Patient Data Research Articles

Protein-losing enteropathy as a new phenotype in atypical hemolytic uremic syndrome caused by CD46 gene mutation.

Atypical hemolytic uremic syndrome (aHUS) is a life-threatening thrombotic microangiopathy. Genetic defects in the alternative complement (AP) pathway have been identified in 60-70% of individuals. Eculizumab is recommended as a first-line therapy. We collected the clinical data of a pediatric patient with aHUS accompanied by protein-losing enteropathy (PLE). Genetic testing was performed. Related literature on aHUS combined with PLE was reviewed. A 15-year-old Chinese girl was diagnosed with aHUS at 3.7years of age and experienced five episodes; her symptoms completely resolved with plasma treatment. Severe gastrointestinal symptoms and hypoalbuminemia presented after the first episode, and PLE was diagnosed. A novel homozygous CD46 variant was identified, and FACS revealed significantly decreased CD46 expression. She presented at a recent relapse with persistent GI symptoms and headache and progressed to chronic kidney failure; peritoneal dialysis was initiated. Eculizumab was given 8months after the last recurrence. Surprisingly, PLE was cured. Afterward, dialysis was discontinued, and eGFR recovered to 44.8ml/min/1.73 m2. A review of the literature indicated that PLE with thrombosis was caused by CD55 variants via hyperactivation of the AP system. We report an aHUS patient with PLE caused by CD46 variants. Symptoms of both PLE and aHUS were significantly alleviated in our patient and patients with CD55 variants treated with eculizumab, indicating that PLE was a new symptom of aHUS in our patient with a CD46 variant. Our case expands the phenotype of aHUS caused by a CD46 mutation and provides evidence of the efficacy of eculizumab after a long phase of chronic kidney failure.

Implementation of integrated care for type 2 diabetes Mellitus and Periodontitis in Germany: study protocol for a practice-based and cluster-randomized trial

BackgroundType 2 Diabetes mellitus (T2DM) and periodontitis share common risk factors and influence one another. However, primary care and oral health care continue to operate separate from each other and fail to synchronize care for patients with T2DM and periodontitis. The purpose of this practice-based trial is to evaluate the implementation of a new integrated care pathway for patients with T2DM and periodontitis. The new approach integrates a screening for T2DM risk in dental care settings in patients with periodontitis, a screening for periodontitis risk in primary care settings in patients with T2DM, and mutual referrals between dentists and primary care physicians.MethodsTwo practice-based studies will be carried out in parallel: (i) In dental care settings: a practice-based, multi-centric, cluster-randomized, controlled trial with a control and an intervention group; (ii) in primary care settings: a practice-based, multi-centric, non-randomized, controlled trial with a synthetic control group calculated from claims data. Following a two-step recruitment approach, 166 dentists and 248 general practitioners will be recruited, who themselves will recruit a total of 3808 patients in their practices. Patient data will be collected at baseline, 12 months, and 24 months after study enrollment. The evaluation comprises: (i) impact evaluation, using a hierarchical linear mixed model; (ii) process evaluation, based on surveys alongside the trials; (iii) economic evaluation. In addition, a Discrete-Choice-Experiment will identify provider’s payment preferences for the new care approach.DiscussionUpon successful implementation, the intervention will enable health care providers to detect a risk for T2DM and periodontitis in patients at an early stage, thus providing patients an opportunity for timely diagnosis and therapy. Ultimately, this can lead to increased quality of life and reduced health care expenditures. On a methodologic level, the project provides novel insights into a complex intervention on the intersection of general practice and dental care.Trial registrationThe study was prospectively registered at the German Clinical Trials Register (https://drks.de/search/de/trial/DRKS00030587) on 3. July 2023 under ID “DRKS00030587“.

The 90-Day Risk of Hospitalization in Heart Transplant Recipients After COVID-19 Infection

BackgroundHeart transplant recipients are at a high-risk of complications from the coronavirus-2019 (COVID-19) infection. Heart transplant recipients are a special group of persistently immunosuppressed people, and COVID-19 may cause them to experience an unpredictable course of infection, with a risk of hospitalization occurring well beyond their initial infection period. The seriousness of COVID-19 disease in heart transplant recipients emphasizes how vital it is to refer patients promptly and early to specialized heart transplant centers. MethodsWe retrospectively reviewed all heart transplant recipients at a single center between March 2019 and October 2021. All recipients with positive nasopharyngeal reverse transcriptase-polymerase chain reaction tests for COVID-19 were included in this study. After IRB approval, we obtained medical records and patient data from electronic medical records. ResultsThis study followed 126 heart transplant patients from March 2019 to October 2021 of which only 49 had COVID-19 infections. The median age at infection was 58 years (49-65), with 41% female. Race distribution was as follows: 59% Caucasian and 39% African American. The median time from transplant to infection was 384 days (237-677). All infected patients had a 50% dose reduction in mycophenolate mofetil per institutional protocol. The majority of symptoms were cough, fatigue, shortness of breath, and fever. Among all patients with COVID-19, 45 (92%) were vaccinated. Of those vaccinated, 27 (60%) patients received Pfizer initial and booster doses, whereas 18 (40%) received Moderna initial and booster doses. Twelve patients (24%) were hospitalized within 90 days of infection, with only two requiring ICU level of care. The median duration of hospitalization was 5 days (4-9). Of the hospitalized patients, 11 (92%) were discharged, and 1 (8%) died in the hospital. Three of the four unvaccinated patients were hospitalized, and one died while hospitalized. The remaining 37 patients were managed as outpatients. ConclusionHeart transplant recipients have an increased risk of contracting COVID-19 and developing severe symptoms due to multiple healthcare contacts, preexisting health conditions, and weakened immune systems. Our data highlight that most vaccinated patients do not require hospitalization within 90 days of infection, and those hospitalized have a high likelihood of survival without needing ICU care.

A Multi-Modal Machine Learning Methodology for Predicting Solitary Pulmonary Nodule Malignancy in Patients Undergoing PET/CT Examination

This study explores a multi-modal machine-learning-based approach to classify solitary pulmonary nodules (SPNs). Non-small cell lung cancer (NSCLC), presenting primarily as SPNs, is the leading cause of cancer-related deaths worldwide. Early detection and appropriate management of SPNs are critical to improving patient outcomes, necessitating efficient diagnostic methodologies. While CT and PET scans are pivotal in the diagnostic process, their interpretation remains prone to human error and delays in treatment implementation. This study proposes a machine-learning-based network to mitigate these concerns, integrating CT, PET, and manually extracted features in a multi-modal manner by integrating multiple image modalities and tabular features). CT and PET images are classified by a VGG19 network, while additional SPN features in combination with the outputs of VGG19 are processed by an XGBoost model to perform the ultimate diagnosis. The proposed methodology is evaluated using patient data from the Department of Nuclear Medicine of the University Hospital of Patras in Greece. We used 402 patient cases with human annotations to internally validate the model and 96 histopathological-confirmed cases for external evaluation. The model exhibited 97% agreement with the human readers and 85% diagnostic performance in the external set. It also identified the VGG19 predictions from CT and PET images, SUVmax, and diameter as key malignancy predictors. The study suggests that combining all available image modalities and SPN characteristics improves the agreement of the model with the human readers and the diagnostic efficiency.

Identifying diseases symptoms and general rules using supervised and unsupervised machine learning

The symptoms of diseases can vary among individuals and may remain undetected in the early stages. Detecting these symptoms is crucial in the initial stage to effectively manage and treat cases of varying severity. Machine learning has made major advances in recent years, proving its effectiveness in various healthcare applications. This study aims to identify patterns of symptoms and general rules regarding symptoms among patients using supervised and unsupervised machine learning. The integration of a rule-based machine learning technique and classification methods is utilized to extend a prediction model. This study analyzes patient data that was available online through the Kaggle repository. After preprocessing the data and exploring descriptive statistics, the Apriori algorithm was applied to identify frequent symptoms and patterns in the discovered rules. Additionally, the study applied several machine learning models for predicting diseases, including stepwise regression, support vector machine, bootstrap forest, boosted trees, and neural-boosted methods. Several predictive machine learning models were applied to the dataset to predict diseases. It was discovered that the stepwise method for fitting outperformed all competitors in this study, as determined through cross-validation conducted for each model based on established criteria. Moreover, numerous significant decision rules were extracted in the study, which can streamline clinical applications without the need for additional expertise. These rules enable the prediction of relationships between symptoms and diseases, as well as between different diseases. Therefore, the results obtained in this study have the potential to improve the performance of prediction models. We can discover diseases symptoms and general rules using supervised and unsupervised machine learning for the dataset. Overall, the proposed algorithm can support not only healthcare professionals but also patients who face cost and time constraints in diagnosing and treating these diseases.

Pattern of Cleft Lip and Palate Clefts at a Tertiary Care Hospital in Saudi Arabia.

Clefts of the lip and palate (CL/P) and cleft palate (CP) are the most common craniofacial congenital anomalies. Clefts are classified as syndromic and nonsyndromic. Nonsyndromic clefts have no known genetic causes. This study combines prospective and retrospective studies to review the patterns of CL/P and CP and associated syndromes and conditions in patients registered for CL/P surgery at a tertiary care pediatric center in our tertiary care hospital in Saudi Arabia. It included patient data from May 2015 through April 2023. Patient record forms and SPSS (IBM version 20.0) were used to collect and analyze data. A significance level of 5% was used, with p ≤ 0.05 considered statistically significant. Of the 319 patients who met our inclusion criteria, 175 were male. Of the total, 99 had a left unilateral isolated cleft lip, 61 had a right unilateral isolated cleft lip, 69 had a bilateral cleft lip, and 90 had an isolated CP. Of the total, 140 had CL/P. Around 242 were nonsyndromic. The Chi-square test revealed a significant association between the prevalence of isolated CP and CLP and gender. The prevalence of left unilateral isolated cleft lip and bilateral and isolated CP was significantly associated with syndromic and nonsyndromic cases. Males are more likely to be affected by orofacial clefts, which is consistent with the global trend. Isolated CP was the most common orofacial cleft. Within the sample, syndromes' association with orofacial clefts was significantly weaker than that of isolated and bilateral clefts.

The indication of palliative whole-brain radiotherapy for patients with brain metastases: a simple prognostic scoring system in the era of stereotactic radiosurgery

BackgroundStereotactic irradiation has become the mainstay treatment for brain metastases (BM), and whole-brain radiotherapy (WBRT) is often used for symptom palliation. However, the survival time of patients with BM undergoing palliative WBRT (pWBRT) is limited, making it difficult to select patients who should receive treatment.MethodsWe collected patient data from 2016 to 2022 at the Shizuoka Cancer Center and retrospectively analyzed the factors related to survival time. Overall survival (OS) was defined as the survival time after WBRT.ResultsA total of 301 patients (median age, 66 years) who underwent pWBRT were included. The primary cancers were lung, breast, gastrointestinal tract, and other cancers in 203 (67%), 38 (13%), 33 (11%), and 27 (9%) patients, respectively. Median OS of all patients was 4.1 months. In the multivariate analysis, male sex (hazard ratio [HR]:1.4), Karnofsky Performance Status (KPS) ≤ 60 (HR:1.7), presence of extracranial metastasis (ECM) (HR:1.6), neutrophil-lymphocyte ratio (NLR) ≥ 5 (HR:1.6), and lactate dehydrogenase (LDH) ≥ upper limit of normal (ULN) (HR:1.3) were significantly associated with shorter OS (all P < 0.05). To predict the OS, we created a prognostic scoring system (PSS). We gave one point to each independent prognostic factor. Median OS for patients with scores of 0–2, 3, and 4–5 were 9.0, 3.5 and 1.7 months, respectively (P < 0.001).ConclusionsMale sex, KPS ≤ 60, presence of ECM, NLR ≥ 5, and LDH ≥ ULN were poor prognostic factors for patients with BM undergoing pWBRT. By PSS combining these factors, it may be possible to select patients who should undergo pWBRT.

Validation of Artificial Intelligence in the Classification of Adolescent Idiopathic Scoliosis and the Compairment to Clinical Manual Handling.

The accurate measurement of Cobb angles is crucial for the effective clinical management of patients with adolescent idiopathic scoliosis (AIS). The Lenke classification system plays a pivotal role in determining the appropriate fusion levels for treatment planning. However, the presence of interobserver variability and time-intensive procedures presents challenges for clinicians. The purpose of this study is to compare the measurement accuracy of our developed artificial intelligence measurement system for Cobb angles and Lenke classification in AIS patients with manual measurements to validate its feasibility. An artificial intelligence (AI) system measured the Cobb angle of AIS patients using convolutional neural networks, which identified the vertebral boundaries and sequences, recognized the upper and lower end vertebras, and estimated the Cobb angles of the proximal thoracic, main thoracic, and thoracolumbar/lumbar curves sequentially. Accordingly, the Lenke classifications of scoliosis were divided by oscillogram and defined by the AI system. Furthermore, a man-machine comparison (n = 300) was conducted for senior spine surgeons (n = 2), junior spine surgeons (n = 2), and the AI system for the image measurements of proximal thoracic (PT), main thoracic (MT), thoracolumbar/lumbar (TL/L), thoracic sagittal profile T5-T12, bending views PT, bending views MT, bending views TL/L, the Lenke classification system, the lumbar modifier, and sagittal thoracic alignment. In the AI system, the calculation time for each patient's data was 0.2 s, while the measurement time for each surgeon was 23.6 min. The AI system showed high accuracy in the recognition of the Lenke classification and had high reliability compared to senior doctors(ICC 0.962). The AI system has high reliability for the Lenke classification and is a potential auxiliary tool for spinal surgeons.

Surgical and radiosurgical treatment of hypothalamic hamartoma: The Italian experience between 2011 and 2021.

To investigate the Italian experience on the surgical and radiosurgical treatment of drug-resistant epilepsy due to hypothalamic hamartoma (HH) in the period 2011-2021 in six Italian epilepsy surgery centers, and to compare safety and efficacy profiles of the different techniques. We collected pseudo-anonymized patient's data with at least 12 months of follow-up. Surgical outcome was defined according to Engel classification of seizure outcome. Univariate analysis was performed to assess the risk of post-operative seizures, categorized in dichotomous variable as favorable and unfavorable; explanatory variables were considered. Mann-Whitney or Chi-squared test were used to assess the presence of an association between variables (p < 0.05). Full presurgical and postoperative data about 42 patients from 6 epilepsy surgery centers were gathered. Engel class I was reached in the 65.8% and 66.6% of patients with gelastic and non-gelastic seizures, respectively. Other than daily non-gelastic seizures were associated with seizure freedom (p = 0.01), and the radiological type presented a trend toward significance (p = 0.12). Endoscopic disconnection and laser interstitial thermal therapy are effective in the treatment of HH-related epilepsy, with a tolerable safety profile. Both gelastic and non-gelastic seizures can be treated, also in patients with a long history of seizures. This study collected data about 42 patients with HH-related epilepsies. Endoscopic disconnection and laser therapy are both effective and safe in the treatment of hypothalamic hamartoma-related epilepsies.

Exploring the discrepancies between clinical trials and real-world data: A small-cell lung cancer study.

The potential of real-world data to inform clinical trial design and supplement control arms has gained much interest in recent years. The most common approach relies on reproducing control arm outcomes by matching real-world patient cohorts to clinical trial baseline populations. However, recent studies pointed out that there is a lack of replicability, generalisability, and consensus. In this article, we propose a novel approach that aims to explore and examine these discrepancies by concomitantly investigating the impact of selection criteria and operations on the measurements of outcomes from the patient data. We tested the approach on a dataset consisting of small-cell lung cancer patients receiving platinum-based chemotherapy regimens from a real-world data cohort (n = 223) and six clinical trial control arms (n = 1224). The results showed that the discrepancy between real-world and clinical trial data potentially depends on differences in both patient populations and operational conditions (e.g., frequency of assessments, and censoring), for which further investigation is required. Discovering and accounting for confounders, including hidden effects of differences in operations related to the treatment process and clinical trial study protocol, would potentially allow for improved translation between clinical trials and real-world data. Continued development of the method presented here to systematically explore and account for these differences could pave the way for transferring learning across clinical studies and developing mutual translation between the real-world and clinical trials to inform clinical study design.

Predictors of PrEP Retention and Attrition in an Urban Publicly Funded Safety-net Specialty Clinic.

Pre-exposure prophylaxis (PrEP) is an effective tool for human immunodeficiency virus (HIV) prevention. The purpose of this study is to identify correlates of PrEP retention using patient data from an urban, publicly funded safety-net clinic in Washington, DC. Cox proportional hazards regression, logistical regression, and survival curves were used to assess the association of age, gender, race/ethnicity, insurance, number of partners, and sexually transmitted infection (STI) diagnosis at PrEP initiation with time on PrEP. From August 2016-December 2020, 1,126 people were prescribed PrEP - patients were mostly Black (44.8%) or Latinx (30.4%) and identified as cisgender men (84.6%). Half had no insurance (49.1%), with the remaining patients reporting private (28.9%) or public (21.5%) insurance. Age at PrEP prescription ranged from 15 to 66 with 80% being 20 to 39 years. For the 87.7% (n = 987) of patients who discontinued PrEP, mean PrEP time was 158 days and median was 28 days. The highest rates of discontinuation were observed within the first month with 44.3% discontinuing by day 30, 52.3% by 3 months, and 73.2% by 1 year. Cisgender women, transgender persons, and those younger than 30 years were more likely to discontinue PrEP. Latinx and patients with less than 3 male partners in the last 90 days were less likely to discontinue PrEP. We demonstrated a high level of PrEP uptake among populations disproportionally affected by HIV. Future analyses are needed to examine ways of reducing barriers to PrEP initiation and improving PrEP adherence.

Evaluating the impact of a ward environment with 20 single occupancy rooms and two four-bedded bays on patient and staff experiences and outcomes in an acute NHS Trust: a mixed-methods study protocol

IntroductionTraditionally, wards in acute care hospitals consist predominately of multioccupancy bays with some single rooms. There is an increasing global trend towards a higher proportion of single rooms in hospitals,...

Effects of red blood cell transfusion on patients undergoing cardiac surgery in Queensland – a retrospective cohort study

BackgroundPacked red blood cell (pRBC) transfusion is a relatively safe and mainstay treatment commonly used in cardiac surgical patients. However, there is limited evidence on clinical effects of transfusing blood nearing end-of shelf life that has undergone biochemical changes during storage.ObjectiveTo investigate evidence of associations between morbidity/mortality and transfusion of blood near end of shelf-life (> 35 days) in cardiac surgical patients.MethodsData from the Queensland Health Admitted Patient Data Collection database 2007–2013 was retrospectively analysed. Coronary artery bypass graft and valvular repair patients were included. Multivariable logistic regression was used to examine the effect of pRBC age (< 35 days vs. ≥ 35 days) on in-hospital mortality and morbidity. As secondary analysis, outcomes associated with the number of pRBC units transfused (≤ 4 units vs. ≥ 5 units) were also assessed.ResultsA total of 4514 cardiac surgery patients received pRBC transfusion. Of these, 292 (6.5%) received pRBCs ≥ 35 days. No difference in in-hospital mortality or frequency of complications was observed. Transfusion of ≥ 5 units of pRBCs compared to the ≤ 4 units was associated with higher rates of in-hospital mortality (5.6% vs. 1.3%), acute renal failure (17.6% vs. 8%), infection (10% vs. 3.4%), and acute myocardial infarction (9.2% vs. 4.3%). Infection carried an odds ratio of 1.37 between groups (CI = 0.9–2.09; p = 0.14) and stroke/neurological complications, 1.59 (CI = 0.96–2.63; p = 0.07).ConclusionIn cardiac surgery patients, transfusion of pRBCs closer to end of shelf-life was not shown to be associated with significantly increased mortality or morbidity. Dose-dependent differences in adverse outcomes (particularly where units transfused were > 4) were supported.

The care cascade of chronic obstructive pulmonary disease in China: a cross-sectional study of individual-level data at enrolment into the national ‘Happy Breathing’ Programme

Understanding the chronic obstructive pulmonary disease (COPD) care cascade is crucial for identifying where and when to intervene to improve COPD outcomes. We aimed to determine the proportion of patients with COPD seeking care in China's health system who are lost at each stage of the COPD care cascade and how the patterns of loss vary across geographical regions and population groups. From November 3, 2018, to April 22, 2021, we used individual-level patient data from the national Chinese 'Happy Breathing' Programme, which aims to identify patients with COPD and provide appropriate care. COPD was defined as a post-bronchodilator ratio of forced expiratory volume in 1s to forced vital capacity (FEV1/FVC)<0.70. We calculated the proportions of individuals who, at enrolment into the 'Happy Breathing' Programme, (i) had ever undergone a pulmonary function test, (ii) had been diagnosed with COPD in the past, (iii) were currently on treatment for COPD, and (iv) had achieved control of their COPD. We examined the association between reaching each stage of the care cascade and individual patient characteristics as well as regional-level economic development and available resources in the health system using multilevel regression. Among the 29,201 patients with COPD in the 'Happy Breathing' Programme, 41.0% (95% confidence interval [CI]: 40.4-41.6%) had ever been tested for COPD, 17.6% (95% CI: 17.1-18.0%) had previously been diagnosed with COPD, 8.5% (95% CI: 8.2-8.8%) were currently on treatment for COPD, 4.6% (95% CI: 4.3-4.8%) of patients had mild or no exacerbations in the prior year, and 3.9% (95% CI: 3.7-4.2%) of patients had suffered no exacerbations in the prior year. On average, patients living in the cities of Beijing, Wuhan, and Yinchuan had progressed further along the COPD care cascade than patients living in Daqing and Luoyang. Using multilevel regression, we found that young age, rural residence, and low regional per-capita GDP were significantly associated with larger losses at each stage of the COPD care cascade. Substantial proportions of patients with COPD are lost at each stage of the COPD care cascade in the Chinese health system. The largest losses occur during the initial stages of the cascade, when diagnosis first occurs. New policies and interventions are required to boost COPD care, especially screening and diagnosis, in the Chinese health system to reduce this large disease burden. This work was supported by Major Programme of National Natural Science Foundation of China (82090011), CAMS Innovation Fund for Medical Sciences (CIFMS) (2021-I2M-1-049), and Horizon Europe (HORIZON-MSCA-2021-SE-01; project number 101086139-PoPMeD-SuSDeV). TB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt professorship award.

Artificial intelligence for early-stage detection of chronic kidney disease

Early-stage detection of chronic kidney disease (CKD) is crucial in research to enable timely intervention, enhance understanding of disease progression, reduce healthcare costs and support public health initiatives. The traditional approaches on early-stage chronic kidney disease detection often suffer from slow convergence and not integrate advanced technologies, impacting their effectiveness. Additionally, security and privacy concerns related to patient data are ineffectively addressed. To overcome these issues, this research incorporates novel optimized artificial intelligence-based approaches. The main aim is to enhance detection process through enhanced hybrid mud ring network (EHMRN), a novel detection technique combining light gradient boosting machine and MobileNet, involving extensive data collection, including a large dataset of 100,000 instances. The introduced network is optimized through the mud ring optimization to attain enhanced performance. Incorporating spark ensures secure cloud-based storage, enhancing privacy and compliance with healthcare data regulations. This approach represents a significant advancement in primary stage detection more effectively and promptly. The results show that the introduced approach outperforms traditional approaches in terms of accuracy (99.96%), F1-score (99.91%), precision (100%), specificity (99.98%), recall (100%) and execution time (0.09 s).

Understanding barriers and facilitators to integrated HIV and hypertension care in South Africa

BackgroundThe burden of hypertension among people with HIV is high, particularly in low-and middle-income countries, yet gaps in hypertension screening and care in these settings persist. This study aimed to identify facilitators of and barriers to hypertension screening, treatment, and management among people with HIV in primary care clinics in Johannesburg, South Africa. Additionally, different stakeholder groups were included to identify discordant perceptions.MethodsUsing a cross-sectional study design, data were collected via interviews (n = 53) with people with HIV and hypertension and clinic managers and focus group discussions (n = 9) with clinic staff. A qualitative framework analysis approach guided by COM-B and the Theoretical Domains Framework were used to identify and compare determinants of hypertension care across stakeholder groups.ResultsData from clinic staff and managers generated three themes characterizing facilitators of and barriers to the adoption and implementation of hypertension screening and treatment: 1) clinics have limited structural and operational capacity to support the implementation of integrated care models, 2) education and training on chronic care guidelines is inconsistent and often lacking across clinics, and 3) clinicians have the goal of enhancing chronic care within their clinics but first need to advocate for health system characteristics that will sustainably support integrated care. Patient data generated three themes characterizing existing facilitators of and barriers to clinic attendance and chronic disease self-management: 1) the threat of hypertension-related morbidity and mortality as a motivator for lifestyle change, 2) the emotional toll of clinic’s logistical, staff, and resource challenges, and 3) hypertension self-management as a patchwork of informational and support sources. The main barriers to hypertension screening, treatment, and management were related to environmental resources and context (i.e., lack of enabling resources and siloed flow of clinic operations) and patients’ knowledge and emotions (i.e., lack of awareness about hypertension risk, fear, and frustration). Clinical actors and patients differed in perceived need to prioritize HIV versus hypertension care.ConclusionsThe convergence of multi-stakeholder data highlight key areas for improvement, where tailored implementation strategies targeting motivations of clinic staff and capacity of patients may address challenges to hypertension screening, treatment, and management recognized across groups.

Secure Patient Data Monitoring and Efficient Routing Optimization using a Hyperelliptic Curve Cryptography with Fuzzy-based Priority in WBSN

Aims and Background: Wireless Body Sensor Network (WBSN) technology is one of the major research areas in the medical and entertainment industries. A wireless sensor network (WSN) is a dense sensor network that senses environmental conditions, processes, and outgoing data at the sink node. A WBSN develops patient monitoring systems that provide the flexibility and mobility needed to monitor patient health. In data communications, it is difficult to find flexible optical routing paths, switching capabilities, and packet processing in the composition of optical networks. Information-centric networks (ICNs) are a new network model and are different from information- centric models. The priority of the information-centric model is the communication network. Objectives: In the existing literature, such methods are typically developed using computationally expensive procedures, such as bilinear pairing, elliptic curve operations, etc., which are unsuitable for biomedical devices with limited resources. Using the concept of hyperelliptic curve cryptography (HECC), we propose a new solution: a smart card-based two-factor mutual authentication scheme. In this new scheme, HECC’s finest properties, such as compact parameters and key sizes, are utilized to enhance the real-time performance of an IoT-based TMIS system. Methodology: A fuzzy–based Priority Aware Data Sharing (FPADS) method is introduced to schedule the priority data and monitor the transmission length. The child node adjusts the transmission speed of the cluster head with the help of a fuzzy logic controller (FLC). Results: The proposed model estimated the traffic load of the child node and the priority of the different amounts of data to be transmitted. The principle of scheduling data packets to be developed is based on the precedence of the data with the lowest transmit length in the network. Conclusion: The proposed FPADS performance increases in terms of scheduling time utilisation, traffic distribution, and mean delay. Simulations have been done using NS2, and the outcomes have shown that the proposed methodology is efficient and improves the overall QoS of the system.

Impact of allergic rhinitis control on work productivity and costs: a real-world data MASK-air study

BackgroundAllergic rhinitis (AR) has a substantial socioeconomic impact associated with impaired work productivity. ObjectiveTo study the impact of AR on work productivity and estimate the corresponding indirect costs for 40 countries. MethodsWe conducted a cross-sectional study using direct patient data from the MASK-air® app on users with self-reported AR. We used the Work Productivity and Activity Impairment Questionnaire: Allergy Specific to measure the impact of AR on work productivity (presenteeism and absenteeism). Weekly indirect costs were estimated per country, for each level of rhinitis control and considering patients with and without asthma. ResultsWe assessed data from 677 weeks (364 patients), 280 of which were reported by patients with asthma. Regarding presenteeism, the median impact of AR in weeks of poor disease control was 60.7% (P25-P75=24.9-74.2%), while partial and good disease control were respectively associated with an impact of 25.0% (P25-P75=12.1-42.4%) and 4.4% (P25-75=0.8-12.9%). In poorly-controlled weeks, presenteeism was associated with indirect costs ranging from 65.7 US Dollars purchase power parity (US$ PPPs) (P25-P75=29.2-143.2) in Brazil to 693.6 US$ PPP (P25-P75=405.2-1094.9) in Iceland. Median absenteeism per week was of 0% for all levels of rhinitis control. Patients with AR+asthma showed higher overall work impairment than patients with AR alone, particularly in poorly-controlled weeks (median work impairment in AR alone=39.1% [P25-P75=12.5-71.9%]; median work impairment in AR+asthma=68.4% [P25-P75=54.6-80.2%]). ConclusionPoor AR control was associated with decreased work productivity and increased indirect costs, particularly in patients with AR+asthma. The estimates from this study underpin the economic burden of AR.

Anifrolumab treatment improves patient-reported quality of life and decreases disease activity and corticosteroid use in patients with systemic lupus erythematosus: A qualitative study in Denmark.

Anifrolumab is a new therapeutic approach for individuals with systemic lupus erythematosus (SLE) directed at blocking the type 1 interferon pathway. Despite the expanding body of literature on Anifrolumab, an essential aspect remains absent: the subjective patient experience of treatment effects and implications on patients' health-related quality of life (HRQoL). The present study aimed to fill this void by elucidating the nuanced perspectives of SLE patients receiving Anifrolumab treatment by conducting qualitative in-depth interviews (IDIs). SLE patients at Aarhus University Hospital who had received at least three infusions of Anifrolumab were approached for inclusion in the study, which comprised two main elements: (1) qualitative IDIs and (2) collection of patient data from electronic medical records (EMRs). The IDIs were semi-structured and based on a discussion guide that included open-ended and close-ended questions. Verbatim transcripts were coded and analysed using qualitative software to understand concepts important to patients and to understand patients' own experiences before and after Anifrolumab therapy. A clinical chart review was conducted using EMR data at baseline, 3months, and 6months after Anifrolumab initiation. IDIs were completed with 14 patients, and EMR data was collected from 16 patients (treatment days range: 62-474). Of the 23 symptoms spontaneously reported by patients prior to Anifrolumab treatment, fatigue, joint pain, sun sensitivity, joint stiffness, skin rashes, and hair loss were the most common. Most symptoms improved, and none worsened during treatment. Patients reported significant impacts of disease on daily life before treatment: day-to-day activities, social life, emotional aspects, physical activity, concentration/memory, work/employment, and family/romantic relationships. Patients reported improvements in all aspects after treatment but were still impacted. From the EMR data, we observed a fall in disease activity after treatment initiation with a concomitant reduction in the use of corticosteroids. This study provides valuable insights into the subjective experiences of SLE patients treated with Anifrolumab, and the findings collectively contribute to a comprehensive understanding of the treatment's efficacy from the patients' perspective and its tangible effects on both subjective and objective parameters in SLE patients.

Gender Differences in Patients with Prolactinoma: Single-center Ukrainian Experience.

Prolactinomas are the most common type of pituitary gland tumors that secrete overly prolactin. They account for approximately 60% of all hormone-secreting hypophysis tumors. This study aims to analyze gender differences in patients with prolactinomas who were operated on transsphenoidal surgery and conduct a single-center retrospective analysis of patient data. This study evaluated the medical records of 109 patients (61 females and 48 males) from 2009 to 2019 at Feofaniya Clinical Hospital of the State Administration of Affairs in Kyiv, Ukraine. The primary criterion for including patients was a Serum Prolactin (PRL) level of over 100 ng/ml and the presence of a pituitary adenoma (PA) as observed on MRI. Additionally, the histological examination needed to confirm the presence of Prolactin-Secreting Pituitary Adenomas (PSPAs) without plurihormonal activity through both microscopy and immunohistochemical (IHC) staining. Significant differences in preoperative PRL levels were not observed. However, males had significantly larger tumor sizes and prevalence of macroadenomas. In male patients, the preoperative PLR levels showed a weak negative correlation with age (r=-0.304, p < 0.036) and a positive correlation with tumor size (r=0.555, p < 0.001) and cavernous sinus invasion (r=0.339, p < 0.018). In females, preoperative PRL was significantly associated only with tumor size and Knosp grade. Prolactin-Secreting Pituitary Adenomas (PSPAs) are more common in women than men and are characterized by larger and more invasive tumors with high PRL levels at diagnosis. The PRL level and tumor size before surgery can predict early biochemical remission in both males and females with an accuracy of 58.3% and 68.8%, respectively.