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Technology/Device
Comparison of Laser and Conventional Lancing Devices for Blood Glucose Measurement Conformance and Patient Satisfaction in Diabetes Mellitus
Jung A Kim, Min Jeong Park, Eyun Song, Eun Roh, So Young Park, Da Young Lee, Jaeyoung Kim, Ji Hee Yu, Ji A Seo, Kyung Mook Choi, Sei Hyun Baik, Hye Jin Yoo, Nan Hee Kim
Diabetes Metab J. 2022;46(6):936-940.   Published online March 30, 2022
DOI: https://doi.org/10.4093/dmj.2021.0293
  • 12,092 View
  • 324 Download
  • 6 Web of Science
  • 6 Crossref
AbstractAbstract PDFPubReader   ePub   
Self-monitoring of capillary blood glucose is important for controlling diabetes. Recently, a laser lancing device (LMT-1000) that can collect capillary blood without skin puncture was developed. We enrolled 150 patients with type 1 or 2 diabetes mellitus. Blood sampling was performed on the same finger on each hand using the LMT-1000 or a conventional lancet. The primary outcome was correlation between glucose values using the LMT-1000 and that using a lancet. And we compared the pain and satisfaction of the procedures. The capillary blood sampling success rates with the LMT-1000 and lancet were 99.3% and 100%, respectively. There was a positive correlation (r=0.974, P<0.001) between mean blood glucose levels in the LMT-1000 (175.8±63.0 mg/dL) and conventional lancet samples (172.5±63.6 mg/dL). LMT-1000 reduced puncture pain by 75.0% and increased satisfaction by 80.0% compared to a lancet. We demonstrated considerable consistency in blood glucose measurements between samples from the LMT-1000 and a lancet, but improved satisfaction and clinically significant pain reduction were observed with the LMT-1000 compared to those with a lancet.

Citations

Citations to this article as recorded by  
  • Laser-Assisted Self-Monitoring of Blood Glucose: Analytical Performance, Clinical Accuracy, and Usability of the HandyRay-Glu System
    Minsup Lim, JunMin Lee, Ji A Seo, Sun-Young Ko
    Diagnostics.2026; 16(11): 1700.     CrossRef
  • Clinical effectiveness and safety of laser lancing for heel puncture in preterm infants: a randomized crossover non-inferiority trial
    Chul Kyu Yun, Hye Won Cho, Eui Kyung Choi, Jaeyoung Kim, Hyung Jin Kim, Byung Chul Park, Byung Min Choi
    Journal of Perinatology.2026;[Epub]     CrossRef
  • Pain-Related Responses in Preterm Babies Using Automated and Laser Heel-Lancing Devices
    Hea Jin Lee, Myoung Soo Kim, Mi Lim Chung
    Creative Nursing.2025; 31(2): 190.     CrossRef
  • Capillary blood glucose testing by paramedics
    Pete Gregory
    Journal of Paramedic Practice.2025; 17(11): 446.     CrossRef
  • Comparison between a laser-lancing device and automatic incision lancet for capillary blood sampling from the heel of newborn infants: a randomized feasibility trial
    Chul Kyu Yun, Eui Kyung Choi, Hyung Jin Kim, Jaeyoung Kim, Byung Cheol Park, Kyuhee Park, Byung Min Choi
    Journal of Perinatology.2024; 44(8): 1193.     CrossRef
  • Comparison of laser and traditional lancing devices for capillary blood sampling in patients with diabetes mellitus and high bleeding risk
    Min Jeong Park, Soon Young Hwang, Ahreum Jang, Soo Yeon Jang, Eyun Song, So Young Park, Da Young Lee, Jaeyoung Kim, Byung Cheol Park, Ji Hee Yu, Ji A Seo, Kyung Mook Choi, Sei Hyun Baik, Hye Jin Yoo, Nan Hee Kim
    Lasers in Medical Science.2024;[Epub]     CrossRef
Review
Cardiovascular Risk/Epidemiology
Article image
Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes
Min Jeong Park, Kyung Mook Choi
Diabetes Metab J. 2022;46(1):49-62.   Published online January 27, 2022
DOI: https://doi.org/10.4093/dmj.2021.0316
  • 14,297 View
  • 299 Download
  • 17 Web of Science
  • 24 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDFPubReader   ePub   
Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.

Citations

Citations to this article as recorded by  
  • The association between visit-to-visit variability in risk factors and incident cardiovascular disease: a post hoc analysis of the Multi-Ethnic Study of Atherosclerosis
    Abderrahim Oulhaj, Abubaker Suliman, Malak Bentaleb, Mohammed Abdulrahman, Rachid Bentoumi, Stephen J Sharp, Harald Sourij
    American Journal of Epidemiology.2026; 195(2): 319.     CrossRef
  • Cardiometabolic Profile Segmentation in Ecuadorian University Students: A Multivariate Analysis of Lipid, Anthropometric, and Demographic Patterns
    Kevin Gabriel Armijo Valverde, Edgar Rolando Morales Caluña, María Victoria Padilla Samaniego, Katherine Denisse Suarez González
    International Journal of Environmental Research and Public Health.2026; 23(4): 467.     CrossRef
  • Within‐Person Seasonal Variability of Aminotransferases and Long‐Term Glycemic Control in Adults With Type 2 Diabetes (JDDM 85)
    Ryota Toki, Masaya Sakamoto, Masahiro Yuki, Miho Iida, Michiko Yamazaki, Seiichi Ichikawa, Ryuzo Horiuchi, Hiroshi Maegawa, Tomonori Okamura, Toru Takebayashi
    Liver International.2026;[Epub]     CrossRef
  • Season‐Aware Interpretation of Aminotransferases Should Not Become Season‐Based Reassurance
    Mengzhu Dai, Qun Wang
    Liver International.2026;[Epub]     CrossRef
  • Variability in Cardiometabolic Parameters and All-Cause and Cause-Specific Mortality in Older Adults: Evidence From 2 Prospective Cohorts
    Jian-Yun Lu, Rui Zhou, Jie-Qiang Huang, Qi Zhong, Yi-Ning Huang, Jia-Ru Hong, Ling-Bing Liu, Da-Xing Li, Xian-Bo Wu
    American Journal of Preventive Medicine.2025; 68(3): 588.     CrossRef
  • Effectiveness of continuous glucose monitoring systems on glycemic control in adults with type 1 diabetes: A systematic review and meta-analysis
    Salya F. Alfadli, Yazeed S. Alotaibi, Maha J. Aqdi, Latifah A. Almozan, Zahra B. Alzubaidi, Hammad A. Altemani, Shaden D. Almutairi, Hussain A. Alabdullah, Alaa Ahmed Almehmadi, Abdulrahman L. Alanzi, Ahmed Y. Azzam
    Metabolism Open.2025; 27: 100382.     CrossRef
  • The additive effect of the estimated glucose disposal rate and a body shape index on cardiovascular disease: A cross-sectional study
    Qinghua Wen, Xiaoyue Wang, Simin Li, Huanhuan Zhu, Fengyin Zhang, Chao Xue, Juan Li, Amin Mansoori
    PLOS One.2025; 20(8): e0331005.     CrossRef
  • A Clinical Review of the Connections Between Diabetes Mellitus, Periodontal Disease, and Cardiovascular Pathologies
    Otilia Țica, Ioana Romanul, Gabriela Ciavoi, Vlad Alin Pantea, Ioana Scrobota, Lucian Șipoș, Cristian Marius Daina, Ovidiu Țica
    Biomedicines.2025; 13(9): 2309.     CrossRef
  • Mobile application-based lifestyle intervention for improving glycemic control and body composition in manufacturing company employees in South Korea
    Dahyeon Koo, Yujin Bang, Dohoung Kim, Irang Im, Pumsoo Kim, Dougho Park
    Diabetology & Metabolic Syndrome.2025;[Epub]     CrossRef
  • Employing an Artificial Intelligence Platform to Enhance Treatment Responses to GLP-1 Agonists by Utilizing Metabolic Variability Signatures Based on the Constrained Disorder Principle
    Jakob Landau, Yariv Tiram, Yaron Ilan
    Biomedicines.2025; 13(11): 2645.     CrossRef
  • Blood pressure variability: From predictive marker to intervention target-breaking the vicious cycle of hypertensive target organ damage
    Ruiqin Luo, Ying Huang, Yanjun Leng, Weiqian Liao
    Clinical and Experimental Hypertension.2025;[Epub]     CrossRef
  • Visit‑to‑visit variability of inflammation–immunity indices and prognosis in hepatocellular carcinoma
    Qiajun Du, Youli Zhao, Jing Yang, Yongxin Yang
    BMC Gastroenterology.2025;[Epub]     CrossRef
  • Cognitive Function in Children with Type 1 Diabetes: A Narrative Review
    Hussein Zaitoon, Maria S. Rayas, Jane L. Lynch
    Diabetology.2025; 7(1): 1.     CrossRef
  • 4-week results of “Linni Slim” synbiotic in patients with metabolic syndrome
    A. S. Rudoy, N. N. Silivinchik
    Experimental and Clinical Gastroenterology.2024; (3): 87.     CrossRef
  • Association between weight loss and cardiovascular outcomes and mortality in Korea: A nationwide cohort study
    So Yoon Kwon, Gyuri Kim, Seohyun Kim, Jae Hyeon Kim
    Diabetes Research and Clinical Practice.2024; 214: 111767.     CrossRef
  • Identifying Personal and Lifestyle Determinants Associated With Glycemic Variability Among Healthy Non-Diabetes Adults
    SuJin Song
    CardioMetabolic Syndrome Journal.2024; 4(2): 93.     CrossRef
  • Новий сучасний скринінговий комплекс профілактичної медицини
    M.S. Cherska, S.V. Kutsevlyak
    Endokrynologia.2024; 29(3): 207.     CrossRef
  • Long-term variability in physiological measures in relation to mortality and epigenetic aging: prospective studies in the USA and China
    Hui Chen, Tianjing Zhou, Shaowei Wu, Yaying Cao, Geng Zong, Changzheng Yuan
    BMC Medicine.2023;[Epub]     CrossRef
  • Dose–response relationship between physical activity and cardiometabolic risk in obese children and adolescents: A pre-post quasi-experimental study
    Zekai Chen, Lin Zhu
    Frontiers in Physiology.2023;[Epub]     CrossRef
  • Association of body weight change with all-cause and cause-specific mortality: A nationwide population-based study
    So Yoon Kwon, Gyuri Kim, Jungkuk Lee, Jiyun Park, You-Bin Lee, Sang-Man Jin, Kyu Yeon Hur, Jae Hyeon Kim
    Diabetes Research and Clinical Practice.2023; 199: 110666.     CrossRef
  • Association between lipid variability and the risk of mortality in cancer patients not receiving lipid-lowering agents
    Seohyun Kim, Gyuri Kim, So Hyun Cho, Rosa Oh, Ji Yoon Kim, You-Bin Lee, Sang-Man Jin, Kyu Yeon Hur, Jae Hyeon Kim
    Frontiers in Oncology.2023;[Epub]     CrossRef
  • Association between visit-to-visit lipid variability and risk of ischemic heart disease: a cohort study in China
    Yonghao Wu, Peng Shen, Lisha Xu, Zongming Yang, Yexiang Sun, Luhua Yu, Zhanghang Zhu, Tiezheng Li, Dan Luo, Hongbo Lin, Liming Shui, Mengling Tang, Mingjuan Jin, Kun Chen, Jianbing Wang
    Endocrine.2023; 84(3): 914.     CrossRef
  • Variability of Metabolic Risk Factors: Causative Factor or Epiphenomenon?
    Hye Jin Yoo
    Diabetes & Metabolism Journal.2022; 46(2): 257.     CrossRef
  • Long-Term Variability in Physiological Measures in Relation to Mortality and Epigenetic Aging: Prospective Studies in the US and China
    Hui Chen, Tianjing Zhou, Shaowei Wu, Yaying Cao, Geng Zong, Changzheng Yuan
    SSRN Electronic Journal .2022;[Epub]     CrossRef

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