Factors associated with blood cord unit bankability: an analysis of a 15-year-long case series.

Blood banking is a long and complex process requiring an accurate screening of potential donors and high-quality control systems. Previous studies in literature investigated factors potentially determining a higher cell levels with the aim of optimizing donors' selection and improving banking process. This study aims to identify factors associated with the concentration of stem cells in umbilical cord blood, so increasing the probability of bankability, focusing on the possible implications in terms of obstetric and resources management. This is a retrospective study conducted in the Obstetric Units of two Italian Hospitals in Montebelluna and Castelfranco Veneto. Study has been conducted on cord blood units banked between 1999 and 2015. Data on medical histories and clinical characteristics of mother and baby have been retrieved via a retrospective examination of medical records. A total of 869 cord blood units were studied. At multivariable analysis, in agreement with literature, birthweight and placental weight have been found to be associated with higher concentration of total nucleated cells. As additional factor, amount of fluid infused was associated with cord blood units' count. This study is the first one to clearly identify the role of fluid infusion on cord blood units' counts in addition to placental weight and delivery. Some non-modifiable features can help in predicting bankability from pre-natal aspects to factors more related with obstetric management is suggested.

Association of Pharmacological Treatments With Long-term Pain Control in Patients With Knee Osteoarthritis: A Systematic Review and Meta-analysis.

Importance: Even though osteoarthritis is a chronic and progressive disease, pharmacological agents are mainly studied over short-term periods, resulting in unclear recommendations for long-term disease management. Objective: To search, review, and analyze long-term (≥12 months) outcomes (symptoms, joint structure) from randomized clinical trials (RCTs) of medications for knee osteoarthritis. Data Sources and Study Selection: The databases of MEDLINE, Scopus, EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials were searched until June 30, 2018 (MEDLINE alerts through August 31, 2018) for RCTs of patients with knee osteoarthritis that had treatment and follow-up lasting 1 year or longer. Data Extraction and Synthesis: Data at baseline and at the longest available treatment and follow-up of 12 months' duration or longer (or the change from baseline) were extracted. A Bayesian random-effects network meta-analysis was performed. Main Outcomes and Measures: The primary outcome was the mean change from baseline in knee pain. Secondary outcomes were physical function and joint structure (the latter was measured radiologically as joint space narrowing). Standardized mean differences (SMDs) and mean differences with 95% credibility intervals (95% CrIs) were calculated. Findings were interpreted as associations when the 95% CrIs excluded the null value. Results: Forty-seven RCTs (22 037 patients; mean age range, mostly 55-70 years; and a higher mean proportion of women than men, around 70%) included the following medication categories: analgesics; antioxidants; bone-acting agents such as bisphosphonates and strontium ranelate; nonsteroidal anti-inflammatory drugs; intra-articular injection medications such as hyaluronic acid and corticosteroids; symptomatic slow-acting drugs in osteoarthritis such as glucosamine and chondroitin sulfate; and putative disease-modifying agents such as cindunistat and sprifermin. Thirty-one interventions were studied for pain, 13 for physical function, and 16 for joint structure. Trial duration ranged from 1 to 4 years. Associations with decreases in pain were found for the nonsteroidal anti-inflammatory drug celecoxib (SMD, -0.18 [95% CrI, -0.35 to -0.01]) and the symptomatic slow-acting drug in osteoarthritis glucosamine sulfate (SMD, -0.29 [95% CrI, -0.49 to -0.09]), but there was large uncertainty for all estimates vs placebo. The association with pain improvement remained significant only for glucosamine sulfate when data were analyzed using the mean difference on a scale from 0 to 100 and when trials at high risk of bias were excluded. Associations with improvement in joint space narrowing were found for glucosamine sulfate (SMD, -0.42 [95% CrI, -0.65 to -0.19]), chondroitin sulfate (SMD, -0.20 [95% CrI, -0.31 to -0.07]), and strontium ranelate (SMD, -0.20 [95% CrI, -0.36 to -0.05]). Conclusions and Relevance: In this systematic review and network meta-analysis of studies of patients with knee osteoarthritis and at least 12 months of follow-up, there was uncertainty around the estimates of effect size for change in pain for all comparisons with placebo. Larger RCTs are needed to resolve the uncertainty around efficacy of medications for knee osteoarthritis.

Is Internet use associated with anxiety in patients with and at risk for cardiomyopathy?

OBJECTIVE: The aim of the study was to determine the relation between online health information seeking behavior and anxiety level among a sample of patients with manifested cardiomyopathy or at risk for cardiomyopathy. METHODS: The research is a cross-sectional study conducted among 104 patients with cardiomyopathy diagnosis and patients at risk for cardiomyopathy. Patients completed 3 different questionnaires: Use of Internet Health Information questionnaire about the use of Internet, Short Form SF-12 items questionnaire on quality of life, and State-Trait Anxiety Inventory measuring general anxiety levels. RESULTS: Forty-eight patients had a diagnosis of primary or secondary cardiomyopathy, and 56 patients, with conditions predisposing to cardiomyopathy. Eighty-five percent of the considered population is surfing the Internet to obtain nonspecific information about health in general, and the 65% use it to look specifically for heart disease. For both groups of patients with cardiomyopathy and at risk for cardiomyopathy, online health information seeking behavior is associated with substantially lower state anxiety levels (P = .041). CONCLUSION: Web use, as a source of health information, has been shown to be associated with anxiety reduction in patients with or at risk for cardiomyopathy, suggesting that Internet technology can be a useful instrument due to its informational power and its potentially therapeutic value.

Sleep Quality in Patients Undergoing Transcatheter Aortic Valve Implantation (TAVI).

The present study aimed to analyze sleep quality and quality of Life (QoL) in patients undergoing Transcatheter Aortic Valve Implantation (TAVI). It was conducted at the Interventional Cardiology Unit of the Department of Cardiac, Thoracic, Vascular Sciences and Public Health of the University of Padova on 27 adult patients who underwent TAVI via the transfemoral approach. Patients completed two validated instruments, i.e., the Pittsburgh Sleep Quality Index (PSQI) and the EuroQoL (EQ-5D-5L), on the day of discharge and one month after the hospital discharge. Twenty-seven patients were enrolled with a severe aortic stenosis diagnosis, treated with transfemoral TAVI procedure. The study population included seventeen poor sleepers and ten good sleepers with a median age of 81.92 years overall. The global PSQI evaluation revealed a small significant improvement at follow-up (p-value 0.007). Small positive changes were detected in the Self-care and Usual activity domains of the EQ-5D-5L and the EQ-VAS. No correlation was detected between EQ-5D-5L and sleep quality. The present study confirms the importance of sleep quality monitoring in patients who undergo TAVI procedure for aortic stenosis treatment.

Evaluating Effectiveness of Outpatient Monitoring in Type 2 Diabetes: The One-Year Experience in an Italian Group of Primary Care.

Nowadays, chronic disease management is the primary challenge of the healthcare system. From 2015, in the Veneto region (Italy), patients with a diagnosis of type 2 diabetes mellitus (T2DM) have been included in the diagnostic-therapeutic pathway (PDTA) program, and their clinical condition has been continuously monitored. The aim of this retrospective study is to determine the effectiveness of PDTA intervention, alone or in combination with a specialized one, in subjects with diagnosis of T2DM. Clinical and behavioral characteristics were collected at baseline and after 1 year of follow-up. Two subgroups were considered: subjects enrolled in PDTA only and subjects enrolled in both the PDTA program and in the care plan proposed by the specialized medical center (CAD group). Longitudinal analysis showed a relevant positive effect of time on diastolic blood pressure, while CAD enrollment appears to be related to higher levels of glycated hemoglobin. When included together in the same model, interaction between time and CAD covariates results in completely nonsignificant effects. As long-term management of chronic disorders, such as T2DM, is often difficult due to disease characteristics and problems in healthcare organization, monitoring programs, such as PDTA, and specialized care programs, such as CAD, do not show a clinically relevant effect in the first year of follow-up. Therefore, they should be analyzed over a longer period. However, they should also carefully consider the need for adequate tools for data collection and sharing, in addition to the context of application, patient expectations and the need for a long-term educational program.

Screening PubMed abstracts: is class imbalance always a challenge to machine learning?

BACKGROUND: The growing number of medical literature and textual data in online repositories led to an exponential increase in the workload of researchers involved in citation screening for systematic reviews. This work aims to combine machine learning techniques and data preprocessing for class imbalance to identify the outperforming strategy to screen articles in PubMed for inclusion in systematic reviews. METHODS: We trained four binary text classifiers (support vector machines, k-nearest neighbor, random forest, and elastic-net regularized generalized linear models) in combination with four techniques for class imbalance: random undersampling and oversampling with 50:50 and 35:65 positive to negative class ratios and none as a benchmark. We used textual data of 14 systematic reviews as case studies. Difference between cross-validated area under the receiver operating characteristic curve (AUC-ROC) for machine learning techniques with and without preprocessing (delta AUC) was estimated within each systematic review, separately for each classifier. Meta-analytic fixed-effect models were used to pool delta AUCs separately by classifier and strategy. RESULTS: Cross-validated AUC-ROC for machine learning techniques (excluding k-nearest neighbor) without preprocessing was prevalently above 90%. Except for k-nearest neighbor, machine learning techniques achieved the best improvement in conjunction with random oversampling 50:50 and random undersampling 35:65. CONCLUSIONS: Resampling techniques slightly improved the performance of the investigated machine learning techniques. From a computational perspective, random undersampling 35:65 may be preferred.

Communicating Risk Regarding Food Consumption: The Case of Processed Meat.

The present research combines real data and parameters found in recent literature that were used to design realistic scenarios demonstrating the potential effects (benefits and costs) of the World Health Organization (WHO)'s risk communication regarding the consumption of processed meat, which was proven to be associated with an increased risk of colorectal cancer (CRC) in an International Agency for Research on Cancer (IARC)/WHO report. The impact of the risk communication of processed meat consumption was simulated using Monte Carlo microsimulation models. The results showed that a 1% reduction in the number of high-level processed meat consumers may lead to a yearly decrease in CRC cases of 406.43 (IC 95%: -243.94, 1056.81), while the more extreme scenario of a 15% reduction may lead to 2086.62 fewer cases (IC 95%: 1426.66, 2746.57). On the other hand, if demand contraction in the processed meat sector resulted in a 0.1% loss in employment, one could expect 27.23 all-cause mortalities attributable to job loss (IC 95%: 16.55, 37.80). This simulation study demonstrates that caution should be taken when implementing public awareness campaigns, particularly when the prevention message is not straightforward.

Fruit and Vegetable Concentrate Supplementation and Cardiovascular Health: A Systematic Review from a Public Health Perspective.

Fruits and vegetables (FV) are very important for the prevention of noncommunicable diseases (NCDs), but it has been demonstrated that FV consumption is below that recommended. Several companies have worked to offer FV concentrates, but it remains unclear whether they represent a potentially effective means of reducing the burden of NCDs. The present study provides a systematic review aimed at assessing the effect of FV concentrate supplementation on select parameters that are known to be risk factors for NCDs. The systematic review was done according to the PRISMA guidelines. Relevant studies were identified through the online databases PubMed, Scopus, Web of Science, and Embase. The physiological parameters of interest were total cholesterol, low-density lipoprotein, plasmatic homocysteine, systolic blood pressure, and body mass index. Data extraction was performed in duplicate. The results of the systematic review provided input for a Markov chain simulation model aimed at estimating the public health consequences of various scenarios of FV concentrate utilization on NCDs burden. The present results suggest a positive and significant role of FV concentrate supplementation on select parameters known to affect the risk of NCDs. Such an effect might be hypothesized to turn into mitigation of the burden of those NCDs modulated by the physiological parameters analyzed in the present systematic review.

(Ab)use of Health Claims in Websites: The Case of Italian Bottled Waters.

The massive use of web marketing makes the monitoring of nutrition and health claims used in advertising campaigns much more difficult. The present study aimed at reviewing the website content for bottled waters produced in Italy to assess (i) if nutrition and health claims are reported, (ii) what types of nutrition and health claims are reported most frequently, and (iii) if the nutrition and health claims could be considered appropriate according to the current regulation in the field. A review of the website content of the 253 bottled waters produced in Italy and reported in the annual report of Bevitalia 2016-2017 was conducted. For each brand, indications related to the preventive, curative or therapeutic properties of the water reported were examined. Bottled waters that included potentially misleading information apparently not consistent with the European Directive on the exploitation and marketing of natural mineral waters were identified. Forty bottled waters with uncertain website content were identified. The information reported in the websites referred most often to beneficial effects for urinary tract and cardiovascular systems. Present results highlight, using the bottled water case study, that website content sometimes happens to deliver misleading information to consumers, also thanks to uncertain regulation in this sensitive field.

Comparison of Machine Learning Techniques for Prediction of Hospitalization in Heart Failure Patients.

The present study aims to compare the performance of eight Machine Learning Techniques (MLTs) in the prediction of hospitalization among patients with heart failure, using data from the Gestione Integrata dello Scompenso Cardiaco (GISC) study. The GISC project is an ongoing study that takes place in the region of Puglia, Southern Italy. Patients with a diagnosis of heart failure are enrolled in a long-term assistance program that includes the adoption of an online platform for data sharing between general practitioners and cardiologists working in hospitals and community health districts. Logistic regression, generalized linear model net (GLMN), classification and regression tree, random forest, adaboost, logitboost, support vector machine, and neural networks were applied to evaluate the feasibility of such techniques in predicting hospitalization of 380 patients enrolled in the GISC study, using data about demographic characteristics, medical history, and clinical characteristics of each patient. The MLTs were compared both without and with missing data imputation. Overall, models trained without missing data imputation showed higher predictive performances. The GLMN showed better performance in predicting hospitalization than the other MLTs, with an average accuracy, positive predictive value and negative predictive value of 81.2%, 87.5%, and 75%, respectively. Present findings suggest that MLTs may represent a promising opportunity to predict hospital admission of heart failure patients by exploiting health care information generated by the contact of such patients with the health care system.

Extending PubMed searches to ClinicalTrials.gov through a machine learning approach for systematic reviews.

OBJECTIVES: Despite their essential role in collecting and organizing published medical literature, indexed search engines are unable to cover all relevant knowledge. Hence, current literature recommends the inclusion of clinical trial registries in systematic reviews (SRs). This study aims to provide an automated approach to extend a search on PubMed to the ClinicalTrials.gov database, relying on text mining and machine learning techniques. STUDY DESIGN AND SETTING: The procedure starts from a literature search on PubMed. Next, it considers the training of a classifier that can identify documents with a comparable word characterization in the ClinicalTrials.gov clinical trial repository. Fourteen SRs, covering a broad range of health conditions, are used as case studies for external validation. A cross-validated support-vector machine (SVM) model was used as the classifier. RESULTS: The sensitivity was 100% in all SRs except one (87.5%), and the specificity ranged from 97.2% to 99.9%. The ability of the instrument to distinguish on-topic from off-topic articles ranged from an area under the receiver operator characteristic curve of 93.4% to 99.9%. CONCLUSION: The proposed machine learning instrument has the potential to help researchers identify relevant studies in the SR process by reducing workload, without losing sensitivity and at a small price in terms of specificity.

Definition of a tolerable upper intake level of niacin: a systematic review and meta-analysis of the dose-dependent effects of nicotinamide and nicotinic acid supplementation.

Context: Nicotinic acid and nicotinamide are soluble compounds of the vitamin B group, widely used to regulate the lipid profile in hyperlipidemic individuals. Higher doses of nicotinic acid are associated with adverse effects, especially flushing. A unique tolerable upper intake level (UL) of nicotinic acid has not been defined. Objective: This meta-analysis aims to evaluate adverse effects and their incidence after supplementation with different doses of nicotinic acid and nicotinamide, comparing results with current ULs in Europe and the United States. Data Sources: PubMed was searched for articles providing detailed information about nicotinic acid or nicotinamide supplementation and related outcomes. Study Selection: A total of 2670 citations were selected for screening. Two primary outcomes were considered: occurrence of adverse effects following nicotinic acid or nicotinamide supplementation, and dose at which adverse effects occurred. Data extraction: Details on study population, type and duration of treatment, dosage of vitamins, association with lipid-influencing drugs, length of follow-up, and incidence and type of adverse events were extracted. Results: After screening, 47 articles involving 11 741 individuals were included. Meta-analysis was based on estimation of benchmark doses for the probability of adverse effects after supplementation. In individuals with dyslipidemia or cardiovascular disease, nicotinic acid monotherapy seems to be protective against any adverse effects considered, as adverse events occurred at doses above those used with other treatments. In healthy individuals treated with nicotinic acid alone, major adverse effects occurred at doses below 1000 mg/d. Conclusions: Results may indicate a high degree of conservativeness in the UL of nicotinic acid, fixed at 35 mg/d in United States and 10 mg/d in Europe. Reconsideration of the UL of nicotinic acid for nutritional supplements, possibly differentiating between ULs in healthy and unhealthy individuals, may be warranted.

Electronic Questionnaires Design and Implementation.

BACKGROUND: Nursing and health care research are increasingly using e-questionnaires and e-forms for data collection and survey conduction. The main reason lies in costs, time and data-entry errors containment, increased flexibility, functionality and usability. In spite of this growing usage, no specifc and comprehensive guidelines for designing and submitting e-questionnaires have been produced so far. OBJECTIVE: The aim of this review is to collect information on the current best practices, taking them from various fields of application. An evaluation of the efficacy of the single indication is provided. METHOD: A literature review of guidelines currently available on WebSM (Web Survey Methodology) about electronic questionnaire has been performed. Four search strings were used: "Electronic Questionnaire Design", "Electronic Questionnaire", "Online Questionnaire" and "Online survey". Articles' inclusion criteria were English language, relevant topic in relation to the aim of the research and the publication date from January 1998 to July 2014. RESULTS: The review process led to identify 48 studies. The greater part of guidelines is reported for Web, and e-mail questionnaire, while a lack of indications emerges especially for app and e-questionnaires. CONCLUSION: Lack of guidelines on e-questionnaires has been found, especially in health care research, increasing the risk of use of ineffective and expensive instruments; more research in this field is needed.

Wearable Devices for Caloric Intake Assessment: State of Art and Future Developments.

BACKGROUND: The self-monitoring of caloric intake is becoming necessary as the number of pathologies related to eating increases. New wearable devices may help people to automatically record energy assumed in their meals. OBJECTIVE: The present review collects the released articles about wearable devices or method for automatic caloric assessments. METHOD: A literature research has been performed with PubMed, Google Scholar, Scopus and ClinicalTrials.gov search engines, considering released articles regarding applications of wearable devices in eating environment, from 2005 onwards. RESULTS: Several tools allow caloric assessment and food registration: wearable devices counting the number of bites ingested by the user, instruments detecting swallows and chewings, methods that analyse food with digital photography. All of them still require more validation and improvement. CONCLUSION: Automatic recording of caloric intake through wearable devices is a promising method to monitor body weight and eating habits in clinical and non-clinical settings, and the research is still going on.

Anchoring Vignettes in EQ-5D-5L Questionnaire: Validation of a New Instrument.

BACKGROUND: Health Related Quality of Life (HRQoL) is an indicator of patient's physical, psychological and social life. HRQoL is influenced by experience, beliefs, perceptions and expectations, and measures subjective perspective of the patient himself. EQ-5D-5L and SF-12 questionnaires are validated instruments useful to measure HRQoL, increasingly administered in electronic formats. OBJECTIVE: The main purpose is to evaluate the feasibility of anchoring vignettes for the EQ-5D-5L questionnaire, with the aim to improve intergroup comparability of responses among different subjects. A comparison with SF-12 questionnaire is carried out. METHOD: This is a cross-sectional study conducted at the ambulatories of cardiology of the University Hospital of Padova, in Italy. Thirty-eight subjects with a diagnosis of cardiovascular disease or at risk of cardiovascular disease were enrolled. A factorial analysis has been performed to assess the convergent validity of EQ-5D-5L questionnaire compared to Sf-12. Moreover, a compound Hierarchical Ordered Probit (Chopit) model has been estimated to evaluate if the questionnaire form affects the subjective evaluation process in order to compare EQ-5D-5L with and without vignettes. RESULTS: Correlation and factor analysis demonstrate that EQ_5D questionnaire is coherent with SF-12 in paper format. Chopit model estimation shows that questionnaire format does not affect the subjective question interpretation. Moreover, in a parametric model including vignettes, education attainment, disease severity, and gender are predictors of HRQoL status. CONCLUSION: The EQ-5D including vignettes in electronic format seems to be a valid tool to measure HRQoL as compared to EQ-5D without vignettes in paper format and to SF-12 questionnaire.