Patient Information Research Articles

Enhancing healthcare security: Time‐based authentication for privacy‐preserving IoMT sensor monitoring framework leveraging blockchain technology

SummaryThe rapid progression of the Internet of Things and its increasing use in healthcare has generated considerable concerns over the safeguarding and privacy of vital medical data. In response to these issues, blockchain has surfaced as a possible remedy, offering transparent, immutable, and decentralized storage. Nevertheless, conventional blockchain‐based systems still encounter constraints in maintaining anonymity, confidentiality, and privacy. Hence, this article suggests a framework based on a secure consortium blockchain that prioritizes data privacy and employs time‐based authentication to streamline patient data monitoring. First, we employ time‐based authentication to verify the identities of authorized users. This process utilizes the NIK‐512 hashing algorithm in conjunction with passwords and registered timestamps, which strengthens the confidentiality of data. Patient information undergoes encryption before transmission within the network. Further, our framework introduces a sensor registration service that the trusted node employs to assign a distinct identity to each sensor connected to a patient. The implementation of data processing and filtering techniques at the edge layer serves the purpose of mitigating disturbances that may occur during the collection of sensor‐based data. Finally, a comprehensive evaluation of performance and security has been carried out with various metrics. The findings indicate that the proposed solution effectively enhances the management of Internet of Medical Things data by providing improved privacy and security.

A Qualitative Evaluation of ChatGPT4 and PaLM2's Response to Patient's Questions Regarding Age-Related Macular Degeneration.

Patient compliance in chronic illnesses is essential for disease management. This also applies to age-related macular degeneration (AMD), a chronic acquired retinal degeneration that needs constant monitoring and patient cooperation. Therefore, patients with AMD can benefit by being properly informed about their disease, regardless of the condition's stage. Information is essential in keeping them compliant with lifestyle changes, regular monitoring, and treatment. Large language models have shown potential in numerous fields, including medicine, with remarkable use cases. In this paper, we wanted to assess the capacity of two large language models (LLMs), ChatGPT4 and PaLM2, to offer advice to questions frequently asked by patients with AMD. After searching on AMD-patient-dedicated websites for frequently asked questions, we curated and selected a number of 143 questions. The questions were then transformed into scenarios that were answered by ChatGPT4, PaLM2, and three ophthalmologists. Afterwards, the answers provided by the two LLMs to a set of 133 questions were evaluated by two ophthalmologists, who graded each answer on a five-point Likert scale. The models were evaluated based on six qualitative criteria: (C1) reflects clinical and scientific consensus, (C2) likelihood of possible harm, (C3) evidence of correct reasoning, (C4) evidence of correct comprehension, (C5) evidence of correct retrieval, and (C6) missing content. Out of 133 questions, ChatGPT4 received a score of five from both reviewers to 118 questions (88.72%) for C1, to 130 (97.74%) for C2, to 131 (98.50%) for C3, to 133 (100%) for C4, to 132 (99.25%) for C5, and to 122 (91.73%) for C6, while PaLM2 to 81 questions (60.90%) for C1, to 114 (85.71%) for C2, to 115 (86.47%) for C3, to 124 (93.23%) for C4, to 113 (84.97%) for C5, and to 93 (69.92%) for C6. Despite the overall high performance, there were answers that are incomplete or inaccurate, and the paper explores the type of errors produced by these LLMs. Our study reveals that ChatGPT4 and PaLM2 are valuable instruments for patient information and education; however, since there are still some limitations to these models, for proper information, they should be used in addition to the advice provided by the physicians.

Attitude and utilization of ChatGPT among registered nurses: A cross-sectional study.

This study explores the influencing factors of attitudes and behaviors toward use of ChatGPT based on the Technology Acceptance Model among registered nurses in Taiwan. The complexity of medical services and nursing shortages increases workloads. ChatGPT swiftly answers medical questions, provides clinical guidelines, and assists with patient information management, thereby improving nursing efficiency. To facilitate the development of effective ChatGPT training programs, it is essential to examine registered nurses' attitudes toward and utilization of ChatGPT across diverse workplace settings. An anonymous online survey was used to collect data from over 1000 registered nurses recruited through social media platforms between November 2023 and January 2024. Descriptive statistics and multiple linear regression analyses were conducted for data analysis. Among respondents, some were unfamiliar with ChatGPT, while others had used it before, with higher usage among males, higher-educated individuals, experienced nurses, and supervisors. Gender and work settings influenced perceived risks, and those familiar with ChatGPT recognized its social impact. Perceived risk and usefulness significantly influenced its adoption. Nurse attitudes to ChatGPT vary based on gender, education, experience, and role. Positive perceptions emphasize its usefulness, while risk concerns affect adoption. The insignificant role of perceived ease of use highlights ChatGPT's user-friendly nature. Over half of the surveyed nurses had used or were familiar with ChatGPT and showed positive attitudes toward its use. Establishing rigorous guidelines to enhance their interaction with ChatGPT is crucial for future training. Nurse managers should understand registered nurses' attitudes toward ChatGPT and integrate it into in-service education with tailored support and training, including appropriate prompt formulation and advanced decision-making, to prevent misuse.

Development and validation of a neoadjuvant chemotherapy pathological complete remission model based on Reg IV expression in breast cancer tissues: a clinical retrospective study.

To develop and authenticate a neoadjuvant chemotherapy (NACT) pathological complete remission (pCR) model based on the expression of Reg IV within breast cancer tissues with the objective to provide clinical guidance for precise interventions. Data relating to 104 patients undergoing NACT were collected. Variables derived from clinical information and pathological characteristics of patients were screened through logistic regression, random forest, and Xgboost methods to formulate predictive models. The validation and comparative assessment of these models were conducted to identify the optimal model, which was then visualized and tested. Following the screening of variables and the establishment of multiple models based on these variables, comparative analyses were conducted using receiver operating characteristic (ROC) curves, calibration curves, as well as net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Model 2 emerged as the most optimal, incorporating variables such as HER-2, ER, T-stage, Reg IV, and Treatment, among others. The area under the ROC curve (AUC) for Model 2 in the training dataset and test dataset was 0.837 (0.734-0.941) and 0.897 (0.775-1.00), respectively. Decision curve analysis (DCA) and clinical impact curve (CIC) further underscored the potential applications of the model in guiding clinical interventions for patients. The prediction of NACT pCR efficacy based on the expression of Reg IV in breast cancer tissue appears feasible; however, it requires further validation.

Is ChatGPT a Reliable Source of Patient Information on Asthma?

ChatGPT (OpenAI, San Francisco, CA, USA) is a novel artificial intelligence (AI) application that is used by millions of people, and the numbers are growing by the day. Because it has the potential to be a source of patient information, the study aimed to evaluate the ability of ChatGPT to answer frequently asked questions (FAQs) about asthma with consistent reliability, acceptability, and easy readability. We collected 30 FAQs about asthma from the Global Initiative for Asthma website. ChatGPT was asked each question twice, by two different users, to assess for consistency. The responses were evaluated by five board-certified internal medicine physicians for reliability and acceptability. The consistency of responses was determined by the differences in evaluation between the two answers to the same question. The readability of all responses was measured using the Flesch Reading Ease Scale (FRES), the Flesch-Kincaid Grade Level (FKGL), and the Simple Measure of Gobbledygook (SMOG). Sixty responses were collected for evaluation. Fifty-six (93.33%) of the responses were of good reliability. The average rating of the responses was 3.65 out of 4 total points. 78.3% (n=47) of the responses were found acceptable by the evaluators to be the only answer for an asthmatic patient. Only two (6.67%) of the 30 questions had inconsistent answers. The average readability of all responses was determined to be 33.50±14.37 on the FRES, 12.79±2.89 on the FKGL, and 13.47±2.38 on the SMOG. Compared to online websites, we found that ChatGPT can be a reliable and acceptable source of information for asthma patients in terms of information quality. However, all responses were of difficult readability, and none followed the recommended readability levels. Therefore, the readability of this AI application requires improvement to be more suitable for patients.

Written information about retinopathy of prematurity in Aotearoa New Zealand: identification, review and opportunities for improvement.

The aims of this research include adapting a patient information tool for whānau (extended family) Māori needs, identifying and reviewing written information provided for the retinopathy of prematurity eye examination (ROPEE) and identifying improvements to ROPEE written information. ROPEE patient information (printed leaflets, website, app) was obtained from all tertiary neonatal intensive care units in Aotearoa New Zealand (Aotearoa). Information was reviewed using an adapted "20 good-design principles" guide and given a star rating and Flesch-Kincaid readability score to identify acceptability and usability for patients. Seven ROPEE information materials were reviewed and varied in alignment with the adapted good-design principles tool. Based on the adapted good-design principles, opportunities were identified in many aspects of the written information for improvement, including words and language, tone and meaning, content and design. The Flesch-Kincaid grade level reading scores ranged from 12-22 years reading age. Written information also did not use te reo Māori (Aotearoa Indigenous language) or extensively use Māori imagery. Opportunities exist to improve ROPEE whānau information, including making content more readable, understandable and visually appealing. Optimising the clinical information on ROPEE nationally for Aotearoa will support whānau decision making, and aligning written information with Māori (Indigenous peoples of Aotearoa) is a priority.

Examining the role of ChatGPT in the management of distal radius fractures: insights into its accuracy and consistency.

The optimal management of distal radius fractures remains a challenge for orthopaedic surgeons. The emergence of Artificial Intelligence (AI) and Large Language Models (LLMs), especially ChatGPT, affords significant potential in improving healthcare and research. This study aims to assess the accuracy and consistency of ChatGPT's knowledge in managing distal radius fractures, with a focus on its capability to provide information for patients and assist in the decision-making processes of orthopaedic clinicians. We presented ChatGPT with seven questions on distal radius fracture management over two sessions, resulting in 14 responses. These questions covered a range of topics, including patient inquiries and orthopaedic clinical decision-making. We requested references for each response and involved two orthopaedic registrars and two senior orthopaedic surgeons to evaluate response accuracy and consistency. All 14 responses contained a mix of both correct and incorrect information. Among the 47 cited references, 13% were accurate, 28% appeared to be fabricated, 57% were incorrect, and 2% were correct but deemed inappropriate. Consistency was observed in 71% of the responses. ChatGPT demonstrates significant limitations in accuracy and consistency when providing information on distal radius fractures. In its current format, it offers limited utility for patient education and clinical decision-making.

Tamper Detection and Self-recovery in a Visual Secret Sharing based Security Mechanism for Medical Records.

Medical records contain highly sensitive patient information. These medical records are significant for better research, diagnosis, and treatment. However, ensuring secure medical records storage is paramount to protect patient confidentiality, integrity, and privacy. Conventional methods involve encrypting and storing medical records in third-party clouds. Such storage enables convenient access and remote consultation. This cloud storage poses single-point attack risks and may lead to erroneous diagnoses and treatment. To address this, a novel (n,n)VSS scheme is proposed with data embedding, permutation ordered binary number system, tamper detection, and self-recovery mechanism. This approach enables the reconstruction of medical records even in the case of tampering. The tamper detection algorithm ensures data integrity. Simulation results demonstrate the superiority of proposed method in terms of security and reconstruction quality. Here, security analysis is done by considering attacks such as brute force, differential, and tampering attacks. Similarly, the reconstruction quality is evaluated using various human visual system parameters. The results show that the proposed technique provides a lower bit error rate ( ≈ 0), high average peak signal-to-noise ratio ( ≈ 35 dB), high structured similarity ( ≈ 1), high text embedding rate ( ≈ 0.7 BPP), and lossless reconstruction in the case of attacks.

RBMS1 reflects a distinct microenvironment and promotes tumor progression in ocular melanoma

Ocular melanoma, including uveal melanoma (UM) and conjunctival melanoma (CM), is the most common ocular cancer among adults with a high rate of recurrence and poor prognosis. Loss of epigenetic homeostasis disturbed gene expression patterns, resulting in oncogenesis. Herein, we comprehensively analyzed the DNA methylation, transcriptome profiles, and corresponding clinical information of UM patients through multiple machine-learning algorithms, finding that a methylation-driven gene RBMS1 was correlated with poor clinical outcomes of UM patients. RNA-seq and single-cell RNA-seq analyses revealed that RBMS1 reflected diverse tumor microenvironments, where high RBMS1 expression marked an immune active TME. Furthermore, we found that tumor cells were identified to have the higher communication probability in RBMS1+ state. The functional enrichment analysis revealed that RBMS1 was associated with pigment granule and melanosome, participating in cell proliferation as well as apoptotic signaling pathway. Biological experiments were performed and demonstrated that the silencing of RBMS1 inhibited ocular melanoma proliferation and promoted apoptosis. Our study highlighted that RBMS1 reflects a distinct microenvironment and promotes tumor progression in ocular melanoma, contributing to the therapeutic customization and clinical decision-making.

Determining the awareness of surgical nurses regarding frail patients: a cross-sectional study

Objective: The objective of this study is to determine the knowledge level and awareness of surgical nurses about fragile patients. Method: Obtained through Introductory Information Survey Form created by the researchers and Fragile Patient Information Evaluation Form methods. Results: The average age of the surgical nurses participating in the study was 28±5.01 years, the average professional experience was 5±5.09 years, and the average experience in the service they worked in was 3±2.83 years. The rate of those who heard the term 'frailty' for the first time is 63%. It was stated that 92.7% of the 110 surgical nurses participating in the study did not receive any training on fragility; It was stated that 50.9% of them think of the most vulnerable and weak patient when they think of a fragile patient. While 50% of them stated that when they suspected frailty in the patient, they evaluated involuntary weight loss, slowness (slowness in walking, muscle weakness), and fatigue; 70% stated that the biggest risk factor for frailty is being depressed or using antidepressant medication. Conclusions: According to the results of the study, it can be said that the awareness of surgical nurses about the "fragile patient" should be increased. In the light of the data obtained, it can be suggested to organize trainings on "fragile patients" for surgical nurses. 'Fragile patient' education should be included in pre-graduation education and in-service training.

728 Laparoscopic Fundoplication as a Day Case Procedure - Patient Comprehension for a Successful Model

Abstract Aim The British Association of Day Surgery states that elective laparoscopic Nissen’s fundoplication procedures should be performed as a day case in 40% of patients. The purpose of the study was to design a model for laparoscopic fundoplication to increase the numbers done as a day case procedure. Method This was a retrospective study of all patients who underwent laparoscopic fundoplication from 2014 - 2019. We introduced patient information leaflets and awareness amongst the patients regarding the procedure following our initial audit in 2014. Further intervention in terms of the surgical team and theatre staff awareness to reach our goal by distributing surgery-oriented pamphlets and information. We re-audited to see if there were any improvements in 2016 and 2019 when compared to our previous cohort. A total of 104 patients were audited through the years. Results In 2019, 34.4 % patients regardless of hiatus hernia size were discharged on the same day; 48.2 % patients were discharged on the next day; 24.1% patients had a large hiatus hernia or gastric volvulus; 40.9% patients excluding large and complicated hiatus hernia were discharged on the same day; 75.8 % patients had intraoperative local anaesthetic inject at the operative field. Conclusions The main two factors which contributed to improvement of our results were Intraoperative injection of local anaesthetic medications to operative field and Patient information pamphlets. Also, when a patient is made aware of the procedure being a day case in advance, they are more prepared to return home the same day following the procedure.

Assessment of Patient Handover Process from Operating Room to Intensive Care Unit at Cardiovascular Surgery Hospital of Ain Shams University

Abstract Background Handovers of post-anesthesia patients to the intensive care unit are commonly unstructured and performed under time pressure. The cardiovascular patients are transferred directly to intensive care unit after the operation, as these vulnerable patients need more and faster care. Therefore, the handover processes are more susceptible to poor communication, loss of information and potential patient harm. Objective To identify the frequency of defects of current practice of healthcare providers during handover process from operating room to ICU after cardiovascular surgery and to determine the contributing factors that affect the transition of care process. Methods This descriptive Cross-sectional study was conducted after cardiovascular surgery the intensive care unit of Cardiovascular Surgery Hospital, one of Ain Shams University Hospitals between December 2021 to March 2022. A checklist was used to assess the performance of handover processes of 120 adult patients after cardiovascular operation, which included 8 main areas (Contributing factor, Pre-handover, Equipment and technology handover, Patient specific information, Anesthesia information, Surgical information, Duration of handover process, Distraction) Results The mean age of patients was 56.03 ± 10.77 years and most of them 85 (70.8%) were males. The median number of errors in pre-handover process was 0(0), patient specific information 3(1), anesthesia information 3(0), surgical information 4.5(2) and equipment handover 3(0). The mean duration of handover processes in minutes was 15.09 ± 5.69 (range 8–35) and 76 (63.3%) of the processes had distractions. There was no significant correlation between age, duration of surgery, duration of handover and number of errors regarding (pre- handover, patient information, anesthesia information, surgical information and equipment handover).The important items were not handed over at all(name of the patient, allergies to medication, estimated blood loss, medications given during surgery which need to be restarted) Conclusions and Recommendations The overall omission is low in spite of the expected to be zero, taking into consideration the type of procedures and the patient condition, so the critical situation need every elements must be fulfilled for patient safety and to avoid complications that may threat the patient life.

P-490 ‘Your Fertility @ Home’, a clinical pilot study on a new diagnostic smartphone app for treatment naive fertility patients

Abstract Study question What are patients’ experiences with a newly developed diagnostic smartphone app? Summary answer The first patients’ experiences with the content of the app are positive. Also, participants made positive changes in their lifestyle after advice from the app. What is known already Previous studies on digital healthcare for fertility patients are promising. However, many e-Health initiatives are not thoroughly evaluated, which hampers implementation. During a fertility trajectory patients often feel a lack of control, we therefore developed a new smartphone app with a dual purpose. First, to give new fertility patients more control and empowerment over their situation by providing reliable information and personalized advice. Second, to support healthcare professionals in choosing the right diagnostic tests and interpretation of the results. This app was first validated on a historical cohort of patient data, before testing the app in a prospective patient group. Study design, size, duration This is an ongoing, prospective pilot study of 70 heterosexual patient couples. Patients were followed up from the start of the fertility workup until the work-up finished. This abstract covers the preliminary results of the first 19 participants. Follow up is expected to be complete at time of the ESHRE annual meeting. Participants/materials, setting, methods The study population consists of treatment naïve infertile couples, who were referred to a fertility-clinic. Before the first appointment, patients used the smartphone app, which consisted of a medical anamnesis questionnaire for both women and partners. Based on the anamnesis the app provided recommendations about lifestyle and diagnostic tests, which were in line with current Dutch guidelines. Patients were given advice on the results of the tests and filled in a questionnaire about their experiences. Main results and the role of chance The experience questionnaire for patients included three parts. The questions in the first part were based on the validated Patient-Centered Questionnaire Infertility. This covered questions about the use of the app, for example the ease of installation and if they felt involved with use of the app. Sixteen out of nineteen patients (84%) felt taken seriously, eleven patients (58%) experienced enough attention to their emotions and fourteen patients (74%) would advise their friends to use the app. The second part included questions about the results of the diagnostic tests. Ten patients (52%) found the explanation of the results clear, three patients (15%) wanted additional information. Eleven patients (58%) thought the results and information matched their personal situation. The third part of the questionnaire asked about the lifestyle advice patients received in the app. Twelve patients (63%) found this advice useful. The other patients found the advice not matching their situation. After using the app, ten patients (52%) said they made a change in their lifestyle to optimize their fertility situation. On a ten point Likert scale, 16 patients (84%) scored the app an eight or higher. Limitations, reasons for caution These are results of a pilot study and thus must be interpreted with caution. Secondly, this is the first version of the app that has been tested with patients, so next the app needs further optimization before it can be fully implemented. Wider implications of the findings Considering the positive reception, this app holds potential for a beneficial change in fertility care. It may increase the accessibility to reliable personal information and advice for new fertility patients in a safe and private environment. This might lead to patient empowerment and positive lifestyle changes enhancing their fertility potential. Trial registration number 2022.09.05.01

Pharmacists' role in combating medical misinformation

AbstractMedical misinformation can pose serious threats to public health. This commentary explores the pharmacist's unique role in addressing and mitigating the impact of medical misinformation. Pharmacists are uniquely positioned to engage with other healthcare providers, patients, and communities to dispel myths, provide accurate information, and promote evidence‐based healthcare decision‐making. This commentary showcases examples of the multifaceted roles of pharmacists in combating medical misinformation. It explores various strategies and interventions that can be used by pharmacists, including patient education, effective communication, information dissemination, and community engagement. Pharmacists' interventions are often at the intersection of medication management and health information needs, making them integral in ensuring patients and providers make informed healthcare choices. Moreover, this commentary highlights the impact pharmacists can have as advocates for scientific rigor and evidence‐based practices within healthcare systems to educate against medical misinformation and discusses the need for continued education, training, and support for pharmacists to excel in their roles as healthcare educators and medication experts. Pharmacists have a role in countering medical misinformation when serving patients by providing information that empowers a more informed society.

20 An Evaluation of the Quality and Readability of Online Information Regarding TMJ Dysfunction

Abstract Aim The accessibility and availability of the internet has allowed people to increasingly seek health information online, and therefore it plays an essential role in the decision-making process of the patient. The study aimed to assess the quality and readability of online health information on TMJ dysfunction. Method The search was conducted on Google using keywords: jaw pain, jaw locking, jaw discomfort, jaw clicking, jaw popping, temporomandibular joint, TMJ dysfunction, TMD and temporomandibular disorder. Ensuring Quality Information for Patient (EQIP) tool was used to assess quality of information and the application of readability score reflected through Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level(FKGL), Gunning-Fog Index(GFI) and Simple Measure of Gobbledygook(SMOG). Results 134 websites were eligible for assessment. The overall median EQIP score was 23, with an IQR of 7 and maximum score of 30. The most common source of information was healthcare industry (n=60; 45%), followed by news services (n=19; 14%), with a median EQIP score of 20 and 25 respectively. Statistically significant differences in overall EQIP scores were found between different sources of information (p=0.004). Only 31(23%) websites achieved the recommended 6th grade or below readability level, and only 14 (10%) discussed complication rates with none mentioning mortality rates at all. Conclusions Most online information on TMJ dysfunction is of suboptimal quality and readability. This study identified areas for improvements when producing patient material regarding TMJ dysfunction. To improve patient education and awareness, content creators should strive to be informative, accurate, and patient-centric.

280 Validating Artificial Intelligence Generated Patient Information Leaflets: A Patient Survey

Abstract Aim Artificial Intelligence (AI) is a ground-breaking technological advancement known for its prowess in processing extensive datasets, gaining recognition among clinicians for its potential in improving patient care. While AI is successfully employed in analysing medical imaging, its use in developing patient information literature (PIL) is limited. Patient access to information aligns with modern healthcare values, emphasizing shared decision-making, a priority in the NHS. This study, conducted under single-blinded conditions, explores the acceptability of AI-generated patient documentation. Method Four PIL examples related to common ENT procedures and conditions were identified. ChatGPT 3.5 modified existing PILs, adjusting for a UK reading age of 14. AI-generated PILs were formatted to match trust documents. Participants were blinded to leaflet sources. Results In 59 responses from ENT outpatients over six weeks, both AI and Trust leaflets had comparable appearance scores (AI 6.82, Trust 6.85). Although a slight preference for Trust leaflets existed, it wasn't statistically significant (p=0.47). In overall presentation preference, most participants had no preference (N=27), with one-third favoring Trust leaflets and 13 preferring AI-generated ones. In explaining conditions, over half had no preference (N=36), while 16 favored human-generated and 7 AI-generated leaflets. Readability and understanding were similar, with 25 participants finding both equally easy to read. Overall satisfaction was comparable, with 26 equally satisfied, 18 preferring human-generated, and 15 AI-generated leaflets. Conclusions AI technology integrated into clinical practice holds potential to transform PIL quality and quantity. As AI accessibility increases, healthcare services must guide the public to safeguard the standard of provided information.

Hybrid Summarization of Medical Records for Predicting Length of Stay in the Intensive Care Unit

Electronic health records (EHRs) are a critical tool in healthcare and capture a wide array of patient information that can inform clinical decision-making. However, the sheer volume and complexity of EHR data present challenges for healthcare providers, particularly in fast-paced environments such as intensive care units (ICUs). To address this problem, the automatic summarization of the main problems of patients from daily progress notes can be extremely helpful. Furthermore, by accurately predicting ICU patients’ lengths of stay (LOSs), resource allocation and management can be optimized, allowing for a more efficient flow of patients within the healthcare system. This work proposes a hybrid method to summarize EHR notes and studies the potential of these summaries together with structured data for the prediction of LOSs of ICU patients. Our investigation demonstrates the effectiveness of combining extractive and abstractive summarization techniques with a concept-based method combined with a text-to-text transfer transformer (T5), which shows the most promising results. By integrating the generated summaries and diagnoses with other features, our study contributes to the accurate prediction of LOSs, with a support vector machine emerging as our best-performing classifier with an accuracy of 77.5%, surpassing existing systems and highlighting the potential for optimal allocation of resources within ICUs.

O-069 The first mitotic spindle instability impacts nucleation, fragmentation, and development in human embryos

Abstract Study question How multinucleation and fragmentation occur in the first mitosis in human embryos? Summary answer The first mitotic spindles had heterogeneity, and the shapes and movements of the spindles were strongly associated with multinucleation and fragmentation. What is known already Studies have shown that many problems occur during the first mitosis, such as fragmentation and multinucleation. However, the cell biologic mechanisms whereby these errors occur during the first mitosis in human embryos remain unknown. To clarify this aspect, it is necessary to analysis the dynamics of DNA and cytoskeleton using live human embryos. Although microinjections of DNA or mRNA into mammalian embryos were widely used for live imaging during early mitosis, the method into human poses the risk of ethical issues. Therefore, we established a method used for real-time imaging in human embryos using chemical fluorescent labeling. Study design, size, duration Frozen human two-pronuclear stage embryos were donated for research by couples who had completed fertility treatment. We obtained written informed consent from patients who donated human embryos. The mean age of patients at embryo freezing was 32.00 ± 3.03 (SD) years. We imaged thirty-one living human embryos using chemical fluorescent labeling and confocal microscopy to visualize DNA and tubulin. Participants/materials, setting, methods Thirty-one human embryos were cultured in medium containing the live-cell stain probes SPY555-DNA and SPY650-Tubulin. The Embryos were imaged using an LSM980 laser scanning confocal microscope every 10–20 min for a period of eight hours. Three-dimensional (3D) visualizations of human embryos were performed using the Imaris software. The first spindle shapes were quantified by image analysis and calculated the aspect ratio of the spindles using ImageJ. Main results and the role of chance We discovered that over 81% of two-pronuclear zygotes became multinucleated 2-cell stage embryos. We demonstrated that there was variation in the first mitotic spindles. There was a significant difference between the aspect ratio (AR) of the spindles leading to the mononuclear and multinuclear types at the 2-cell stage (p < 0.005). In addition, the low-AR spindles were unstable and often had more defocused poles than the high-AR spindles, which lead to multinucleation at the 2-cell stage (55 % vs. 0%, p < 0.05). More embryo having high-aspect ratio spindles tend to develop blastocysts than those having low aspect-ratio spindles (p < 0.05). Moreover, the movement of the central spindles varied after chromosome segregation. The embryos with more fragments at two cell stage had a significantly longer period for the central spindles to transform into midbodies compared to those with fewer fragments. The central spindles of embryos with more fragments moved a longer distance from the beginning of furrow ingression to the completion of the first division (p < 0.05). These results suggest that the first mitotic spindle instability and heterogeneity cause many errors such as multinucleation, fragmentation, and embryonic development. Limitations, reasons for caution Imaged human embryos were donated from a fertility clinic, and detailed patient information, such as underlying disease and method of ovarian stimulation, was not available. It is possible that the human zygotes used in this study had a bias in patient characteristics. Wider implications of the findings Our study showed that there were instability and heterogeneity in the first mitotic spindle, which was strongly associated with multinucleation, fragmentation, and embryonic development. Revealing the mechanism underlying spindle formation in cleavage-stage embryos will contribute to improving the success rate of assisted reproduction technologies in humans. Trial registration number not applicable

Improved security of medical images using DWT–SVD watermarking mechanisms based on firefly Photinus search algorithm

Security is the primary concern in the transmission of medical images, as it involves sensitive patient information. This study introduces an optimized watermarking approach, constructed using discrete wavelet transform and singular value decomposition. The Low- level frequency bands (LL3) sub-band singular values of the host image were embedded with the singular values of a binary watermark using multiple scaling factors. These MSFs were optimized using a recently proposed firefly Photinus algorithm to balance robustness and imperceptibility. The proposed method was applied to various images, including computed tomography images, where the visual quality of the signed and attacked images was evaluated by peak signal-to-noise ratio (PSNR) and normalized cross-correlation. The performance of the proposed algorithm demonstrates significant improvements in the embedding and extraction processes, showing an enhancement in the balance between robustness and imperceptibility, with a PSNR above 79.28 dB, compared to other related works.

Integrity and Privacy Assurance Framework for Remote Healthcare Monitoring Based on IoT

Remote healthcare monitoring (RHM) has become a pivotal component of modern healthcare, offering a crucial lifeline to numerous patients. Ensuring the integrity and privacy of the data generated and transmitted by IoT devices is of paramount importance. The integration of blockchain technology and smart contracts has emerged as a pioneering solution to fortify the security of internet of things (IoT) data transmissions within the realm of healthcare monitoring. In today’s healthcare landscape, the IoT plays a pivotal role in remotely monitoring and managing patients’ well-being. Furthermore, blockchain’s decentralized and immutable ledger ensures that all IoT data transactions are securely recorded, timestamped, and resistant to unauthorized modifications. This heightened level of data security is critical in healthcare, where the integrity and privacy of patient information are nonnegotiable. This research endeavors to harness the power of blockchain and smart contracts to establish a robust and tamper-proof framework for healthcare IoT data. Employing smart contracts, which are self-executing agreements programmed with predefined rules, enables us to automate and validate data transactions within the IoT ecosystem. These contracts execute automatically when specific conditions are met, eliminating the need for manual intervention and oversight. This automation not only streamlines the process of data processing but also enhances its accuracy and reliability by reducing the risk of human error. Additionally, smart contracts provide a transparent and tamper-proof mechanism for verifying the validity of transactions, thereby mitigating the risk of fraudulent activities. By leveraging smart contracts, organizations can ensure the integrity and efficiency of data transactions within the IoT ecosystem, leading to improved trust, transparency, and security. Our experiments demonstrate the application of a blockchain approach to secure transmissions in IoT for RHM, as will be illustrated in the paper. This showcases the practical applicability of blockchain technology in real-world scenarios.