Patient Registration Research Articles

Integration of a lightweight and table-mounted robotic alignment tool with automated patient-to-image registration using robotic cone-beam CT for intracranial biopsies and stereotactic electroencephalography.

Robotics in neurosurgery is becoming increasingly prevalent. The integration of intraoperative imaging for patient registration into workflows of newer robotic systems enhances precision and has further driven their widespread adoption. In this study, the authors report on a lightweight, table-mounted robotic system integrating robotic cone-beam CT (CB-CT) for automated patient registration in cranial biopsies and stereotactic electroencephalography (sEEG). This prospective cohort study included patients who underwent stereotactic biopsy or sEEG with the Cirq system from January 2023 to August 2024. For patient-to-image registration, an external registration matrix was secured near the patient's head before conducting CB-CT with robotic Artis Pheno. CT was then fused with preoperative planning MRI and used as the navigation dataset. Demographic and clinical data were evaluated, and entry and target errors, as well as vector deviation of sEEG electrodes, were assessed and compared with those of patients who underwent biopsies and sEEG with the frameless VarioGuide system. In 26 Cirq-assisted surgical procedures, robotic CB-CT was used for image registration in 20 cases. Of these, 15 were biopsies (mean ± SD 7 ± 1 specimens) and 5 were sEEG with 31 depth electrodes, compared to 29 VarioGuide biopsies and 3 VarioGuide sEEG cases with 25 electrodes. The mean age was 56 ± 19 years, with a male/female ratio of 1.9:1. Lesion size averaged 19 ± 17 cm3 on T1-weighted imaging and 61 ± 53 cm3 on T2-weighted imaging for Cirq and 14 ± 14 cm3 and 68 ± 47 cm3 for VarioGuide. The mean surgical times were 117 ± 34 minutes for biopsy and 269 ± 54 minutes for sEEG in the Cirq group, with skin-to-skin times of 40 ± 23 minutes for biopsy and 208 ± 74 minutes for sEEG; in comparison, surgical times of 78 ± 21 minutes for biopsy and 218 ± 33 minutes for sEEG were reported with VarioGuide, with skin-to-skin times of 34 ± 13 and 158 ± 27 minutes. No complications occurred. The mean dosage area product was 983 ± 351 µGym2 for biopsies and 1772 ± 968 µGym2 for sEEG. Cirq-assisted sEEG electrodes had mean entry and target errors of 1.4 ± 1.2 mm and 2.6 ± 1.6 mm, compared to 5.3 ± 3.3 mm and 6.5 ± 2.8 mm with VarioGuide. Mean vector deviation was 1.6 ± 0.9 mm with Cirq versus 4.9 ± 2.9 mm with VarioGuide. The integration of a lightweight, table-mounted robotic alignment tool with intraoperative CB-CT for automated patient-to-image registration enables high precision and a seamless workflow. This combination is safe, has a manageable learning curve, and holds potential to replace traditional frame-based and frameless procedures. Its efficiency and accuracy are likely to contribute to the increasing adoption of robotics in neurosurgery.

Statistical Data on Myelodysplastic Syndrome in the Russian Federation

Introduction. Myelodysplastic syndrome (MDS) is a nosology that requires examination using cytogenetic, molecular-genetic and immunophenotypic analysis of bone marrow and/or blood, as well as mandatory bone marrow trepan biopsy with pathomorphological and immunohistochemically studies. Until recently, there was no official statistical data on MDS in Russia.Aim: to present data on the incidence and prevalence of MDS in Russia based on official statistical forms.Materials and methods. Information from statistical form №7 «Information on malignant neoplasms» (SF No. 7) for 2022 and 2023 on the incidence and prevalence of MDS, updated at the initiative of the National Medical Research Center for Hematology, is presented. For the first time, additional lines (35–37) with information on the movement of patients, including MDS (code D46 according to ICD-10), have been introduced into table 2100.Results. According to SF No. 7, in 2022 and 2023, 2,827 and 3,411 cases of MDS were registered, respectively. The estimated primary incidence in the Russian Federation was 0.58 and 0.50 per 100 thousand of the adult population in 2022 and 2023, respectively, and the prevalence was 2.4 per 100 thousand of the adult population. The estimated incidence of MDS by federal districts in 2022 ranged from 0.13 to 1.05 with variations from 0.03 to 2.57 per 100 thousand of the adult population, depending on the region of residence. At the end of 2023, 3001 (88 %) patients with MDS were registered under dispensary observation, of which 860 (28.7 %) were under observation for 5 years or more.Conclusion. The obtained statistical data on the incidence and prevalence of MDS showed the high significance of the work carried out both for the subsequent improvement of the system of registration of patients with diseases of the blood system in general, and MDS, particularly the Russian Federation, and will make it possible to use this data in the planning of healthcare in the Russia.

Automatic Image Registration Provides Superior Accuracy Compared with Surface Matching in Cranial Navigation.

The precision of neuronavigation systems relies on the correct registration of the patient's position in space and aligning it with radiological 3D imaging data. Registration is usually performed by the acquisition of anatomical landmarks or surface matching based on facial features. Another possibility is automatic image registration using intraoperative imaging. This could provide better accuracy, especially in rotated or prone positions where the other methods may be difficult to perform. The aim of this study was to validate automatic image registration (AIR) using intraoperative cone-beam computed tomography (CBCT) for cranial neurosurgical procedures and compare the registration accuracy to the traditional surface matching (SM) registration method based on preoperative MRI. The preservation of navigation accuracy throughout the surgery was also investigated. Adult patients undergoing intracranial tumor surgery were enrolled after consent. A standard SM registration was performed, and reference points were acquired. An AIR was then performed, and the same reference points were acquired again. Accuracy was calculated based on the referenced and acquired coordinates of the points for each registration method. The reference points were acquired before and after draping and at the end of the procedure to assess the persistency of accuracy. In total, 22 patients were included. The mean accuracy was 6.6 ± 3.1 mm for SM registration and 1.0 ± 0.3 mm for AIR. The AIR was superior to the SM registration (p < 0.0001), with a mean improvement in accuracy of 5.58 mm (3.71-7.44 mm 99% CI). The mean accuracy for the AIR registration pre-drape was 1.0 ± 0.3 mm. The corresponding accuracies post-drape and post-resection were 2.9 ± 4.6 mm and 4.1 ± 4.9 mm, respectively. Although a loss of accuracy was identified between the preoperative and end-of-procedure measurements, there was no statistically significant decline during surgery. AIR for cranial neuronavigation consistently delivered greater accuracy than SM and should be considered the new gold standard for patient registration in cranial neuronavigation. If intraoperative imaging is a limited resource, AIR should be prioritized in rotated or prone position procedures, where the benefits are the greatest.

The Added Value of Using Video in Out-of-Hours Primary Care Telephone Triage Among General Practitioners: Cross-Sectional Survey Study.

Many countries have introduced video consultations in primary care both inside and outside of office hours. Despite some relational and technical limitations, general practitioners (GPs) have reported the benefits of video use in the daytime as it provides faster and more flexible access to health care. Studies have indicated that video may be specifically valuable in out-of-hours primary care (OOH-PC), but additional information on the added value of video use is needed. This study aimed to investigate triage GPs' perspectives on video use in GP-led telephone triage in OOH-PC by exploring their reasons for choosing video use and its effect on triage outcome, the decision-making process, communication, and invested time. We conducted a cross-sectional questionnaire study among GPs performing telephone triage in the OOH-PC service in the Central Denmark Region from September 5, 2022, until December 21, 2022. The questionnaire was integrated into the electronic patient registration system as a pop-up window appearing after every third video contact. This setup automatically linked background data on the contact, patient, and GP to the questionnaire data. We used descriptive analyses to describe reasons for and effects of video use and GP evaluation, stratified by patient age. A total of 2456 questionnaires were completed. The most frequent reasons for video use were to assess the severity (n=1951, 79.4%), to increase the probability of self-care (n=1279, 52.1%), and to achieve greater certainty in decision-making (n=810, 33%) (multiple answers were possible for reasons of video use). In 61.9% (n=1516) of contacts, the triage GPs anticipated that the contact would have resulted in a different triage outcome if video had not been used. Use of video resulted in a downgrading of severity level in 88.3% (n=1338) of cases. Triage GPs evaluated the use of video as positive in terms of their decision-making process (n=2358, 96%), communication (n=2214, 90.1%), and invested time (n=2391, 97.3%). Triage GPs assessed that the use of video in telephone triage did affect their triage outcome, mostly by downgrading the level of care needed. The participating triage GPs found video in OOH-PC to be of added value, particularly in communication and the decision-making process.

Performance of ChatGPT in Ophthalmic Registration and Clinical Diagnosis: Cross-Sectional Study.

Artificial intelligence (AI) chatbots such as ChatGPT are expected to impact vision health care significantly. Their potential to optimize the consultation process and diagnostic capabilities across range of ophthalmic subspecialties have yet to be fully explored. This study aims to investigate the performance of AI chatbots in recommending ophthalmic outpatient registration and diagnosing eye diseases within clinical case profiles. This cross-sectional study used clinical cases from Chinese Standardized Resident Training-Ophthalmology (2nd Edition). For each case, 2 profiles were created: patient with history (Hx) and patient with history and examination (Hx+Ex). These profiles served as independent queries for GPT-3.5 and GPT-4.0 (accessed from March 5 to 18, 2024). Similarly, 3 ophthalmic residents were posed the same profiles in a questionnaire format. The accuracy of recommending ophthalmic subspecialty registration was primarily evaluated using Hx profiles. The accuracy of the top-ranked diagnosis and the accuracy of the diagnosis within the top 3 suggestions (do-not-miss diagnosis) were assessed using Hx+Ex profiles. The gold standard for judgment was the published, official diagnosis. Characteristics of incorrect diagnoses by ChatGPT were also analyzed. A total of 208 clinical profiles from 12 ophthalmic subspecialties were analyzed (104 Hx and 104 Hx+Ex profiles). For Hx profiles, GPT-3.5, GPT-4.0, and residents showed comparable accuracy in registration suggestions (66/104, 63.5%; 81/104, 77.9%; and 72/104, 69.2%, respectively; P=.07), with ocular trauma, retinal diseases, and strabismus and amblyopia achieving the top 3 accuracies. For Hx+Ex profiles, both GPT-4.0 and residents demonstrated higher diagnostic accuracy than GPT-3.5 (62/104, 59.6% and 63/104, 60.6% vs 41/104, 39.4%; P=.003 and P=.001, respectively). Accuracy for do-not-miss diagnoses also improved (79/104, 76% and 68/104, 65.4% vs 51/104, 49%; P<.001 and P=.02, respectively). The highest diagnostic accuracies were observed in glaucoma; lens diseases; and eyelid, lacrimal, and orbital diseases. GPT-4.0 recorded fewer incorrect top-3 diagnoses (25/42, 60% vs 53/63, 84%; P=.005) and more partially correct diagnoses (21/42, 50% vs 7/63 11%; P<.001) than GPT-3.5, while GPT-3.5 had more completely incorrect (27/63, 43% vs 7/42, 17%; P=.005) and less precise diagnoses (22/63, 35% vs 5/42, 12%; P=.009). GPT-3.5 and GPT-4.0 showed intermediate performance in recommending ophthalmic subspecialties for registration. While GPT-3.5 underperformed, GPT-4.0 approached and numerically surpassed residents in differential diagnosis. AI chatbots show promise in facilitating ophthalmic patient registration. However, their integration into diagnostic decision-making requires more validation.

State of oncology care in Russia: pancreatic cancer (C25). Diagnosis, prevalence, quality of patient registration, and annual mortality. Part 1. (clinical-population study)

The study focuses on pancreatic cancer (C25), a malignant neoplasm arising from the ductal epithelium or glandular tissue of the pancreas, which accounts for 3% of the overall cancer incidence in Russia. The rates of incidence and mortality are rising, with the number of newly registered patients in Russia being lower than the number of recorded deaths, although the one-year mortality rate among patients is decreasing. The direct cause of pancreatic cancer (C25) remains unknown. Risk factors for developing this condition include genetics, smoking, alcohol abuse, a sedentary lifestyle, excessive meat consumption, and a lack of plant-based foods in the diet. Diseases associated with a high risk of this pathology include long-standing chronic pancreatitis, newly diagnosed type 2 diabetes in individuals aged 50-70, and cystic neoplasms of the pancreas. The aim of the study is to examine the patterns of incidence and mortality, the quality of patient registration, the characteristics of tumor localization, and the histological structure of pancreatic cancer (C25). The study will also track the nature of annual mortality among patients and explore the possibilities, methods, and techniques of modern diagnosis and treatment for these patients. The research confirmed the significant burden of pancreatic cancer (C25), primarily due to the late detection of this disease. The study provided sufficient material to analyze age-related risk factors, as well as the patterns of incidence and mortality in the population. It also examined and presented mortality rates among patients, including during the first year of observation.

FDA Analysis of Race and Ethnic Enrollment of Clinical Trials for Drug Registration in Adult Patients for Leukemia and Myelodysplastic Syndrome

FDA Analysis of Race and Ethnic Enrollment of Clinical Trials for Drug Registration in Adult Patients for Leukemia and Myelodysplastic Syndrome

Improving Timely Medication Access for Endocrinology and Diabetes Patients: A Quality Improvement Initiative

ABSTRACT Introduction Managing chronic conditions such as endocrinology and diabetes requires consistent access to medications. Traditional methods of medication refill often involve in-person visits to healthcare providers or pharmacies, posing challenges for patients. Online medication refill services offer a promising solution to improve accessibility and convenience. Methods This is a digital-based solution using online medication refill services to enhance the management of endocrinology and diabetes medication refills. It examines the process of online medication refill, including patient registration, refill request submission, verification, provider input, processing, and pickup or delivery. Results Online medication refill services empower patients to easily request refills from the comfort of their homes, streamlining the refill process, and reducing walk-in pressure in clinics. The online medication refill with the option for home delivery option eliminates the need for patients to visit the hospital, further enhancing the patient experience. Before implementing the online medication refill solution, 26 patients will come to the clinic as walk-ins to request medication refills. The average waiting time for each patient is 45 minutes. Each provider will be interrupted for an average of 10 minutes to accommodate the request. The overall processing time required for each walk-in patient to submit the medication request is 1 hour on average. After implementing the online medication refill intervention, zero patients come to the clinic as walk-ins and hence, no interruption to the daily regular clinics. The overall processing time required for submitting the online medication request is now 2 minutes. These interventions promote medication adherence and patient engagement by facilitating access to medications and offering educational resources. Conclusion Online medication refill services represent a valuable tool in the comprehensive management of endocrinology and diabetes. They offer accessibility, convenience, and patient empowerment, potentially improving health outcomes and enhancing the overall patient experience.

Socio-spatial inequalities in presence of primary care physicians and patients' ability to register: A simulated-patient survey in the Paris Region

ObjectivesWe studied the socio-spatial inequalities of three types of general practitioner (GP) density in the Paris metropolitan area: the density of GPs present (that is, practising) in the census block and of those registering new patients for office visits and, separately, for house calls. Study designAn exhaustive simulated patient survey enabled us to determine the number of GPs practising in the Paris metropolitan region accepting new patient registration for continuing care at their office and/or for house calls. MethodsWe measured at the level of a census block three types of GP densities: density of GPs present, density of GPs registering new patients at their office and density of GP registering new patients for house calls. We compared the association between the social deprivation level and each density measurement overall, then by stratifying for the population density of the census block. ResultsIn 2017–2018, we contacted 8171 physicians (87.6 % of the GPs in the region). Although more than 55 % of Ile-de-France census blocks had (at least) one practising GP, fewer than 40 % had one willing to register a new patient for ongoing office care, and fewer than 20 % for home care. Regardless of the GP density considered, it decreased as the census block's deprivation index rose. However, these inequalities were more marked for registration than for presence and in the most densely populated blocks. ConclusionsIn conclusion, the indicators of GPs' mere presence appear to minimise the socio-spatial disparities associated with access to registration.

Exploring the Association between Complexity of Care, Medical Complexity, and Length of Stay in the Paediatric Setting Using a Nursing Minimum Data Set: A Study Protocol.

The complexity of care requires systematic documentation to fully understand its relationship with medical complexity and its impact on patient outcomes. The Nursing Minimum Data Set (NMDS) plays a crucial role by capturing essential nursing data, enabling a detailed analysis of care and its impact on outcomes, such as length of stay (LOS). However, despite its potential, the use of NMDS in paediatric care remains limited. This study aims to explore the association between nursing and medical complexities and LOS in paediatric patients. A descriptive, retrospective, monocentric study will be conducted. The data will be collected through a nursing information system (Professional Assessment Instrument (PAIped)) and the hospital discharge register of patients admitted to the paediatric department in 2022 in an Italian university hospital. Conclusions and Expected Results: The use of PAIped will allow for the description of the complexity of care and enable an analysis of its relationship with medical complexity and LOS.

Developmental and epileptic encephalopathy 56 due to YWHAG variants: 12 new cases and review of the literature

Background and objectivesDevelopmental and epileptic encephalopathy 56 (DEE-56) is caused by pathogenic variants in YWHAG and is characterized by early-onset epilepsy and neurodevelopmental delay. This study reports on a cohort of DEE-56 individuals, correlating antiseizure medication usage and comorbidities, to aid in understanding disease evolution. MethodsWe analyzed data from thirty-nine individuals aged 3–40 years with YWHAG variants, including 12 previously unreported individuals (2 of these with recurrent distal 7q11.23 deletions) and 27 previously published cases (21 families, including 3 adult individuals reported in a family case). Our assessments encompassed clinical, radiological, and genetic evaluations. All procedures adhered to standardized protocols for patient approvals, registrations, and data collection. ResultsIndividuals with YWHAG variants exhibited variable psychomotor delay, with the majority experiencing mild intellectual disability. Early-onset seizures, particularly febrile seizures, were common, with various seizure types reported. Valproic acid has emerged as an effective antiseizure medication. Movement disorders were present in a subset of individuals, primarily manifesting as ataxia and tremor. Comorbidities such as autism spectrum disorders and attention deficit-hyperreactivity disorder were observed in a proportion of individuals. We identified a novel YWHAG variant (c.634_645del/p.Asn212_Ser215del) and expanded the genotypic spectrum of the disease. ConclusionsWe provide insights into the clinical, radiological, and genetic features of YWHAG-related epileptic encephalopathy. Despite mild clinical symptoms, affected individuals face challenges in daily functioning, underscoring the need for comprehensive care. Valproic acid has been used for seizure control with variable results.

Evaluation of cumulative dose distributions from external beam radiation therapy using CT-to-CBCT deformable image registration (DIR) for cervical cancer patients.

To investigate dose differences between the planning CT (pCT) and dose calculated on pre-treatment verification CBCTs using DIR and dose summation for cervical cancer patients. Cervical cancer patients treated at our institution with 45Gy EBRT undergo a pCT and 5 CBCTs, once every five fractions of treatment. A free-form intensity-based DIR in MIM was performed between the pCT and each CBCT using the "Merged CBCT" feature to generate an extended FOV-CBCT (mCBCT). DIR-generated bladder and rectum contours were adjusted by a physician, and dice similarity coefficients (DSC) were calculated. After deformation, the investigated doses were (1) recalculated in Eclipse using original plan parameters (ecD), and (2) deformed from planning dose (pD) using the deformation matrix in MIM (mdD). Dose summation was performed to the first week's mCBCT. Dose distributions were compared for the bladder, rectum, and PTV in terms of percent dose difference, dose volume histograms (DVHs), and gamma analysis between the calculated doses. For the 20 patients, the mean DSC was 0.68±0.17 for bladder and 0.79±0.09 for rectum. Most patients were within 5% of pD for D2cc (19/20), Dmax (17/20), and Dmean (16/20). All patients demonstrated a percent difference>5% for bladder V45 due to variations in bladder volume from the pCT. D90 showed fewer differences with 19/20 patients within 2% of pD. Gamma rates between pD and ecD averaged 94% for bladder and 94% for rectum, while pD and mdD exhibited slightly better performance for bladder (93%) and lower for rectum (85%). Using DIR with weekly CBCT images, the MIM deformed dose (mdD) was found to be in close agreement with the Eclipse calculated dose (ecD). The proposed workflow should be used on a case-by-case basis when the weekly CBCT shows marked difference in organs-at-risk from the planning CT.

Canada's Recreational Cannabis Legalization and Medical Cannabis Patient Activity, 2017-2022.

Objectives. To estimate changes in medical cannabis patient activity after Canada's recreational cannabis legalization. Methods. I used linear regressions of interrupted times series models to analyze medical cannabis patient registrations per 10 000 residents, purchases per 100 registrations, and packages per purchase in Canada's 10 provinces between April 2017 and December 2022. I tested relationships between the recreational law's passage in June 2018, recreational sales starting in October 2018, and the arrival of edibles and vapes in December 2019. Results. Medical patient registrations initially increased; they slowed after the law passed and started decreasing after edibles became available. Medical purchasing frequencies initially decreased; they decreased further in proportion to recreational sales but stabilized after edibles became available. Medical purchase sizes were initially stable; they began increasing after edibles became available. Conclusions. Canada saw substantial decreases in medical cannabis patient registrations, but the remaining patients stabilized their purchasing frequencies and increased their purchase sizes. Public Health Implications. Other countries might see significant changes in patient usage of their medical cannabis systems after nationwide recreational cannabis legalization. (Am J Public Health. 2024;114(S8):S673-S680. https://doi.org/10.2105/AJPH.2024.307721).

Automated orofacial virtual patient creation: A proof of concept

ObjectivesTo (1) construct a virtual patient (VP) using facial scan, intraoral scan, and low-dose computed tomography scab based on an Artificial intelligence (AI)-approach, (2) quantitatively compare it with AI-refined and semi-automatic registration, and (3) qualitatively evaluate user satisfaction when using virtual patient as a communication tool in clinical practice. Materials and methodsA dataset of 20 facial scans, intraoral scans, and low-dose computed tomography scans was imported into the Virtual Patient Creator platform to create an automated virtual patient. The accuracy of the virtual patients created using different approaches was further analyzed in the Mimics software. The accuracy (% of corrections required), consistency, and time efficiency of the AI-driven virtual patient registration were then compared with the AI-refined and semi-automatic registration (clinical reference). User satisfaction was assessed through a survey of 35 dentists and 25 laypersons who rated the virtual patient's realism and usefulness for treatment planning and communication on a 5-point scale. ResultsThe accuracy for AI-driven, AI-refined, and semi-automatic registration virtual patient was 85 %, 85 %, and 100 % for the upper and middle thirds of the face, and 30 %, 30 %, and 35 % for the lower third. Registration consistency was 1, 1 and 0.99, and the average time was 26.5, 30.8, and 385 s, respectively (18-fold time reduction with AI). The inferior facial third exhibited the highest registration mismatch between facial scan and computed tomography. User satisfaction with the virtual patient was consistently high among both dentists and laypersons, with most responses indicating very high satisfaction regarding realism and usefulness as a communication tool. ConclusionThe AI-driven registration can provide clinically accurate, fast, and consistent virtual patient creation using facial scans, intraoral scans, and low-dose computed tomography scans, enabling interpersonal communication. Clinical significanceUsing AI for automated segmentation and registration of maxillofacial structures leads to clinically efficient and accurate VP creation, opening the doors for its widespread use in diagnosis, treatment planning, and interprofessional and professional-patient communication.

Validity of a Hypertrophic Cardiomyopathy Diagnosis in Adult Patients in the Danish National Patient Register.

To assess the positive predictive value (PPV) of the diagnostic codes for hypertrophic cardiomyopathy (HCM) in the Danish National Patient Register (DNPR) and identify factors affecting the PPV. We randomly sampled 200 patients registered in DNPR with the diagnostic codes DI421 (obstructive) or DI422 (non-obstructive) HCM, from Eastern Denmark, between December 1st, 2017, and September 16th, 2021. We assessed patients' medical records and classified whether the diagnosis of HCM was correct, incorrect, or uncertain according to the European Society of Cardiology (ESC) guidelines. Overall PPVs were estimated for all hospitals irrespective of specialty and for dedicated centers for inherited cardiac diseases. Of the 200 patients, seven were excluded; six were younger than 18 years when initially diagnosed and one adult patient had requested that their medical records be unavailable for research purposes. Of the 193 patients (median age 61 years, Interquartile range (IQR) 50-70, 40% female) with medical records available for assessment, 148 (77%) patients were registered correctly, 41 (21%) were incorrectly registered and for four (2%) patients there was insufficient data to determine if the diagnosis was correct. The overall PPV was 0.77 (95% confidence interval (CI) 0.70-0.82). The PPV for patients diagnosed in dedicated centers for inherited cardiac diseases was 0.91 (95% CI 0.84-0.95). For patients diagnosed in a dedicated center for inherited cardiac diseases with more than one clinical visit, the PPV increased to 0.99 (95% CI 0.93-1), however with the risk of a reduced sensitivity as these patients constituted only 52% of the correctly registered patients. The overall PPV of the HCM diagnostic codes in the DNPR was 0.77 (95% CI 0.70-0.82). The validity of the diagnosis was higher at dedicated centers for inherited cardiac diseases. These findings may prove useful for future register-based research.

Reasons for encounter in video contacts at a Danish out-of-hours primary care service: a questionnaire study

ObjectiveTo investigate reasons for encounter in telephone triage contacts to an out-of-hours primary care service for which general practitioners (GPs) use video consultations (video contact), overall and stratified for patient...

A Multivariate Approach to Quantifying Risk Factors Impacting Stereotactic Robotic-Guided Stereoelectroencephalography.

Stereoelectroencephalography (SEEG) is an important method for invasive monitoring to establish surgical candidacy in approximately half of refractory epilepsy patients. Identifying factors affecting lead placement can mitigate potential surgical risks. This study applies multivariate analyses to identify perioperative factors affecting stereotactic electrode placement. We collected registration and accuracy data for consecutive patients undergoing SEEG implantation between May 2022 and November 2023. Stereotactic robotic guidance, using intraoperative imaging and a novel frame-based fiducial, was used for planning and SEEG implantation. Entry-point (EE), target-point (TE), and angular errors were measured, and statistical univariate and multivariate linear regression analyses were performed. Twenty-seven refractory epilepsy patients (aged 15-57 years) undergoing SEEG were reviewed. Sixteen patients had unilateral implantation (10 left-sided, 6 right-sided); 11 patients underwent bilateral implantation. The mean number of electrodes per patient was 18 (SD = 3) with an average registration mean error of 0.768 mm (SD = 0.108). Overall, 486 electrodes were reviewed. Univariate analysis showed significant correlations of lead error with skull thickness (EE: P = .003; TE: P = .012); entry angle (EE: P < .001; TE: P < .001; angular error: P = .030); lead length (TE: P = .020); and order of electrode implantation (EE: P = .003; TE: P = .001). Three multiple linear regression models were used. All models featured predictors of implantation region (157 temporal, 241 frontal, 79 parietal, 9 occipital); skull thickness (mean = 5.80 mm, SD = 2.97 mm); order (range: 1-23); and entry angle in degrees (mean = 75.47, SD = 11.66). EE and TE error models additionally incorporated lead length (mean = 44.08 mm, SD = 13.90 mm) as a predictor. Implantation region and entry angle were significant predictors of error (P ≤ .05). Our study identified 2 primary predictors of SEEG lead error, region of implantation and entry angle, with nonsignificant contributions from lead length or order of electrode placement. Future considerations for SEEG may consider varying regional approaches and angles for more optimal accuracy in lead placement.

General practice preconception care invitations: a qualitative study of women’s acceptability and preferences

BackgroundIn general practice, primary care providers can potentially use electronic medical records (EMRs) to identify and invite reproductive-aged women with preconception health risk factors to increase their engagement in preconception...

Optimizing the Queuing System at the Grogol Sukoharjo District Health Center Using the Line Balancing Method

The average number of patients served by the Grogol Health Center in the general polyclinic is 40 to 45 patients every day. Based on these data, there is a buildup of 7-10 patients, with an average service time of 10 minutes per patient. From the results of further observations, there is a buildup of patients in the general polyclinic of the Grogol Health Center. This study aims to solve the queue problem with the line balancing method and develop an online registration application at the Grogol Health Center that can increase the efficiency of the patient registration process and reduce waiting time. Line Balancing is a method for solving queue system problems. So that the results of this study are the creation of an integrated application and online registration that can reduce waiting time

Implementasi Data Mining Klasifikasi Gejala Penyakit TB Menggunakan Algoritma Naive Bayes pada Studi Kasus Puskesmas Pegangsaan Dua B

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. The bacteria can enter the lungs, causing the patient to experience shortness of breath and chronic coughing. The infection process in TB progresses through three main stages: primary infection, latent infection, and active infection. During the primary infection stage, the bacteria enter the lungs through inhaled air. If the immune system successfully controls the bacteria, the infection becomes latent, where the bacteria remain inactive and cause no symptoms. However, if the immune system fails, the infection becomes active, and the bacteria attack healthy lung cells, leading to severe symptoms. Tuberculosis remains a major cause of global morbidity and mortality. According to the 2022 WHO report, Indonesia ranks second in the world with an estimated 969,000 TB cases, or 354 per 100,000 people, and a mortality rate of 144,000, or 52 per 100,000 people. This study aims to improve the accuracy of TB diagnosis through the application of the Naive Bayes algorithm, applied to patient data from the Pegangsaan Dua B Community Health Center. The dataset includes 1,527 training data and 1,029 testing data, covering attributes such as patient name, gender, age, identification number, registration date, address, diagnosis status, and diagnosis results. The results indicate that the Naive Bayes algorithm achieved an accuracy of 99.71%, showing its potential for early and accurate TB diagnosis prediction.