Transparent Reporting Research Articles

The Impact of the Covid-19 on Real Estate Companies: Vanke A and Poly Development

The COVID-19 pandemic has had a profound impact on the global macroeconomic landscape, social order, and corporate operations. In light of the prevailing trend of economic globalization, the pandemic has significantly affected this process, but it will not deter the progress of economic globalization. The COVID-19 pandemic has not only had a considerable impact on various countries worldwide but has also affected China. To protect the lives and health of our citizens, China has implemented strict containment policies. The pandemic has also had a significant impression on company operations. Our research focuses on two major Chinese real estate companies, "Poly Developments" and "Vanke A." Both companies have publicly available and transparent financial reports that include information on profit figures, profit margins, cash flow, and debt situations. Despite the impact of the COVID-19 pandemic, Vanke witnessed a downward trend in total revenue and cash flow from 2019 to 2021, but a slight recovery was observed in 2022. Vanke displayed stable revenue growth in its development activities and gradually stabilized its profitability. The company also prioritized effective cash flow management and pursued a diversified development strategy, leading to a significant year-on-year increase in investment cash flow. Overall, Vanke exhibited remarkable performance in sustainable strategic planning, collaboration, and operational activities, maintaining its position as an industry leader.

Radiomics for predicting survival in patients with locally advanced rectal cancer: a systematic review and meta-analysis.

Radiomics has recently received considerable research attention for providing potential prognostic biomarkers for locally advanced rectal cancer (LARC). We aimed to comprehensively evaluate the methodological quality and prognostic prediction value of radiomic studies for predicting survival outcomes in patients with LARC. The Cochrane, Embase, Medline, and Web of Science databases were searched. The radiomics quality score (RQS), Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist, the Image Biomarkers Standardization Initiative (IBSI) guideline, and the Prediction Model Risk of Bias Assessment Tool were used to assess the quality of the selected studies. A further meta-analysis of hazard ratio (HR) regarding disease-free survival (DFS) and overall survival (OS) was performed. Among the 358 studies reported, 15 studies were selected for our review. The mean RQS score was 7.73±4.61 (21.5% of the ideal score of 36). The overall TRIPOD adherence rate was 64.4% (251/390). Most of the included studies (60%) were assessed as having a high risk of bias (ROB) overall. The pooled estimates of the HRs were 3.14 [95% confidence interval (CI): 2.12-4.64, P<0.01] for DFS and 3.36 (95% CI: 1.74-6.49, P<0.01) for OS. Radiomics has potential to noninvasively predict outcome in patients with LARC. However, the overall methodological quality of radiomics studies was low, and the adherence to the TRIPOD statement was moderate. Future radiomics research should put a greater focus on enhancing the methodological quality and considering the influence of higher-order features on reproducibility in radiomics.

Nationally determined contributions to the 2015 Paris Agreement goals: transparency in communications from developing country Parties

ABSTRACT The goals of the Paris Agreement (PA) on collectively managing climate change can only be reached if all parties to the United Nations Framework Convention on Climate Change (UNFCCC) commit to actions supporting their Nationally Determined Contributions (NDCs). Developing-economy nations play a crucial role in reaching the PA targets, particularly in the Agriculture, Forest, and Other Land Uses (AFOLU) sector. However, developing country Parties also face several constraints in tracking and communicating progress towards their climate policy targets and implementation of their NDCs. The operationalization of Biennial Transparency Report (BTR) and Enhanced Transparency Framework (ETF) under the PA will bring stricter reporting timeframes and advanced transparency for all parties. With these requirements rapidly coming into force, addressing reporting gaps is now a pressing priority. The present study analyzes the NDCs, and Biennial Update Reports (BURs) submitted by developing country Parties under the UNFCCC. In an illustrative exercise, our in-depth analysis concentrates on reporting on the AFOLU sector and identifies issues impeding a comprehensive and comparable Global Stock Take (GST): (i) issues of consistency in reporting timeframes (ii) issues in transparency of reporting on mitigation sectors and on relevant progress indicators (iii) incomparability of methodological approaches proposed and used, and (iv) the implications of limited national capacity for transparent reporting. The UNFCCC and developed country Parties now have the opportunity of providing specialized support for developing country Parties. This could include tailored guidance to address gaps in both greenhouse-gas (GHG) emissions accounting, and reporting challenges, to ensure consistent, comprehensive, and transparent reporting to reinforce capacities moving forward following the next GST.

Optimizing Giri Cendana edutourism as support for the SDGs of Ngrancah Village

Ngrancah Village has the potential for coffee education tourism, which is crucial for supporting the community's economic independence towards achieving the Village Sustainable Development Goals (SDGs). However, there are several challenges hindering business development, such as a lack of strong branding and insufficient knowledge among human resources regarding institutional and financial management. This results in the less organized running of edutourism. Additionally, partnerships and collaboration with village officials are not optimal, further hampering business development. This community service involves activities in the form of outreach, training, and mentoring based on Participatory Rural Appraisal (PRA). The outcomes of these community service activities are as follows: (1) Ngrancah Village's coffee edutourism now has strong branding, expanding its market share; (2) increased knowledge regarding institutional management, enabling members to fulfill their duties and collaborate with stakeholders for business development; and (3) enhanced knowledge and understanding of financial management, leading to the preparation of accountable and transparent financial reports.

Around the EQUATOR with Clin-STAR: Prediction modeling opportunities and challenges in aging research.

The 2015 Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Statement was published to improve reporting transparency for prediction modeling studies. The objective of this review is to highlight methodologic challenges that aging-focused researchers will encounter when designing and reporting studies involving prediction models for older adults and provide guidance for addressing these challenges. In following the 22-item TRIPOD checklist, researchers must consider the representativeness of cohorts used (e.g., whether older adults with frailty, cognitive impairment, and social isolation were included), strategies for incorporating common geriatric predictors (e.g., age, comorbidities, functional status, and frailty), methods for handling missing data and competing risk of death, and assessment of model performance heterogeneity across important subgroups (e.g., age, sex, race, and ethnicity). We provide guidance to help aging-focused researchers develop, validate, and report models that can inform and improve patient care, which we label "TRIPOD-65."

Development and Validation of the Early-Stage Hodgkin Lymphoma (HL) International Prognostication Index (E-HIPI): A Report from the Hodgkin Lymphoma International Study for Individual Care (HoLISTIC) Consortium

Background: There are a lack of clinical prediction tools in early-stage Hodgkin lymphoma (E-HL). We developed and validated a modern-day model, known as E-HIPI, to predict progression-free survival (PFS) within the first 5 years (y) incorporating detailed individual patient (pt) data from international clinical trials and prospective registry data that were standardized, normalized &amp; harmonized as part of the HoLISTIC Consortium (www.hodgkinconsortium.org). Methods: Model development utilized Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines (Moons, Ann Intern Med 2015) on a cohort of 3,080 newly-diagnosed E-HL pts treated on 4 seminal phase 3 clinical trials (NCIC: Meyer, NEJM 2012; RAPID: Radford, NEJM 2015; EORTC-GELA H9U: Ferme, E ur J Cancer 2017; EORTC/LYSA/FIL H10: Andre, JCO 2017). External validation was done in an independent cohort of 462 E-HL pts from a large registry (Princess Margaret, Toronto). Pts with classic HL, stage I or II disease, and ages 18-65 y were included. The primary outcome was PFS. Cox models were utilized with follow-up truncated at 5 years. Baseline predictors were: sex, stage, B symptoms, histology, number &amp; location of nodal sites, and continuous data values of age, maximum tumor diameter (MTD), white blood cell count (WBC), lymphocyte count, hemoglobin, albumin &amp; erythrocyte sedimentation rate (ESR). Multiple imputation was used for missing data. To consider possible non-linear relationships for continuous variables we examined plots &amp; cubic splines. We used backward elimination ( P&amp;lt;0.1) to develop the models &amp; internal validation with 200 bootstrap samples was conducted to estimate optimism &amp; correct for overfitting. The final prediction equations applied optimism corrections to beta coefficients &amp; hazard ratios (HR). Sensitivity analyses included model results stratified by PET staging (vs CT) and each HL trial. The models were evaluated in the external validation cohort &amp; compared using c-statistics. Model scores were also grouped by tertiles for visualization in Kaplan-Meier (KM) curves. Results: Median age in the development cohort was 35y; 51% were female; 81% had nodular sclerosis &amp; 77% stage II disease; 26% had B symptoms; 32% had mediastinal bulk (≥10cm or &amp;gt;1/3 diameter) and the mean MTD was 6.4 cm (interquartile range (IQR), 3.9-8.2). Median follow-up was 60 months (IQR 45-75). KM estimates at 5y was 90.7% (264 events) for PFS, and 97.1% (78 events) for overall survival (OS). After backward elimination, significant variables retained were age, sex, nodal location (cervical region), MTD &amp; albumin. Stage, ESR, or the number of nodal sites were not significant. Age was modeled with piecewise linear splines due to its non-linear relationship. See the Table for the final prediction model and optimism-corrected HRs. Optimism-corrected c-statistics in the development model was 0.63. Sensitivity analyses of stratification by type of imaging at staging or by each clinical trial demonstrated no change in model parameters or c-statistics. Most baseline characteristics and outcomes of the external validation cohort were similar besides median follow-up time (74 months, IQR 37-129). C-statistics for the E-HIPI model in external validation was 0.63. In addition, observed 5y outcomes stratified by tertile of predicted risk in the external cohort separated pts into a low &amp; higher-risk group, which comprised 1/3 &amp; 2/3 of pts, respectively ( Figure). Finally, model diagnostics revealed the potential for time dependency in the retained covariates. Further assessment of differential prediction between early (&amp;lt;2y) vs. later (2-5y) PFS events is ongoing. Conclusion: Following TRIPOD methodology, we rigorously developed and externally validated the E-HIPI among &amp;gt;3,500 E-HL pts.Discrete risk groups were delineated, and we identified several novel factors, including nodal location, sex &amp; key continuous variables that predict 5y PFS. Additional model refinement is underway, including formal calibration &amp; external validation via other HL registries (Stanford, Mayo/Iowa SPORE). A web-based calculator to simplify application of the E-HIPI will also be presented at ASH. Future planned modeling includes integration of differing treatments &amp; response-adapted imaging via multistate modeling to enrich individualized survival estimates and simulation modeling to predict late consequences.

Quality Appraisal of Research Reporting for Aromatherapy and Essential Oil Studies in Humans: Proposed Checklist for "Transparent Reporting for Essential oil and Aroma Therapeutic Studies".

Introduction: Reporting of aromatherapy-focused research often lacks sufficient quality and detail for replication and subsequent application of results. To our knowledge currently, no quality appraisal tool exists for aromatherapy research reporting. To address this gap, the Aromatic Research Quality Appraisal Taskforce (ARQAT) composed of aromatherapy professionals with varied expert backgrounds came together. Presented here is the Transparent Reporting for Essential oil and Aroma Therapeutic Studies (TREATS) checklist, which is a result of this collaborative effort. Methods: Creation of TREATS followed a three-stage process, including determination of interest/need, development, and dissemination. The shortcomings of existing aromatherapy research reporting quality were evaluated and responses to address these shortcomings were used to create checklist items that were then grouped into sections. Items for each section were brain-stormed with reference to the aromatherapy literature and ARQAT's expert knowledge, and the development of each section followed an iterative process until agreement was reached. An explanatory document was also created to assist more accurate use of the tool; it and the checklist were reviewed by a group of aromatherapy experts. Results: The TREATS checklist with 38 items in four sections was developed along with the explanatory document. The ARQAT and a global group of aromatherapy experts reviewed the TREATS. Their results and comments assisted development of the current version. The TREATS identifies key components of research involving essential oils, their application, and olfactory considerations that ARQAT considers the minimum necessary for high-quality aromatherapy research. Conclusion: The TREATS, explanatory document, and associated website (www.arqat.org) contribute to thorough aromatherapy research critique. The TREATS checklist aids appraisal of quality and can be used with any study design. It lays the foundation for the future development of aromatic research reporting guidelines.

PENGELOLAAN DANA DESA DALAM MENINGKATKAN PEMBANGUNAN NON FISIK DI DESA PALIAT KECAMATAN KELUA KABUPATEN TABALONG

&#x0D; &#x0D; &#x0D; &#x0D; Village Fund Management in Paliat Village, Kelua District, Tabalong Regency in order to achieve development goals, especially in non-physical development effectively and efficiently. With the existence of the Village Fund, the opportunity for development is greater in this case to fulfill the wishes of the community. From the results of observations there are problems, namely the lack of public understanding of transparency or budget reports from the Village Government, lack of community participation in the implementation of non-physical development, and the Not Optimal Process of Implementing Non-physical Development. The purpose of this researcher is to find out the management of Village Funds in increasing non- physical development in Paliat Village, Kelua District, Tabalong Regency and the influencing factors. This study used a qualitative approach with a qualitative descriptive type. The data collection techniques used were interviews, observation and documentation. The data source was taken through purposive sampling of 13 people. After the data was collected, it was analyzed using techniques including data condensation, data presentation and extension of observations, trigulation, analysis of negative cases, and conducting member checks .The results of the study showed that the management of village funds in Paliat Village, District the two districts of Tabalong Regency is are still not good. Good management can be seen from the planning aspect by formulating activities, the organizing aspect, assigning tasks, and grouping activities from the aspect of activating the division of labor for each. what is desired, the aspect of organizing how to collect human resources from the aspect of mobilizing there is a way to optimize human resources and from the aspect of supervision seen from monitoring and evaluation of performance Factors that influence inhibiting factors management is limited budget funds and less optimal monitoring activities. And the supporting factors for management are good planning by holding village development planning meetings and good division of tasks in an activity, which is under special coordination from the Head of Village Services. In order to improve the management of Village Funds in increasing non-physical development in Paliat Village, Kelua District, it is suggested to the Head of Paliat Village to be further improved in terms of non-physical development as well as providing a personal approach or outreach in planning for further development, and provide clarity of understanding of village fund management reports so that under development can run well. To the BPD to actively carry out supervision. To the community to always participate in participating in the implementation of development, especially training..&#x0D; &#x0D; &#x0D; &#x0D;

Pharmacological treatment of post-traumatic stress disorder: a treatment guide based on a systematic literature review

Objective: To review the literature from the last twenty years on pharmacological treatments for post-traumatic stress disorder to clarify questions about the efficacy and tolerability of pharmacotherapy and the superiority of one specific agent over another for creating a treatment guideline based on levels of evidence. Methods: Randomized clinical trials and systematic reviews were searched in Medline-PubMed, PsycINFO, Web of Science, Scielo, and Lilacs. The screening of the criteria established by the Transparent Reporting of Systematic Reviews and Meta-Analyses was used, followed by the analysis of risk of bias of the Critical Appraisal Skills Programme. Lastly, the level of evidence and grade of recommendation was acquired, following the Oxford Center for Evidence-based Medicine 2009 Levels of Evidence. Results: The search retrieved double-blind, randomized and placebo-controlled clinical trials. Comparative clinical trials between different drugs were also evaluated and systematic reviews on drug efficacy and meta-analyses. A total of 1.458 studies were found; 58 of these studies were pre-selected and the final sample was composed of 20 studies. Conclusions: Of the 17 drugs included, the following is the order of recommendation based on the levels of evidence established in this study - 1st sertraline; 2nd venlafaxine and paroxetine; 3rd atypical antipsychotics.

Whole slide imaging of tumour microenvironment in classical Hodgkin’s lymphoma: development of a clinical prediction model based on programmed death-ligand 1 and tumorous Reed-Sternberg cells

AimsThe prognostic impact of programmed death-ligand 1 (PD-L1) cells in classic Hodgkin lymphoma (cHL) tumour microenvironment remains undefined.MethodsModel development via Transparent Reporting of a multivariable prediction model for Individual Prognosis...

Clinical Prediction Models for Hospital-Induced Delirium Using Structured and Unstructured Electronic Health Record Data: Protocol for a Development and Validation Study.

Hospital-induced delirium is one of the most common and costly iatrogenic conditions, and its incidence is predicted to increase as the population of the United States ages. An academic and clinical interdisciplinary systems approach is needed to reduce the frequency and impact of hospital-induced delirium. The long-term goal of our research is to enhance the safety of hospitalized older adults by reducing iatrogenic conditions through an effective learning health system. In this study, we will develop models for predicting hospital-induced delirium. In order to accomplish this objective, we will create a computable phenotype for our outcome (hospital-induced delirium), design an expert-based traditional logistic regression model, leverage machine learning techniques to generate a model using structured data, and use machine learning and natural language processing to produce an integrated model with components from both structured data and text data. This study will explore text-based data, such as nursing notes, to improve the predictive capability of prognostic models for hospital-induced delirium. By using supervised and unsupervised text mining in addition to structured data, we will examine multiple types of information in electronic health record data to predict medical-surgical patient risk of developing delirium. Development and validation will be compliant to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. Work on this project will take place through March 2024. For this study, we will use data from approximately 332,230 encounters that occurred between January 2012 to May 2021. Findings from this project will be disseminated at scientific conferences and in peer-reviewed journals. Success in this study will yield a durable, high-performing research-data infrastructure that will process, extract, and analyze clinical text data in near real time. This model has the potential to be integrated into the electronic health record and provide point-of-care decision support to prevent harm and improve quality of care. DERR1-10.2196/48521.

Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review

Parkinson’s disease (PD) is a neurodegenerative disorder that produces both motor and non-motor complications, degrading the quality of life of PD patients. Over the past two decades, the use of wearable devices in combination with machine learning algorithms has provided promising methods for more objective and continuous monitoring of PD. Recent advances in artificial intelligence have provided new methods and algorithms for data analysis, such as deep learning (DL). The aim of this article is to provide a comprehensive review of current applications where DL algorithms are employed for the assessment of motor and non-motor manifestations (NMM) using data collected via wearable sensors. This paper provides the reader with a summary of the current applications of DL and wearable devices for the diagnosis, prognosis, and monitoring of PD, in the hope of improving the adoption, applicability, and impact of both technologies as support tools. Following PRISMA (Systematic Reviews and Meta-Analyses) guidelines, sixty-nine studies were selected and analyzed. For each study, information on sample size, sensor configuration, DL approaches, validation methods and results according to the specific symptom under study were extracted and summarized. Furthermore, quality assessment was conducted according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) method. The majority of studies (74%) were published within the last three years, demonstrating the increasing focus on wearable technology and DL approaches for PD assessment. However, most papers focused on monitoring (59%) and computer-assisted diagnosis (37%), while few papers attempted to predict treatment response. Motor symptoms (86%) were treated much more frequently than NMM (14%). Inertial sensors were the most commonly used technology, followed by force sensors and microphones. Finally, convolutional neural networks (52%) were preferred to other DL approaches, while extracted features (38%) and raw data (37%) were similarly used as input for DL models. The results of this review highlight several challenges related to the use of wearable technology and DL methods in the assessment of PD, despite the advantages this technology could bring in the development and implementation of automated systems for PD assessment.

Analysis of the Presentation of Financial Statements and the Morality of Apparatus on the Potential of Fraud in Village Financial Management

Referring to Permendagri (Minister of Home Affairs Regulation) No. 20 of 2018, the presentation of transparent and accountable financial reports can serve as a deterrent against fraud in village funds. Furthermore, the moral support of village officials can aid in the proper management of funds in accordance with the provisions outlined in Permendagri. Thus, the presentation of financial reports is expected to provide accurate information and assist users in their decision-making processes. The research method employed in this study is a case study with a descriptive analysis approach. Nonprobability sampling with saturated samples is utilized as the sampling technique. Data collection techniques involve observation, in-depth interviews, and documentation. The results indicate that the presentation of financial statements in Karyalaksana Village and Lampegan Village is considered satisfactory. Similarly, the level of moral conduct among the village officials ranges from conventional to post-conventional, thereby reducing the potential for fraud in village financial management.&#x0D; Keywords: financial statement presentation, morality, fraud potential

Open science practices need substantial improvement in prognostic model studies in oncology using machine learning

ObjectiveTo describe the frequency of open science practices in a contemporary sample of studies developing prognostic models using machine learning methods in the field of oncology. Study design and settingWe conducted a systematic review, searching the MEDLINE database between December 1, 2022, and December 31, 2022, for studies developing a multivariable prognostic model using machine learning methods (as defined by the authors) in oncology. Two authors independently screened records and extracted open science practices. ResultsWe identified 46 publications describing the development of a multivariable prognostic model. The adoption of open science principles was poor. Only one study reported availability of a study protocol, and only one study was registered. Funding statements and conflicts of interest statements were common. Thirty-five studies (76%) provided data sharing statements, with 21 (46%) indicating data were available on request to the authors and seven declaring data sharing was not applicable. Two studies (4%) shared data. Only 12 studies (26%) provided code sharing statements, including 2 (4%) that indicated the code was available on request to the authors. Only 11 studies (24%) provided sufficient information to allow their model to be used in practice. The use of reporting guidelines was rare: eight studies (18%) mentioning using a reporting guideline, with 4 (10%) using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis statement, 1 (2%) using Minimum Information About Clinical Artificial Intelligence Modeling and Consolidated Standards Of Reporting Trials-Artificial Intelligence, 1 (2%) using Strengthening The Reporting Of Observational Studies In Epidemiology, 1 (2%) using Standards for Reporting Diagnostic Accuracy Studies, and 1 (2%) using Transparent Reporting of Evaluations with Nonrandomized Designs. ConclusionThe adoption of open science principles in oncology studies developing prognostic models using machine learning methods is poor. Guidance and an increased awareness of benefits and best practices of open science are needed for prediction research in oncology.

Models and Approaches for Comprehension of Dysarthric Speech Using Natural Language Processing: Systematic Review.

Speech intelligibility and speech comprehension for dysarthric speech has attracted much attention recently. Dysarthria is characterized by irregularities in the speed, strength, pitch, breath control, range, steadiness, and accuracy of muscle movements required for articulatory aspects of speech production. This study examined the contributions made by other studies involved in dysarthric speech comprehension. We focused on the modes of meaning extraction used in generalizing speaker-listener underpinnings in light of semantic ontology extraction as a desired technique, applied method types, speech representations used, and databases sourced from. This study involved a systematic literature review using 7 electronic databases: Cochrane Database of Systematic Reviews, Web of Science Core Collection, Scopus, PubMed, ACM, IEEE Xplore, and Google Scholar. The main eligibility criterion was the extraction of meaning from dysarthric speech using natural language processing or understanding approaches to improve on dysarthric speech comprehension. In total, out of 834 search results, 30 studies that matched the eligibility requirements were acquired following screening by 2 independent reviewers, with a lack of consensus being resolved through joint discussion or consultation with a third party. In order to evaluate the studies' methodological quality, the risk of bias assessment was based on the Cochrane risk-of-bias tool version 2 (RoB2) with 23 of the studies (77%) registering low risk of bias and 7 studies (33%) raising some concern over the risk of bias. The overall quality assessment of the study was done using TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis). Following a review of 30 primary studies, this study revealed that the reviewed studies focused on natural language understanding or clinical approaches, with an increase in proposed solutions from 2020 onwards. Most studies relied on speaker-dependent speech features, while others used speech patterns, semantic knowledge, or hybrid approaches. The prevalent use of vector representation aligned with natural language understanding models, while Mel-frequency cepstral coefficient representation and no representation approaches were applied in neural networks. Hybrid representation studies aimed to reconstruct dysarthric speech or improve comprehension. Comprehensive databases, like TORGO and UA-Speech, were commonly used in combination with other curated databases, while primary data was preferred for specific or unique research objectives. We found significant gaps in dysarthric speech comprehension characterized by the lack of inclusion of important listener or speech-independent features in the speech representations, mode of extraction, and data sources used. Further research is therefore proposed regarding the formulation of models that accommodate listener and speech-independent features through semantic ontologies that will be useful in the inclusion of key features of listener and speech-independent features for meaning extraction of dysarthric speech.

Could Accountant Be Facilitator To Zero Net Emission Programs?

The study aims to highlight the role of accountants in supporting and facilitating the implementation of the Net Zero Emission Programme in Indonesia with a focus on emission measurement and reporting, sustainable financial management, related audits and verification, as well as its impact on environmental sustainability and the achievement of climate change targets. The research is based on a qualitative approach of literature review using data in the form of annual reports and sustainability reports from mining companies in 2022 as well as from various related research journals. The results of this study show that accountants have a key role to play in helping companies and organizations achieve zero emission targets while ensuring compliance with relevant regulations. They can also help in measuring the financial impact of sustainability initiatives and make transparent reports to stakeholders.

Increased endorsement of TRIPOD and other reporting guidelines by high impact factor journals: survey of instructions to authors

ObjectivesTo assess the endorsement of reporting guidelines by high impact factor journals over the period 2017–2022, with a specific focus on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. Study Design and SettingWe searched the online ‘instructions to authors’ of high impact factor medical journals in February 2017 and in January 2022 for any reference to reporting guidelines and TRIPOD in particular. ResultsIn 2017, 205 out of 337 (61%) journals mentioned any reporting guideline in their instructions to authors and in 2022 this increased to 245 (73%) journals. A reference to TRIPOD was provided by 27 (8%) journals in 2017 and 67 (20%) in 2022. Of those journals mentioning TRIPOD in 2022, 22% provided a link to the TRIPOD website and 60% linked to TRIPOD information on the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network website. Twenty-five percent of the journals required adherence to TRIPOD. ConclusionAbout three-quarters of high-impact medical journals endorse the use of reporting guidelines and 20% endorse TRIPOD. Transparent reporting is important in enhancing the usefulness of health research and endorsement by journals plays a critical role in this.

Validity of Clinical Severity Scores for Respiratory Syncytial Virus: A Systematic Review.

Respiratory syncytial virus (RSV) is a widespread respiratory pathogen, and RSV-related acute lower respiratory tract infections are the most common cause of respiratory hospitalization in children <2 years of age. Over the last 2 decades, a number of severity scores have been proposed to quantify disease severity for RSV in children, yet there remains no overall consensus on the most clinically useful score. We conducted a systematic review of English-language publications in peer-reviewed journals published since January 2000 assessing the validity of severity scores for children (≤24 months of age) with RSV and/or bronchiolitis, and identified the most promising scores. For included articles, (1) validity data were extracted, (2) quality of reporting was assessed using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis checklist (TRIPOD), and (3) quality was assessed using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). To guide the assessment of the validity data, standardized cutoffs were employed, and an explicit definition of what we required to determine a score was sufficiently validated. Our searches identified 8541 results, of which 1779 were excluded as duplicates. After title and abstract screening, 6670 references were excluded. Following full-text screening and snowballing, 32 articles, including 31 scores, were included. The most frequently assessed scores were the modified Tal score and the Wang Bronchiolitis Severity Score; none of the scores were found to be sufficiently validated according to our definition. The reporting and/or design of all the included studies was poor. The best validated score was the Bronchiolitis Score of Sant Joan de Déu, and a number of other promising scores were identified. No scores were found to be sufficiently validated. Further work is warranted to validate the existing scores, ideally in much larger datasets.

Analisis Penerapan Akuntansi Isak 35 Pada Organisasi Keagamaan (Studi Kasus 5 Masjid Di Kabupaten Labuhanbatu Selatan)

This research aims to analyze the application of ISAK 35 accounting standards in religious organizations by taking case studies of five mosques in South Labuhanbatu Regency. ISAK 35 is an accounting standard that regulates the recognition, measurement, and placement of transactions and events in hazardous organizations. In the context of religious organizations, namely mosques, the implementation of ISAK 35 has an important importance in ensuring transparency and accountability in financial management. This research uses a qualitative approach with a case study method. Primary data was collected through in-depth interviews with mosque administrators and related financial staff. Secondary data was obtained through literature and documentation studies related to the implementation of ISAK 35 in religious organizations. The research results show that five mosques located in South Labuhanbatu Regency still have not implemented the ISAK 35 standard in preparing their financial reports. This shows that there are deficiencies in the presentation and delivery of financial information in accordance with applicable accounting standards. This research provides an overview of the importance of implementing ISAK 35 standards in producing more transparent, accurate and trustworthy financial reports for mosques in the region. These factors include limited knowledge and understanding of ISAK 35 by mosque administrators, a lack of human resources skilled in accounting, and a lack of support from external parties such as local governments or financial supervisory bodies.

Prognostic prediction models for oropharyngeal squamous cell carcinoma (OPSCC): a protocol for systematic review, critical appraisal and meta-analysis

IntroductionOropharyngeal squamous cell carcinoma (OPSCC) is increasingly prevalent and has significantly heterogeneous risks of survival for diagnosed individuals due to the inter-related risk factors. Precise prediction of the risk of...