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      Prognostic Value of Blood Urea Nitrogen to Serum Albumin Ratio in Intensive Care Unit Patients with Lung Cancer

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          Abstract

          Background

          We aimed to evaluate the prognostic ability of blood urea nitrogen (BUN) to serum albumin ratio (BAR) to predict in-hospital mortality in patients with lung cancer in the intensive care unit (ICU).

          Methods

          Medical Information Mart for Intensive Care IV (MIMIC-IV v1.0) database was used to identify patients who were diagnosed with lung cancer. The primary outcome was in-hospital mortality. Multivariate COX regression was used to investigate the association between BAR and in-hospital mortality and propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were also used to ensure the robustness of our findings. eICU-CRD database (validation cohort) was also applied to validate our findings.

          Results

          The optimal cut-off value for BAR was 6.8mg/g. Among 1202 patients who were diagnosed with lung cancer, 287 high-BAR group (≥6.8mg/g) patients and 287 low-BAR group (<6.8mg/g) patients, who had similar propensity scores were included in this study. After matching, the high-BAR group had significantly higher in-hospital mortality (hazard ratio, HR, 2.24, 95% confidence index, 95% CI, 1.57–3.19, P<0.001) even after adjustment for confounding factors. Moreover, the performance of BAR was superior to that of BUN and serum albumin alone and could add net benefit in predicting in-hospital mortality. Those results were further confirmed in the validation cohort.

          Conclusion

          As an easily accessible and cost-effective parameter, BAR could serve as a good prognostic predictor for lung cancer patients in ICU.

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          Most cited references43

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          The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).

          Definitions of sepsis and septic shock were last revised in 2001. Considerable advances have since been made into the pathobiology (changes in organ function, morphology, cell biology, biochemistry, immunology, and circulation), management, and epidemiology of sepsis, suggesting the need for reexamination.
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            Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

            Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms. ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms. Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyo's ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm. These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.
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              Lung Cancer 2020

              Despite advances in our understanding of risk, development, immunologic control, and treatment options for lung cancer, it remains the leading cause of cancer death. Tobacco smoking remains the predominant risk factor for lung cancer development. Nontobacco risk factors include environmental and occupational exposures, chronic lung disease, lung infections, and lifestyle factors. Because tobacco remains the leading risk factor for lung cancer, disease prevention is focused on smoking avoidance and cessation. Other prevention measures include healthy diet choices and maintaining a physically active lifestyle. Future work should focus on smoking cessation campaigns and better understanding disease development and treatment strategies in nonsmokers.
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                Author and article information

                Journal
                Int J Gen Med
                Int J Gen Med
                ijgm
                International Journal of General Medicine
                Dove
                1178-7074
                28 October 2021
                2021
                : 14
                : 7349-7359
                Affiliations
                [1 ]Department of Oncology, The Second Affiliated Hospital of Jianghan University , Wuhan, Hubei, People’s Republic of China
                [2 ]Department of Hepatopancreatobiliary Surgery, Sinopharm Dongfeng General Hospital, Hubei University of Medicine , Wuhan, Hubei, People’s Republic of China
                [3 ]Department of Intensive Care Unit, The Second Affiliated Hospital of Jianghan University , Wuhan, Hubei, People’s Republic of China
                [4 ]Department of Diagnostics, JiangHan University , Wuhan, Hubei, People’s Republic of China
                Author notes
                Correspondence: Xiulan Peng Department of Oncology, The Fifth Hospital of Wuhan, The Second Affiliated Hospital of Jianghan University , 122 Xianzheng Road, Wuhan, Hubei, 430050, People’s Republic of China Tel +86027-84830120 Email pengxlwh@163.com
                [*]

                These authors contributed equally to this work

                Article
                337822
                10.2147/IJGM.S337822
                8560134
                34737629
                2b638370-944e-47e0-9be0-0fb2421fa02e
                © 2021 Peng et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 07 September 2021
                : 11 October 2021
                Page count
                Figures: 4, Tables: 8, References: 42, Pages: 11
                Funding
                Funded by: Wuhan Municipal Health Commission;
                This study was supported by Wuhan Municipal Health Commission (No: WX21D42).
                Categories
                Original Research

                Medicine
                blood urea nitrogen to serum albumin ratio,lung cancer,intensive care unit,medical information mart for intensive care,eicu-crd,prognosis

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