Patient Information Research Articles

Standardizing Multidisciplinary Case Conferences and Improving Communication Between Referring Physicians and Radiologists: A Quality Improvement Initiative.

Purpose: Assess the effectiveness of standardizing multidisciplinary case conferences (MDCs). Methods: Anonymous electronic surveys gauged opinions of abdominal radiologists engaged in recurring MDCs. A standardized Excel template, following Cancer Care Ontario guidelines and relevant literature, was distributed to MDC managers. Physicians were instructed to send cases 36 hours prior to MDC. Template adherence was assessed at 1.5 and 8 months. A follow-up survey at 4 months evaluated the intervention's effectiveness. Results: 27/34 abdominal radiologists provided 47 baseline responses, and 12 delegated radiologists provided 23 follow-up responses. "Often/always" being provided the image's location increased from 36% (17/47) at baseline to 70% (16/23) at follow-up. Non-adherence to the 36-hour cut-off decreased from 36% (16/45) to 17% (4/23). 72% disagreed that uploading remote imaging to hospital servers is easy (33/46), similar to follow-up (18/23, 78%). In assessing the intervention, 41% noted improved standardization (9/22), another 41% considered MDCs already standardized (9/22), and 18% reported no change (4/22). Those reporting no change experienced a higher frequency of non-adherence to the 36-hour cut-off (3/4, 75%) than others (1/18, 6%), and less frequent "often/always" ratings for image location being provided (3/4, 75%) than others (2/18, 11%). 89% (25/28) of MDCs adhered to the template. Issues regarding last-minute add-on cases may be mitigated through EPIC force functions. Artificial intelligence advancements may assist in retrieving external images and patient information. Conclusion: Adherence to MDC standardization was high, allowing for more efficient preparation, potentially reducing radiologist administrative burdens. Future force functions and artificial intelligence integration into electronic patient records may further augment this.

Tele-dermatology for Skin Cancer Management

Teledermatology plays a significant role in the UK National Health Service (NHS) for the management of skin cancers by enhancing early detection, diagnosis, and treatment pathways. It uses digital platforms to allow dermatologists to remotely evaluate skin lesions, including potential malignancies, based on high-quality images and patient information submitted by general practitioners (GPs) or other healthcare providers.This approach has proven particularly valuable in reducing wait times for specialist consultations, which is critical for skin cancers where early detection greatly improves outcomes. Through teledermatology, GPs can rapidly refer suspicious lesions to dermatologists, who assess whether further investigation, such as a biopsy or urgent in-person consultation, is required. It helps prioritize high-risk patients for fast-track appointments under the NHS's two-week referral rule for suspected cancers. Teledermatology also facilitates efficient triaging of cases, enabling healthcare systems to manage resources more effectively. Low-risk cases can often be monitored remotely or managed within primary care, reducing unnecessary hospital visits, and easing the burden on specialist services. During the COVID-19 pandemic, the adoption of teledermatology surged, helping maintain continuity of care for skin cancer patients despite restrictions on in-person visits. Overall, teledermatology in the NHS enhances access to specialist care, speeds up the diagnostic process, and improves the management of skin cancers, making it a crucial tool in modern dermatological practice. This article describes a tele-dermatology service and its outcomes.

Artificial intelligence in cardiology: a peek at the future and the role of ChatGPT in cardiology practice.

Artificial intelligence has increasingly become an integral part of our daily activities. ChatGPT, a natural language processing technology developed by OpenAI, is widely used in various industries, including healthcare. The application of ChatGPT in healthcare is still evolving, with studies exploring its potential in clinical decision-making, patient education, workflow optimization, and scientific literature. ChatGPT could be exploited in the medical field to improve patient education and information, thus increasing compliance. ChatGPT could facilitate information exchange on major cardiovascular diseases, provide clinical decision support, and improve patient communication and education. It could assist the clinician in differential diagnosis, suggest appropriate imaging modalities, and optimize treatment plans based on evidence-based guidelines. However, it is unclear whether it will be possible to use ChatGPT for the management of patients who require rapid decisions. Indeed, many drawbacks are associated with the daily use of these technologies in the medical field, such as insufficient expertise in specialized fields and a lack of comprehension of the context in which it works. The pros and cons of its use have been explored in this review, which was not written with the help of ChatGPT.

Real-time privacy-preserved auditing for shared outsourced data

Health providers need to share patient information across healthcare networks efficiently and securely to improve medical and health services. Timely data synchronization among relevant parties is crucial for effectively containing and preventing the worsening of the condition. However, ensuring rapid information sharing while maintaining the security of sensitive patient data remains a pressing concern. In this paper, we introduce a cloud storage integrity auditing scheme that can protect auditors from procrastinating and preserve the privacy of sensitive information. Our proposed system requires healthcare institutions to encrypt sensitive patient data before uploading it to the cloud. It mandates the use of a data sanitizer for the secure processing of encrypted data blocks. Auditors must verify data integrity and promptly submit their audit results to the blockchain within a predefined time frame. Leveraging the time-sensitive nature of blockchain technology, healthcare institutions can monitor auditor compliance within the allotted validation timeframe. We conducted comprehensive security analysis and performance evaluations to demonstrate the feasibility and effectiveness of our solution in addressing the challenges of secure and timely cloud storage in healthcare settings.

Chest wall muscle area, ventilatory efficiency and exercise capacity in systemic sclerosis.

To investigate the potential contribution of chest wall muscle area (CWMA) to the ventilatory efficiency and exercise capacity in patients with Systemic Sclerosis (SSc) without interstitial lung disease (ILD). Forty-four consecutive SSc patients [F = 37, median age 53.5years (IQR 43.5-58)] were examined using chest high-resolution computed tomography (HRCT), pulmonary function tests and cardiopulmonary exercise testing (CPET). The CWMA was evaluated at the level of the ninth thoracic vertebra on CT images by two independent evaluators blinded to the patient information. CPET parameters analyzed were maximum oxygen uptake (VO2 max) and VO2 at anaerobic threshold (VO2@AT); minute ventilation (VE); maximum tidal volume (VT). A statistically significant positive correlation was found between CWMA and maximum workload (r = 0.470, p < 0.01), VO2 max ml/min (r = 0.380, p < 0.01), VO2@AT (r = 0.343, p < 0.05), VE (r = 0.308, p < 0.05), VT (r = 0.410, p < 0.01) and VO2/heart rate (r = 0.399, p < 0.01). In multiple regression analysis, VO2 max (ml/min) was significantly associated with CWMA [β coefficient = 5.226 (95% CI 2.824, 7.628); p < 0.001], diffusing capacity for carbon monoxide (DLco) [β coefficient = 6.749 (95% CI 1.460, 12.039); p < 0.05] and body mass index (BMI) [β coefficient = 41.481 (95% CI 8.802, 74.161); p < 0.05]. In multiple regression analysis, maximum workload was significantly associated with CWMA [β coefficient = 0.490 (95% CI 0.289, 0.691); p < 0.001], DLco [β coefficient = 0.645 (95% CI 0.202, 1.088); p < 0.01] and BMI [β coefficient = 3.747 (95% CI 1.013, 6.842); p < 0.01]. In SSc-patients without ILD, CWMA represents an important variable in exercise capacity and can be evaluated by the mediastinal window available in the HRCT images required for lung disease staging.

Artificial Intelligence-Prompted Explanations of Common Primary Care Diagnoses

Background: Artificial intelligence (AI)-generated explanations about medical topics may be clearer and more accessible than traditional evidence-based sources, enhancing patient understanding and autonomy. We evaluated different AI explanations for patients about common diagnoses to aid in patient care. Methods: We prompted ChatGPT 3.5 , Google Bard, HuggingChat, and Claude 2 separately to generate a short patient education paragraph about seven common diagnoses. We used the Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKGL) to evaluate the readability and grade level of the responses. We used the Agency for Healthcare Research and Quality’s Patient Education Materials Assessment Tool (PEMAT) grading rubric to evaluate the understandability and actionability of responses. Results: Claude 2 demonstrated scores of FRE (67.0), FKGL (7.4), and PEMAT, 69% for understandability, and 34% for actionability. ChatGPT scores were FRE (58.5), FKGL (9.3), PEMAT (69% and 31%, respectively). Google Bard scores were FRE (50.1), FKGL (9.9), PEMAT (52% and 23%). HuggingChat scores were FRE (48.7) and FKGL (11.6), PEMAT (57% and 29%). Conclusion: Claude 2 and ChatGPT demonstrated superior readability and understandability, but practical application and patient outcomes need further exploration. This study is limited by the rapid development of these tools with newer improved models replacing the older ones. Additionally, the accuracy and clarity of AI responses is based on that of the user-generated response. The PEMAT grading rubric is also mainly used for patient information leaflets that include visual aids and may contain subjective evaluations.

Lessons from the COVID-19 pandemic to strengthen NCD care and policy in humanitarian settings: a mixed methods study exploring humanitarian actors’ experiences

BackgroundThe COVID-19 pandemic and response severely impacted people living with non-communicable diseases (PLWNCDs) globally. It exacerbated pre-existing health inequalities, severely disrupted access to care, and worsened clinical outcomes for PLWNCDs, who were at higher risk of morbidity and mortality from the virus. The pandemic’s effects were likely magnified in humanitarian settings, where there were pre-existing gaps in continuity of care for non-communicable diseases (NCDs). We sought to explore factors affecting implementation of NCD care in crisis settings during the COVID-19 pandemic and the adaptations made to support implementation.MethodsGuided by the Consolidated Framework for Implementation Research, we undertook an online survey of 98 humanitarian actors from multiple regions and organization types (March-July 2021), followed by in-depth interviews with 13 purposively selected survey respondents (October-December 2021). Survey data were analysed using descriptive statistics, while interview data were analysed thematically, using both deductive and inductive approaches.ResultsInitially, humanitarian actors faced challenges influenced by external actors’ priorities, such as de-prioritisation of NCD care by governments, travel restrictions and supply chain interruptions. With each infection wave and lockdown, humanitarian actors were better able to adapt and maintain NCD services. The availability of COVID-19 vaccines was a positive turning point, especially for the risk management of people with NCDs and protection of health workers. Key findings include that, despite pre-existing challenges, humanitarian actors largely continued NCD services during the crisis. Enabling factors that supported continuity of NCD services included the ability to quickly pivot to remote means of communication with PLWNCDs, flexibility in medicine dispensing, and successful advocacy to prioritize NCD management within health systems. Key lessons learned included the importance of partnerships and cooperation with other health actors, and the mobilisation or repurposing of community health workers/volunteer networks.ConclusionsThe COVID-19 experience should prompt national and global health stakeholders to strengthen inclusion of NCDs in emergency preparedness, response, and resilience planning. Key lessons were learned around remote care provision, including adapting to NCD severity, integrating community health workers, providing context-adapted patient information, combating misinformation, and strengthening cross-sectoral partnerships.

Health professionals’ perceptions of electronic health records system: a mixed method study in Ghana

BackgroundElectronic Health Record systems (EHRs) offer significant benefits and have transformed healthcare in developed countries. However, their implementation and adoption in low- and middle-income countries (LMICs) remains low due to challenges and competing interests. Health professionals’ perception of EHRs can influence their adoption and continued use. The objectives of this study are to explore the perception of health professionals regarding implemented EHR systems in three hospitals in Ghana and identify factors influencing their perception and satisfaction.MethodsIn this study, we employed a concurrent mixed method design to collect data from study participants from May to June 2023. The quantitative part employed a descriptive-survey and the qualitative (in-depth interview) techniques was applied. After obtaining written informed consent from each respondent, a structured survey questionnaire was filled out by the health professionals from three hospitals. An a priori power calculation was used to determine the sample size for the quantitative component. Two hundred and sixty-three (263) health professionals completed the questionnaire from the three facilities. A purposive sampling technique was used to select fifteen [1] participants for the interviews. A semi-structured interview guide was used for the in-depth interviews. The interviews were audio recorded, transcribed, and coded into themes using QSR Nvivo 12 software before thematic content analysis.ResultsOur findings revealed that 213 (80.99%) health professionals perceived the EHRs as beneficial to patients and were generally satisfied. An overwhelming majority, 197 (74.90%) of the health professionals, were satisfied with its use and expressed interest in continuing to use the system. The majority of health professionals viewed the EHRs to have improved their work and workflow processes and provided the desired results. However, few other health professionals were dissatisfied with the system because they viewed the EHRs as frustrating due to unstable internet connectivity and power supply. Other concerns were related to the privacy and confidentiality of patient information. They believe access to patient information should be on a need-to-know basis, and patient information should not be accessible to all other clinicians except those involved directly in their care processes.ConclusionThe study revealed that health professionals have a positive perception of the implemented EHRs, are highly satisfied with them, and are interested in continuing to use them. However, health professionals’ concerns about the unstable power supply, poor internet connectivity, security, and confidentiality of patient’s information need attention, to mitigate their frustrations and boost their confidence in the system.

Outcomes of Patients with End-Stage Renal Disease Hospitalized with COVID-19 in Ahvaz Razi Hospital from February 2020 to May 2021

Background: End-stage renal disease patients on maintenance hemodialysis (ESRD-HD) are at very high risk for COVID-19 infections due to their older age and comorbidities such as diabetes and hypertension. Objectives: This study aimed to investigate the outcomes of COVID-19 in ESRD-HD patients. Methods: This was a retrospective study conducted on ESRD-HD patients aged 18 years and older who were referred to Razi Hospitals in Ahvaz from February 2020 to May 2021 for hemodialysis and diagnosed with COVID-19. Patient information was extracted retrospectively from their medical records. Results: A total of 180 patients were examined. The average age of the patients was 61.5 years, and 118 (65.6%) were men. The most common underlying condition was hypertension (81.1%). The most prevalent clinical symptom was shortness of breath (70.6%), followed by cough (47.8%). Seventy-five patients (41.66%) were admitted to the intensive care unit (ICU), with an average stay of 5 days. Hypertension and ischemic heart disease were significantly more common among patients admitted to the ICU (P = 0.008 and 0.015, respectively). In-hospital mortality was 32.8%. Advanced age, fever, shortness of breath, cough, and the need for a ventilator were significant predictors of mortality in hospitalized ESRD patients with COVID-19 (P = 0.016, 0.033, 0.001, 0.012, and 0.011, respectively). Conclusions: Our study demonstrated that ESRD-HD patients with COVID-19 are at high risk for ICU admission and mortality. Advanced age and clinical symptoms such as fever, shortness of breath, cough, and the need for a ventilator significantly predict in-hospital mortality in these patients.

EHR Interoperability Challenges Leveraging HL7 FHIR for Seamless Data Exchange in Healthcare

Electronic health records, often known as EHRs, have revolutionised the healthcare industry by making patient information more easily accessible and more efficient on the whole. There is still a huge obstacle to overcome in order to achieve seamless data transmission across different electronic health record systems. variances in data formats, terminologies, and standards often give rise to interoperability concerns. These variances impede the smooth flow of information across various systems and have the potential to cause problems. The Fast Healthcare Interoperability Resources (FHIR) standard, which is based on Health Level Seven (HL7), has emerged as a potentially useful option to overcome these difficulties. Through the provision of a uniform and standardized method for the sharing of healthcare data, FHIR is intended to facilitate the interchange of data in a manner that is both more efficient and trustworthy. The issues that are involved with electronic health record (EHR) interoperability are investigated in this study, as is the manner in which HL7 FHIR may ease the interchange of data in healthcare settings in a smooth manner. It starts out by providing an overview of the basic problems that exist in electronic health record (EHR) interoperability. These problems include data fragmentation, inconsistent data formats, and the absence of standardized protocols. HL7 FHIR is then presented in the article, along with a description of its fundamental principles. These concepts include the emphasis placed on interoperability, the simplicity of implementation, and the support for contemporary web technologies.

Double-layer data-hiding mechanism for ECG signals

Due to the advancement in biomedical technologies, to diagnose problems in people, a number of psychological signals are extracted from patients. We should be able to ensure that psychological signals are not altered by adversaries and it should be possible to relate a patient to his/her corresponding psychological signal. As far as our awareness extends, none of the existing methods possess the capability to both identify and verify the authenticity of the ECG signals. Consequently, this paper introduces an innovative dual-layer data-embedding approach for electrocardiogram (ECG) signals, aiming to achieve both signal identification and authenticity verification. Since file name-based signal identification is vulnerable to modifications, we propose a robust watermarking method which will embed patient-related details such as patient identification number, into the medically less-significant portion of the ECG signals. The proposed robust watermarking algorithm adds data into ECG signals such that the patient information hidden in an ECG signal can resist the filtering attack (such as high-pass filtering) and noise addition. This is achieved via the use of error buffers in the embedding algorithm. Further, modification-sensitive fragile watermarks are added to ECG signals. By extracting and checking the fragile watermark bits, we can determine whether an ECG signal is modified or not. To ensure the security of the proposed mechanism, two secret keys are used. Our evaluation demonstrates the usefulness of the proposed system.

EuMAR stakeholder engagement: an analysis of medically assisted reproduction (MAR) data collection practices in EU countries†.

What are the current national medically assisted reproduction (MAR) data collection systems across EU Member States, and how can these countries contribute to a unique, cycle-by-cycle registry for the European Monitoring of Medically Assisted Reproduction (EuMAR) project? The study identified significant variation in MAR data collection practices across Member States, with differences in data types, collection methods, and reporting requirements; the EuMAR project emerges as an opportunity to enhance data standardization and improve MAR data collection in the EU. There is a need for new approaches in MAR data collection that include long-term and cross border follow-up. The EuMAR project intends to establish a unified, cycle-by-cycle registry of data on MAR treatments in EU countries, from which accurate cumulative outcomes can be calculated. This cross-sectional study involved a survey and interviews with stakeholders from 26 EU Member States conducted in 2023 over a period of seven months. Representatives from national competent authorities and professional associations involved in MAR data collection in EU countries were invited to complete the survey and interviewed to assess current data flows, information requirements, and their interest in the EuMAR project. Half of the participating countries reported having a national MAR registry with cycle-by-cycle data (n = 13), while 31% reported having a national registry with aggregated data (n = 8) and 19% reported having no national registry (n = 5). Of the countries with a national cycle-by-cycle registry, eight countries collect identifiable data, five countries collect pseudonymized data, and one country collects fully anonymized data. Informed consent is required in 10 countries. The main advantages that participants expected from a European registry like EuMAR were the possibility of obtaining national statistics in the absence of a national registry and improving the calculation of cumulative outcomes. The results of the study are based on self-reported data, which may be subject to bias, however, the validity of the collected information was verified with different means, including follow-up calls for clarifications and sharing final transcript reports. The feasibility of the proposed data flow models will be tested in a pilot study. Despite the heterogeneity of data collection practices across EU countries, the results show that stakeholders have high expectations of the benefits that the EuMAR registry can bring, namely the improvement of data consistency, cross-border comparability, and cumulative live birth rates, leading to better information for patients, health care providers and policy makers. The EuMAR project was co-founded by ESHRE and the European Commission (101079865-EuMAR-EU4H-2021-PJ2). No competing interests were declared. N/A.

A Circadian Rhythm-related Signature to Predict Prognosis, Immunei Infiltration, and Drug Response in Breast Cancer.

Circadian rhythm genes (CRRGs) play essential roles in cancer occurrence and development. However, the prognostic significance of CRRGs in breast cancer (BC) has not been fully elucidated. Our study aimed to develop a prognostic gene signature based on CRRGs that can accurately and stably predict the prognosis of BC. The transcriptome data and clinical information for BC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A consensus unsupervised clustering analysis was carried out to investigate the roles of CRRGs in BC. A CRRGs-related prognostic risk model was established by using logistic least absolute shrinkage and selection operator (LASSO) Cox regression and univariate Cox regression analyses. Kaplan-Meier (KM) curves analysis, time-dependent receptor operation characteristics (ROC) curves analysis, and nomogram were plotted to evaluate the predictive efficacy of the model. The relevance of risk score to the immune cell infiltration, tumor burden mutation (TMB), and therapeutic response was assessed. A risk model comprising six CRRGs (SLC44A4, SLC16A6, TPRG1, FABP7, GLYATL2, and FDCSP) was constructed and validated, demonstrating a good predictor of BC. The low-risk group displayed a higher number of immune activities and immune checkpoint expression and a lower burden of tumor mutation. Additionally, drug sensitivity analysis demonstrated the prognostic signature may serve as a potential chemosensitivity predictor. We established 6 CRRGs-related risk signatures for the prognosis of BC, which is of great value in predicting the prognosis of patients with BC and guiding the treatment for BC.

Liquid-liquid phase separation-related genes associated with prognosis, tumor microenvironment characteristics, and tumor cell features in bladder cancer.

This study aimed to explore the Liquid-liquid phase separation (LLPS)-related genes associated with the prognosis of bladder cancer (BCa) and assess the potential application of LLPS-related prognostic signature for predicting prognosis in BCa patients. Clinical information and transcriptome data of BCa patients were extracted from the Cancer Genome Atlas-BLCA (TCGA-BLCA) database and the GSE13507 database. Furthermore, 108 BCa patients who received treatment at our institution were subjected to a retrospective analysis. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an LLPS-related prognostic signature for BCa. The CCK8, wound healing and Transwell assays were performed. Based on 62 differentially expressed LLPS-related genes (DELRGs), three DELRGs were screened by LASSO analysis including kallikrein-related peptidase 5 (KLK5), monoacylglycerol O-acyltransferase 2 (MOGAT2) and S100 calcium-binding protein A7 (S100A7). Based on three DELRGs, a novel LLPS-related prognostic signature was constructed for individualized prognosis assessment. Kaplan-Meier curve analyses showed that LLPS-related prognostic signature was significantly correlated with overall survival (OS) of BCa. ROC analyses demonstrated the LLPS-related prognostic signature performed well in predicting the prognosis of BCa patients in the training group (the area under the curve (AUC) = 0.733), which was externally verified in the validation cohort 1 (AUC = 0.794) and validation cohort 2 (AUC = 0.766). Further experiments demonstrated that inhibiting KLK5 could affect the proliferation, migration, and invasion of BCa cells. In this study, a novel LLPS-related prognostic signature was successfully developed and validated, demonstrating strong performance in predicting the prognosis of BCa patients.

The red blood cell distribution width to albumin ratio was a potential prognostic biomarker for acute respiratory failure: a retrospective study

BackgroundThe association between red blood cell distribution width (RDW) to albumin ratio (RAR) and prognosis in patients with acute respiratory failure (ARF) admitted to the Intensive Care Unit (ICU) remains unclear. This retrospective cohort study aims to investigate this association.MethodsClinical information of ARF patients was collected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) version 2.0 database. The primary outcome was, in-hospital mortality and secondary outcomes included 28-day mortality, 60-day mortality, length of hospital stay, and length of ICU stay. Cox regression models and subgroup analyses were conducted to explore the relationship between RAR and mortality.ResultsA total of 4547 patients with acute respiratory failure were enrolled, with 2277 in the low ratio group (RAR < 4.83) and 2270 in the high ratio group (RAR > = 4.83). Kaplan-Meier survival analysis demonstrated a significant difference in survival probability between the two groups. After adjusting for confounding factors, the Cox regression analysis showed that the high RAR ratio had a higher hazard ratio (HR) for in-hospital mortality (HR 1.22, 95% CI 1.07–1.40; P = 0.003), as well as for 28-day mortality and 60-day mortality. Propensity score-matched (PSM) analysis further supported the finding that high RAR was an independent risk factor for ARF.ConclusionThis study reveals that RAR is an independent risk factor for poor clinical prognosis in patients with ARF admitted to the ICU. Higher RAR levels were associated with increased in-hospital, 28-day and 60-day mortality rates.

Postpartum thromboprophylaxis with enoxaparin: a prospective cohort study on patients' adherence, injection experience, and information retention after counselling by pharmacists.

This research aimed to determine postpartum females' self-reported adherence to and experience with short-term thromboprophylaxis using enoxaparin injection, after counselling by pharmacists. It also sought to assess their knowledge of thromboprophylaxis, injection techniques, and confidence in self-injecting. This prospective cohort study was conducted at a public tertiary hospital in Malaysia from March to June 2023. Self-injection-naïve postpartum females who were initiated on thromboprophylaxis and counselled by a pharmacist were conveniently sampled. Knowledge regarding thromboprophylaxis, injection readiness, and technique were assessed one day after the counselling session. A telephonic interview was conducted at the end of the 10-day therapy to determine adherence and adverse effects experienced. A total of 259 subjects were successfully followed up, with 87.6% (n = 227) adherent to the therapy. Nonadherence was predominantly due to forgetfulness; four had their treatment withheld due to bleeding. One-third of subjects experienced localised pain and bruising. Subjects answered a median of 5/7 knowledge questions and recalled a median of 8/10 injection steps correctly, with those who read the information leaflet provided after counselling scoring significantly higher (P = .02). The majority declared moderate confidence in their ability to self-inject. Subjects who intended to self-inject (P < .01) and were more confident (P = .02) demonstrated better injection technique. Postpartum females counselled by pharmacists largely adhered to short-term enoxaparin for thromboprophylaxis. The impact of the counselling session may be enhanced by addressing their psychological readiness to self-inject, awareness of adverse effects identification, mitigation, and management, as well as setting reminders to prevent forgetfulness to inject.

Analysis of Trends in the Use of Artificial Intelligence in Diagnosis and Treatment

AI in healthcare has improved, making diagnostics more accurate and increasing the effectiveness of treatments. The present study discusses the AI trends in diagnostic and therapeutic applications and focuses on the presented practical applications and their effects on patient care. The purpose of this particular review is to focus on the current developments in the implementation of AI in the field of health care, present main use cases and successes, as well as discuss about the issues and concerns in the topic at hand. Previous studies on AI in healthcare with specific consideration of diagnostic image analysis and interpretation, histology and molecular pathology, whole-genome sequencing, and therapeutic decision support are discussed. The selection criteria included papers with data gathered from real-life AI cases and quantitative findings. Study materials were obtained from e-journals, conference papers, and established online sources with descriptive analysis being done on the data collected. A summary of the findings revealed a number of highly impactful subcategories focused on the use of artificial intelligence diagnostic imaging, especially in radiology, pathology, and genomics. The AI applications used in the fields of operations and drug discovery revealed the ability to accurately predict clinical trial outcomes and to create effective treatments. First of all, AI can become a game changer in healthcare by enhancing diagnostics accuracy and treatment outcomes. The future research questions include further developing the methods that explain the AI models’ decisions, protecting the privacy of patient information, and reducing algorithmic bias for better fair healthcare for all. Therefore, better interactions between creators of AI and clinicians and regulatory authorities are pertinent to make sure that the full advantages of AI are realized in clinical practice to advance patient care.

A retrospective study on the influence of inclination of cusp on implant marginal bone height in patients with periodontal disease.

To investigate the correlation between the marginal bone height of implants in the posterior maxilla of patients with periodontal disease and the inclination of cusp, providing a theoretical basis for the occlusal design of implant restorations in such patients. Methods: A total of 80 patients with periodontal disease who underwent implant restoration in the posterior maxilla (55 men and 25 women; mean age 56.66 ± 12.70 years) were selected, with a total of 80 implant restorations (one implant restoration per patient). In addition to recording the main research factor of the inclination of cusp, general patient information, implant characteristics and restoration characteristics were taken, and retrospective analysis of the case data and imaging data of the 80 patients from over 3 years was conducted. Cone beam computed tomography was performed preoperatively and 3 years after implant loading to measure and calculate the marginal bone height of the implants using the One Volume Viewer software. Correlation analysis was performed to determine the relationship between the inclination of the cusp and marginal bone height. Results: There was a positive correlation between the inclination of cusp and the marginal bone height of the implants, with a correlation coefficient of 0.661 (p < 0.001); the diameter of the implants, implant type and restoration type were negatively correlated with the marginal bone height of the implants, with correlation coefficients of -0.364 (p = 0.001), -0.232 (p = 0.038) and -0.298 (p = 0.007), respectively. Conclusion: When designing the occlusion of implant restorations in the posterior maxilla of patients with periodontal disease, it is advisable to appropriately reduce the restoration's inclination of cusp.

Assessing the quality and readability of online patient information: ENT UK patient information e-leaflets vs responses by a Generative Artificial Intelligence.

The evolution of artificial intelligence has introduced new ways to disseminate health information, including natural language processing models like ChatGPT. However, the quality and readability of such digitally-generated information remains understudied. This study is the first to compare the quality and readability of digitally-generated health information against leaflets produced by professionals. Patient information leaflets for five ENT UK leaflets and their corresponding ChatGPT responses were extracted from the Internet. Assessors with various degree of medical knowledge evaluated the content using the Ensuring Quality Information for Patients (EQIP) tool and readability tools including the Flesch-Kincaid Grade Level (FKGL). Statistical analysis was performed to identify differences between leaflets, assessors, and sources of information. ENT UK leaflets were of moderate quality, scoring a median EQIP of 23. Statistically significant differences in overall EQIP score were identified between ENT UK leaflets but ChatGPT responses were of uniform quality. Non-specialist doctors rated the highest EQIP scores while medical students scored the lowest. The mean readability of ENT UK leaflets was higher than ChatGPT responses. The information metrics of ENT UK leaflets were moderate and varied between topics. Equivalent ChatGPT information provided comparable content quality, but with reduced readability. ChatGPT patient information and professionally-produced leaflets had comparable content, but LLM content were required a higher reading age. With the increasing use of online health resources, this study highlights the need for a balanced approach that considers optimises both the quality and readability of patient education materials.

Clinical and biochemical factors for bacteria in bile among patients with acute cholangitis.

Acute cholangitis is a clinical syndrome caused by a bacterial infection in the biliary system. The bacteria could exist in the bile before bile drainage despite empirical antibiotic treatment. Patients with acute cholangitis admitted to a tertiary hospital in Southeastern China from August 2011 to September 2021 were involved when bile cultures were performed. Patient information before bile cultures and during hospitalization was extracted from the clinical record database. The risk factors related to bacteria in bile were assessed by univariable and multivairable logistic regression analysis, respectively. A total of 533 patients (66.05%) had bacterial growth in bile. Alanine aminotransferase concentration [odds ratio (OR) = 0.998, P < 0.001], absolute monocyte count (OR = 0.335, P = 0.001), and duration of antibiotic use (OR = 0.933, P = 0.026) were negatively correlated with bacteria in bile. In contrast, C-reactive protein (OR = 1.006, P = 0.003), thrombin time (OR = 1.213, P = 0.033), prothrombin time (OR = 1.210, P = 0.011), and age (OR = 1.025, P < 0.001) were positively correlated with bacteria in bile. Based on an area under the receiver operating characteristic curve of 0.737 (95% CI, 0.697-0.776, P < 0.001), combining these seven variables could efficiently predict the presence of bacteria in bile among patients with acute cholangitis. The combination of clinical indicators before bile drainage could predict the risk of bacteria in bile for patients with acute cholangitis.