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Han GR, Goncharov A, Eryilmaz M, Joung HA, Ghosh R, Yim G, Chang N, Kim M, Ngo K, Veszpremi M, Liao K, Garner OB, Di Carlo D, Ozcan A. Deep Learning-Enhanced Paper-Based Vertical Flow Assay for High-Sensitivity Troponin Detection Using Nanoparticle Amplification. ACS NANO 2024; 18:27933-27948. [PMID: 39365271 PMCID: PMC11483942 DOI: 10.1021/acsnano.4c05153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 09/20/2024] [Accepted: 09/25/2024] [Indexed: 10/05/2024]
Abstract
Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, and data processing, coupled with deep learning, can help improve POCT. To demonstrate the performance of our approach, we present a rapid and cost-effective paper-based high-sensitivity vertical flow assay (hs-VFA) for quantitative measurement of cardiac troponin I (cTnI), a biomarker widely used for measuring acute cardiac damage and assessing cardiovascular risk. The hs-VFA includes a colorimetric paper-based sensor, a portable reader with time-lapse imaging, and computational algorithms for digital assay validation and outlier detection. Operating at the level of a rapid at-home test, the hs-VFA enabled the accurate quantification of cTnI using 50 μL of serum within 15 min per test and achieved a detection limit of 0.2 pg/mL, enabled by gold ion amplification chemistry and time-lapse imaging. It also achieved high precision with a coefficient of variation of <7% and a very large dynamic range, covering cTnI concentrations over 6 orders of magnitude, up to 100 ng/mL, satisfying clinical requirements. In blinded testing, this computational hs-VFA platform accurately quantified cTnI levels in patient samples and showed a strong correlation with the ground truth values obtained by a benchtop clinical analyzer. This nanoparticle amplification-based computational hs-VFA platform can democratize access to high-sensitivity point-of-care diagnostics and provide a cost-effective alternative to laboratory-based biomarker testing.
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Affiliation(s)
- Gyeo-Re Han
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Artem Goncharov
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Merve Eryilmaz
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Hyou-Arm Joung
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Rajesh Ghosh
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Geon Yim
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Nicole Chang
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Minsoo Kim
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Kevin Ngo
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Marcell Veszpremi
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Kun Liao
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Omai B. Garner
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Dino Di Carlo
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
| | - Aydogan Ozcan
- Electrical
& Computer Engineering Department, Bioengineering Department, Department of Chemistry
and Biochemistry, Department of Pathology and Laboratory Medicine, California NanoSystems Institute
(CNSI), Department
of Surgery, University of California, Los Angeles, California 90095, United States
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Zhang L, Liu ZH, Lv YJ, Fu S, Luo ZM, Guo ML. Comprehensive improvements in the emergency laboratory test process based on information technology. BMC Med Inform Decis Mak 2023; 23:292. [PMID: 38115101 PMCID: PMC10729567 DOI: 10.1186/s12911-023-02387-x] [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: 12/17/2022] [Accepted: 12/04/2023] [Indexed: 12/21/2023] Open
Abstract
OBJECTIVE To explore the application effects of information technology (IT) on emergency laboratory testing procedures. METHODS In this study, IT-based optimisation of the emergency laboratory testing process was implemented between October and December 2021. Thus, the emergency laboratory test reports from January to September 2021 were placed into the pre-optimised group, while those from January to September 2022 were categorised into the post-optimised group. Besides, the emergency laboratory test report time, emergency laboratory test report time limit coincidence rate, error rate, and employee and patient satisfaction levels in individual months and across the whole period were described. Moreover, changes in the above indicators before and after the implementation of IT-based optimisation were explored and the application effects of IT-based optimisation were also evaluated. RESULTS The emergency laboratory test report times after the implementation of IT-based optimisation were shorter than those before IT-based optimisation (P < 0.05). The total number of laboratory test items before and after information optimization amounted to 222,139 and 259,651, respectively. Also, IT-based optimisation led to an increase in the emergency laboratory test report time limit coincidence rate from 98.77% to 99.03% (P < 0.05), while the emergency laboratory test report error rate fell from 0.77‱ to 0.15‱ (P < 0.05). Additionally, IT-based optimisation resulted in increases in both employee satisfaction, from 80.65% to 93.55% (N = 31, P > 0.05), and patient satisfaction, from 93.06% to 98.44% (P < 0.05). CONCLUSION The automation and IT-based optimisation of the emergency laboratory testing process significantly reduces the emergency laboratory test report time and error rate. Additionally, IT-driven optimization enhances the alignment of emergency laboratory test report deadlines and enhances the overall quality and safety of emergency laboratory testing.
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Affiliation(s)
- Liang Zhang
- Department of Clinical Laboratory, The Second Affiliated Hospital of Zhejiang University School of Medicine, Linping Campus, 311100, Hangzhou, Zhejiang Province, People's Republic of China
| | - Zhen Hua Liu
- Department of General Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Linping Campus, 311100, Hangzhou, Zhejiang Province, People's Republic of China
| | - Yin Jiang Lv
- Department of Clinical Laboratory, The Second Affiliated Hospital of Zhejiang University School of Medicine, Linping Campus, 311100, Hangzhou, Zhejiang Province, People's Republic of China
| | - Shui Fu
- Department of Clinical Laboratory, The Second Affiliated Hospital of Zhejiang University School of Medicine, Linping Campus, 311100, Hangzhou, Zhejiang Province, People's Republic of China
| | - Zhang Mei Luo
- Department of Clinical Laboratory, The Second Affiliated Hospital of Zhejiang University School of Medicine, Linping Campus, 311100, Hangzhou, Zhejiang Province, People's Republic of China
| | - Mei Li Guo
- Department of Clinical Laboratory, The People's Hospital of Cangnan Zhejiang, No. 2288 Yucang Road, Cangnan County, 325800, Wenzhou, Zhejiang Province, People's Republic of China.
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Imoh LC, Mohammed IY, Nnakenyi ID, Egbuagha EU, Adaja TM, Onyenekwu CP. Critical values notification: A nationwide survey of practices among clinical laboratories across Nigeria. Afr J Lab Med 2023; 12:2249. [PMID: 38116517 PMCID: PMC10729493 DOI: 10.4102/ajlm.v12i1.2249] [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: 07/04/2023] [Accepted: 10/12/2023] [Indexed: 12/21/2023] Open
Abstract
Background Critical value notification (CVN) entails notifying doctors or other laboratory users of aberrant laboratory results that threaten the patient's life and of any values for which reporting delays could negatively impact the patient's health. Critical value notification practices in clinical laboratories in Nigeria and sub-Saharan Africa are largely unknown. Objective We conducted a nationwide survey to obtain baseline information on CVN practice by Nigeria's laboratories. Methods This cross-sectional study was conducted among purposively selected secondary- and tertiary-tier, public and private clinical laboratories across northern and southern Nigeria between October 2015 and December 2015. Consenting senior laboratory staff completed and returned a structured questionnaire, that gathered data on respondents' demographics, designations, and institutional characteristics and practices regarding CVN. Results One hundred and thirty-four laboratories responded to the questionnaires. Only 69 (51.5 %) laboratories practised CVN; only 23 (33.3%) had existing written policies guiding the practice. Most (43; 62.3%) laboratories use similar critical values (CVs) for adult and paediatric populations. Most laboratories (27; 39.1%) obtained their CVs by combining published literature and local opinions from stakeholders. Physical dispatch (42; 60.9%) followed by telephone calls (38; 55.1%) were the most common means of notification. Private laboratories, compared with public hospital laboratories, were likelier to have separate paediatric CV lists (p = 0.019) and practise telephone notifications (p < 0.001). Conclusion Critical value notification practices vary and are often suboptimal in many clinical laboratories in Nigeria, which is exacerbated by the absence of guiding policies and national recommendations for post-analytical procedures. What this study adds This study provides baseline information on CVN practice by Nigeria's laboratories. The study explores the causes of practice variations that can serve as a foundation for enhancing critical reporting and post-analytical services, particularly in clinical laboratories in sub-Saharan Africa.
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Affiliation(s)
- Lucius C Imoh
- Department of Chemical Pathology, Faculty of Medical Sciences, University of Jos, Jos, Plateau State, Nigeria
| | - Idris Y Mohammed
- Department of Chemical Pathology & Immunology, College of Health Sciences, Bayero University and Aminu Kano Teaching Hospital, Kano, Kano State, Nigeria
| | - Ifeyinwa D Nnakenyi
- Department of Chemical Pathology, Faculty of Medical Sciences, University of Nigeria Nsukka and University of Nigeria Teaching Hospital, Enugu, Enugu State, Nigeria
| | - Ephraim U Egbuagha
- Department of Pathology, Clinix Healthcare Ltd, Lagos, Lagos State, Nigeria
| | - Tomisin M Adaja
- Department of Chemical Pathology, Federal Medical Centre, Owo, Ondo State, Nigeria
| | - Chinelo P Onyenekwu
- Department of Chemical Pathology, Ben Carson Snr School of Medicine, Babcock University and Babcock University Teaching Hospital, Ilishan-Remo, Ogun State, Nigeria
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Karnchanaphiboonwong A, Sringam P, Niwattakul K, Krommuang T, Gammie A. Innovation, Automation and Informatics Improves Quality in Lerdsin Hospital, Thailand. Br J Biomed Sci 2023; 80:11532. [PMID: 37405195 PMCID: PMC10317056 DOI: 10.3389/bjbs.2023.11532] [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: 05/02/2023] [Accepted: 05/31/2023] [Indexed: 07/06/2023]
Abstract
This paper describes a planned, continuous improvement journey, of a laboratory that has installed a system with a single sample touch from blood draw to result. To achieve this, physical connectivity of systems from phlebotomy through pre-analytical to the analytical phase were paired with informatics connectivity from the patient's national identity card to the hospital and laboratory informatics management systems (LIMS) and associated middleware. This allowed accurate time stamps to track turnaround time (TAT). TAT metrics were collected from the LIMS for inpatient, emergency room and outpatient samples and tests over a period of 7 months. This time span incorporated the 2-month period before automation was implemented. The results for all tests and specific tests are shown and the results of an analysis of the outpatient phlebotomy workflow are given. The implemented solution has improved outpatient TAT by over 54% and has shown that samples can be collected, and results obtained without touching the sample. Improving intra-laboratory TAT is an important quality goal for all laboratories. The implementation of automation is important in achieving this albeit more about obtaining predictable TAT. Automation does not necessarily improve TAT it removes variation which leads to predictable TAT (PTAT). Automation should only be considered with a strategic vision for the future as it is important to have clear goals and objectives based on the individual laboratories process and needs. Automating a poor process leads to an automated poor process. Here, an innovative use of automation, hardware and software has resulted in marked improvement in TAT across all samples processed in the central laboratory.
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