Prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease: systematic review and critical appraisal

OBJECTIVE: To map and assess prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease (COPD). DESIGN: Systematic review. DATA SOURCES: PubMed until November 2018 and hand searched references from eligible articles. ELIGIBILITY CRITERIA FOR STUDY SELECTION: Studies developing, validating, or updating a prediction model in COPD patients and focusing on any potential clinical outcome. RESULTS: The systematic search yielded 228 eligible articles, describing the development of 408 prognostic models, the external validation of 38 models, and the validation of 20 prognostic models derived for diseases other than COPD. The 408 prognostic models were developed in three clinical settings: outpatients (n=239; 59%), patients admitted to hospital (n=155; 38%), and patients attending the emergency department (n=14; 3%). Among the 408 prognostic models, the most prevalent endpoints were mortality (n=209; 51%), risk for acute exacerbation of COPD (n=42; 10%), and risk for readmission after the index hospital admission (n=36; 9%). Overall, the most commonly used predictors were age (n=166; 41%), forced expiratory volume in one second (n=85; 21%), sex (n=74; 18%), body mass index (n=66; 16%), and smoking (n=65; 16%). Of the 408 prognostic models, 100 (25%) were internally validated and 91 (23%) examined the calibration of the developed model. For 286 (70%) models a model presentation was not available, and only 56 (14%) models were presented through the full equation. Model discrimination using the C statistic was available for 311 (76%) models. 38 models were externally validated, but in only 12 of these was the validation performed by a fully independent team. Only seven prognostic models with an overall low risk of bias according to PROBAST were identified. These models were ADO, B-AE-D, B-AE-D-C, extended ADO, updated ADO, updated BODE, and a model developed by Bertens et al. A meta-analysis of C statistics was performed for 12 prognostic models, and the summary estimates ranged from 0.611 to 0.769. CONCLUSIONS: This study constitutes a detailed mapping and assessment of the prognostic models for outcome prediction in COPD patients. The findings indicate several methodological pitfalls in their development and a low rate of external validation. Future research should focus on the improvement of existing models through update and external validation, as well as the assessment of the safety, clinical effectiveness, and cost effectiveness of the application of these prognostic models in clinical practice through impact studies. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017069247

Prognostic factors for adverse outcomes in patients with COVID-19: a field-wide systematic review and meta-analysis

INTRODUCTION: The individual prognostic factors for COVID-19 are unclear. For this reason, we aimed to present a state-of-the-art systematic review and meta-analysis on the prognostic factors for adverse outcomes in COVID-19 patients. METHODS: We systematically reviewed PubMed from January 1, 2020 to July 26, 2020 to identify non-overlapping studies examining the association of any prognostic factor with any adverse outcome in patients with COVID-19. Random-effects meta-analysis was performed, and between-study heterogeneity was quantified using I2 metric. Presence of small-study effects was assessed by applying the Egger's regression test. RESULTS: We identified 428 eligible articles, which were used in a total of 263 meta-analyses examining the association of 91 unique prognostic factors with 11 outcomes. Angiotensin-converting enzyme inhibitors, obstructive sleep apnea, pharyngalgia, history of venous thromboembolism, sex, coronary heart disease, cancer, chronic liver disease, chronic obstructive pulmonary disease, dementia, any immunosuppressive medication, peripheral arterial disease, rheumatological disease and smoking were associated with at least one outcome and had >1000 events, p-value <0.005, I2 <50%, 95% prediction interval excluding the null value, and absence of small-study effects in the respective meta-analysis. The risk of bias assessment using the Quality In Prognosis Studies tool indicated high risk of bias in 302 of 428 articles for study participation, 389 articles for adjustment for other prognostic factors, and 396 articles for statistical analysis and reporting. CONCLUSIONS: Our findings could be used for prognostic model building and guide patients' selection for randomised clinical trials

Real-Time Object Detection on High-Voltage Powerlines Using an Unmanned Aerial Vehicle (UAV)

Unmanned Aerial Vehicles (UAVs) are gaining significant scientific interest in critical infrastructure inspection due to their flexibility, cost-effectiveness and advanced computer vision capabilities. This research focuses on high-voltage powerline surveillance, where automatic inspection is a priority for grid companies to prevent power failures. To address the need for real-time detection with limited computational power, we evaluate the recently developed object detection algorithm, YOLOvS. We propose a fine-tuned model trained on a custom dataset to detect key components, i. e. towers, insulators and conductors. The proposed method achieves an overall accuracy rate of 82.3% ([email protected]) and enables real-time detection, demonstrating its suitability for inspection tasks and visual-based navigation. Our model was also tested on a custom-built quadcopter with an Nvidia Jetson Nano (4GB) on board, achieving a frame rate of 33fps on live video under real environmental conditions

Exploring the negotiation thesis application among ski resort tourists: a segmentation approach

The negotiation thesis offers a framework for understanding the participation decision making of tourists. Unlike previous studies that investigate the causal relationship between constraints and tourists’ revisit intention, this study identified distinct segments of ski tourist based on the relative strength of constraints experienced and then investigated their decision-making process across a sample of 1,348 tourists of ski resorts. Chi-Squared Automated Interaction Detection (CHAID) analysis revealed that the decision making process regarding intention to revisit a ski destination varies between highly versus less constrained ski tourists, indicating different relative strengths of interpersonal, intrapersonal and structural constraints and different interactions among them when predicting revisit intention. On a practical basis, albeit the vast majority of participants were willing to repeat its visit, we offer customized per segment recommendations on increasing frequency of visitation and spending levels

Genetic risk for alzheimer disease is distinct from genetic risk for amyloid deposition

OBJECTIVE: Alzheimer disease (AD) is the most common form of dementia and is responsible for a huge and growing health care burden in the developed and developing world. The polygenic risk score (PRS) approach has shown 75 to 84% prediction accuracy of identifying individuals with AD risk. // METHODS: In this study, we tested the prediction accuracy of AD, mild cognitive impairment (MCI), and amyloid deposition risks with PRS, including and excluding APOE genotypes in a large publicly available dataset with extensive phenotypic data, the Alzheimer's Disease Neuroimaging Initiative cohort. Among MCI individuals with amyloid-positive status, we examined PRS prediction accuracy in those who converted to AD. In addition, we divided polygenic risk score by biological pathways and tested them independently for distinguishing between AD, MCI, and amyloid deposition. // RESULTS: We found that AD and MCI are predicted by both APOE genotype and PRS (area under the curve [AUC] = 0.82% and 68%, respectively). Amyloid deposition is predicted by APOE only (AUC = 79%). Further progression to AD of individuals with MCI and amyloid-positive status is predicted by PRS over and above APOE (AUC = 67%). In pathway-specific PRS analyses, the protein-lipid complex has the strongest association with AD and amyloid deposition even when genes in the APOE region were removed (p = 0.0055 and p = 0.0079, respectively). // INTERPRETATION: The results showed different pattern of APOE contribution in PRS risk predictions of AD/MCI and amyloid deposition. Our study suggests that APOE mostly contributes to amyloid accumulation and the PRS affects risk of further conversion to AD

A genetic link between risk for Alzheimer's disease and severe COVID-19 outcomes via the OAS1 gene

Recently, we reported oligoadenylate synthetase 1 (OAS1) contributed to the risk of Alzheimer's disease, by its enrichment in transcriptional networks expressed by microglia. However, the function of OAS1 within microglia was not known. Using genotyping from 1313 individuals with sporadic Alzheimer's disease and 1234 control individuals, we confirm the OAS1 variant, rs1131454, is associated with increased risk for Alzheimer's disease. The same OAS1 locus has been recently associated with severe coronavirus disease 2019 (COVID-19) outcomes, linking risk for both diseases. The single nucleotide polymorphisms rs1131454(A) and rs4766676(T) are associated with Alzheimer's disease, and rs10735079(A) and rs6489867(T) are associated with severe COVID-19, where the risk alleles are linked with decreased OAS1 expression. Analysing single-cell RNA-sequencing data of myeloid cells from Alzheimer's disease and COVID-19 patients, we identify co-expression networks containing interferon (IFN)-responsive genes, including OAS1, which are significantly upregulated with age and both diseases. In human induced pluripotent stem cell-derived microglia with lowered OAS1 expression, we show exaggerated production of TNF-α with IFN-γ stimulation, indicating OAS1 is required to limit the pro-inflammatory response of myeloid cells. Collectively, our data support a link between genetic risk for Alzheimer's disease and susceptibility to critical illness with COVID-19 centred on OAS1, a finding with potential implications for future treatments of Alzheimer's disease and COVID-19, and development of biomarkers to track disease progression

In-hospital informal caregivers' needs as perceived by themselves and by the nursing staff in Northern Greece: A descriptive study

<p>Abstract</p> <p>Background</p> <p>Informal care is common in many countries, especially in Greece, where families provide care in hospitals. Health education and informational needs are important factors for family members which are often underestimated by nursing staff. The aim of this study was to compare the perceptions of the nurses and the in-hospital informal caregivers about the in-hospital informal caregivers' knowledge and informational needs, as well as the factors that influence these perceptions.</p> <p>Methods</p> <p>This was a non-experimental descriptive study conducted in three general hospitals in Greece. The sample consisted of 320 nurses and 370 in-hospital informal caregivers who completed questionnaires. Descriptive statistics were analyzed using t-tests; group comparisons were conducted using ANOVA.</p> <p>Results</p> <p>The score of the questionnaire for health education and informational needs was significantly greater for informal caregivers (57.1 ± 6.9 and 26.6 ± 2.8) than for nurses (53.4 ± 5.7 and 22.4 ± 3.1) (p < 0.001). For the nursing staff, the factors that influence the informational needs of patients' caregivers were <it>level of education </it>and <it>working experience</it>, while for the caregivers the <it>level of education </it>was independently associated with the score for the health education needs. Finally, <it>age, marital status</it>, and <it>level of education </it>of informal caregivers' were independently associated with informational needs.</p> <p>Conclusions</p> <p>The in-hospital informal caregivers perceived that they have more educational and informational needs than the nurses did. The findings of this study also show that the nursing staff has to identify the needs of in-hospital informal caregivers in order to be able to meet these needs.</p

Validation of the Organizational Culture Assessment Instrument

Organizational culture is a commonly studied area in industrial/organizational psychology due to its important role in workplace behaviour, cognitions, and outcomes. Jung et al.'s [1] review of the psychometric properties of organizational culture measurement instruments noted many instruments have limited validation data despite frequent use in both theoretical and applied situations. The Organizational Culture Assessment Instrument (OCAI) has had conflicting data regarding its psychometric properties, particularly regarding its factor structure. Our study examined the factor structure and criterion validity of the OCAI using robust analysis methods on data gathered from 328 (females = 226, males = 102) Australian employees. Confirmatory factor analysis supported a four factor structure of the OCAI for both ideal and current organizational culture perspectives. Current organizational culture data demonstrated expected reciprocally-opposed relationships between three of the four OCAI factors and the outcome variable of job satisfaction but ideal culture data did not, thus indicating possible weak criterion validity when the OCAI is used to assess ideal culture. Based on the mixed evidence regarding the measure's properties, further examination of the factor structure and broad validity of the measure is encouraged