PubMed İndeksli Yayın Koleksiyonu

Usefulness of novel Martin/Hopkins and Sampson equations over Friedewald equation in cardiology outpatients: A CVSCORE-TR substudy

2023-01-28T12:17:26Z

Usefulness of novel Martin/Hopkins and Sampson equations over Friedewald equation in cardiology outpatients: A CVSCORE-TR substudy Dinç Asarcıklı, Lale; Kış, Mehmet; Güvenç, Tolga Sinan; Tosun, Veysel; Acar, Burak; Avcı Demir, Fulya; Zoghi, Mehdi Background and aims The Friedewald equation (LDL-Cf) is known to produce inaccurate estimations of low-density lipoprotein cholesterol (LDL-C) when triglycerides are high (>400 mg/dL) or LDL-C is low (<70 mg/dL). The Martin/Hopkins (LDL-Cmh) and Sampson (LDL-Cs) equations were developed to overcome these limitations, but few data are available to assess whether these equations offer incremental usefulness over LDL-Cf. Our aim was to understand whether there was any incremental usefulness of novel equations on decisions regarding patient management. Methods Four thousand one hundred and ninety-six cardiology patients who were included in a multicentre registry database were analysed. Each patient was assigned to a cardiovascular risk class using the SCORE (Systematic COronary Risk Evaluation) algorithm, and relevant European guidelines were used to assess LDL-C targets. Results Compared with LDL-Cmh and LDL-Cs, LDL-Cf was able to correctly identify 96.9%-98.08% of patients as within or outside the LDL-C target, respectively, and 1.95%-2.8% of patients were falsely identified as being within the LDL-C target. Kappa coefficients for agreement between LDL-Cf vs LDL-Cmh and LDL-Cf vs LDL-Cs were 0.868 and 0.918 (P < .001). For patients not on cholesterol-lowering drugs, the decision to initiate treatment would be different in 1.2%-1.8% of cases if LDL-Cs or LDL-Cmh were used, respectively. For those already on cholesterol-lowering drugs, decisions regarding treatment intensification would be different in 1.5%-2.4% of cases if LDL-Cs or LDL-Cmh were used. Conclusions In most cardiology outpatients, the Friedewald equation has excellent agreement with the novel Martin/Hopkins and Sampson equations, and treatment decisions should not change in most patients.

Embedding of atoms into the nanopore sites of the C6N6 and C6N8 porous carbon nitride monolayers with tunable electronic properties

2023-01-28T12:23:30Z

Embedding of atoms into the nanopore sites of the C6N6 and C6N8 porous carbon nitride monolayers with tunable electronic properties Bafekry, Asadollah; Stampfl, Catherine; Akgenç, Berna; Mortazavi, Bohayra; Ghergherehchi, Mitra; Ch V Nguyen Using first-principles calculations, we study the effect of embedding various atoms into the nanopore sites of both C6N6 and C6N8 monolayers. Our results indicate that the embedded atoms significantly affect the electronic and magnetic properties of C6N6 and C6N8 monolayers and lead to extraordinary and multifarious electronic properties, such as metallic, half-metallic, spin-glass semiconductor and dilute-magnetic semiconductor behaviour. Our results reveal that the H atom concentration dramatically affects the C6N6 monolayer. On increasing the H coverage, the impurity states also increase due to H atoms around the Fermi-level. C6N6 shows metallic character when the H atom concentration reaches 6.25%. Moreover, the effect of charge on the electronic properties of both Cr@C6N6 and C@C6N8 is also studied. Cr@C6N6 is a ferromagnetic metal with a magnetic moment of 2.40 mu(B), and when 0.2 electrons are added and removed, it remains a ferromagnetic metal with a magnetic moment of 2.57 and 2.77 mu(B), respectively. Interestingly, one can observe a semi-metal, in which the VBM and CBM in both spin channels touch each other near the Fermi-level. C@C6N8 is a semiconductor with a nontrivial band gap. When 0.2 electrons are removed, it remains metallic, and under excess electronic charge, it exhibits half-metallic behaviour.

The reliability and validity of the Turkish version of the postdialysis fatigue scale

2023-01-28T12:23:26Z

The reliability and validity of the Turkish version of the postdialysis fatigue scale Özen, Nurten; Sayılan, Aylin Aydın; Ozkaptan, Bilge Bal; Sousa, Clemente Neves; Unver, Vesile Aim Haemodialysis (HD) commonly leads to postdialysis fatigue (PDF) and, thus, worsens the quality of life and the clinical outcomes. The aim of this study was to translate, linguistically validate and determine the psychometric properties of the Postdialysis Fatigue Scale for Turkish patients with HD. Study Design A methodological study. Methods The standard lingual translation and validation methods for the initial translation of the PDF Scale and then assessed the psychometric properties of reliability and validity of the translated scale. Visual analogue scale (VAS) and Piper Fatigue Scale were used to assess concurrent and construct validity. In addition, postdialysis recovery time was used it as an indirect measurement method for PDF. Results A total of 93 patients participated in the study. The Cronbach's alpha coefficient of PDF was 0.773. There was a statistically significant relationship between the test and retest scores (ICC: 0.973; P < .001). PDF Scale was acceptable with 11 items. There was a positive correlation with a statistically significant relationship was present between the PDF scores and Piper Fatigue Scale (r = .488; P < .001) and VAS score (r = .656; P < .001). There was a statistically significant positive correlation between the PDF Scale and the postdialysis recovery time (r = .270; P = .009), Conclusion The study results have shown that the Turkish form of the PDF Scale is a valid and reliable tool in patients undergoing HD treatment. Postdialysis recovery time may be used as an indirect measurement method to evaluate PDF.

Application of machine learning to the prediction of postoperative sepsis after appendectomy

2023-01-28T12:23:28Z

Application of machine learning to the prediction of postoperative sepsis after appendectomy Bunn, Corinne; Kulshrestha, Sujay; Boyda, Jason; Balasubramanian, Neelam; Birch, Steven; Karabayır, İbrahim; Akbilgiç, Oğuz Background: We applied various machine learning algorithms to a large national dataset to model the risk of postoperative sepsis after appendectomy to evaluate utility of such methods and identify factors associated with postoperative sepsis in these patients. Methods: The National Surgery Quality Improvement Program database was used to identify patients undergoing appendectomy between 2005 and 2017. Logistic regression, support vector machines, random forest decision trees, and extreme gradient boosting machines were used to model the occurrence of postoperative sepsis. Results: In the study, 223,214 appendectomies were identified; 2,143 (0.96%) were indicated as having postoperative sepsis. Logistic regression (area under the curve 0.70; 95% confidence interval, 0.68-0.73), random forest decision trees (area under the curve 0.70; 95% confidence interval, 0.68-0.73), and extreme gradient boosting (area under the curve 0.70; 95% confidence interval, 0.68-0.73) afforded similar performance, while support vector machines (area under the curve 0.51; 95% confidence interval, 0.50-0.52) had worse performance. Variable importance analyses identified preoperative congestive heart failure, transfusion, and acute renal failure as predictors of postoperative sepsis. Conclusion: Machine learning methods can be used to predict the development of sepsis after appendectomy with moderate accuracy. Such predictive modeling has potential to ultimately allow for preoperative recognition of patients at risk for developing postoperative sepsis after appendectomy thus facilitating early intervention and reducing morbidity. (c) 2020 Elsevier Inc. All rights reserved.