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Familial hypercholesterolaemia (FH) is an autosomal dominant inherited disorder of lipid metabolism and a preventable cause of premature cardiovascular disease. Current detection rates for this highly treatable condition are low. Early detection and management of FH can significantly reduce cardiac morbidity and mortality. This study aims to implement a primary-tertiary shared care model to improve detection rates for FH. The primary objective is to evaluate the implementation of a shared care model and support package for genetic testing of FH. This protocol describes the design and methods used to evaluate the implementation of the shared care model and support package to improve the detection of FH.
This mixed methods pre-post implementation study design will be used to evaluate increased detection rates for FH in the tertiary and primary care setting. The primary-tertiary shared care model will be implemented at NSW Health Pathology and Sydney Local Health District in NSW, Australia, over a 12-month period. Implementation of the shared care model will be evaluated using a modification of the implementation outcome taxonomy and will focus on the acceptability, evidence of delivery, appropriateness, feasibility, fidelity, implementation cost and timely initiation of the intervention. Quantitative pre-post and qualitative semistructured interview data will be collected. It is anticipated that data relating to at least 62 index patients will be collected over this period and a similar number obtained for the historical group for the quantitative data. We anticipate conducting approximately 20 interviews for the qualitative data.
Ethical approval has been granted by the ethics review committee (Royal Prince Alfred Hospital Zone) of the Sydney Local Health District (Protocol ID: X23-0239). Findings will be disseminated through peer-reviewed publications, conference presentations and an end-of-study research report to stakeholders.
To investigate the relationship between climate change cognition and behaviours (awareness, concern, motivation, behaviours at home and behaviours at work), positive and negative future cognition, and environmental sustainability attitudes in nurses and to identify the factors affecting environmental sustainability attitudes.
A cross-sectional study.
In total, 358 nurses currently working in tertiary hospitals in Korea were recruited. Data were collected using an online questionnaire link from 1 August to 7 August 2022. Climate change cognition and behaviours were measured using the Korean version of the Climate, Health, and Nursing Tool. Positive and negative future cognition were measured using the Korean version of the Future Event Questionnaire. Environmental sustainability attitude was measured using the Korean version of the Sustainability Attitudes in Nursing Survey-2. Multiple regression analysis was used to identify the factors affecting environmental sustainability attitudes.
Motivation, concern and behaviours at work were factors affecting environmental sustainability attitudes. Motivation was a pivotal influencing factor. Better scores for environmental sustainability attitudes were specifically correlated with higher scores for motivation, concern and behaviours at work.
Nurses' motivation, climate change concern and pro-environmental workplace practices should all be considered to improve their attitudes towards environmental sustainability.
To enhance nurses' environmental sustainability attitudes and behaviours, nurse educators must educate them to increase their motivation for climate action.
Nurses are increasingly expected to contribute to environmental sustainability. Hence, awareness of climate change and environmental sustainability among nurses must be improved, and nursing engagement and action encouraged. Nurse educators and managers should explore barriers to pro-environmental behaviour engagement among nurses, examine workplace cultures that encourage pro-environmental behaviours and develop policies/regulations to develop more environmentally sustainable workplaces.
We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Neither patients nor the public were involved in our research's design, conduct, reporting or dissemination plans. The nurses partook in this study exclusively as research participants and were not involved in any research process.
Advance care planning is a process through which people communicate their goals and preferences for future medical care. Due to the complexity of the decision-making process, decision aids can assist individuals in balancing potential benefits and risks of treatment options.
While decision aids have the potential to better promote advance care planning, their characteristics, content and application effectiveness are unclear and lack systematic review. Therefore, we aimed to explore these three aspects and establish a foundation for future research.
Scoping review.
This scoping review adheres to the framework proposed by Arksey and O'Malley and the PRISMA-ScR list. Six English-language databases were systematically searched from the time of construction until 1 December 2023. Two researchers conducted the article screening and data extraction, and the extracted data was presented in written tables and narrative summaries.
Of the 1479 titles and abstracts, 20 studies fulfilled the inclusion criteria. Types of decision aids were employed, mainly websites and videos. Decision aid's primary components center around 11 areas, such as furnishing information, exploring treatment and care preferences. The main manifestations were a significant increase in knowledge and improved recognition of patients' target value preferences. Among the aids, websites and videos for advance care planning have relatively high content acceptability and decision-making process satisfaction, but their feasibility has yet to be tested.
Decision aids were varied, with content focused on describing key information and exploring treatment and care preferences. Regarding application effects, the aids successfully facilitated the advance care planning process and improved the quality of participants' decisions. Overall, decision aids are efficient in improving the decision-making process for implementing advance care planning in cancer and geriatric populations. In the future, personalised decision aids should be developed based on continuous optimization of tools' quality and promoted for clinical application.
The paper has adhered to the EQUATOR guidelines and referenced the PRISMAg-ScR checklist.
This is a review without patient and public contribution.
Registration: https://doi.org/10.17605/OSF.IO/YPHKF, Open Science DOI: 10.17605/OSF.IO/YPHKF.
To conduct systematic evaluation of the risk predictors of glycaemic control in children and adolescents with type 1 diabetes mellitus.
Cohort studies on risk predictors of glycaemic control in children and adolescents with type 1 diabetes were retrieved from CNKI, PubMed, Web of Science, Embase databases, etc. from the construction of the repository to 3 February 2023. Literature screening was conducted according to inclusion and exclusion criteria, then data extraction of region, sample size, age, follow-up time, risk predictors, outcome indicators, etc., and quality evaluation of The Newcastle-Ottawa Scale were conducted by two researchers while the third researcher makes decisions if there are disagreements. Finally, Revman5.4 and StataMP17 were used for meta-analysis.
A total of 29 studies were included, and the results showed that insulin pump [Weighed mean difference (WMD) = −.48, 95% CI (−.73, −.24), p < .01], high-frequency sensor monitoring, early use of insulin pumps, prospective follow-up male, white race, large body mass index-standardised scoring, conscientiousness, agreeableness of mothers, eicosapentaenoic acid, leucine and protein (p < .05) were beneficial for reducing HbA1c levels in children and adolescents with diabetes. Ketoacidosis [WMD = .39, 95% CI (.28, .50), p < .01], selective admission, higher HbA1c level at one time (p < .01), higher glutamate decarboxylase antibody at 1 month after diagnosis, lower socio-economic status, non-living with biological parents, non-two-parent family, family disorder, family history of diabetes and high carbohydrate intake (p < .05) increased HbA1c levels in children and adolescents with diabetes.
For children and adolescents with type 1 diabetes mellitus, the use of insulin pump, high-frequency sensor monitoring, prospective follow-up, good family support and reasonable diet are conducive to blood glucose control, while selective admission and DKA are not. Disease characteristics and demographic characteristics of children are closely related to subsequent blood glucose control, and the relationship between diagnosis age and blood glucose control needs to be further explored.
by Junhao Sun, Siqi Yang, Yue Zhang, Wenzhi Xiang, Xiubo Jiang
As a new definition for the evidence of hepatic steatosis and metabolic dysfunctions, the relationship between phthalates (PAEs) and metabolic dysfunction-associated fatty liver disease (MAFLD) remains virtually unexplored. This study included 3,137 adults from the National Health and Nutrition Examination Survey spanning 2007–2018. The diagnosis of MAFLD depended on the US Fatty Liver Index (US FLI) and evidence of metabolic dysregulation. Eleven metabolites of PAEs were included in the study. Poisson regression, restricted cubic spline (RCS), and weighted quantile sum (WQS) regression were used to assess the associations between phthalate metabolites and MAFLD. After adjusting for potential confounders, Poisson regression analysis showed that mono-2-ethyl-5-carboxypentyl phthalate (MECPP), mono-n-butyl phthalate, mono-(3-carboxypropyl) phthalate, mono-ethyl phthalate (MEP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) and mono-(2-ethyl-5-oxohexyl) phthalate were generally significant positively associated with MAFLD (Pby Gabriela Ferreira Siano, Camila Stefanie Fonseca de Oliveira, Felipe Gaia de Sousa, Suzane Lilian Beier, Adriane Pimenta da Costa-Val
Animal welfare encompasses the overall well-being of an animal, spanning both its physical and mental health, assessable through potential measurements. It stands in contrast to mistreatment, which involves actions, direct or indirect, that endanger an animal’s well-being. This study sought to appraise the factors influencing the Brazilian population’s understanding of dog welfare and mistreatment. The survey questions were adapted from the Animal Welfare Examination Protocol, utilized by veterinarians to evaluate suspected passive abuse cases in dogs. Out of 1377 responses, 1353 were valid and analyzed. Among the 19 assessed indicators, 15 demonstrated an adequate response rate surpassing 90% of all 1353 responses. However, for three questions related to comfort, a smaller yet notable percentage of responses were only minimally adequate. Moreover, in one question within the comfort assessment, 186 participants (13.74%) provided inadequate responses. This implies that these people could potentially subject animals to a state of low Animal Welfare. Lack of knowledge emerged as a potential root of passive abuse, specifically negligence. In the assessment of nutritional indicators, water supply and quality received unanimous adequate responses. In evaluating comfort perceptions, significant associations were noted between gender, dog ownership, family income, and responses regarding resting surface. Regarding health indicators, the majority responded appropriately. Female gender and dog ownership correlated with providing the appropriate response, while not owning a dog was associated with minimally adequate responses. In the context of comfort indicators, "Hitting the Dog" also demonstrated an association with gender, with females tending towards appropriate responses. Given the lack of significant correlation between educational levels and the most suitable responses, it underscores the urgency of implementing environmental education programs in schools with a focus on animal protection.by Nicodemus Songose Awarayi, Frimpong Twum, James Ben Hayfron-Acquah, Kwabena Owusu-Agyemang
This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. The model was trained and evaluated using a 10-fold cross-validation sampling approach with a learning rate of 0.001 and 200 training epochs at each instance. The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. The model recorded 94.39%, 94.92%, and 95.62% accuracies for Alzheimer’s disease versus normal controls, Alzheimer’s disease versus mild cognitive impairment, and mild cognitive impairment versus normal controls classes, respectively.Chronic diseases have a high prevalence worldwide, and patients with chronic diseases often suffer from depression, leading to a poor prognosis and a low quality of life. Metacognitive therapy is a transdiagnostic psychotherapy intervention focused on thinking patterns, with the advantages of reliable implementation effect, short intervention period and low cost. It can help patients change negative metacognition, alleviate depression symptoms, and has a higher implementation value compared with other cognitive interventions. Therefore, metacognitive therapy may be an effective way to improve the mental health of patients with chronic diseases.
CNKI, Wanfang Database, VIP Database for Chinese Technical Periodicals, Sinomed, PubMed, SCOPUS, Embase, The Cochrane Library, Web of Science and PsycINFO will be used to select the eligible studies. As a supplement, websites (eg, the Chinese Clinical Registry, ClinicalTrials.gov) will be searched and grey literature will be included. The heterogeneity and methodological quality of the eligible studies will be independently screened and extracted by two experienced reviewers. All the data synthesis and analysis (drawing forest plots, subgroup analysis and sensitive analysis) will be conducted using RevMan 5.4.1.
This article is a literature review that does not include patients’ identifiable information. Therefore, ethical approval is not required in this protocol. The findings of this systematic review and meta-analysis will be published in a peer-reviewed journal as well as presentations at relevant conferences.
CRD42023411105.
Approximately 250 million children under 5 years of age are at risk of poor development in low-income and middle-income countries. However, existing early childhood development (ECD) interventions can be expensive, labour intensive and challenging to deliver at scale. Mass media may offer an alternative approach to ECD intervention. This protocol describes the planned economic evaluation of a cluster-randomised controlled trial of a radio campaign promoting responsive caregiving and opportunities for early learning during the first 3 years of life in rural Burkina Faso (SUNRISE trial).
The economic evaluation of the SUNRISE trial will be conducted as a within-trial analysis from the provider’s perspective. Incremental costs and health outcomes of the radio campaign will be compared with standard broadcasting (ie, ‘do nothing’ comparator). All costs associated with creating and broadcasting the radio campaign during intervention start-up and implementation will be captured. The cost per child under 3 years old reached by the intervention will be calculated. Incremental cost-effectiveness ratios will be calculated for the trial’s primary outcome (ie, incremental cost per SD of cognitive gain). A cost-consequence analysis will also be presented, whereby all relevant costs and outcomes are tabulated. Finally, an analysis will be conducted to assess the equity impact of the intervention.
The SUNRISE trial has ethical approval from the ethics committees of the Ministry of Health, Burkina Faso, University College London and the London School of Hygiene and Tropical Medicine. The results of the economic evaluation will be disseminated in a peer-reviewed journal and presented at a relevant international conference.
The SUNRISE trial was registered with ClinicalTrials.gov on 19 April 2019 (identifier: NCT05335395).
Respiratory syncytial virus (RSV) is a causative virus for the common cold worldwide and can result in hospitalisations and even death in patients with high-risk conditions and older adults. However, the relationship between RSV or other incidental respiratory infections and acute exacerbations of underlying conditions has not been well investigated. The primary objective of this study is to estimate RSV prevalence, risk factors for adverse outcomes or hospitalisation and their effect on the hospital course of patients with acute respiratory symptoms admitted from emergency departments. Furthermore, we evaluate the prevalence of other respiratory viruses associated with respiratory symptoms.
We are conducting a multicentre prospective cohort study in Japan. We plan to enrol 3000 consecutive patients admitted from emergency departments with acute respiratory symptoms or signs from 1 July 2023 to 30 June 2024. A nasopharyngeal swab is obtained within 24 hours of admission and the prevalence of RSV and other respiratory viruses is measured using the FilmArray Respiratory 2.1 panel. Paired serum samples are collected from patients with suspected lower respiratory infections to measure RSV antibodies at admission and 30 days later. Information on patients’ hospital course is retrieved from the electronic medical records at discharge, death or 30 days after admission. Furthermore, information on readmission to the hospital and all-cause mortality is collected 180 days after admission. We assess the differences in clinical outcomes between patients with RSV or other respiratory viruses and those without, adjusting for baseline characteristics. Clinical outcomes include in-hospital mortality, length of hospital stay, disease progression, laboratory tests and management of respiratory symptoms or underlying conditions.
The study protocol was approved by the institutional review boards of participating hospitals. Our study reports will be published in academic journals as well as international meetings.
Globally, cardiovascular disease (CVD) remains the leading cause of death, warranting effective management and prevention measures. Risk prediction tools are indispensable for directing primary and secondary prevention strategies for CVD and are critical for estimating CVD risk. Machine learning (ML) methodologies have experienced significant advancements across numerous practical domains in recent years. Several ML and statistical models predicting CVD time-to-event outcomes have been developed. However, it is not known as to which of the two model types—ML and statistical models—have higher discrimination and calibration in this regard. Hence, this planned work aims to systematically review studies that compare ML with statistical methods in terms of their predictive abilities in the case of time-to-event data with censoring.
Original research articles published as prognostic prediction studies, which involved the development and/or validation of a prognostic model, within a peer-reviewed journal, using cohort or experimental design with at least a 12-month follow-up period will be systematically reviewed. The review process will adhere to the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist.
Ethical approval is not required for this review, as it will exclusively use data from published studies. The findings of this study will be published in an open-access journal and disseminated at scientific conferences.
CRD42023484178.
The triglyceride glucose (TyG) index has been confirmed a predictive value for type 2 diabetes mellitus (T2DM). However, no research has yet confirmed whether there is a linear correlation between the TyG index and MACCEs in DFUs. The present study aimed to delve into the association between the TyG index and the risk of MACCEs in patients with DFUs. A total of 960 inpatients with DFUs were recruited. All participants were followed up every 6 months for 11 years with a median of 83 months. According to the cut-off value of the TyG index acquired from receiver operating characteristic (ROC) analysis, the subjects were divided into two groups: low-level (<9.12, n = 480) and high-level (≥9.12, n = 480). The relationship between the TyG index and MACCEs was evaluated by the multivariable Cox regression model, restricted cubic spline (RCS) model, stratified analysis and the Kaplan–Meier survival analysis. Out of 960 participants, 271 experienced MACCEs (28.22%), of whom 79 (29.15%) died. ROC analysis got the optimal TyG index cut-off value of 9.12. Multivariable Cox regression analysis combined with the RCS model showed that the TyG index was positively associated with MACCEs in an S-shaped non-linear dose-dependent manner within the range of TyG index 7.5–9.5 (p < 0.001). The Kaplan–Meier survival analysis indicated the higher the TyG index, the greater the cumulative incidence of MACCEs (log-rank, p < 0.001). The study first confirmed an S-shaped non-linear dose-dependent positive relationship between the TyG index and the risk of MACCEs in DFUs. Consequently, lowering the TyG index level aids in improving the prognosis of patients with DFUs.
Compared to other providers, nurses spend more time with patients, but the exact quantity and nature of those interactions remain largely unknown. The purpose of this study was to characterize the interactions of nurses at the bedside using continuous surveillance over a year long period.
Nurses' time and activity at the bedside were characterized using a device that integrates the use of obfuscated computer vision in combination with a Bluetooth beacon on the nurses' identification badge to track nurses' activities at the bedside. The surveillance device (AUGi) was installed over 37 patient beds in two medical/surgical units in a major urban hospital. Forty-nine nurse users were tracked using the beacon. Data were collected 4/15/19–3/15/20. Statistics were performed to describe nurses' time and activity at the bedside.
A total of n = 408,588 interactions were analyzed over 670 shifts, with >1.5 times more interactions during day shifts (n = 247,273) compared to night shifts (n = 161,315); the mean interaction time was 3.34 s longer during nights than days (p < 0.0001). Each nurse had an average of 7.86 (standard deviation [SD] = 10.13) interactions per bed each shift and a mean total interaction time per bed of 9.39 min (SD = 14.16). On average, nurses covered 7.43 beds (SD = 4.03) per shift (day: mean = 7.80 beds/nurse/shift, SD = 3.87; night: mean = 7.07/nurse/shift, SD = 4.17). The mean time per hourly rounding (HR) was 69.5 s (SD = 98.07) and 50.1 s (SD = 56.58) for bedside shift report.
As far as we are aware, this is the first study to provide continuous surveillance of nurse activities at the bedside over a year long period, 24 h/day, 7 days/week. We detected that nurses spend less than 1 min giving report at the bedside, and this is only completed 20.7% of the time. Additionally, hourly rounding was completed only 52.9% of the time and nurses spent only 9 min total with each patient per shift. Further study is needed to detect whether there is an optimal timing or duration of interactions to improve patient outcomes.
Nursing time with the patient has been shown to improve patient outcomes but precise information about how much time nurses spend with patients has been heretofore unknown. By understanding minute-by-minute activities at the bedside over a full year, we provide a full picture of nursing activity; this can be used in the future to determine how these activities affect patient outcomes.
Conflicting evidence for the association between COVID-19 and adverse perinatal outcomes exists. This study examined the associations between maternal COVID-19 during pregnancy and adverse perinatal outcomes including preterm birth (PTB), low birth weight (LBW), small-for-gestational age (SGA), large-for-gestational age (LGA) and fetal death; as well as whether the associations differ by trimester of infection.
The study used a retrospective Mexican birth cohort from the Instituto Mexicano del Seguro Social (IMSS), Mexico, between January 2020 and November 2021.
We used the social security administrative dataset from IMSS that had COVID-19 information and linked it with the IMSS routine hospitalisation dataset, to identify deliveries in the study period with a test for SARS-CoV-2 during pregnancy.
PTB, LBW, SGA, LGA and fetal death. We used targeted maximum likelihood estimators, to quantify associations (risk ratio, RR) and CIs. We fit models for the overall COVID-19 sample, and separately for those with mild or severe disease, and by trimester of infection. Additionally, we investigated potential bias induced by missing non-tested pregnancies.
The overall sample comprised 17 340 singleton pregnancies, of which 30% tested positive. We found that those with mild COVID-19 had an RR of 0.89 (95% CI 0.80 to 0.99) for PTB and those with severe COVID-19 had an RR of 1.53 (95% CI 1.07 to 2.19) for LGA. COVID-19 in the first trimester was associated with fetal death, RR=2.36 (95% CI 1.04, 5.36). Results also demonstrate that missing non-tested pregnancies might induce bias in the associations.
In the overall sample, there was no evidence of an association between COVID-19 and adverse perinatal outcomes. However, the findings suggest that severe COVID-19 may increase the risk of some perinatal outcomes, with the first trimester potentially being a high-risk period.
by Hirokazu Okada, Atsushi Ono, Koji Tomori, Tsutomu Inoue, Norio Hanafusa, Ken Sakai, Ichiei Narita, Toshiki Moriyama, Yoshitaka Isaka, Kei Fukami, Seiji Itano, Eiichiro Kanda, Naoki Kashihara
BackgroundInformation of short-term prognosis after hemodialysis (HD) introduction is important for elderly patients with chronic kidney disease (CKD) and their families choosing a modality of renal replacement therapy. Therefore, we developed a risk score to predict early mortality in incident elderly Japanese hemodialysis patients.
Materials and methodsWe analyzed data of incident elderly HD patients from a nationwide cohort study of the Japanese Society for Dialysis Therapy Renal Data Registry (JRDR) to develop a prognostic risk score. Candidate risk factors for early death within 1 year was evaluated using multivariate logistic regression analysis. The risk score was developed by summing up points derived from parameter estimate values of independent risk factors. The association between risk score and early death was tested using Cox proportional hazards models. This risk score was validated twice by using an internal validation cohort derived from the JRDR and an external validation cohort collected for this study.
ResultsUsing the development cohort (n = 2,000), nine risk factors were retained in the risk score: older age (>85), yes = 2, no = 0; sex, male = 2, female = 0; lower body mass index (2.0 mg/dL), yes = 2, no = 0. In the internal and external validation cohorts (n = 739, 140, respectively), the medium- and high-risk groups (total score, 6 to 10 and 11 or more, respectively) showed significantly higher risk of early death than the low-risk group (total score, 0 to 5) (p Conclusion
We developed a prognostic risk score predicting early death within 1 year in incident elderly Japanese HD patients, which may help detect elderly patients with a high-risk of early death after HD introduction.
by Mina Baek, Minjae Kim, Hae In Choi, Bert Binas, Junho Cha, Kyoung Hwa Jung, Sungkyoung Choi, Young Gyu Chai
The multikinase inhibitor sorafenib is the standard first-line treatment for advanced hepatocellular carcinoma (HCC), but many patients become sorafenib-resistant (SR). This study investigated the efficacy of another kinase inhibitor, regorafenib (Rego), as a second-line treatment. We produced SR HCC cells, wherein the PI3K-Akt, TNF, cAMP, and TGF-beta signaling pathways were affected. Acute Rego treatment of these cells reversed the expression of genes involved in TGF-beta signaling but further increased the expression of genes involved in PI3K-Akt signaling. Additionally, Rego reversed the expression of genes involved in nucleosome assembly and epigenetic gene expression. Weighted gene co-expression network analysis (WGCNA) revealed four differentially expressed long non-coding RNA (DElncRNA) modules that were associated with the effectiveness of Rego on SR cells. Eleven putative DElncRNAs with distinct expression patterns were identified. We associated each module with DEmRNAs of the same pattern, thus obtaining DElncRNA/DEmRNA co-expression modules. We discuss the potential significance of each module. These findings provide insights and resources for further investigation into the potential mechanisms underlying the response of SR HCC cells to Rego.Clinical practice guideline (CPG) developers conduct systematic summaries of research evidence, providing them great capacity and ability to identify research priorities. We systematically analysed the reporting form and content of research priorities in CPGs related to knee osteoarthritis (KOA) to provide a valuable reference for guideline developers and clinicians.
A methodological literature analysis was done and the characteristics of the reporting form and the content of the research priorities identified in KOA CPGs were summarised.
Six databases (PubMed, Embase, China National Knowledge Infrastructure, VIP Database for Chinese Technical Periodicals, Wanfang and Chinese Biomedical Literature Database) were searched for CPGs published from 1 January 2017 to 4 December 2022. The official websites of 40 authoritative orthopaedic societies, rheumatology societies and guideline development organisations were additionally searched.
We included all KOA CPGs published in English or Chinese from 1 January 2017 that included at least one recommendation for KOA. We excluded duplicate publications, older versions of CPGs as well as guidance documents for guideline development.
Reviewers worked in pairs and independently screened and extracted the data. Descriptive statistics were used, and absolute frequencies and proportions of related items were calculated.
187 research priorities reported in 41 KOA CPGs were identified. 24 CPGs reported research priorities, of which 17 (41.5%) presented overall research priorities for the entire guideline rather than for specific recommendations. 110 (58.8%) research priorities were put forward due to lack of evidence. Meanwhile, more than 70% of the research priorities reflected the P (population) and I (intervention) structural elements, with 135 (72.2%) and 146 (78.1%), respectively. More than half of the research priorities (118, 63.8%) revolved around evaluating the efficacy of interventions. Research priorities primarily focused on physical activity (32, 17.3%), physical therapy (30, 16.2%), surgical therapy (27, 14.6%) and pharmacological treatment (26, 14.1%).
Research priorities reported in KOA CPGs mainly focused on evaluating non-pharmacological interventions. There exists considerable room for improvement for a comprehensive and standardised generation and reporting of research priorities in KOA CPGs.
To demonstrate how interoperable nursing care data can be used by nurses to create a more holistic understanding of the healthcare needs of multiple traumas patients with Impaired Physical Mobility. By proposing and validating linkages for the nursing diagnosis of Impaired Physical Mobility in multiple trauma patients by mapping to the Nursing Outcomes Classification (NOC) and Nursing Interventions Classification (NIC) equivalent terms using free-text nursing documentation.
A descriptive cross-sectional design, combining quantitative analysis of interoperable data sets and the Kappa's coefficient score with qualitative insights from cross-mapping methodology and nursing professionals' consensus.
Cross-mapping methodology was conducted in a Brazilian Level 1 Trauma Center using de-identified records of adult patients with a confirmed medical diagnosis of multiple traumas and Impaired Physical Mobility (a nursing diagnosis). The hospital nursing free-text records were mapped to NANDA-I, NIC, NOC and NNN linkages were identified. The data records were retrieved for admissions from September to October 2020 and involved medical and nursing records. Three expert nurses evaluated the cross-mapping and linkage results using a 4-point Likert-type scale and Kappa's coefficient.
The de-identified records of 44 patients were evaluated and then were mapped to three NOCs related to nurses care planning: (0001) Endurance; (0204) Immobility Consequences: Physiological, and (0208) Mobility and 13 interventions and 32 interrelated activities: (6486) Environmental Management: Safety; (0840) Positioning; (3200) Aspiration Precautions; (1400) Pain Management; (0940) Traction/Immobilization Care; (3540) Pressure Ulcer Prevention; (3584) Skincare: Topical Treatment; (1100) Nutrition Management; (3660) Wound Care; (1804) Self-Care Assistance: Toileting; (1801) Self-Care Assistance: Bathing/Hygiene; (4130) Fluid Monitoring; and (4200) Intravenous Therapy. The final version of the constructed NNN Linkages identified 37 NOCs and 41 NICs.
These valid NNN linkages for patients with multiple traumas can serve as a valuable resource that enables nurses, who face multiple time constraints, to make informed decisions efficiently. This approach of using evidence-based linkages like the one developed in this research holds high potential for improving patient's safety and outcomes.
In this study, there was no direct involvement of patients, service users, caregivers or public members in the design, conduct, analysis and interpretation of data or preparation of the manuscript. The study focused solely on analysing existing de-identified medical and nursing records to propose and validate linkages for nursing diagnoses.
FreshRSS 