Blood biochemical indicators are an important basis for the diagnosis and treatment by doctors. The performance of related instruments, the qualification of operators, the storage method and time of blood samples and other factors will affect the accuracy of test results. However, it is difficult to meet the clinical needs of rapid detection and early screening of diseases with currently available methods. Point-of-care testing (POCT) is a new diagnostic technology with the characteristics of instant, portability, accuracy and efficiency. Microfluidic chips can provide an ideal experimental reaction platform for POCT. This paper summarizes the existing detection methods for common biochemical indicators such as blood glucose, lactic acid, uric acid, dopamine and cholesterol, and focuses on the application status of POCT based on microfluidic technology in blood biochemistry. It also summarizes the advantages and challenges of existing methods and prospects for development. The purpose of this paper is to provide relevant basis for breaking through the technical barriers of microfluidic and POCT product development in China.
Humans ; Point-of-Care Testing ; Lactic Acid/blood* ; Microfluidic Analytical Techniques/methods* ; Blood Glucose/analysis* ; Point-of-Care Systems ; Blood Chemical Analysis/instrumentation* ; Uric Acid/blood* ; Cholesterol/blood* ; Dopamine/blood* ; Microfluidics/methods*

Point-of-care testing (POCT), as an emerging diagnostic technology, is gradually becoming an important part of the clinical diagnostic field due to its advantages, such as ease of operation, rapid response, and portability. This paper primarily introduces two mainstream technologies in POCT: lateral flow assays and nucleic acid amplification. It covers the basic principles, applications, and quality control points in design and development of the two mainstream technologies, aiming to provide a technical reference for device manufacturers, researchers, and regulatory agencies.
Point-of-Care Testing ; Point-of-Care Systems ; Quality Control ; Equipment Design ; Nucleic Acid Amplification Techniques ; Humans

The accurate and timely detection of biochemical coagulation indicators is pivotal in pulmonary and critical care medicine. Despite their reliability, traditional laboratories often lag in terms of rapid diagnosis. Point-of-care testing (POCT) has emerged as a promising alternative, which is awaiting rigorous validation. We assessed 226 samples from patients at the First Affiliated Hospital of Guangzhou Medical University using a Beckman Coulter AU5821 and a PUSHKANG POCT Biochemistry Analyzer MS100. Furthermore, 350 samples were evaluated with a Stago coagulation analyzer STAR MAX and a PUSHKANG POCT Coagulation Analyzer MC100. Metrics included thirteen biochemical indexes, such as albumin, and five coagulation indices, such as prothrombin time. Comparisons were drawn against the PUSHKANG POCT analyzer. Bland-Altman plots (MS100: 0.8206‒0.9995; MC100: 0.8318‒0.9911) evinced significant consistency between methodologies. Spearman correlation pinpointed a potent linear association between conventional devices and the PUSHKANG POCT analyzer, further underscored by a robust correlation coefficient (MS100: 0.713‒0.949; MC100: 0.593‒0.950). The PUSHKANG POCT was validated as a dependable tool for serum and whole blood biochemical and coagulation diagnostics. This emphasizes its prospective clinical efficacy, offering clinicians a swift diagnostic tool and heralding a new era of enhanced patient care outcomes.
Humans ; Point-of-Care Testing ; Critical Care ; Blood Coagulation Tests/methods* ; Male ; Blood Coagulation ; Female ; Middle Aged ; Reproducibility of Results ; Prothrombin Time ; Aged ; Adult ; Point-of-Care Systems

OBJECTIVE: To investigate the current status of pre-hospital and in-hospital emergency medical information connectivity in China and provide evidence for optimizing the emergency medical system. METHODS: A multi-center cross-sectional study was conducted using a multi-level convenience sampling method to select provincial-level administrative regions and their corresponding capital cities, prefectural cities, and county-level emergency medical institutions. The questionnaire included basic information about respondents, the institutions, the current status of pre-hospital and in-hospital emergency information connectivity, and the satisfaction with the connectivity. The questionnaire has undergone reliability testing and split-half reliability testing, supplemented by semi-structured interviews. Data collection was carried out from January to May 2024, with one responsible person from each institution completing the questionnaire. Multiple Logistic regression analysis to investigated the relevant factors of pre-hospital and in-hospital information connectivity. RESULTS: A total of 225 questionnaires were distributed, and 199 valid responses were collected, with a response rate of 88.4%. Participants were from 199 emergency medical institutions across 13 provincial-level administrative regions. Of the institutions, 112 (56.3%) could achieve pre-hospital and in-hospital information connectivity. The proportion of pre-hospital to in-hospital information connection between emergency institutions in different provinces varies (χ² = 39.398, P < 0.001), with Beijing and Zhejiang having the highest proportion of information connection (both at 100%), and Hainan having the lowest (11.8%). The proportion of information integration in county-level emergency institution was lower than that of provincial and municipal level emergency institutions [40.4% (19/47) vs. 61.7% (29/47), 61.0% (64/105), χ² = 6.304, P = 0.043]. Provinces with high per capita disposable income have a higher proportion of information connectivity than provinces with low per capita disposable income [77.3% (34/44) vs. 50.3% (78/155), χ² = 10.122, P = 0.001]. The information connection ratio of independent pre-hospital emergency centers was higher than that of hospital emergency departments/hospital records [74.6% (47/63) vs. 47.8% (65/136), χ² = 12.581, P < 0.001]. The proportion of information integration in advanced provinces with digital development was higher than that in other provinces [77.6% (38/49) vs. 49.3% (74/150), χ² = 11.849, P = 0.001]. Logistic regression analysis showed that the per capita disposable income of residents in the province was an independent risk factor for the information connection between pre-hospital and in-hospital emergency institutions [odds ratio (OR) = 3.21, 95% confidence interval was 1.56-6.62, P < 0.01]. 72.3% institutions used the information connection mode for less than 5 years. Telephone and WeChat were the main communication methods (83.0%), and 17.0% of emergency institutions use dedicated APP for communication. 52.7% of respondents were very or relatively satisfied with the information integration before and after the hospital. The main deficiencies in current information integration were insufficient, untimely, inaccurate communication and delayed feedback between pre-hospital and in-hospital information. Optimizing top-level design and improving network quality are the directions for improving the integration of pre-hospital and in-hospital information in the future. CONCLUSIONS Pre-hospital and in-hospital emergency information connectivity in some provinces in China remains underdeveloped, with significant regional and institutional disparities. Future efforts should focus on integrating digital technologies and strengthening grassroots-level connectivity systems.
Cross-Sectional Studies ; China ; Humans ; Surveys and Questionnaires ; Emergency Medical Services ; Emergency Service, Hospital ; Hospital Information Systems

OBJECTIVE: To evaluate the prognosis of septic right ventricular dysfunction (SRVD) based on bedside ultrasound and explore its risk factors. METHODS: A prospective observational study was conducted involving septic and septic shock patients admitted to the intensive care unit (ICU) of the General Hospital of Ningxia Medical University from February 2021 to January 2022. Tricuspid annular plane systolic excursion (TAPSE) was measured by M-mode ultrasound within 24 hours after ICU admission. According to the results of TAPSE, the subjects were divided into SRVD group (TAPSE < 16 mm) and non-SRVD group (TAPSE ≥ 16 mm). The gender, age, occurrence of septic shock, underlying diseases, source of patients, acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, maximal body temperature within 24 hours after ICU admission, location and number of infections, duration of mechanical ventilation, and 28-day mortality were collected. Hemodynamic parameters, organ function indexes, oxygen therapy parameters and arterial blood gas analysis indexes were recorded within 24 hours after ICU admission. The differences of the above indexes between the two groups were compared. Binary multivariate Logistic regression analysis was used to screen out the independent risk factors for SRVD, and a nomogram of SRVD risk factors was drawn. RESULTS: 116 patients with sepsis and septic shock were enrolled, of which 24 (20.7%) had SRVD and 92 (79.3%) had no SRVD. Compared with the non-SRVD group, the patients in the SRVD group had higher emergency transfer and infection site ≥ 2 ratio, APACHE II score, SOFA score, higher cardiac troponin I (cTnI), myoglobin (Mb), MB isoenzyme of creatine kinase (CK-MB), N-terminal pro-brain natriuretic peptide (NT-proBNP), serum creatinine (SCr), arterial blood lactic acid (Lac) and lower left ventricular ejection fraction (LVEF), platelet count (PLT) within 24 hours after ICU admission, and higher proportion of norepinephrine application and continuous renal replacement therapy (CRRT). Binary multivariate Logistic regression analysis showed that LVEF [odds ratio (OR) = 0.918, 95% confidence interval (95%CI) was 0.851-0.991, P = 0.028], PLT (OR = 0.990, 95%CI was 0.981-0.999, P = 0.035), SCr (OR = 1.008, 95%CI was 1.001-1.016, P = 0.025), and the usage of norepinephrine (OR = 15.198, 95%CI was 1.541-149.907, P = 0.020) were independent risk factors for SRVD in patients with sepsis and septic shock. Based on the above four independent risk factors, a nomogram of SRVD risk factors was drawn. The results showed that the score was 64 when LVEF was 0.50, 18 when SCr was 100 μmol/L, 85 when PLT was 100×10⁹/L, and 39 when norepinephrine was used. When the total score reached 253, the risk of SRVD was 88%. Compared with non-SRVD group, the duration of mechanical ventilation in SRVD group was slightly longer [hours: 80.0 (28.5, 170.0) vs. 47.0 (10.0, 135.0), P > 0.05], and the 28-day mortality was significantly higher [41.7% (10/24) vs. 21.7% (20/92), P < 0.05]. CONCLUSIONS Patients with sepsis may have right ventricular dysfunction, impaired renal function and increased mortality in the early stage. The decrease in LVEF and PLT, the increase in SCr and the application of norepinephrine are independent risk factors for SRVD in patients with sepsis.
Humans ; Prognosis ; Ventricular Dysfunction, Right/diagnostic imaging* ; Risk Factors ; Prospective Studies ; Intensive Care Units ; Shock, Septic ; Male ; Ultrasonography ; Female ; Sepsis/complications* ; Middle Aged ; Point-of-Care Systems ; Aged ; Logistic Models ; APACHE

Visual detection is a technique for evaluating the results through visual judgment without relying on complex optical detection systems. It obtains results quickly based on signals, such as visible light, changes in air pressure, and migration distance, that can be directly observed by naked eyes, being widely used in the in vitro diagnostics industry. The CRISPR-Cas system has the potential to be used in the development of point of care testing (POCT) technologies due to the advantages of mild reaction conditions, no need for thermal cycling or other control measures, and a robust signal amplification capability. In recent years, the combination of visual detection and CRISPR-Cas has significantly reduced the need for laboratory infrastructures, precision instruments, and specialized personnel for nucleic acid detection. This has promoted the development of POCT technology and methods for nucleic acids. This article summarizes the signal output modes and characteristics of the visual detection of nucleic acid by CRISPR-Cas and discusses the issues in the application. Finally, its future clinical translation is envisioned with a view to informing the development of CRISPR-Cas visualization assays.
CRISPR-Cas Systems ; Humans ; Nucleic Acids/analysis* ; Point-of-Care Testing

Humans ; Female ; MicroRNAs/genetics* ; Breast Neoplasms/genetics* ; Point-of-Care Systems ; Early Detection of Cancer ; Gene Expression Regulation, Neoplastic

In December 2022, the American Academy of Pediatrics released a clinical guideline for point-of-care ultrasonography (POCUS) in the neonatal intensive care unit (NICU). The guideline outlined the development and current status of POCUS in the NICU, and summarized the key elements and implementation guidelines for successful implementation of POCUS in the NICU. This article provides an overview of the key points of the clinical guideline and analyzes the current status of POCUS in China, providing a reference for the implementation of POCUS in neonatal care in China.
Infant, Newborn ; Humans ; United States ; Child ; Intensive Care Units, Neonatal ; Point-of-Care Systems ; Ultrasonography ; China

OBJECTIVE: To develop a mortality prediction model for critically ill patients based on multidimensional and dynamic clinical data collected by the hospital information system (HIS) using random forest algorithm, and to compare the prediction efficiency of the model with acute physiology and chronic health evaluation II (APACHE II) model. METHODS: The clinical data of 10 925 critically ill patients aged over 14 years old admitted to the Third Xiangya Hospital of Central South University from January 2014 to June 2020 were extracted from the HIS system, and APACHE II scores of the critically ill patients were extracted. Expected mortality of patients was calculated according to the death risk calculation formula of APACHE II scoring system. A total of 689 samples with APACHE II score records were used as the test set, and the other 10 236 samples were used to establish the random forest model, of which 10% (n = 1 024) were randomly selected as the validation set and 90% (n = 9 212) were selected as the training set. According to the time series of 3 days before the end of critical illness, the clinical characteristics of patients such as general information, vital signs data, biochemical test results and intravenous drug doses were selected to develope a random forest model for predicting the mortality of critically ill patients. Using the APACHE II model as a reference, receiver operator characteristic curve (ROC curve) was drawn, and the discrimination performance of the model was evaluated through the area under the ROC curve (AUROC). According to the precision and recall, Precision-Recall curve (PR curve) was drawn, and the calibration performance of the model was evaluated through the area under the PR curve (AUPRC). Calibration curve was drawn, and the consistency between the predicted event occurrence probability of the model and the actual occurrence probability was evaluated through the calibration index Brier score. RESULTS: Among the 10 925 patients, there were 7 797 males (71.4%) and 3 128 females (28.6%). The average age was (58.9±16.3) years old. The median length of hospital stay was 12 (7, 20) days. Most patients (n = 8 538, 78.2%) were admitted to intensive care unit (ICU), and the median length of ICU stay was 66 (13, 151) hours. The hospitalized mortality was 19.0% (2 077/10 925). Compared with the survival group (n = 8 848), the patients in the death group (n = 2 077) were older (years old: 60.1±16.5 vs. 58.5±16.4, P < 0.01), the ratio of ICU admission was higher [82.8% (1 719/2 077) vs. 77.1% (6 819/8 848), P < 0.01], and the proportion of patients with hypertension, diabetes and stroke history was also higher [44.7% (928/2 077) vs. 36.3% (3 212/8 848), 20.0% (415/2 077) vs. 16.9% (1 495/8 848), 15.5% (322/2 077) vs. 10.0% (885/8 848), all P < 0.01]. In the test set data, the prediction value of random forest model for the risk of death during hospitalization of critically ill patients was greater than that of APACHE II model, which showed by that the AUROC and AUPRC of random forest model were higher than those of APACHE II model [AUROC: 0.856 (95% confidence interval was 0.812-0.896) vs. 0.783 (95% confidence interval was 0.737-0.826), AUPRC: 0.650 (95% confidence interval was 0.604-0.762) vs. 0.524 (95% confidence interval was 0.439-0.609)], and Brier score was lower than that of APACHE II model [0.104 (95% confidence interval was 0.085-0.113) vs. 0.124 (95% confidence interval was 0.107-0.141)]. CONCLUSIONS The random forest model based on multidimensional dynamic characteristics has great application value in predicting hospital mortality risk for critically ill patients, and it is superior to the traditional APACHE II scoring system.
Female ; Male ; Humans ; Aged ; Adult ; Middle Aged ; Adolescent ; Critical Illness ; Hospitalization ; Length of Stay ; APACHE ; Hospital Information Systems

The COVID-19 global pandemic has overwhelmed health services with large numbers of patients presenting to hospital, requiring immediate triage and diagnosis. Complications include acute respiratory distress syndrome, myocarditis, septic shock, and multiple organ failure. Point of care ultrasound is recommended for critical care triage and monitoring in COVID-19 by specialist critical care societies, however current guidance has mainly been published in webinar format, not a comprehensive review. Important limitations of point of care ultrasound include inter-rater variability and subjectivity in interpretation of imaging findings, as well as infection control concerns. A practical approach to clinical integration of point of care ultrasound findings in COVID-19 patients is presented to enhance consistency in critical care decision making, and relevant infection control guidelines and operator precautions are discussed, based on a narrative review of the literature.
Humans ; COVID-19/complications* ; SARS-CoV-2 ; Point-of-Care Systems ; Decision Support Systems, Clinical ; Ultrasonography