Complete Data Research Articles

PRECOCIOUS PUBERTY: EPIDEMIOLOGY, CLINICAL PRESENTATION, DIAGNOSIS, AND ETIOLOGIES

Precocious puberty, defined as the onset of sexual characteristics before the age of 8 in girls and 9 in boys, can arise from various causes, including central and peripheral mechanisms. While central precocious puberty (CPP) originates from premature activation of the hypothalamic-pituitary axis, peripheral precocious puberty (PPP) results from gonadal or adrenal hormone secretion independent of hypothalamic control. We conducted a retrospective study spanning eight years, from 2015 to 2023, at the Mohamed 6 University Hospital in Marrakech, Morocco, to investigate the epidemiological, clinical findings, laboratory, and etiological aspects of precociuos puberty in 12 children. We found a predominance of CPP, particularly in girls, with breast development being the most common clinical sign. In boys, early puberty typically presented with pubic hair development and increased penile size. Diagnostic evaluation included hormonal assays and imaging studies, with elevated levels of gonadal hormones confirming the diagnosis. CPP was predominantly idiopathic in girls, while traumatic brain injury and CNS lesions were common causes in boys. Adrenal disorders, including congenital adrenal hyperplasia, accounted for PPP cases. Brain imaging was crucial for identifying central lesions, while adrenal imaging aided in diagnosing adrenal pathologies. Despite limitations such as retrospective design and incomplete data, our study emphasizes the importance of early recognition and appropriate diagnostic procedures for children showing signs of early puberty to optimize management and outcomes.

Ethical Considerations of Including Minors in Clinical Trials Using the Example of the Indicated Prevention of Psychotic Disorders

Ethical Considerations of Including Minors in Clinical Trials Using the Example of the Indicated Prevention of Psychotic Disorders Abstract: As a vulnerable group, minors require special protection in studies. For this reason, researchers are often reluctant to initiate studies, and ethics committees are reluctant to authorize such studies. This often excludes minors from participating in clinical studies. This exclusion can lead to researchers and clinicians receiving only incomplete data or having to rely on adult-based findings in the treatment of minors. Using the example of the study "Computer-Assisted Risk Evaluation in the Early Detection of Psychotic Disorders" (CARE), which was conducted as an 'other clinical investigation' according to the Medical Device Regulation, we present a line of argumentation for the inclusion of minors which weighs the ethical principles of nonmaleficence (especially regarding possible stigmatization), beneficence, autonomy, and fairness. We show the necessity of including minors based on the development-specific differences in diagnostics and early intervention. Further, we present specific protective measures. This argumentation can also be transferred to other disorders with the onset in childhood and adolescence and thus help to avoid excluding minors from appropriate evidence-based care because of insufficient studies.

Prevalence of HCV infection in Europe in the DAA era: Review.

In 2016, the Global Health Sector Strategy, ratified by the 69th World Health Assembly, set the ambitious goal of eliminating hepatitis C virus (HCV) and hepatitis B virus infections by 2030, emphasizing the importance of national screening programmes. Achieving this goal depends on each country's ability to identify and treat 80% of chronic hepatitis C cases, a critical threshold set by the World Health Organization. Traditionally, estimates of HCV prevalence have been based on interferon era studies that focused on high-risk subgroups rather than the general population. In addition, the incomplete data available from national registries also limited the understanding of HCV prevalence. The 2016 report from the European Centre for Disease Prevention and Control highlighted that HCV rates varied across European counties, ranging from .1% to 5.9%. However, data were only available for 13 countries, making the overall picture less clear. Additionally, the epidemiological data may have underestimated the true burden of HCV due to lack of awareness among those with chronic infection. The main objective of this review is to provide a comprehensive summary of HCV epidemiology in Europe in the current era of direct-acting antivirals (DAAs). The data included in the analysis range from the end of 2013 to December 2023 and have been categorised according to the United Nations Geoscheme. The resulting synthesis underscores the noteworthy impact of DAA treatment on the epidemiological situation.

The omission of seed banks in demography as an example of bias in ecology

Abstract Despite enthusiasm for big data in the life sciences, challenges arise because of biases and incomplete data. Demographic studies often overlook dormant life stages, which can skew inferences. They also tend to focus on few populations and short time spans. We assessed omissions of seed banks in demographic studies, exploring trends across life forms, climates, and taxonomic groups. We compared 172 species (192 cases) with independent seed bank and demographic studies. Approximately 25% of the demographic studies excluded known seed bank stages. The probability of omissions was lower for annuals and shrubs and higher for perennial herbs. We found no evidence that ecoregion or phylogeny explained these omissions. Modeling choices and study designs may explain patterns of seed bank omissions. Considering more populations reduced the chance of omissions. Omissions raise concerns for ecological analyses using databases. Leveraging large data is important, but we must be careful to understand their biases and limitations.

Learning semi-supervised enrichment of longitudinal imaging-genetic data for improved prediction of cognitive decline

BackgroundAlzheimer’s Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Given that there is currently no cure, it is critical to detect AD in its early stage during the disease progression. Recently, many statistical learning methods have been presented to identify cognitive decline with temporal data, but few of these methods integrate heterogeneous phenotype and genetic information together to improve the accuracy of prediction. In addition, many of these models are often unable to handle incomplete temporal data; this often manifests itself in the removal of records to ensure consistency in the number of records across participants.ResultsTo address these issues, in this work we propose a novel approach to integrate the genetic data and the longitudinal phenotype data to learn a fixed-length “enriched” biomarker representation derived from the temporal heterogeneous neuroimaging records. Armed with this enriched representation, as a fixed-length vector per participant, conventional machine learning models can be used to predict clinical outcomes associated with AD.ConclusionThe proposed method shows improved prediction performance when applied to data derived from Alzheimer’s Disease Neruoimaging Initiative cohort. In addition, our approach can be easily interpreted to allow for the identification and validation of biomarkers associated with cognitive decline.

Quality assessment of paediatric randomized controlled trials published in China from 1999 to 2022: a cross-sectional study

BackgroundRandomized controlled trials (RCTs) are usually the basis of evidence-based medicine, but whether the results of RCTs can be correctly translated into clinical practice depends on the quality of the literature reported. In this study, we evaluated the general characteristics and quality of paediatric RCTs published in China to provide evidence for the reporting of paediatric RCTs and their application in clinical practice.MethodsWe conducted a cross-sectional observational study of paediatric RCTs published in paediatric journals in China between January 1, 1999, and December 30, 2022. All RCTs that included children (younger than 18 years old) were retrieved, and the general characteristics of the RCTs were extracted and analysed. The quality of the RCTs was assessed by the Cochrane quality assessment protocol.ResultsAfter screening 20 available paediatric journals, 3545 RCTs were included for analysis. The average annual growth rate of the number of published paediatric RCTs from 1999 to 2022 was 7.8% (P = 0.005, R2 = 0.311). Most of the studies were carried out in East China [1148 (32.4%]; the centres of the RCTs were mainly single-centre [3453 (97.4%], and the interventions were mainly medication [2442 (68.9%)]. Comparing RCTs published in 2017–2022 with RCTs published in 1999–2004, the quality of RCTs significantly improved in terms of random sequence generation, allocation concealment, blinding participants and personnel, incomplete outcome data and selective outcome reporting. RCTs published in multiple centres from the Chinese Science Citation Database were identified, and the approval of the ethics committee was of better quality for all the analysed risk of bias items.ConclusionThe number and quality of paediatric RCTs reported in China have improved in recent years, but the overall quality was relatively low. Special attention should be given to allocation concealment and blinding outcome assessment, and dropouts, adverse effects and sample size calculations should be reported. Promoting government policies, strengthening the standardization of journal publishing and advancing the registration of clinical trials are feasible measures.

Modeling Technical Risk Propagation Using Field-Effects in Automotive Technology Infusion Design Studies

Abstract The infusion of new technology into existing product architectures introduces significant challenges, particularly in managing the risks associated with higher-order effects on system functionality and reliability. Within current industrial practices, the development of such integration support is challenging as it requires integrating data related to component and system testing activities, and product architecture design. There is a need to make decisions based on incomplete data due to the difficulty of evaluating all potential configurations, as well as to proactively identify areas of the product architecture that could be problematic in the future. This study aims to support the development of new products at a prominent international automotive company, by examining the field effects generated and influenced by their components and the impact of infusing new technology on the system architecture. We propose integrating and linking these concerns about field effects and architectural impact within a DSM-based method. The method has been implemented in a case study based on the introduction of a steer-by-wire system. The method is proven effective for finding relevant configurations for integrating new technology into products under development. Thus, a robust framework is proposed for harmonizing the evolution of products with the evolution of technology, fostering innovation within product platform design.

Infilling of high‐dimensional rainfall networks through multiple imputation by chained equations

AbstractAccurate precipitation records are an essential component when monitoring the climate and studying its changes. However, analysis is typically limited by the large quantities of missing values present. This article proposes two new imputation techniques for incomplete monthly data collected from a rainfall monitoring network in the Republic of Ireland from 1981 to 2010. The data considered is high‐dimensional due to the large number of over 1100 rain gauge stations present, and the methods presented are designed to handle such cases. These are Elastic‐Net Chained Equations (ENCE) and Multiple Imputation by Chained Equations with Direct use of Regularized Regression by elastic‐net (MICE DURR). Both methods predict missing data by a series of regularized regression models, where MICE DURR differs from ENCE by also using multiple imputation. Through various evaluations across different levels of missingness, ENCE and MICE DURR consistently outperformed existing imputation methods in terms of RMSE and . Moreover, they have provided the best results both seasonally and for accurately predicting extreme values. An RMSE of 14.16 and 14.17 mm per month were reported for ENCE and MICE DURR, respectively, when stations that were at least 50% complete during the study period were included. For increasingly sparser data, the imputation accuracy achieved from MICE DURR surpasses ENCE, demonstrating the efficacy of multiple imputation when handling a substantial amount of missing data. Validation metrics indicate that these methods compare very favourably to existing methods in the literature, such as those that use random forests or multiple linear regression.

Analysis of connection fault and service maintenance strategy for subsea horizontal clamp connector

The deep-sea environment restricts the collection of reliable data for subsea connectors, leading to a lack of available failure data to develop connection fault detection processes and maintenance strategies. Therefore, this paper proposes an FMECA-BN model. The model developed an algorithm for mapping Risk Priority Number (RPN) to Bayesian network (BN) parameters and enhanced the details for mapping BN structures to match the diversity of FMEA. This enables the establishment of a BN based on a given Failure Mode, Effects, and Criticality Analysis (FMECA). The model was applied to the development of the Subsea Horizontal Clamp Connector (SHCC) to quantify and evaluate failure modes during the connection stage, creating an effective detection process. Then, the system's reliability variations caused by component degradation were analyzed using transformed dynamic BN, offering information for maintenance strategies based on availability. The reliability analysis results of the FMECA-BN model demonstrate a statistical error of 4.5% compared to actual data samples, proving the model's efficacy in addressing issues of information asymmetry, incomplete reliability data, and uncertainty. The analysis revealed that the developed SHCC requires a maintenance cycle of 14,892 h to maintain a 0.99 reliability level, with a cumulative failure probability of 4.6% after 20 years.

Robust Point Cloud Registration for Aircraft Engine Pipeline Systems

Aircraft engine systems are composed of numerous pipelines. It is crucial to regularly inspect these pipelines to detect any damages or failures that could potentially lead to serious accidents. The inspection process typically involves capturing complete 3D point clouds of the pipelines using 3D scanning techniques from multiple viewpoints. To obtain a complete and accurate representation of the aircraft pipeline system, it is necessary to register and align the individual point clouds acquired from different views. However, the structures of aircraft pipelines often appear similar from different viewpoints, and the scanning process is prone to occlusions, resulting in incomplete point cloud data. The occlusions pose a challenge for existing registration methods, as they can lead to missing or wrong correspondences. To this end, we present a novel registration framework specifically designed for aircraft pipeline scenes. The proposed framework consists of two main steps. First, we extract the point feature structure of the pipeline axis by leveraging the cylindrical characteristics observed between adjacent blocks. Then, we design a new 3D descriptor called PL-PPFs (Point Line–Point Pair Features), which combines information from both the pipeline features and the engine assembly line features within the aircraft pipeline point cloud. By incorporating these relevant features, our descriptor enables accurate identification of the structure of the engine’s piping system. Experimental results demonstrate the effectiveness of our approach on aircraft engine pipeline point cloud data.

#2256 Safety and effectiveness of avacopan beyond 52 weeks: experience to date in the Early Access Program (EAP)

Abstract Background and Aims ANCA-associated vasculitis (AAV), including granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA), is characterized by a high burden of organ damage, as well as increased mortality [1]. Both the disease itself and the immunosuppression required for its management contribute significantly to poor prognosis [2]. Avacopan is a first-in-class C5aR1 antagonist that demonstrated efficacy and safety over 52 weeks in patients with GPA or MPA, and was associated with a significantly lower requirement of glucocorticoids for disease management [3]. Significant data on long-term avacopan use in the context of real-life settings are sparse. Here, we describe experience with avacopan in 59 patients with GPA or MPA treated beyond 52 weeks within an ongoing Early Access Program (EAP). Method Patients with newly diagnosed or relapsing severe, active GPA or MPA were treated in the EAP. Safety data, including lack of effect and other events (i.e., relapse or worsening of disease) in these patients were recorded in a CSL Vifor safety database from Feb 2019 – Dec 2023. We performed analysis of these data for patients treated beyond 52 weeks. Results 237 patients received ≥ 1 dose of avacopan with a median overall treatment duration of 7 months (range 1-45) at the time of this analysis. 43 of 237 patients had at least one adverse event (AE) reported (18.1%) with a median of 2 (range 1-11) AEs per patient; 19/237 (8.0%) patients experienced a serious AE (SAE). Most of the reported AEs belonged to the System Organ Classes (SOC) of infections and infestations, and gastrointestinal disorders, with COVID-19 being the most frequently-reported event. At the time of this analysis, 59 patients continued treatment beyond 52 weeks, with a median overall duration of treatment of 16 months (range 13-45). Within this group, 12 of 59 patients experienced at least one AE (20.3%) with a total of 46 AEs. 9/ 12 patients reported AEs during the first 52 weeks treatment, while in 3 patients the date of AE occurrence was not available (Table 1). The results in these 59 patients are summarized below. 6 patients experienced at least one SAE (7 SAEs in total). As in the overall EAP population, most of the reported AEs belonged to the SOC of gastrointestinal disorders, followed by infections and infestations, with COVID-19 being the most common AE occurring in 3 patients. 18 AEs were assessed as related to avacopan, with 3 events in 2 patients being classified as serious (deep vein thrombosis [DVT] in one patient, lower urinary tract symptoms and JC polyomavirus test positive in the second). The patient experiencing DVT temporary discontinued avacopan. In the patient who developed lower urinary tract symptoms with active replication of JC virus (1.728.405 copies/mL), avacopan was permanently withdrawn. According to the reporter, the concomitant use of prednisone, rituximab and denosumab could have contributed to these events. Three patients experienced events implying worsening of underlying disease. These events occurred within the first 52 weeks of treatment. The first patient experienced a vasculitis flare 6 months following avacopan initiation that coincided with an unintended dose reduction to 20 mg BID due to a product supply issue. The second patient experienced a worsening of known GPA related mononeuritis multiplex, possibly induced by concomitant treatment with isoniazid and a likely result of pharmacological interaction between rifampicin and avacopan. The third patient experienced an increase of creatinine, proteinuria and microhematuria in the context of avacopan withdrawal due to other events. Conclusion These results confirm that avacopan has a manageable safety profile with the potential to be effective beyond 52 weeks in sustaining disease control. Limitations of this analysis include potential underreporting, incomplete data and no control group.

Concordance Rate of Pre-Operative Radiological Stage with Postoperative Pathological Stage in Colon Cancer

Aim: This study aimed to assess the concordance rate between pre-operative radiological staging using CT imaging and postoperative pathological staging in patients with colon cancer. Methodology: A prospective observational study was conducted at the Oncology Department of Jinnah Postgraduate Medical Center, Pakistan, with ethical committee approval between February 2023 to July 2023. Inclusion criteria involved patients diagnosed with colon adenocarcinoma aged >18 receiving treatment at the center, while exclusion criteria comprised unconfirmed colon cancer, lack of consent, benign colonic polyps, metastatic cancer, chemotherapy recipients, and incomplete data. Sample size estimation yielded 227 patients. Recruitment used consecutive sampling, and data were collected using a predefined proforma. CT scans were performed, and T-stage was assessed by radiologists and pathologists. Histological analysis followed established guidelines, with final pathology serving as the gold standard. Results: The diagnostic accuracy of CT imaging was evaluated, with statistically significant concordance found between CT scans and histopathological diagnoses (p-value = 0.046). CT scans demonstrated a sensitivity of 57.14% for Stage I tumors and a specificity of 88.18% for Stage II-III tumors. The positive predictive value (PPV) was 13.3%, and the negative predictive value (NPV) was 98.48%, resulting in an overall accuracy of 87.22%. These findings suggest that CT imaging is valuable for identifying Stage II-III tumors, exhibiting good specificity and NPV, although sensitivity and PPV for Stage I tumors were comparatively lower. Chi-square testing confirmed the statistical significance of these results (p-value ≤ 0.05) Conclusion: This study highlights the utility of CT imaging in pre-operative staging of colon cancer, particularly for Stage II-III tumors, where it exhibits notable accuracy. However, improvements may be needed to enhance sensitivity and PPV for Stage I tumors. Keywords: Colon cancer, CT imaging, pathological staging, concordance rate, diagnostic accuracy.

#2014 Exercise safety and efficacy as a rehabilitation therapy for patients on hemodiafiltration: a 6-month controlled study

Abstract Background and Aims Individuals with chronic kidney disease (CKD) stage 5D face challenges due to the accumulation of uremic toxins. Hemodiafiltration (HDF) stands out for its efficacy in removing solutes of various molecular weights, offering mortality benefits. Although exercise rehabilitation is established as a beneficial adjunct therapy for patients on maintenance hemodialysis, its impact on maintenance HDF programs remains understudied. The primary aim was to evaluate the safety and efficacy of exercise as rehabilitation in patients undergoing HDF. The secondary aim was to compare the outcomes between intra- and inter-HDF exercise sessions. Method This study enrolled CKD 5D patients at Fenix Nephrology Group from 2021 to 2023. The assessment occurred at the initiation of the exercise program and after six months of exercise rehabilitation. Physical tests included the step-test, handgrip, and one-repetition maximum (1RM), and the Kidney Disease Quality of Life Short Form (KDQOL-SF), a patient-reported outcome measure. The urea reduction ratio (URR) reflected HDF adequacy. Patients engaged in twice-weekly aerobic exercises achieving 70% of maximum heart rate and resistance exercises (60% 1RM). Results Data from 234 patients were obtained, and 81 were not on the exercise program. From the remaining 153 patients, we excluded 64. Twelve patients were excluded because underwent kidney transplantation during their participation, 41 had incomplete data, and 11 patients carried out less than 80% of the scheduled exercise sessions. We included in our final analysis data from 89 patients (55 ± 15 years; 58.4% male). The mean dialysis vintage was 9 ± 7 years, including high-flux hemodialysis and HDF. Specifically, for HDF, the mean dialysis vintage was 5 ± 4 years. Mean exercise session adherence was 94 ± 4%, and the mean number of sessions was 39 ± 4. Concerning the performance outcomes, we observed significant improvements in the step-test (80 ± 22 to 93 ± 25 steps; p < 0.001) and handgrip measurement (28 ± 7 to 30 ± 7 kgf; p < 0.001), alongside an approximate 4% increase in lean body mass (13 ± 2 to 14 ± 2 kg; p < 0.001) during the 6 months. The KDQOL-SF improved in physical functioning (64 ± 22 to 72 ± 23; p < 0.001), general health (55 ± 23 to 61 ± 2; p = 0.01), social function (73 ± 26 to 80 ± 21; p = 0.004), physical (43 ± 9 to 47 ± 8; p < 0.001) and mental composite scores (46 ± 10 to 48 ± 9; p = 0.04), along with a reduction in fatigue (57 ± 17 to 60 ± 17; p = 0.03). A similar favorable trend was observed for the URR (68 ± 10% vs. 71 ± 8%; p < 0.05). We also analyzed the exercise rehabilitation program in two different groups. Thirty-five patients carried out intradialytic exercise (i.e., during the dialysis session). In this group, the mean dialysis vintage was 10 ± 7 years and specifically 5 ± 3 years on HDF. The other group included 54 patients performing interdialytic exercise (i.e., pre- or post-session). In this group, the mean dialysis vintage was 8 ± 6 years and specifically 4 ± 2 years on HDF. We did not observe complications during the exercise program, and no sessions were interrupted due to adverse events. Demographic and anthropometric data (age, sex, weight, and body mass index) were comparable between the groups. Furthermore, exercise performance was equivalent in both groups. Conclusion Our findings suggest that a supervised exercise program for maintenance dialysis patients performing HDF is safe and efficacious, yielding substantial improvements in patient-reported and performance outcomes. Notably, the positive effects of exercise persisted whether conducted during intradialytic or interdialytic periods.

#358 The efficacy and safety of ripertamab (SCT400) in the treatment of primary membranous nephropathy: a single center retrospective study

Abstract Background and Aims Anti-CD20 monoclonal antibody is gaining increasing clinical acceptance in the treatment of primary membranous nephropathy (PMN). Ripertamab, a novel anti-CD20 monoclonal antibody developed in China, has been shown to be non-inferior to rituximab in efficacy and safety in patients with B-cell non Hodgkin's lymphoma. We aimed to identify the efficacy and safety of ripertamab in PMN retrospectively. Method The PMN patients who were diagnosed by renal biopsy and received ripertamab-based therapy between November 1 2022 and June 30 2023 were included. The inclusion criteria were: aged ≥ 18 years, and total B-lymphocyte ratio < 1% after using ripertamab. The exclusion criteria were: follow-up < 6 months, incomplete clinical data, secondary membranous nephropathy due to malignant tumor, systemic lupus erythematosus, hepatitis, etc. The primary outcome was clinical efficacy at 6 months after initial of treatment and secondary outcomes were clinical efficacy at 3 months, safety and the occurrence of adverse events. Complete remission (CR) was defined as urine protein/creatinine ratio (UPCR) < 300 mg/g or 24-hour urinary protein (UP) < 0.3 g, serum albumin >35 g, and stable renal function (eGFR with ≤50% reduction compared with baseline). Partial remission (PR) was defined as UPCR or UP with ≥ 50% reduction compared with baseline, serum albumin >30 g, and stable renal function. No response (NR) was defined as UPCR or UP with < 50% reduction compared with baseline. Results A total of 31 patients were included in this retrospective study. The baseline characteristics of the study population and ripertamab treatment responses were described in Table 1. At 6 months, 20 of 31 (64.6%) patients achieved CR (n = 10, 32.3%) or PR (n = 10, 32.3%) after ripertamab treatment (Table 2). Furthermore, 21 of 31 (67.7%) patients who were not given any immunosuppressive therapy before receiving ripertamab achieved CR or PR. Non-responders showed a higher level of proteinuria and a worse renal function at baseline than those of responders. All patients achieved complete B-cell depletion. No adverse events were observed in patients in this study. Conclusion Ripertamab can effectively induce remission of PMN and have a favorable safety profile.

Characteristics of “do not resuscitate” orders among elderly patients receiving mechanical ventilation in the intensive care unit in Taiwan

ObjectiveAs patient life expectancy has increased and people are living longer than before, the rate of mechanical ventilation among elderly patients in the intensive care unit has increased. Older patients who receive mechanical ventilation and have multiple comorbidities are more likely to have a do not resuscitate order than are younger patients with fewer comorbidities. The aim of our study was to describe the patient characteristics and predictive factors of do not resuscitate orders during hospitalization among elderly patients who received ventilation in the intensive care unit.MethodsThis was a retrospective review of the electronic medical records of patients in the intensive care unit of a teaching hospital in southern Taiwan. We enrolled patients admitted to the general intensive care unit from January 1, 2018, to September 31, 2020, and patients older than 80 years who experienced respiratory failure, were intubated and received mechanical ventilation. We analyzed patient demographics, disease severity during hospitalization and comorbidities. If a patient had multiple admissions to the intensive care unit, only the first admission was recorded.ResultsOf the 305 patients over 80 years of age with respiratory failure who were intubated and placed on a ventilator, 66 were excluded because of incomplete data, and 13 were excluded because they had already signed a do not resuscitate order prior to admission to the hospital. Ultimately, 226 patients were included in this study. A higher acute physiology and chronic health evaluation II score (>30) was also associated with an increased likelihood of a do not resuscitate order (odds ratio (OR) = 3.85, 95% CI = 1.09–13.62, p = 0.0362). Patients who had acute kidney injury or cerebrovascular accident were more likely to have a do not resuscitate order (OR = 2.74, 95% CI = 1.03–7.28, p = 0.0428 and OR = 7.32, 95% CI = 2.02–26.49, p = 0.0024, respectively).ConclusionOur study showed that older age, greater disease severity, and certain critical interventions were associated with a greater propensity for do not resuscitate orders, which is crucial for understanding patient preferences and guiding end-of-life care discussions. These findings highlight the importance of clinical severity and specific health events in predicting end-of-life care preferences in older patient groups.

Performance measurement of Brazilian federal university hospitals: an overview of the public health care services through principal component analysis.

This paper aimed to contextualize the process of public hospital providing services, based on the measurement of the performance of Federal University Hospitals (HUFs) of Brazil, using the technique of multivariate statistics of principal component analysis. This research presented a descriptive and quantitative character, as well as exploratory purpose and followed the inductive logic, being empirically structured in two stages, that is, the application of principal component analysis (PCA) in four healthcare performance dimensions; subsequently, the full reapplication of principal component analysis in the most highly correlated variables, in module, with the first three main components (PC1, PC2 and PC3). From the principal component analysis, considering mainly component I, with twice the explanatory power of the second (PC2) and third components (PC3), it was possible to evidence the efficient or inefficient behavior of the HUFs evaluated through the production of medical residency, by specialty area. Finally, it was observed that the formation of two groups composed of seven and eight hospitals, that is, Groups II and IV shows that these groups reflect similarities with respect to the scores and importance of the variables for both hospitals' groups. Among the main limitations it was observed that there was incomplete data for some HUFs, which made it impossible to search for information to explain and better contextualize certain aspects. More specifically, a limited number of hospitals with complete information were dealt with for 60% of SIMEC/REHUF performance indicators. The use of PCA multivariate technique was of great contribution to the contextualization of the performance and productivity of homogeneous and autonomous units represented by the hospitals. It was possible to generate a large quantity of information in order to contribute with assumptions to complement the decision-making processes in these organizations. Development of public policies with emphasis on hospitals linked to teaching centers represented by university hospitals. This also involved the projection of improvements in the reach of the efficiency of the services of assistance to the public health, from the qualified formation of professionals, both to academy, as to clinical practice. The originality of this paper for the scenarios of the Brazilian public health sector and academic area involved the application of a consolidated performance analysis technique, that is, PCA, obtaining a rich work in relation to the extensive exploitation of techniques to support decision-making processes. In addition, the sequence and the way in which the content, formed by object of study and techniques, has been organized, generates a particular scenario for the measurement of performance in hospital organizations.

Gingivoperiosteoplasty in Children with Cleft Lip and Palate: The Need for Alveolar Bone Grafting.

This study aimed to determine the efficacy of gingivoperiosteoplasty (GPP) in preventing alveolar bone grafting (ABG) among children with cleft lip and palate (CLP). Retrospective university hospital single center study. Children with CLP treated with GPP from 2000-2015 were included. Those under eight years of age, without definitive conclusions regarding need for ABG or with incomplete data were excluded. Included patients were analyzed for demographics, cleft type, age at GPP, associated cleft surgery, use of nasoalveolar molding (NAM), indication for ABG, operating surgeon and presence of residual alveolar fistula. T-tests and Fisher's exact tests were utilized for statistical analysis. The need for ABG. Of the 1682 children identified with CLP, 64 underwent GPP and met inclusion criteria. 78% of patients with CLP who underwent GPP were recommended for ABG. Those who received GPP at a younger age (P = .004) and at the time of initial cleft lip repair (P = .022) were less likely to be recommended for ABG. Patients with complete CLP were more likely to be recommended for ABG than patients with cleft lip and alveolus only (P = .015). The operating surgeon impacted the likelihood of ABG (P = .004). Patient gender, race, ethnicity, laterality, and NAM were not significantly associated with recommendation for ABG. GPP does not preclude the need for ABG. Therefore, the success of ABG after GPP and maxillary growth restriction should be analyzed further to determine if GPP is a worthwhile adjunct to ABG in cleft care.

Recent Progress of Advanced AIE Materials for Visualization of 3‐Level Latent Fingerprints

The 3‐level features of Latent fingerprints (LFPs) are pivotal in linking suspects with problematic or incomplete fingerprint data, constituting one of the most robust forms of evidence. Aggregation‐induced emission (AIE) materials, known for their heightened emissive properties in high aggregation states, provide a robust and powerful approach for developing techniques for 3‐level details of LFPs. So far, tremendous efforts have been devoted to solving high background fluorescence interference during the 3‐level LFPs visualization process. This review commences with an overview of 3‐level features and summarizes the interaction and mechanism of visualizing LFPs involving AIE materials and LFPs secretions. Moreover, it encompasses strategies to enhance the contrast and brightness of 3‐level LFPs images. We highlight the mechanism of AIE's physicochemical properties and their effects on the visualization of 3‐level LFPs. Additionally, we provide insights into potential challenges and opportunities in this emerging field.

Ultrahigh frequency path loss prediction based on K-nearest neighbors

Abstract Path loss prediction (PLP) is an important feature of wireless communications because it allows a receiver to anticipate the signal strength that will be received from a transmitter at a given distance. The PLP is done by using machine learning models that take into account numerous aspects such as the frequency of the signal, the surroundings, and the type of antenna. Various machine learning methods are used to anticipate path loss propagation but it is difficult to predict path loss in unknown propagation conditions. In existing models rely on incomplete or outdated data, which can affect the accuracy and reliability of predictions and they do not take into account the effects of environmental factors, such as terrain, foliage, and weather conditions, on path loss. Furthermore, existing models are not robust enough to handle the real-world variability and uncertainty, leading to significant errors in predictions. To tackle this issue, a novel ultrahigh frequency (UHF) PLP based on K-nearest neighbors (KNNs) is developed for predicting and optimizing the path loss for UHF. In this proposed model, a KNN-based PLP has been used to predict the path loss in the UHF. This technique is used for high-accuracy PLP through KNN forecast route loss by determining the K-nearest data points to a particular test point based on a distance metric. Moreover, the existing models were not able to optimize path loss due to complex and large-scale machine learning models. Therefore, the stochastic gradient descent technique has been used to minimize the objective function, which is often a measure of the difference between the model’s predictions and the actual output that will fine-tune the parameters of the KNN model, by measuring the similarity between data points. This model is implemented using Python to make it a lot more convenient.

Finite element model updating and response prediction of a frame structure based on optimal sensor placement

This paper proposes an approach for finite element (FE) model updating and response prediction of frame structures based on optimal sensor placement (OSP), which integrates sensor placement optimization, mode expansion, and model updating techniques. Firstly, sensor optimization layout and modal testing analysis are conducted on a bolted laboratory frame structure. The covariance-driven stochastic subspace identification (SSI-COV) method identifies the real-world structure’s natural frequencies, modal damping, and mode shapes. Secondly, the complete mode shapes are expanded using the measured incomplete modal data from the limited number of sensors. Thirdly, a multi-objective function based on frequency and mode shapes is established to adjust the parameters of the FE model. This ensures that the updated model accurately represents the dynamic properties of the actual structure within a specific frequency range. Finally, the Rayleigh damping of the frame structure is estimated, and the damping matrix is assembled to enhance the accuracy of dynamic response prediction in the updated model. By comparing the response prediction results of the updated FE model with and without considering the updated damping effects to the measurement data of the real-world structure, it is demonstrated that the proposed method considering updated damping effects can more effectively predict the structural response.