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Chen H, Zhou L, Yan M, Li C, Liu B, Liu X, Shan W, Guo Y, Zhang Z, Wang L. Classification of Laboratory Test Outcomes for Maintenance Hemodialysis Patients Using Cellular Bioelectrical Measurements. Int J Gen Med 2024; 17:3733-3743. [PMID: 39219668 PMCID: PMC11365496 DOI: 10.2147/ijgm.s471161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 08/23/2024] [Indexed: 09/04/2024] Open
Abstract
Background End-stage kidney disease (ESKD) patients often face complications like anemia, malnutrition, and cardiovascular issues. Serological tests, which are uncomfortable and not frequently conducted, assist in medical assessments. A non-invasive, convenient method for determining these test results would be beneficial for monitoring patient health. Objective This study develops machine learning models to estimate key serological test results using non-invasive cellular bioelectrical impedance measurements, a routine procedure for ESKD patients. Methods The study employs two machine learning models, Support Vector Machine (SVM) and Random Forest (RF), to determine key serological tests by classifying cell bioelectrical indicators. Data from 688 patients, comprising 3,872 biochemical-bioelectrical records, were used for model validation. Results Both SVM and RF models effectively categorized key serological results (albumin, phosphorus, parathyroid hormone) into low, normal, and high. RF generally outperformed SVM, except in classifying calcium levels in women. Conclusion The machine learning models effectively classified serological test results for maintenance hemodialysis patients using cellular bioelectrical indicators, therefore can help in making judgments about physicochemical indicators using electrical signals, thereby reducing the frequency of serological tests.
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Affiliation(s)
- Hanzhi Chen
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Leting Zhou
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Meilin Yan
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Cheng Li
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Bin Liu
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Xiaobin Liu
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Weiwei Shan
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Ya Guo
- Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, Jiangsu, 214122, People’s Republic of China
| | - Zhijian Zhang
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
| | - Liang Wang
- Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, 214000, People’s Republic of China
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Zarubin NY, Kharenko EN, Bredikhina OV, Lavrukhina EV, Rysakova KS, Novikov VY, Leonov GE, Vakhrushev IV, Zolotarev KV, Mikhailov AN, Mikhailova MV. An Isotonic Drink Containing Pacific Cod ( Gadus macrocephalus) Processing Waste Collagen Hydrolysate for Bone and Cartilage Health. Mar Drugs 2024; 22:202. [PMID: 38786592 PMCID: PMC11122821 DOI: 10.3390/md22050202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 04/25/2024] [Accepted: 04/26/2024] [Indexed: 05/25/2024] Open
Abstract
Malnutrition is one of the major factors of bone and cartilage disorders. Pacific cod (Gadus macrocephalus) processing waste is a cheap and highly promising source of bioactive substances, including collagen-derived peptides and amino acids, for bone and cartilage structure stabilization. The addition of these substances to a functional drink is one of the ways to achieve their fast intestinal absorption. Collagen hydrolysate was obtained via enzymatic hydrolysis, ultrafiltration, freeze-drying, and grinding to powder. The lyophilized hydrolysate was a light gray powder with high protein content (>90%), including collagen (about 85% of total protein) and a complete set of essential and non-essential amino acids. The hydrolysate had no observed adverse effect on human mesenchymal stem cell morphology, viability, or proliferation. The hydrolysate was applicable as a protein food supply or a structure-forming food component due to the presence of collagen fiber fragments. An isotonic fitness drink (osmolality 298.1 ± 2.1 mOsm/L) containing hydrolysate and vitamin C as a cofactor in collagen biosynthesis was prepared. The addition of the hydrolysate did not adversely affect its organoleptic parameters. The production of such functional foods and drinks is one of the beneficial ways of fish processing waste utilization.
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Affiliation(s)
- Nikita Yu. Zarubin
- Russian Federal Research Institute of Fisheries and Oceanography, 19 Okruzhnoy Proyezd, 105187 Moscow, Russia; (N.Y.Z.); (E.N.K.); (O.V.B.); (E.V.L.); (K.S.R.); (V.Y.N.)
- Polar Branch, Russian Federal Research Institute of Fisheries and Oceanography, 6 Akademik Knipovich Str., 183038 Murmansk, Russia
| | - Elena N. Kharenko
- Russian Federal Research Institute of Fisheries and Oceanography, 19 Okruzhnoy Proyezd, 105187 Moscow, Russia; (N.Y.Z.); (E.N.K.); (O.V.B.); (E.V.L.); (K.S.R.); (V.Y.N.)
- Polar Branch, Russian Federal Research Institute of Fisheries and Oceanography, 6 Akademik Knipovich Str., 183038 Murmansk, Russia
| | - Olga V. Bredikhina
- Russian Federal Research Institute of Fisheries and Oceanography, 19 Okruzhnoy Proyezd, 105187 Moscow, Russia; (N.Y.Z.); (E.N.K.); (O.V.B.); (E.V.L.); (K.S.R.); (V.Y.N.)
- Polar Branch, Russian Federal Research Institute of Fisheries and Oceanography, 6 Akademik Knipovich Str., 183038 Murmansk, Russia
| | - Elizaveta V. Lavrukhina
- Russian Federal Research Institute of Fisheries and Oceanography, 19 Okruzhnoy Proyezd, 105187 Moscow, Russia; (N.Y.Z.); (E.N.K.); (O.V.B.); (E.V.L.); (K.S.R.); (V.Y.N.)
- Polar Branch, Russian Federal Research Institute of Fisheries and Oceanography, 6 Akademik Knipovich Str., 183038 Murmansk, Russia
| | - Kira S. Rysakova
- Russian Federal Research Institute of Fisheries and Oceanography, 19 Okruzhnoy Proyezd, 105187 Moscow, Russia; (N.Y.Z.); (E.N.K.); (O.V.B.); (E.V.L.); (K.S.R.); (V.Y.N.)
- Polar Branch, Russian Federal Research Institute of Fisheries and Oceanography, 6 Akademik Knipovich Str., 183038 Murmansk, Russia
| | - Vitaly Yu. Novikov
- Russian Federal Research Institute of Fisheries and Oceanography, 19 Okruzhnoy Proyezd, 105187 Moscow, Russia; (N.Y.Z.); (E.N.K.); (O.V.B.); (E.V.L.); (K.S.R.); (V.Y.N.)
- Polar Branch, Russian Federal Research Institute of Fisheries and Oceanography, 6 Akademik Knipovich Str., 183038 Murmansk, Russia
| | - Georgy E. Leonov
- Institute of Biomedical Chemistry, 10 Pogodinskaya Str., 119121 Moscow, Russia; (G.E.L.); (I.V.V.); (A.N.M.); (M.V.M.)
| | - Igor V. Vakhrushev
- Institute of Biomedical Chemistry, 10 Pogodinskaya Str., 119121 Moscow, Russia; (G.E.L.); (I.V.V.); (A.N.M.); (M.V.M.)
| | - Konstantin V. Zolotarev
- Institute of Biomedical Chemistry, 10 Pogodinskaya Str., 119121 Moscow, Russia; (G.E.L.); (I.V.V.); (A.N.M.); (M.V.M.)
| | - Anton N. Mikhailov
- Institute of Biomedical Chemistry, 10 Pogodinskaya Str., 119121 Moscow, Russia; (G.E.L.); (I.V.V.); (A.N.M.); (M.V.M.)
| | - Marina V. Mikhailova
- Institute of Biomedical Chemistry, 10 Pogodinskaya Str., 119121 Moscow, Russia; (G.E.L.); (I.V.V.); (A.N.M.); (M.V.M.)
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Lopes MMGD, Sousa IM, Queiroz SA, Bezerra MRO, Gonzalez MC, Fayh APT. Bioelectrical impedance vector analysis is different according to the comorbidity burden in post-acute myocardial infarction. Nutr Clin Pract 2024; 39:450-458. [PMID: 37740504 DOI: 10.1002/ncp.11074] [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: 04/27/2023] [Revised: 08/01/2023] [Accepted: 08/20/2023] [Indexed: 09/24/2023] Open
Abstract
BACKGROUND The prevalence of a high comorbidity burden in patients who suffered an acute myocardial infarction (AMI) is increasing with the aging population, and the nutrition status also may be a predictor of clinical outcomes for these patients. This study aimed to investigate the relationship between the comorbidity burden and the characteristics of the bioelectrical impedance vector analysis (BIVA) in patients post-AMI. METHODS This prospective observational cohort study was conducted with adult patients who were hospitalized with AMI. Pre-existing comorbidities were assessed by the Charlson comorbidity index (CCI) adjusted by age, and anthropometric and BIVA characteristics were evaluated after the hemodynamic stabilization. All patients were followed-up until hospital discharge, and their length of stay was observed. RESULTS A total of 184 patients (75% were males; mean age, 60.2 ± 12.3 years) were included. The most common comorbidities were dyslipidemia (73.9%), hypertension (62%), and type 2 diabetes (34.2%). A higher CCI (≥3) was associated with sex (P = 0.008) and age (P < 0.001). Regarding BIVA, statistically significant differences were detected between sex (P < 0.001), age (P < 0.001), and CCI (P = 0.003), with longer vectors in female, older adults, and those with CCI ≥ 3. CONCLUSION Finding a relationship between BIVA and CCI suggests the first identified coherent differences, potentially correlated with diseases, representing a first contribution to support this type of assessment. Therefore, with BIVA, healthcare professionals may monitor abnormalities and adopt preventive nutrition care measures on patients post-AMI to improve their clinical status.
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Affiliation(s)
- Marcia M G D Lopes
- Department of Nutrition, Center for Health Sciences, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
- Applied Sciences to Women's Health, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Iasmin M Sousa
- Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Sandra Azevedo Queiroz
- Department of Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Mara R O Bezerra
- Department of Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Maria Cristina Gonzalez
- Department of Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Ana Paula Trussardi Fayh
- Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
- Department of Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
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Xiang T, Zhou L, Fu P, Yan XP, Zeng XQ. Value of quantitative ultrasound and bioelectrical impedance analysis in detecting low bone mineral density in hemodialysis. Ren Fail 2021; 43:1198-1204. [PMID: 34369272 PMCID: PMC8354166 DOI: 10.1080/0886022x.2021.1959347] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 07/19/2021] [Accepted: 07/19/2021] [Indexed: 02/08/2023] Open
Abstract
INTRODUCTION Patients on maintenance hemodialysis (MHD) are highly predisposed to low bone mineral density (BMD). This study aims to assess the value of quantitative ultrasound (QUS), bioelectrical impedance analysis (BIA), and their combination in detecting high-risk patients for low BMD in MHD. METHODS Patients' BMD of the total hip, femoral neck, and lumbar spine were measured using dual-energy X-ray absorptiometry (DXA). Bone mineral content (BMC) was assessed using BIA. Calcaneal BMD was measured using QUS. Patients with a T-score of ≤-2.5 were recorded as 'low BMD.' RESULTS Overall, 93 subjects (62.37% female; mean age, 60.8 ± 16.2 years) were included in this cross-sectional study; approximately 36.56% met the 'low BMD' criteria. QUS-T score predicted low BMD with an area under the curve (AUC) value of 0.738, sensitivity of 70.59%, and specificity of 76.27%. The AUC for low BMD diagnosis using the BMC index (BMCI) measured through BIA was 0.679 (sensitivity, 91.18%; specificity, 38.98%). On the other hand, the combination of QUS-T score and BMCI yielded a higher AUC value of 0.762 with an improved specificity of 88.14%. Compared with the QUS and BIA alone, the net reclassification improvement (NRI) of the combination model increased by 47.16% (p = 0.022) and 78.36% (p < 0.0001), respectively. Integrated discrimination improvement (IDI) increased by 5.25% (p = 0.043) and 9.99% (p = 0.003), respectively. QUS-T score and BMCI were related to BMD independently assessed by DXA. CONCLUSION The combination of QUS and BIA is effective in screening for low BMD among MHD patients.
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Affiliation(s)
- Ting Xiang
- Division of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Li Zhou
- Division of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Ping Fu
- Division of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xue-Ping Yan
- Division of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiao-Qing Zeng
- Nutrition Department, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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Santos BC, Ferreira LG, Ribeiro HS, Correia MITD, Lima AS, Penna FGCE, Anastácio LR. Bioelectrical impedance vector analysis in patients on the waiting list for liver transplant: Associated factors and prognostic effects. Nutrition 2021; 94:111528. [PMID: 34891107 DOI: 10.1016/j.nut.2021.111528] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/30/2021] [Accepted: 10/20/2021] [Indexed: 12/28/2022]
Abstract
OBJECTIVES The aim of this study was to assess patients on the waiting list for liver transplant (LTx) according to bioelectrical impedance vector analysis (BIVA), as well as to verify the association between the placement of the vectors on the graph with clinical outcomes and identify the predictors to vector placement in quadrant 4 (Q4; indicating more hydration and less cellularity). METHODS This was a retrospective observational study including 129 patients ≥20 y of age awaiting LTx. Patients' nutritional status was assessed by using different tools, including single-frequency bioelectrical impedance analysis and the Subjective Global Assessment (SGA). Clinical data were registered. The BIVA was evaluated by comparing the individual vectors plotted for all patients to the tolerance ellipses of 50%, 75%, and 95% of the reference healthy population. The quadrant of the vector for each patient was registered. RESULTS The majority of the vectors were placed in Q1 (n = 54; 41.9%) and Q4 (n = 39; 30.2%). The presence of ascites or edema (hazard ratio [HR], 2.43; 95% confidence interval [CI], 1.15-5.12; P = 0.019) and the BIVA vector placed in Q4 in any ellipse (HR, 2.10; 95% CI, 1.07-4.09; P = 0.029) were independent predictors for mortality on the waiting list or ≤1 y after LTx. BIVA was not associated with longer hospital length of stay. The predictors of vector placement in Q4 were higher age, malnutrition according to SGA, and presence of ascites or edema. CONCLUSION Patients on the waiting list for LTx with BIVA vectors placed in Q4, in the 50%, 75%, or 95% tolerance ellipses, presented a worse prognosis.
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Affiliation(s)
- Bárbara Chaves Santos
- Food Science Graduate Program, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Lívia Garcia Ferreira
- Nutrition and Health Graduate Program, Universidade Federal de Lavras, Lavras, Minas Gerais, Brazil
| | - Helem Sena Ribeiro
- Surgery Graduate Program, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Maria Isabel Toulson Davisson Correia
- Surgery Graduate Program, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; Alfa Institute of Gastroenterology, Hospital das Clínicas-Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Agnaldo Soares Lima
- Surgery Graduate Program, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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