results: Of 303 patients followed-up with for 14.8 (interquartile range: 9.8-22) years, 257 (84.8%) achieved sCR. The probability of achieving sCR progressively increased over time reaching 90% at 15 years. Baseline age (hazard ratio [HR]: 1.017; 95% confidence interval [CI]: 0.005-1.029; P = 0.004), hydroxychloroquine intake (HR: 1.385; 95% CI: 1.051-1.825; P = 0.021), and absence of arterial hypertension (HR: 0.699; 95% CI: 0.532-0.921; P = 0.011) were independent predictors of sCR. Among patients who achieved sCR, 142 (55.3%) developed a lupus flare after a median time of 3.6 (2.3-5.9) years. In the remaining 115 patients, sCR persisted for 9.5 (5.8-14.5) years. The probability of sCR to persist at 15 years was 38%. SLE flare risk decreased to 10%, 5%, and 2% in patients with sCR lasting <5, 5 to 10, and >10 years, respectively. At the last observation, 57 patients (18.81%) had IKF. sCR achievement (HR: 0.18, P < 0.001) and its duration (HR: 0.83, P < 0.001) were protective against IKF. Conclusion: sCR is an achievable target in LN management and protects against IKF. The longer the sCR, the higher the chance of its persistence and the lower the risk of SLE flares.

Transcriptome based identification of mouse cumulus cell markers that predict the developmental competence of their enclosed antral oocytes.

BACKGROUND: The cumulus cells (CCs) enveloping antral and ovulated oocytes have been regarded as putative source of non-invasive markers of the oocyte developmental competence. A number of studies have indeed observed a correlation between CCs gene expression, embryo quality, and final pregnancy outcome. Here, we isolated CCs from antral mouse oocytes of known developmental incompetence (NSN-CCs) or competence (SN-CCs) and compared their transcriptomes with the aim of identifying distinct marker transcripts. RESULTS: Global gene expression analysis highlighted that both types of CCs share similar transcriptomes, with the exception of 422 genes, 97.6% of which were down-regulated in NSN-CCs vs. SN-CCs. This transcriptional down-regulation in NSN-CCs was confirmed by qRT-PCR analysis of CC-related genes (Has2, Ptx3, Tnfaip6 and Ptgs2). Only ten of the 422 genes were up-regulated with Amh being the most up-regulated in NSN-CCs, with an average 4-fold higher expression when analysed by qRT-PCR. CONCLUSIONS: The developmental incompetence (NSN) or competence (SN) of antral oocytes can be predicted using transcript markers expressed by their surrounding CCs (i.e., Has2, Ptx3, Tnfaip6, Ptgs2 and Amh). Overall, the regulated nature of the group of genes brought out by whole transcriptome analysis constitutes the molecular signature of CCs associated either with developmentally incompetent or competent oocytes and may represent a valuable resource for developing new molecular tools for the assessment of oocyte quality and to further investigate the complex bi-directional interaction occurring between CCs and oocyte.

Changes in circulating pro-angiogenic cytokines, other than VEGF, before progression to sunitinib therapy in advanced renal cell carcinoma patients.

OBJECTIVES: This study included a cohort of advanced renal cell carcinoma patients treated with sunitinib. Since resistance to sunitinib may be mediated through angiogenic cytokines other than VEGF, we measured the circulating levels of three pro-angiogenic cytokines: basic fibroblast growth factor (bFGF), hepatocyte growth factor (HGF), and interleukin (IL)-6. METHODS: Cytokines were measured at baseline and on the first day of each treatment cycle until progression in 85 advanced kidney cancer patients treated with sunitinib using a quantitative sandwich enzyme immunoassay (ELISA) technique. RESULTS: Even though no statistically significant differences in the titers of the three cytokines were observed between baseline and the time of progression in the whole patient cohort, in 45.3, 46.6, and 37.3% of the patients a more than 50% increase between baseline and the time of progression was shown in circulating IL-6, bFGF, and HGF, respectively. Furthermore, this increase was more than 100% in 37.3, 44, and 30.6% of the patients, respectively. We also demonstrated that, in these patients, cytokines tended to increase and to remain high immediately before progression. CONCLUSIONS: In a large percentage of kidney cancer patients, progression is preceded by a significant increase in pro-angiogenic cytokines other than VEGF.