Patient Data Research Articles

The impact of smartphone-dispatched CPR-trained volunteers on OHCA outcomes is influenced by patient age

The early initiation of cardiopulmonary resuscitation (CPR) measures by non-professionals before the arrival of Emergency Medical Service (EMS) is known to be crucial for improving outcomes after out-of-hospital cardiac arrest (OHCA). We assessed the impact of deploying CPR-trained volunteers via a smartphone-based alerting system on the outcome of OHCA patients. In a retrospective nonrandomized cohort study, all OHCA cases in the city of Aachen over a six-year period were analysed. We compared patient data, CPR metrics, alerting system data as well as outcome data between the intervention and control groups. From June 2017 to May 2023, 101 out of 852 resuscitations were initiated by volunteers alerted via a smartphone-based alerting system in OHCA events. We found no overall rise in the return of spontaneous circulation (ROSC) rate. An age-dependent subgroup analysis indicated an increased incidence of initially shockable rhythms and an increased ROSC rate for patients younger than 60 years in the intervention group, while implying a lower ROSC rate in patients older than 80 years after mobile responder CPR. Although this study was underpowered to yield statistically significant results, our findings suggest the need for an age-sensitive approach when evaluating the effects of first-responder systems on OHCA cases.

Accurate Differential Diagnosis of Cardiomyopathy Phenotype Based on Multimodal AI Technology

Cardiomyopathy is a group of diseases involving the heart muscle, mainly manifested by the abnormality of the structure and function of the heart muscle. According to etiology and pathological characteristics, cardiomyopathy can be divided into various types, including hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), arrhythmogenic right ventricular cardiomyopathy (ARVC), non-dilated left ventricular cardiomyopathy (NDLVC) and restrictive cardiomyopathy (RCM). These different types of cardiomyopathy differ significantly in clinical presentation, pathophysiological mechanisms, and treatment strategies, so accurately differentiating the different phenotypes of cardiomyopathy is critical to developing a personalized treatment plan. However, traditional diagnostic methods such as electrocardiogram (ECG), echocardiography, magnetic resonance imaging (MRI) and genetic testing, while able to provide useful information to a certain extent, still have limitations in complex cases and can lead to misdiagnosis or missed diagnosis. In order to overcome the limitations of traditional diagnostic methods and improve the ability of accurate diagnosis of different phenotypes of cardiomyopathy, this study developed a cardiomyopathy phenotypic differential diagnosis system based on multimodal artificial intelligence (AI) technology. We integrate patient data from multiple centers, including clinical data, electrocardiograms (ECG), echocardiograms, magnetic resonance imaging (MRI), and genomic data, standardized and pre-processed. Through machine learning and deep learning algorithms, multimodal AI models are constructed and trained using large-scale training data sets. The accuracy and stability of the model in the differentiation of different cardiomyopathy phenotypes were verified on an independent data set, and the model parameters were optimized according to the verification results to improve the generalization ability and clinical applicability of the model.

Evaluating Large Language Model-Assisted Emergency Triage: A Comparison of Acuity Assessments by GPT-4 and Medical Experts.

To evaluate the accuracy of the Emergency Severity Index (ESI) assignments by GPT-4, a large language model (LLM), compared to senior emergency department (ED) nurses and physicians. An observational study of 100 consecutive adult ED patients was conducted. ESI scores assigned by GPT-4, triage nurses, and by a senior clinician. Both model and human experts were provided the same patient data. GPT-4 assigned a lower median ESI score (2.0) compared to human evaluators (median 3.0; p < 0.001), suggesting a potential overestimation of patient severity by the LLM. The results showed differences in the triage assessment approaches between GPT-4 and the human evaluators, including variations in how patient age and vital signs were considered in the ESI assignments. While GPT-4 offers a novel methodology for patient triage, its propensity to overestimate patient severity highlights the necessity for further development and calibration of LLM tools in clinical environments. The findings underscore the potential and limitations of LLM in clinical decision-making, advocating for cautious integration of LLMs in healthcare settings. This study adhered to relevant EQUATOR guidelines for reporting observational studies.

Rapid in vivo EPID image prediction using a combination of analytically calculated attenuation and AI predicted scatter.

The electronic portal imaging device (EPID) can be used in vivo, to detect on-treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the patient's anatomy and plan information. To date in vivo transit images have been predicted using Monte Carlo (MC) algorithms. A deep learning approach can make predictions faster than MC and only requires patient information for training. To test the feasibility and reliability of creating a deep-learning model with patient data for predicting in vivo EPID images for IMRT treatments. In our approach, the in vivo EPID image was separated into contributions from primary and scattered photons. A primary photon attenuation function was determined by measuring attenuation factors for various thicknesses of solid water. The scatter component ofin vivoEPID images was estimated using a convolutional neural network (CNN). The CNN input was a 3-channel image comprised of the non-transit EPID image and ray tracing projections through a pretreatment CBCT. The predicted scatter component was added to the primary attenuation component to give the full predictedin vivo EPID image. We acquired 193 IMRT fields/images from 93 patients treated on the Varian Halcyon. Model training:validation:test dataset ratios were 133:20:40 images. Additional patient plans were delivered to anthropomorphic phantoms, yielding 75 images for further validation. We assessed model accuracy by comparing model-calculated and measuredin vivoimages with a gamma comparison. Comparing the model-calculated and measured in vivo images gives a mean gamma pass rate for the training:validation:test datasets of 95.4%:94.1%:92.9% for 3%/3 mm and 98.4%:98.4%:96.8% for 5%/3mm. For images delivered to phantom data sets the average gamma pass rate was 96.4% (3%/3 mm criteria). In all data sets, the lower passing rates of some images were due to CBCT artifacts and patient motion that occurred between the time of CBCT and treatment. CONCLUSIONS: The developed deep-learning-based model can generatein vivoEPID images with a mean gamma pass rate greater than 92% (3%/3 mm criteria).This approach provides an alternative to MC prediction algorithms. Image predictions can be made in 30 ms on a standard GPU. In future work, image predictions from this model can be used to detectin vivo treatment errors and on-treatment changes in patient anatomy, providing an additional layer of patient-specific quality assurance.

Type 2 diabetes mellitus remission following laparoscopic sleeve gastrectomy and hindgut-based procedure: a retrospective multicenter study.

Sleeve gastrectomy (SG) is considered the standard bariatric surgery due to its excellent outcomes. However, in patients with obesity and type 2 diabetes mellitus (T2DM), SG alone carries a high risk of metabolic failure. To achieve better metabolic results, SG can be combined with either foregut- or hindgut-based procedures, although a direct comparison between these approaches is lacking. In this retrospective study, we compared the bariatric and metabolic effects of SG (n = 20 patients) with SG associated with duodenal diversion and ileal interposition (SG-DD-II) (n = 20), SG associated with duodenal-ileal anastomosis (SADI-S) (n = 20), and SG associated with single gastro-ileal anastomosis (SASI-S) (n = 20). Patient data, including anthropometric measurements and T2DM characteristics, were extracted from our database. The evaluation criteria included weight loss (% excess weight loss), fasting glycemia (FGL), glycated hemoglobin (HbA1C) percentage, and T2DM remission rates. Our statistical analysis (p < 0.05) revealed that shortly after surgery, all procedures demonstrated acceptable outcomes in terms of weight loss and T2DM remission. However, after 3 and 5years post-surgery, the T2DM relapse rate was significantly higher following SG alone compared to hindgut-based operations. In patients with obesity and T2DM, we recommend combining SG with a hindgut-based procedure to reduce the long-term relapse rate.

Serum S100A8/A9 Correlates to Surgery-Free Interval in Idiopathic Subglottic Stenosis.

Idiopathic subglottic stenosis (iSGS) is a progressive fibrotic condition of the subglottis that presents in women of northern European descent. Endoscopic dilation is a common surgical approach to management of iSGS. The surgery-free interval, or the time between endoscopic dilation procedures is considered an indicator of disease severity. Variations in surgery-free intervals among iSGS patients underscore the necessity for prognostic biomarkers. The objective of this study was to explore serum levels of the damage-associated molecular pattern S100A8/A9 as a prognostic biomarker in iSGS. Serum from 20 iSGS patients and eight healthy controls was collected and S100A8/A9 levels were quantified using an ELISA. Patient data, including demographics and surgery-free intervals, were obtained from medical records. Serum S100A8/A9 levels were compared to surgery-free intervals. S100A8/A9 was also assessed using gene expression and immunofluorescence in iSGS specimens. S100A8/A9 was significantly elevated (p = 0.0413) in the serum of iSGS patients compared to controls (312.75 vs. 181.49 ng/mL). Linear regression analysis revealed a correlation (p = 0.009) between S100A8/A9 levels and endoscopic surgery-free interval. S100A8/A9 was significantly elevated (p = 0.0011) in patients with surgery-free intervals less than 1 year (455.2 ± 60.45 ng/mL; n = 8) compared to patients with intervals over 1 year (292.5.93 ± 162.4; n = 6). S100A8/A9 is increased in the serum and tissue of patients with iSGS. In this cohort of iSGS patients, serum S100A8/A9 was associated with surgery-free intervals, potentially representing a prognostic biomarker. Further research within a larger cohort is needed to confirm these findings. Level 3 Laryngoscope, 2024.

Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review.

Clinical decision support systems (CDSSs) are designed to assist in health care delivery by supporting medical practice with clinical knowledge, patient information, and other relevant types of health information. CDSSs are integral parts of health care technologies assisting in disease management, including diagnosis, treatment, and monitoring. While electronic medical records (EMRs) serve as data repositories, CDSSs are used to assist clinicians in providing personalized, context-specific recommendations derived by comparing individual patient data to evidence-based guidelines. This targeted literature review (TLR) aimed to identify characteristics and features of both stand-alone and EMR-integrated CDSSs that influence their outcomes and benefits based on published scientific literature. A TLR was conducted using the Embase, MEDLINE, and Cochrane databases to identify data on CDSSs published in a 10-year frame (2012-2022). Studies on computerized, guideline-based CDSSs used by health care practitioners with a focus on chronic disease areas and reporting outcomes for CDSS utilization were eligible for inclusion. A total of 49 publications were included in the TLR. Studies predominantly reported on EMR-integrated CDSSs (ie, connected to an EMR database; n=32, 65%). The implementation of CDSSs varied globally, with substantial utilization in the United States and within the domain of cardio-renal-metabolic diseases. CDSSs were found to positively impact "quality assurance" (n=35, 69%) and provide "clinical benefits" (n=20, 41%), compared to usual care. Among CDSS features, treatment guidance and flagging were consistently reported as the most frequent elements for enhancing health care, followed by risk level estimation, diagnosis, education, and data export. The effectiveness of a CDSS was evaluated most frequently in primary care settings (n=34, 69%) across cardio-renal-metabolic disease areas (n=32, 65%), especially in diabetes (n=13, 26%). Studies reported CDSSs to be commonly used by a mixed group (n=27, 55%) of users including physicians, specialists, nurses or nurse practitioners, and allied health care professionals. Overall, both EMR-integrated and stand-alone CDSSs showed positive results, suggesting their benefits to health care providers and potential for successful adoption. Flagging and treatment recommendation features were commonly used in CDSSs to improve patient care; other features such as risk level estimation, diagnosis, education, and data export were tailored to specific requirements and collectively contributed to the effectiveness of health care delivery. While this TLR demonstrated that both stand-alone and EMR-integrated CDSSs were successful in achieving clinical outcomes, the heterogeneity of included studies reflects the evolving nature of this research area, underscoring the need for further longitudinal studies to elucidate aspects that may impact their adoption in real-world scenarios.

Prevalence and influencing factors of sarcopenia among patients with knee osteoarthritis: a systematic review and meta-analysis protocol

IntroductionEpidemiological literature indicates that sarcopenia (SA) is increasingly prevalent among patients with knee osteoarthritis (KOA). This study aims to provide the pooled prevalence of SA and identify determinant factors associated...

Survival trends and conditional survival in patients with pulmonary metastases from differentiated thyroid carcinoma.

Patients with pulmonary metastases from differentiated thyroid carcinoma (DTC) have a significantly poorer prognosis compared to DTC patients without metastases. This study aimed to establish a nomogram combined with dynamic survival analysis to predict the survival probability of patients with pulmonary metastases from differentiated thyroid carcinoma and compensate for the underestimation of survival in patients with very poor prognosis. Patient data were collected from the Surveillance, Epidemiological, and End Result (SEER) data resource from 2010 to 2019. Multivariate analysis was carried out by the Cox proportional hazards regression to construct a nomogram. Receiver operating characteristic (ROC) curves along with calibration were employed to assess the effectiveness of the model.The life table was used to estimate the conditional cancer-specific survival (CSS). In the training set, the AUCs for the CSS nomogram were 0.728, 0.741, and 0.779, with a c-index of 0.682, indicating good predictive performance at 3, 5, and 10 years. In the validation set, the AUCs for the CSS nomogram were 0.706, 0.726, and 0.769, with a c-index of 0.696, while the AUCs for the 8th TNM staging system were 0.521, 0.555, and 0.601, with a c-index of 0.579. The overall 5-year conditional survival rate for patients increased slightly from 63.44 to 70.52%. The survival gap was greatest between patients aged <55 years and those aged ≥55 years. We established a nomogram combined with dynamic survival analysis, which serve as promising options for prognosis estimation, to enhance personalized evaluation of survival risks and provide the basis for the development of more clinical treatment approaches.

The role of artificial intelligence in enhancing healthcare for people with disabilities

The integration of artificial intelligence (AI) in healthcare delivery represents a transformative opportunity to enhance the lives of people living with disabilities. AI-driven technologies, such as assistive devices, conversational agents, and rehabilitation tools, can mitigate health disparities, improve diagnostic accuracy, and facilitate effective communication with healthcare providers, fostering more equitable healthcare environments. This commentary explores these applications while addressing the ethical challenges and limitations associated with AI deployment. Specific challenges, such as algorithmic bias, privacy risks with patient data, and the complexity of designing inclusive technologies, are discussed to provide a balanced perspective. For example, biased diagnostic tools may lead to inequitable care, and privacy breaches can compromise sensitive data. Key areas of focus include personalised care through AI-powered systems, the design of inclusive AI technologies incorporating continuous feedback loops and partnerships with advocacy groups, and the development of AI-enabled robotics for physical assistance. This commentary paper emphasises the importance of addressing these limitations alongside advancing ethical AI practices and ensuring continuous user involvement to meet the diverse needs of people living with disabilities, ultimately promoting greater independence and participation in society. Consequently, while AI holds transformative potential in advancing equitable and inclusive healthcare for people with disabilities, addressing ethical challenges, overcoming limitations, and fostering user-centred design are essential to fully realise its benefits and ensure these innovations promote autonomy, accessibility, and well-being.

Adequacy of histopathology request forms and specimens sent to two histopathology centers in Khartoum, Sudan

Abstract Background Every branch of surgery relies in some way on histology to obtain a conclusive diagnosis. Since precise and comprehensive information on the request form is crucial to the correct analysis and interpretation of test results, it is anticipated that all patient data and information for any requested test be provided. One of the most significant duties of the peri-operative team is the care and handling of intraoperative surgical specimens. Poor labeling and handling of surgical specimens can lead to unfavorable consequences such as misdiagnosis, incorrect or delayed therapy, and even the need for repeat surgery. The study’s. objective is to highlight the primary mistakes that occur in the pre analytical stage of histopathology request forms and specimens at two Khartoum-based histopathological institutions. Methods A prospective descriptive laboratory based cross-sectional study was carried out on 528 request forms and specimens sent to two histopathology centers between the period of May to August 2019 having gotten Ethical clearance from SMSB. Results A total of 528 laboratory request forms and specimens, Age was written in 75.6% (n 399), while the gender only was written only in 46.2% (n 244). No clinical history in 48.3% (n 255). The differential diagnosis found only in 29.5% (n156) of request forms. Regarding specimen 15.7% (83) were inadequate relative to the size of the container and only 5.3% (28) were not labeled with any information. 17.4% (92) were not sent in formalin but in normal saline. Marking of the specimen was not needed in 60% (317) and among the rest cases; 34.2% was not marked. Conclusion The study shows that laboratory request forms were not properly and thoroughly completed. Most of the specimens sent for histology had inadequate fixative and unsuitable containers, or they were mislabeled and not properly tagged. This for sure will have a detrimental effect on the quality of care.

Homozygous CDKN2A/B deletions in low- and high-grade glioma: a meta-analysis of individual patient data and predictive values of p16 immunohistochemistry testing.

CDKN2A/B deletions are prognostically relevant in low- and high-grade gliomas. Data on this is derived from heterogeneous series, an accurate estimation of survival risk from homozygous CDKN2A/B deletion is missing. Besides genetic testing, p16-immunohistochemistry (IHC) as a less cost intensive means for indirect detection of CDKN2A/B alterations is possible but not validated in larger datasets. The present meta-analysis aimed to (1) reconstruct individual patient data (IPD) and estimate overall survival (OS) stratified by CDKN2A/B status from all literature and to (2) determine accuracy of p16 testing for CDKNA2/B detection from published studies. For survival analysis according to CDKN2A/B status 460 records were screened, four articles with 714 participants were included. In IDH-wildtype (IDH-wt) gliomas, 57.07% harbored the deletion compared to 9.76% in IDH-mutant (IDH-mut) gliomas. Median OS of patients with IDH-wt gliomas and homozygous CDKN2A/B deletion was 13.0 months compared to 18.0 months with non-deleted CDKN2A/B (p = 0.014, Log-Rank). With homozygous deletion of CDKN2A/B the risk of death was increased by 1.5 (95%-CI 1.1-2.1). Median OS in patients with IDH-mut gliomas without CDKN2A/B deletion was 92.0 months compared to 40.0 months with CDKN2A/B deletion (p < 0.001, Log-Rank). CDKN2A/B deletions were associated with a significantly shorter OS (HR = 3.2; 95%-CI 2.2-5.5). For p16 IHC analysis, 10 eligible studies with 1087 examined samples were included. The cut-off for retention differed between the studies. In 588/662 p16 retained cases CDKN2A/B deletions was not detected, implying a negative predictive value (NPV) of p16 staining of 88.8%. Conversely, 279/425 p16 absent cases showed a CDKN2A/B deletion resulting in a positive predictive value (PPV) of 65.6%. Sensitivity of p16 staining for CDKN2A/B detection was 79.0%, specificity 80.1%. Highest diagnostic accuracy of p16 IHC was reached with a cut-off of > 5% and within IDH-mut glioma.

Inhalation corticosteroids for COVID-19 - a real world data analysis on guideline adherence.

The recommendation to consider prescribing inhalation corticosteroids to a subgroup of vulnerable COVID-19 patients was added to the Dutch medical guideline on November 11, 2021, and was also adopted by other countries during the pandemic. To evaluate the adherence of general practitioners to this guideline, and whether real-world data quality is sufficient to study the effect of revised guidelines on prescribing behaviour. A retrospective cohort study using Dutch primary care data from the Extramural LUMC Academic Network database, containing patient data of 129 general practices in the Leiden - The Hague area. We performed an interrupted time series analysis to measure the effect of the new guideline on the prescription rate of ICS, accounting for general trend and seasonal fluctuations. Between July 1, 2020 to August 1, 2022, 131,482 patients had 164,098 COVID-19 consultations. During this period, 1,709 patients received 2094 ICS prescriptions for COVID-19. After the guideline update, there was an instantaneous decrease in prescription rate (IRR 0.47, 95% CI 0.32-0.69). Prescription rate in the subgroup of vulnerable patients did not change significantly (IRR 0.93, 95% CI 0.66-1.32), while less vulnerable patients were significantly prescribed less (IRR 0.29, 95% CI 0.14-0.59). The revision to COVID-19 guidelines had significant impact on general practitioners' prescription behaviour soon after publication: prescription rate remained constant for vulnerable patients, while less vulnerable patient were significantly prescribed less often. Using electronic health records it is feasible to assess changes in guideline adherence using interrupted time series.

Enhancing Care Coordination in Oncology and Nononcology Thoracic Surgery Care Pathways Through a Digital Health Solution: Mixed Methods Study.

Health-system fragmentation in Quebec significantly impacts care coordination, leading to interruptions in patients' care pathways and adverse effects on their health. Coordinating interfacility service corridors is complex and requires collaboration between multiple health care providers (HCPs) and care settings. Effective care coordination is essential to ensure optimal patient management at transition points. This study aims to improve oncology and nononcology thoracic surgery care pathways by enhancing care coordination during interfacility transfers through a digital health solution. A multicenter implementation study was conducted across 2 health regions and 2 health care facilities in Quebec. We conducted 27 semistructured interviews with HCPs and managers to better understand the care pathways. Participatory design workshops were held with future users and key stakeholders at an early stage of the technology's design to validate the prototype's functionalities and workflows. A web survey was sent to all end users (N=13) to assess their experience with the platform. All participants (100%) either "agreed" or "strongly agreed" that the platform provided significant benefits. It enhanced interestablishment coordination (4/13, 31% agreed and 9/13, 69% strongly agreed) and continuity of care and services (8/13, 62% agreed and 5/13, 38% strongly agreed), and it contributed to better management and patient intake (10/13, 77% agreed and 3/13, 23% strongly agreed) and process fluidity (3/13, 77% agreed and 3/13, 23% strongly agreed). Surgeons from the McGill University Health Centre confirmed that the platform facilitated and secured information transmission (2/5, 40% agreed and 3/5, 60% strongly agreed) and kept track of oncology patient referrals, follow-up needs, and cases where surgery is unnecessary (2/5, 40% agreed and 3/5, 60% strongly agreed). Nursing staff from the Centre intégré de santé et de services sociaux de l'Outaouais and McGill University Health Centre reported high satisfaction with the platform's support during preoperative visit, surgery, and discharge processes. All participants perceived the platform as intuitive and easy to use. Additionally, participants valued its efficiency in providing rapid access to patient data, which reduces task time and ensures document security, thereby improving care coordination across facilities. The project's success has convinced the HCPs and senior management at both health care facilities to pursue long-term use of the Akinox digital health platform. This pilot project represents a significant advancement in thoracic surgery care pathways and the coordination of interfacility health care service corridors. The project provides care pathways that are adaptable to other surgical specialties. It also paves the way for improving care in cancer and other health care networks while highlighting the key role of nurse navigators in patient care management. The project underscores the value of strategic leadership and stakeholders' collaboration to improve care coordination and operational efficiency by demonstrating technology's essential role in patient care pathways.

Concomitant Use of Proton Pump Inhibitors and CDK4/6 inhibitors in Metastatic Hormone-Positive Breast Cancer: A Real World Cohort Study

Introduction: Conflicting evidence exists regarding the concurrent use of cyclin-dependent kinase (CDK) 4/6 inhibitors and proton pump inhibitors (PPIs) in the treatment of breast cancer. This study aimed to investigate whether PPI use interferes with the efficacy of CDK4/6 inhibitors. Methods: This retrospective, multicenter, real-world study included 205 patients with hormone receptor-positive, HER2-negative metastatic breast cancer. Patient data were collected from January 2020 to August 2023. Patients who received either ribociclib or palbociclib, with or without a PPI, were included. Median progression-free survival (mPFS) was estimated using the Kaplan-Meier method, and factors associated with mPFS were analyzed using Cox regression. Results: Among the patients, 100 received palbociclib and 105 received ribociclib. In the palbociclib group, 40 patients (40%) used a PPI, and 60 (60%) did not. The mPFS was 16.1 months for patients with a PPI versus 22.2 months for those without (p=0.26). In the ribociclib group, 44 patients used a PPI and 61 did not use a PPI. The median PFS was comparable between patients receiving PPIs and those not receiving PPIs. (19.3 months and 20.7 months, respectively). Poor PFS was associated with liver metastasis, brain metastasis, and high Ki-67. Conclusion: Concomitant use of PPIs with ribociclib or palbociclib did not affect the efficacy of either CDK4/6 inhibitor. PPIs can be administered alongside these medications when clinically indicated

Steganography Algorithms in Computed Tomography (CT) Scan Images

Steganography is a technique which allows to hide information or data inside a medium without giving an idea to people that the hidden data even existed. In the medical field, there are cases where patient’s medical images breached along with their sensitive and personal data because of poor security. This problem leads to a wanting of a good solution to have the medical image with secured patient data. Here is where the image steganography takes place to hide the patient data inside the medical images. This study is conducted to determine the effective image steganography algorithm to be used in the medical field to embed the patient information inside their medical images specifically in Computed Tomography (CT) scan images. The image steganography algorithms that will be used in this study are Least Significant Bit (LSB), Exploiting Modification Direction (EMD) and Discrete Wavelet Transform (DWT). The flow of the image steganography technique will be studied and analyzed and after that, the algorithms will be implemented with different file formats which are Portable Network Graphics (PNG), Bitmap (BMP) and Joint Photographic Experts Group (JPG) and different image sizes which are 1024x1024 and 2048x2048 pixels. After that, the results are evaluated with performance metrics which are Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM) and Pairs Analysis. The results are then compared to determine the best image steganography algorithm along with the image file format which gives the highest robustness, visual quality, security and imperceptibility. The research result displays the EMD algorithm as the best paired with BMP file format in image steganography where it resulted in producing highest average of SSIM and PSNR which is 1.0 and 67.421 respectively and lowest MSE average of 0.012 with no traces in pairs analysis.

A novel comprehensive metric balancing imaging dose and setup accuracy in image-guided radiotherapy: concept proposal and clinical validation

PurposeTo propose and validate a comprehensive novel metric balancing the registration accuracy and imaging dose for image-guided-radiotherapy based on real patient data.Materials and methodsWith written informed consent and ethical approval, 56 patients were scanned using 6MV CBCT, 140 kV CBCT, and 100 kV CBCT on Halcyon system for three consecutive treatment fractions. Online registration was performed by various on-duty therapists under routine clinical pressure and time limitation. Offline registration was carried out by an experienced physicist without pressure. The consistency between the online and offline results was used as a surrogate of the missing ground-truth of registration accuracy, which was usually developed by introducing ‘known’ setup errors and rescan the phantoms, yet is ethnically not applicable to real patients. The registration differences (ΔD) between various imaging methods and observers were analyzed. The weighted CT dose index (CTDIw) for kV and MV CBCT was acquired using the PTW CTDI head phantom. The weighted-Dose-Accuracy-Product (DAPw) index was defined as DAPw =ΔD(mm) w1* CTDIw(mGy) w2, where w1 and w2 are the weighting factors of accuracy and dose respectively (w1+w2 = 1).ResultsThe mean and interquartile range (IQR) of ΔD decreased monotonically for MV CBCT, 100 kV CBCT, and 140 kV CBCT, supporting the registration consistency as a surrogate metric of image quality. Significant differences of ΔD were observed between the online and offline registration across three imaging methods (P&amp;lt;0.05). The 140 kV CBCT provides superior positioning accuracy, less dependency on observer subjectivity and time pressure of clinical workflow. Using w1=w2 = 0.5 as an example, the smallest mean, standard deviation, and IQR of DAPw were observed on the 100 kV CBCT, indicating optimal balance between dose and accuracy than the other two methods. Analysis of variance (ANOVA) showed statistically significant differences in DAPw among the different imaging methods (P&amp;lt;0.01, F=50.57).ConclusionUsing registration consistency as a surrogate indicator of image quality, this study proposed and validated a novel “DAPw” parameter based on real patient data, providing a purpose-specific tool for balancing setup accuracy and radiation dose in clinic.

Intrauterine Fetal Death and the COVID-19 Pandemic: Looking beyond SARS- CoV-2 Infection

Background: COVID-19 pandemic has caused high numbers of deaths and complications since 2020. Though the risk is the same as in the general population, pregnant women with COVID-19 are especially susceptible to developing complications because of their altered physiology. The objective of this retrospective study is to investigate the relationship betweenthe COVID-19 pandemic period and intrauterine fetal death, which can help to take steps to reduce intrauterine fetal death during the pandemic. Materials and methods: This retrospective study compared the intrauterine fetal death rate during the pre-pandemic (March 01, 2019 to February 29, 2020) and the pandemic period (March 01, 2020, to February 28, 2021) in a tertiary referral hospital in Bangladesh. Patient data were collected from the record-keeping register of the Department of Obstetrics and Gynecology and analyzed by computer-based software presented in graph, chart and table. Results: Out of 21717 obstetric patients admitted patients,821 (3.78%) were documented as cases of intrauterine fetal death in the pre-pandemic period, whereas in the pandemic period, the number was 895 (4.86%) out of 18424. Due to inadequate data records and considering the exclusion criteria, a total of 790 IUFD patients of the pre-pandemic period and 860 IUFD patients of the pandemic period were included in this study. Conclusion: The percentage of IUFD on obstetric admission showed significantly (p&lt;0.001) higher in the pandemic period compared to that in the pre-pandemic period. This result is important for providing insights to the policy makers for future planning, counseling of women wishing to become pregnant, and prioritizing their safety, including their vaccination. Chatt Maa Shi Hosp Med Coll J; Vol.22 (2); July 2023; Page 47-50

Spinal Metastases in Non-Seminomatous Germ Cell Testicular Tumors: Prognosis and Integrated Therapeutic Approaches—A Systematic Review with an Institutional Case Illustration

(1) Background: Testicular cancer, although accounting for only 0.5% to 1% of all solid male cancers, is the most common malignancy in males aged 15 to 35 years. Non-seminomatous germ cell tumors (NSGCT) represent nearly half of all testicular germ cell tumors and are associated with a more aggressive clinical course. Spinal metastases, while rare, pose significant challenges due to their potential to cause spinal cord compression, neurological deficits, and severe pain. This systematic review aims to evaluate prognosis and treatment approaches for spinal metastases in NSGCT, with a focus on multidisciplinary care and treatment outcomes. (2) Methods: A systematic review was conducted following PRISMA guidelines. PubMed, Scopus, and Embase were searched on 18 September 2024, using the Boolean search strategy [(Nonseminomatous germ cell tumor (NSGCT) AND (spinal OR vertebral metastases)]. Case reports, case series, and cohort studies providing detailed patient data were included. Data on patient demographics, tumor histology, metastatic site, treatments, and outcomes were extracted for analysis. (3) Results: A total of 164 cases of NSGCT with spinal metastases were analyzed, with patients aged 23 to 40 years (median: 31.5 years). The lumbar spine was involved in all cases, and spinal cord compression occurred in 59.8% of patients, often causing severe neurological symptoms such as cauda equina syndrome. Chemotherapy, primarily cisplatin-based, was administered in all cases, while surgical interventions, including laminectomy and vertebrectomy, were performed in cases of spinal compression and instability. Complete remission occurred in only 2.4% of patients. Progressive improvement was observed in 56.7% of cases, while 20.1% of patients died. Outcomes varied, highlighting the importance of individualized, multidisciplinary care to manage both systemic and localized disease. (4) Conclusions: Spinal metastases in NSGCT represent a complex clinical scenario, requiring a combination of chemotherapy, surgery, and in some cases, radiotherapy. Chemotherapy remains essential, but surgery is critical for addressing spinal compression and instability. A multidisciplinary approach is vital for optimizing outcomes, as prognosis is variable, with some patients achieving improvement while others face progressive disease or death. Further research is needed to refine the role of radiotherapy and improve long-term treatment strategies for this rare complication.

Peripherally inserted central venous catheter in outpatient antibiotic spinal infection treatment is safe, effective and leads to significant reduction in healthcare expenses

Prolonged antibiotic therapy is often recommended for the treatment of spinal infections. This study aimed to evaluate the efficacy and safety of outpatient intravenous (IV) antibiotic therapy for spinal neurosurgery patients with spondylodiscitis. We carried out a retrospective study involving 67 patients who were administered peripherally inserted central catheter (PICC) for IV antibiotic treatment from January 2020 to December 2022. We assessed patient data concerning infections and neurosurgical concerns. Each patient underwent a minimum of 6 weeks of IV antibiotics, both as inpatients and outpatients. The study included 67 patients with a median age of 61 years (SD +/- 14.18 years), with approximately 44% being female. The average hospital stay for inpatient treatment was 20 days (SD +/- 8.8 days). Subsequent outpatient antibiotic therapy lasted an average of 70.32 days (SD +/- 18.24 days), with outpatient IV therapy accounting for 44.74 days (SD +/- 9.15 days). The most common pathogens identified were Staphylococcus epidermidis and methicillin-sensitive Staphylococcus aureus. Microbiological analysis did not detect any pathogens in 18% of patients. Radiographic and laboratory evidence of spondylodiscitis was absent in 99% of patients during the final follow-up. No catheter-related complications occurred. Outpatient IV antibiotic therapy using a PICC line catheter is a safe and effective treatment option for spinal infections, especially in elderly patients.