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Shi Q, Xu J, Zeng L, Lu Z, Chen Y. A nomogram for predicting short-term mortality in ICU patients with coexisting chronic obstructive pulmonary disease and congestive heart failure. Respir Med 2024; 234:107803. [PMID: 39251097 DOI: 10.1016/j.rmed.2024.107803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 08/29/2024] [Accepted: 09/07/2024] [Indexed: 09/11/2024]
Abstract
OBJECTIVE This study aimed to develop and validate a nomogram for predicting 28-day and 90-day mortality in intensive care unit (ICU) patients who have chronic obstructive pulmonary disease (COPD) coexisting with congestive heart failure (CHF). METHODS An extensive analysis was conducted on clinical data from the Medical Information Mart for Intensive Care IV database, covering patients over 18 years old with both COPD and CHF, who were were first-time ICU admissions between 2008 and 2019. The least absolute shrinkage and selection operator (LASSO) regression method was employed to screen clinical features, with the final model being optimized using backward stepwise regression guided by the Akaike Information Criterion (AIC) to construct the nomogram. The predictive model's discrimination and clinical applicability were evaluated via receiver operating characteristic (ROC) curves, calibration curves, the C-index, and decision curve analysi s (DCA). RESULTS This analysis was comprised of a total of 1948 patients. Patients were separated into developing and validation cohorts in a 7:3 ratio, with similar baseline characteristics between the two groups. The ICU mortality rates for the developing and verification cohorts were 20.8 % and 19.5 % at 28 days, respectively, and 29.4 % and 28.3 % at 90 days, respectively. The clinical characteristics retained by the backward stepwise regression include age, weight, systolic blood pressure (SBP), respiratory rate (RR), oxygen saturation (SpO2), red blood cell distribution width (RDW), lactate, partial thrombosis time (PTT), race, marital status, type 2 diabetes mellitus (T2DM), malignant cancer, acute kidney failure (AKF), pneumonia, immunosuppressive drugs, antiplatelet agents, vasoactive agents, acute physiology score III (APS III), Oxford acute severity of illness score (OASIS), and Charlson comorbidity index (CCI). We developed two separate models by assigning weighted scores to each independent risk factor: nomogram A excludes CCI but includes age, T2DM, and malignant cancer, while nomogram B includes only CCI, without age, T2DM, and malignant cancer. Based on the results of the AUC and C-index, this study selected nomogram A, which demonstrated better predictive performance, for subsequent validation. The calibration curve, C-index, and DCA results indicate that nomogram A has good accuracy in predicting short-term mortality and demonstrates better discriminative ability than commonly used clinical scoring systems, making it more suitable for clinical application. CONCLUSION The nomogram developed in this study offers an effective assessment of short-term mortality risk for ICU patients with COPD and CHF, proving to be a superior tool for predicting their short-term prognosis.
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Affiliation(s)
- Qiangqiang Shi
- Department of Respiratory Medicine, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, China.
| | - Jiali Xu
- Department of Respiratory Medicine, Changxing People's Hospital, Huzhou, China.
| | - Longhuan Zeng
- Department of High Dependency Unit (Respiratory Support), Hangzhou Geriatric Hospital, Hangzhou, China.
| | - Ziyi Lu
- Department of Cardiology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, China.
| | - Yang Chen
- Department of High Dependency Unit (Respiratory Support), Hangzhou Geriatric Hospital, Hangzhou, China.
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Liu T, Joshu CE, Lu J, Prizment A, Chatterjee N, Wu L, Platz EA. Validation of candidate protein biomarkers previously identified by genetic instruments for prostate cancer risk: A prospective cohort analysis of directly measured protein levels in the ARIC study. Prostate 2024. [PMID: 39148211 DOI: 10.1002/pros.24774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 07/02/2024] [Accepted: 07/29/2024] [Indexed: 08/17/2024]
Abstract
BACKGROUND Multiple novel protein biomarkers have been shown to be associated with prostate cancer risk using genetic instruments. This study aimed to externally validate the associations of 30 genetically predicted candidate proteins with prostate cancer risk using aptamer-based levels in US Black and White men in the Atherosclerosis Risk in Communities (ARIC) study. Plasma protein levels were previously measured by SomaScan® using the blood collected in 1990-1992. METHODS Among 4864 eligible participants, we ascertained 667 first primary prostate cancer cases through 2015. Hazard ratios (HRs) of prostate cancer and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression for tertiles of each protein. We adjusted for age, race, and other risk factors. RESULTS Of the 30 proteins and considering a nominal p trend < 0.05, two were positively associated with prostate cancer risk-RF1ML (tertile 3 vs. 1: HR = 1.23; 95% CI 1.02-1.48; p trend = 0.037) and TPST1 (1.28, 95% CI 1.06-1.55; p trend = 0.0087); two were inversely associated-ATF6A (HR = 0.80, 95% CI 0.65-0.98; p trend = 0.028) and SPINT2 (HR = 0.74, 95% CI 0.61-0.90; p trend = 0.0025). One protein, KDEL2, which was nonlinearly associated (test-for-linearity: p < 0.01) showed a statistically significant lower risk in the second tertile (HR = 0.79, 95% CI 0.65-0.95). Of these five, four proteins-ATF6A, KDEL2, RF1ML, and TPST1-were consistent in the direction of association with the discovery studies. CONCLUSION This study validated some pre-diagnostic protein biomarkers of the risk of prostate cancer.
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Affiliation(s)
- Tanxin Liu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Corinne E Joshu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland, USA
| | - Jiayun Lu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Anna Prizment
- Division of Hematology, Oncology and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
- University of Minnesota Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Nilanjan Chatterjee
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Lang Wu
- University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland, USA
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Evans DS, Young D, Tanaka T, Basisty N, Bandinelli S, Ferrucci L, Campisi J, Schilling B. Proteomic Analysis of the Senescence-Associated Secretory Phenotype: GDF-15, IGFBP-2, and Cystatin-C Are Associated With Multiple Aging Traits. J Gerontol A Biol Sci Med Sci 2024; 79:glad265. [PMID: 37982669 PMCID: PMC10876076 DOI: 10.1093/gerona/glad265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Indexed: 11/21/2023] Open
Abstract
Cellular senescence, a hallmark of aging, results in a senescence-associated secretory phenotype (SASP) with an increased production of proinflammatory cytokines, growth factors, and proteases. Evidence from nonhuman models demonstrates that SASP contributes to tissue dysfunction and pathological effects of aging. However, there are relatively few human studies on the relationship between SASP and aging-related health outcomes. Proteins from the SASP Atlas were measured in plasma using aptamer-based proteomics (SomaLogic). Regression models were used to identify SASP protein associations with aging-related traits representing multiple aspects of physiology in 1 201 participants from 2 human cohort studies (BLSA/GESTALT and InCHIANTI). Traits examined were fasting glucose, C-reactive protein, interleukin-6, alkaline phosphatase, blood urea nitrogen, albumin, red blood cell distribution width, waist circumference, systolic and diastolic blood pressure, gait speed, and grip strength. Study results were combined with a fixed-effect inverse-variance weighted meta-analysis. In the meta-analysis, 28 of 77 SASP proteins were significantly associated with age. Of the 28 age-associated SASP proteins, 18 were significantly associated with 1 or more clinical traits, and 7 SASP proteins were significantly associated with 3 or more traits. Growth/differentiation factor 15, Insulin-like growth factor-binding protein 2, and Cystatin-C showed significant associations with inflammatory markers and measures of physical function (grip strength or gait speed). These results support the relevance of SASP proteins to human aging, identify specific traits that are potentially affected by SASP, and prioritize specific SASP proteins for their utility as biomarkers of human aging.
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Affiliation(s)
- Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, California, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
| | - Danielle Young
- California Pacific Medical Center Research Institute, San Francisco, California, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
| | - Toshiko Tanaka
- Longitudinal Studies Section, Translational Gerontology Branch, NIA, NIH, Baltimore, Maryland, USA
| | - Nathan Basisty
- Longitudinal Studies Section, Translational Gerontology Branch, NIA, NIH, Baltimore, Maryland, USA
| | | | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, NIA, NIH, Baltimore, Maryland, USA
| | - Judith Campisi
- Buck Institute for Research on Aging, Novato, California, USA
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Li S, Zhang W, Liang X. Red blood cell distribution width and mortality risk in critically ill cardiovascular patients. Heliyon 2023; 9:e22225. [PMID: 38045131 PMCID: PMC10692801 DOI: 10.1016/j.heliyon.2023.e22225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 10/30/2023] [Accepted: 11/07/2023] [Indexed: 12/05/2023] Open
Abstract
Background The association between red blood cell distribution width (RDW) and mortality risk in critically ill cardiovascular patients has not been well studied. Objective To examine the association between RDW and 30-day all-cause and cause-specific mortality in critically ill cardiovascular patients. Methods This cohort study included 47,266 patients from the eICU database. RDW was categorized as <13.0 %, 13.0-13.4 %, 13.5-13.9 %, 14.0-14.4 %, 14.5-14.9 %, ≥15.0 %. Logistic regression model was used to estimate adjusted odds ratios (ORs), and log-linear regression model was used to examine absolute rate differences (RDs) in mortality risk. Cubic spline curve was used to explore the nonlinear association between changes in RDW and mortality. Results A graded association between higher RDW and incremental risk of death was observed. Compared with RDW of <13.0 %, the adjusted odds ratios for all-cause mortality were 1.29 (95 % CI, 1.10 to 1.53) for RDW of 13.5-13.9 %, 1.57 (95 % CI, 1.33 to 1.85) for RDW of 14.0-14.4 %, 1.94 (95 % CI, 1.64 to 2.29) for RDW of 14.5-15.0 %, and 3.15 (95 % CI, 2.74 to 3.63) for RDW of ≥15.0 %. The absolute rate differences for RDW of 13.5-13.9 %, 14.0-14.4 %, 14.5-14.9 %, and ≥15.0 % indicated an additional 6, 13, 14, and 40 deaths per 1000 patients, respectively. RDW was associated with most, but not all, cause-specific deaths. Conclusion RDW was strongly associated with all-cause mortality and most cause-specific mortality in critically ill cardiovascular patients. These findings underscore the importance of this readily available hematologic indicator in mortality risk stratification.
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Affiliation(s)
- Shan Li
- Department of Cardiology, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Wei Zhang
- Department of Cardiology, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Xiao Liang
- Department of Cardiology, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
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Tan M, Liu B, You R, Huang Q, Lin L, Cai D, Yang R, Li D, Huang H. Red Blood Cell Distribution Width as a Potential Valuable Survival Predictor in Hepatitis B Virus-related Hepatocellular Carcinoma. Int J Med Sci 2023; 20:976-984. [PMID: 37324183 PMCID: PMC10266047 DOI: 10.7150/ijms.79619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/13/2023] [Indexed: 06/17/2023] Open
Abstract
Objectives: Red blood cell distribution width (RDW) is a widely used clinical parameter recently deployed in predicting various cancers. This study aimed to evaluate the prognostic value of RDW in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Methods: We conducted a retrospective study of 745 patients with HBV-related HCC, 253 patients with chronic hepatitis B (CHB), and 256 healthy individuals to compare their hematological parameters and analyze their RDW levels. Potential risk factors for long-term all-cause mortality in patients with HBV-related HCC were predicted using Multivariate Cox regression. A nomogram was generated, and its performance was evaluated. Results: The RDW of patients with HBV-related HCC was significantly higher than that of those with CHB and healthy controls. In the former, splenomegaly, liver cirrhosis, larger tumor diameter, multiple tumor number, portal vein tumor thrombus, and lymphatic or distant metastasis were significantly increased, and the later the Child-Pugh grade and Barcelona clinic liver cancer stage, the higher the RDW. Furthermore, multivariate Cox regression analysis identified RDW as an independent risk factor for predicting long-term all-cause mortality in patients with HBV-related HCC. Finally, we successfully generated a nomogram incorporating RDW and validated its predictive ability. Conclusions: RDW is a potentially valuable hematological marker for predicting the survival and prognosis of patients with HBV-related HCC. The nomogram incorporating RDW can be used as an effective tool to plan the individualized treatment of such patients.
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Affiliation(s)
- Maoqing Tan
- Central Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China
| | - Bang Liu
- Department of Hepatobiliary Disease, Fuzong Clinical Medical College of Fujian Medical University (900TH Hospital of Joint Logistics Support Force), Fuzhou, Fujian, 350025, China
| | - Ruolan You
- Central Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China
| | - Qiqi Huang
- Central Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China
| | - Liyan Lin
- Central Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China
| | - Danni Cai
- Central Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China
| | - Rong Yang
- Follow-up Center of Union Hospital Affiliated to Fujian Medical University, Fuzhou, Fujian, 350001, China
| | - Dongliang Li
- Department of Hepatobiliary Disease, Fuzong Clinical Medical College of Fujian Medical University (900TH Hospital of Joint Logistics Support Force), Fuzhou, Fujian, 350025, China
| | - Huifang Huang
- Central Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China
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Di Lorenzo B, Pau MC, Zinellu E, Mangoni AA, Paliogiannis P, Pirina P, Fois AG, Carru C, Zinellu A. Association between Red Blood Cell Distribution Width and Obstructive Sleep Apnea Syndrome: A Systematic Review and Meta-Analysis. J Clin Med 2023; 12:jcm12093302. [PMID: 37176740 PMCID: PMC10179738 DOI: 10.3390/jcm12093302] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 04/26/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023] Open
Abstract
Although polysomnography is the gold standard method to diagnose obstructive sleep apnea syndrome (OSAS), there is an ongoing quest for simpler and relatively inexpensive biomarkers of disease presence and severity. To address this issue, we conducted a systematic review of the potential diagnostic role of the red blood cell distribution width (RDW), a routine hematological parameter of red blood cell volume variability, in OSAS. A total of 1478 articles were initially identified in the databases PubMed, Web of Science, Scopus, Embase, and Google Scholar, from their inception to February 2023, and 20 were selected for final analysis. The RDW was significantly higher in OSAS than in non-OSAS subjects (SMD = 0.44, 95% CI 0.20 to 0.67, p < 0.001; low certainty of evidence). In univariate meta-regression, the mean oxygen saturation (SpO2) was significantly associated with the effect size. No significant between-group differences were observed in subgroup analyses. Notably, in OSAS subjects, the RDW SMD progressively increased with disease severity. In conclusion, these results suggest that the RDW is a promising biomarker of OSAS (PROSPERO registration number: CRD42023398047).
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Affiliation(s)
- Biagio Di Lorenzo
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
| | - Maria Carmina Pau
- Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy
| | - Elisabetta Zinellu
- Clinical and Interventional Pulmonology, University Hospital of Sassari (AOU), 07100 Sassari, Italy
| | - Arduino A Mangoni
- Discipline of Clinical Pharmacology, College of Medicine and Public Health, Flinders University, Bedfor Park, SA 5042, Australia
- Department of Clinical Pharmacology, Flinders Medical Centre, Southern Adelaide Local Health Network, Bedford Park, SA 5042, Australia
| | | | - Pietro Pirina
- Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy
- Clinical and Interventional Pulmonology, University Hospital of Sassari (AOU), 07100 Sassari, Italy
| | - Alessandro G Fois
- Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy
- Clinical and Interventional Pulmonology, University Hospital of Sassari (AOU), 07100 Sassari, Italy
| | - Ciriaco Carru
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
- Quality Control Unit, University Hospital of Sassari (AOU), 07100 Sassari, Italy
| | - Angelo Zinellu
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
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Liu M, Zhou J, Xi Q, Liang Y, Li H, Liang P, Guo Y, Liu M, Temuqile T, Yang L, Zuo Y. A computational framework of routine test data for the cost-effective chronic disease prediction. Brief Bioinform 2023; 24:7034465. [PMID: 36772998 DOI: 10.1093/bib/bbad054] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 01/04/2023] [Accepted: 01/26/2023] [Indexed: 02/12/2023] Open
Abstract
Chronic diseases, because of insidious onset and long latent period, have become the major global disease burden. However, the current chronic disease diagnosis methods based on genetic markers or imaging analysis are challenging to promote completely due to high costs and cannot reach universality and popularization. This study analyzed massive data from routine blood and biochemical test of 32 448 patients and developed a novel framework for cost-effective chronic disease prediction with high accuracy (AUC 87.32%). Based on the best-performing XGBoost algorithm, 20 classification models were further constructed for 17 types of chronic diseases, including 9 types of cancers, 5 types of cardiovascular diseases and 3 types of mental illness. The highest accuracy of the model was 90.13% for cardia cancer, and the lowest was 76.38% for rectal cancer. The model interpretation with the SHAP algorithm showed that CREA, R-CV, GLU and NEUT% might be important indices to identify the most chronic diseases. PDW and R-CV are also discovered to be crucial indices in classifying the three types of chronic diseases (cardiovascular disease, cancer and mental illness). In addition, R-CV has a higher specificity for cancer, ALP for cardiovascular disease and GLU for mental illness. The association between chronic diseases was further revealed. At last, we build a user-friendly explainable machine-learning-based clinical decision support system (DisPioneer: http://bioinfor.imu.edu.cn/dispioneer) to assist in predicting, classifying and treating chronic diseases. This cost-effective work with simple blood tests will benefit more people and motivate clinical implementation and further investigation of chronic diseases prevention and surveillance program.
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Affiliation(s)
- Mingzhu Liu
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
- Inner Mongolia International Mongolian Hospital, Hohhot 010065, China
| | - Jian Zhou
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
| | - Qilemuge Xi
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Yuchao Liang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
| | - Haicheng Li
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
| | - Pengfei Liang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Yuting Guo
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Ming Liu
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Temuqile Temuqile
- Inner Mongolia International Mongolian Hospital, Hohhot 010065, China
| | - Lei Yang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
| | - Yongchun Zuo
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot 010021, China
- Digital College, Inner Mongolia Intelligent Union Big Data Academy, Inner Mongolia Wesure Date Technology Co., Ltd., Hohhot 010010, China
- Inner Mongolia International Mongolian Hospital, Hohhot 010065, China
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Bizjak DA, John L, Matits L, Uhl A, Schulz SVW, Schellenberg J, Peifer J, Bloch W, Weiß M, Grüner B, Bracht H, Steinacker JM, Grau M. SARS-CoV-2 Altered Hemorheological and Hematological Parameters during One-Month Observation Period in Critically Ill COVID-19 Patients. Int J Mol Sci 2022; 23:15332. [PMID: 36499657 PMCID: PMC9735540 DOI: 10.3390/ijms232315332] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 11/24/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
Hematological and hemorheological parameters are known to be altered in COVID-19; however, the value of combined monitoring in order to deduce disease severity is only scarcely examined. A total of 44 acute SARS-CoV-2-infected patients (aCOV) and 44 age-matched healthy controls (Con) were included. Blood of aCOV was sampled at admission (T0), and at day 2 (T2), day 5 (T5), day 10 (T10), and day 30 (T30) while blood of Con was only sampled once. Inter- and intra-group differences were calculated for hematological and hemorheological parameters. Except for mean cellular volume and mean cellular hemoglobin, all blood cell parameters were significantly different between aCOV and Con. During the acute disease state (T0-T5), hematological and hemorheological parameters were highly altered in aCOV; in particular, anemic conditions and increased immune cell response/inflammation, oxidative/nitrosative stress, decreased deformability, as well as increased aggregation, were observed. During treatment and convalescence until T30, almost all abnormal values of aCOV improved towards Con values. During the acute state of the COVID-19 disease, the hematological, as well as the hemorheological system, show fast and potentially pathological changes that might contribute to the progression of the disease, but changes appear to be largely reversible after four weeks. Measuring RBC deformability and aggregation, as well as oxidative stress induction, may be helpful in monitoring critically ill COVID-19 patients.
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Affiliation(s)
| | - Lucas John
- Division of Sports and Rehabilitation Medicine, University Hospital Ulm, 89075 Ulm, Germany
| | - Lynn Matits
- Division of Sports and Rehabilitation Medicine, University Hospital Ulm, 89075 Ulm, Germany
- Clinical & Biological Psychology, Institute of Psychology and Education, Ulm University, 89081 Ulm, Germany
| | - Alisa Uhl
- Division of Sports and Rehabilitation Medicine, University Hospital Ulm, 89075 Ulm, Germany
| | | | - Jana Schellenberg
- Division of Sports and Rehabilitation Medicine, University Hospital Ulm, 89075 Ulm, Germany
| | - Johannes Peifer
- Central Emergency Services, University Hospital Ulm, 89081 Ulm, Germany
| | - Wilhelm Bloch
- Institute of Cardiovascular Research and Sports Medicine, Molecular and Cellular Sports Medicine, German Sport University Cologne, 50933 Cologne, Germany
| | - Manfred Weiß
- Clinic for Anaesthesiology and Intensive Care Medicine, University Hospital Medical School, 89081 Ulm, Germany
| | - Beate Grüner
- Department of Internal Medicine III, Division of Infectious Diseases, University Hospital Ulm, 89081 Ulm, Germany
| | - Hendrik Bracht
- Central Emergency Services, University Hospital Ulm, 89081 Ulm, Germany
| | | | - Marijke Grau
- Institute of Cardiovascular Research and Sports Medicine, Molecular and Cellular Sports Medicine, German Sport University Cologne, 50933 Cologne, Germany
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Zinellu A, Mangoni AA. The Emerging Clinical Significance of the Red Cell Distribution Width as a Biomarker in Chronic Obstructive Pulmonary Disease: A Systematic Review. J Clin Med 2022; 11:jcm11195642. [PMID: 36233510 PMCID: PMC9571455 DOI: 10.3390/jcm11195642] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/22/2022] [Accepted: 09/22/2022] [Indexed: 11/16/2022] Open
Abstract
There is an intense focus on the identification of novel biomarkers of chronic obstructive pulmonary disease (COPD) to enhance clinical decisions in patients with stable disease and acute exacerbations (AECOPD). Though several local (airway) and circulatory inflammatory biomarkers have been proposed, emerging evidence also suggests a potential role for routine haematological parameters, e.g., the red cell distribution width (RDW). We conducted a systematic literature search in PubMed, Web of Science, and Scopus, from inception to April 2022, for articles investigating the diagnostic and prognostic role of the RDW in stable COPD and AECOPD. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Significant associations between the RDW and the presence and severity of disease, outcomes (mortality, hospital readmission), and other relevant clinical parameters (right heart failure, pulmonary arterial hypertension) were reported in 13 out of 16 studies in stable COPD (low risk of bias in 11 studies), and 17 out of 21 studies of AECOPD (low risk of bias in 11 studies). Pending further research, our systematic review suggests that the RDW might be useful, singly or in combination with other parameters, for the diagnosis and risk stratification of patients with stable COPD and AECOPD (PROSPERO registration number: CRD42022348304).
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Affiliation(s)
- Angelo Zinellu
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
| | - Arduino A. Mangoni
- Discipline of Clinical Pharmacology, College of Medicine and Public Health, Flinders University, Sturt Road, Bedford Park, SA 5042, Australia
- Department of Clinical Pharmacology, Flinders Medical Centre, Southern Adelaide Local Health Network, Flinders Drive, Bedford Park, SA 5042, Australia
- Correspondence:
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Li D, Li S, Xia Z, Cao J, Zhang J, Chen B, Zhang X, Zhu W, Fang J, Liu Q, Hua W. Prognostic significance of pretreatment red blood cell distribution width in primary diffuse large B-cell lymphoma of the central nervous system for 3P medical approaches in multiple cohorts. EPMA J 2022; 13:499-517. [PMID: 36061828 PMCID: PMC9437163 DOI: 10.1007/s13167-022-00290-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 07/04/2022] [Indexed: 12/08/2022]
Abstract
Background/aims Predicting the clinical outcomes of primary diffuse large B-cell lymphoma of the central nervous system (PCNS-DLBCL) to methotrexate-based combination immunochemotherapy treatment in advance and therefore administering the tailored treatment to the individual is consistent with the principle of predictive, preventive, and personalized medicine (PPPM/3PM). The red blood cell distribution width (RDW) has been reported to be associated with the clinical outcomes of multiple cancer. However, its prognostic role in PCNS-DLBCL is yet to be evaluated. Therefore, we aimed to effectively stratify PCNS-DLBCL patients with different prognosis in advance and early identify the patients who were appropriate to methotrexate-based combination immunochemotherapy based on the pretreatment level of RDW and a clinical prognostic model. Methods A prospective-retrospective, multi-cohort study was conducted from 2010 to 2020. We evaluated RDW in 179 patients (retrospective discovery cohorts of Huashan Center and Renji Center and prospective validation cohort of Cancer Center) with PCNS-DLBCL treated with methotrexate-based combination immunochemotherapy. A generalized additive model with locally estimated scatterplot smoothing was used to identify the relationship between pretreatment RDW levels and clinical outcomes. The high vs low risk of RDW combined with MSKCC score was determined by a minimal P-value approach. The clinical outcomes in different groups were then investigated. Results The pretreatment RDW showed a U-shaped relationship with the risk of overall survival (OS, P = 0.047). The low RDW (< 12.6) and high RDW (> 13.4) groups showed significantly worse OS (P < 0.05) and progression-free survival (PFS; P < 0.05) than the median group (13.4 > RDW > 12.6) in the discovery and validation cohort, respectively. RDW could predict the clinical outcomes successfully. In the discovery cohort, RDW achieved the area under the receiver operating characteristic curve (AUC) of 0.9206 in predicting the clinical outcomes, and the predictive value (AUC = 0.7177) of RDW was verified in the validation cohort. In addition, RDW combined with MSKCC predictive model can distinguish clinical outcomes with the AUC of 0.8348 for OS and 0.8125 for PFS. Compared with the RDW and MSKCC prognosis variables, the RDW combined with MSKCC scores better identified a subgroup of patients with favorable long-term survival in the validation cohort (P < 0.001). RDW combined MSKCC score remained to be independently associated with clinical outcomes by multivariable analysis. Conclusions Based on the pretreatment RDW and MSKCC scores, a novel predictive tool was established to stratify PCNS-DLBCL patients with different prognosis effectively. The predictive model developed accordingly is promising to judge the response of PCNS-DLBCL to methotrexate-based combination immunochemotherapy treatment. Thus, hematologists and oncologists could tailor and adjust therapeutic modalities by monitoring RDW in a prospective rather than the reactive manner, which could save medical expenditures and is a key concept in 3PM. In brief, RDW combined with MSKCC model could serve as an important tool for predicting the response to different treatment and the clinical outcomes for PCNS-DLBCL, which could conform with the principles of predictive, preventive, and personalized medicine. Supplementary Information The online version contains supplementary material available at 10.1007/s13167-022-00290-5.
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Affiliation(s)
- Danhui Li
- Department of Pathology, Renji Hospital, School of Medicine, Shanghai JiaoTong University, No. 160 PuJian Road, Shanghai, 200127 China
| | - Shengjie Li
- Department of Neurosurgery, Huashan Hospital, Fudan University, No. 12 Wulumuqi Road, Shanghai, 200040 China
- Institute of Neurosurgery, Fudan University, Shanghai, 200040 China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040 China
- Department of Clinical Laboratory, EENT Hospital, Shanghai Medical College, Fudan University, Shanghai, 200032 China
| | - Zuguang Xia
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032 China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032 China
| | - Jiazhen Cao
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032 China
- Department of Clinical Laboratory, Fudan University Shanghai Cancer Center, Shanghai, 200032 China
| | - Jinsen Zhang
- Department of Neurosurgery, Huashan Hospital, Fudan University, No. 12 Wulumuqi Road, Shanghai, 200040 China
- Institute of Neurosurgery, Fudan University, Shanghai, 200040 China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040 China
| | - Bobin Chen
- Department of Hematology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Xin Zhang
- Department of Neurosurgery, Huashan Hospital, Fudan University, No. 12 Wulumuqi Road, Shanghai, 200040 China
- Institute of Neurosurgery, Fudan University, Shanghai, 200040 China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040 China
| | - Wei Zhu
- Department of Neurosurgery, Huashan Hospital, Fudan University, No. 12 Wulumuqi Road, Shanghai, 200040 China
- Institute of Neurosurgery, Fudan University, Shanghai, 200040 China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040 China
| | - Jianchen Fang
- Department of Pathology, Renji Hospital, School of Medicine, Shanghai JiaoTong University, No. 160 PuJian Road, Shanghai, 200127 China
| | - Qiang Liu
- Department of Pathology, Renji Hospital, School of Medicine, Shanghai JiaoTong University, No. 160 PuJian Road, Shanghai, 200127 China
| | - Wei Hua
- Department of Neurosurgery, Huashan Hospital, Fudan University, No. 12 Wulumuqi Road, Shanghai, 200040 China
- Institute of Neurosurgery, Fudan University, Shanghai, 200040 China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200040 China
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Ananthaseshan S, Bojakowski K, Sacharczuk M, Poznanski P, Skiba DS, Prahl Wittberg L, McKenzie J, Szkulmowska A, Berg N, Andziak P, Menkens H, Wojtkowski M, Religa D, Lundell F, Guzik T, Gaciong Z, Religa P. Red blood cell distribution width is associated with increased interactions of blood cells with vascular wall. Sci Rep 2022; 12:13676. [PMID: 35953533 PMCID: PMC9366818 DOI: 10.1038/s41598-022-17847-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 08/02/2022] [Indexed: 11/09/2022] Open
Abstract
The mechanism underlying the association between elevated red cell distribution width (RDW) and poor prognosis in variety of diseases is unknown although many researchers consider RDW a marker of inflammation. We hypothesized that RDW directly affects intravascular hemodynamics, interactions between circulating cells and vessel wall, inducing local changes predisposing to atherothrombosis. We applied different human and animal models to verify our hypothesis. Carotid plaques harvested from patients with high RDW had increased expression of genes and proteins associated with accelerated atherosclerosis as compared to subjects with low RDW. In microfluidic channels samples of blood from high RDW subjects showed flow pattern facilitating direct interaction with vessel wall. Flow pattern was also dependent on RDW value in mouse carotid arteries analyzed with Magnetic Resonance Imaging. In different mouse models of elevated RDW accelerated development of atherosclerotic lesions in aortas was observed. Therefore, comprehensive biological, fluid physics and optics studies showed that variation of red blood cells size measured by RDW results in increased interactions between vascular wall and circulating morphotic elements which contribute to vascular pathology.
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Affiliation(s)
| | - Krzysztof Bojakowski
- 2nd Vascular Surgery and Angiology Department, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Mariusz Sacharczuk
- Department of Internal Medicine, Hypertension and Vascular Diseases, Medical University of Warsaw, 1a Banacha Street, 02-097, Warsaw, Poland.,Department of Experimental Genomics, Institute of Genetics and Animal Biotechnology, Polish Academy of Sciences, Jastrzebiec, Poland
| | - Piotr Poznanski
- Department of Experimental Genomics, Institute of Genetics and Animal Biotechnology, Polish Academy of Sciences, Jastrzebiec, Poland
| | - Dominik S Skiba
- Department of Experimental Genomics, Institute of Genetics and Animal Biotechnology, Polish Academy of Sciences, Jastrzebiec, Poland
| | | | - Jordan McKenzie
- KTH Mechanics, Royal Institute of Technology, Stockholm, Sweden
| | | | - Niclas Berg
- KTH Mechanics, Royal Institute of Technology, Stockholm, Sweden
| | - Piotr Andziak
- 2nd Vascular Surgery and Angiology Department, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - Hanna Menkens
- Department of Medicine, Solna, Karolinska Institute, Stockholm, Sweden
| | | | | | - Fredrik Lundell
- KTH Mechanics, Royal Institute of Technology, Stockholm, Sweden
| | - Tomasz Guzik
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Zbigniew Gaciong
- Department of Internal Medicine, Hypertension and Vascular Diseases, Medical University of Warsaw, 1a Banacha Street, 02-097, Warsaw, Poland.
| | - Piotr Religa
- Department of Medicine, Solna, Karolinska Institute, Stockholm, Sweden.,Department of Internal Medicine, Hypertension and Vascular Diseases, Medical University of Warsaw, 1a Banacha Street, 02-097, Warsaw, Poland
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