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"Cho, Han"
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Diagnostic and prognostic value of interleukin-6, pentraxin 3, and procalcitonin levels among sepsis and septic shock patients: a prospective controlled study according to the Sepsis-3 definitions
Background
This study investigated the clinical value of interleukin-6 (IL-6), pentraxin 3 (PTX3), and procalcitonin (PCT) in patients with sepsis and septic shock diagnosed according to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).
Methods
Serum levels of IL-6, PTX3, and PCT were measured in 142 enrolled subjects (51 with sepsis, 46 with septic shock, and 45 as controls). Follow-up IL-6 and PTX3 levels were measured in patients with initial septic shock within 24 h of hospital discharge. Optimal cut-off values were determined for sepsis and septic shock, and prognostic values were evaluated.
Results
Serum IL-6 levels could discriminate sepsis (area under the curve [AUC], 0.83–0.94,
P
< 0.001; cut-off value, 52.60 pg/mL, 80.4% sensitivity, 88.9% specificity) from controls and could distinguish septic shock (AUC, 0.71–0.89; cut-off value, 348.92 pg/mL, 76.1% sensitivity, 78.4% specificity) from sepsis. Twenty-eight-day mortality was significantly higher in the group with high IL-6 (≥ 348.92 pg/mL) than in the group with low IL-6 (< 348.92 pg/mL) (
P
= 0.008). IL-6 was an independent risk factor for 28-day mortality among overall patients (hazard ratio, 1.0004; 95% confidence interval, 1.0003–1.0005;
p
= 0.024). In septic shock patients, both the initial and follow-up PTX3 levels were consistently significantly higher in patients who died than in those who recovered (initial
p
= 0.004; follow-up
P
< 0.001).
Conclusions
The diagnostic and prognostic value of IL-6 was superior to those of PTX3 and PCT for sepsis and septic shock.
Journal Article
Research of multi-object detection and tracking using machine learning based on knowledge for video surveillance system
Recently, as the risk of crime and accidents increases, interest in security and surveillance of individuals and the public is increasing rapidly, and video surveillance system technology is continuously developing. Reliable object detection in the system is the basis of all elements using image information and it is used in various applications using the information, so accurate object detection and tracking are needed. Therefore, we propose a system for analyzing images with a knowledge-based deep learning technology for multi-object recognition and tracking enhancement. Algorithms for recognizing objects using existing convolution neural network (CNN) classifiers have a problem that it is difficult to process in real time because the processing time is increased when there are a lot of objects to be classified in the image. Therefore, we propose an algorithm that combines optical flow while maintaining the recognition performance through a knowledge-based CNN. An optical flow-based tracker can forecast the position of objects in the next frame based on the position of objects in the current frame. A CNN-based detector can detect the position of objects through a knowledge-based mining method between the two images. CNN-based detectors also carry out mining method on current frame information. This detector can select more capacity features based on the background to more accurately forecast the location of the tracked targets and targets. The fusion of the tracker and detector compensates for accumulated errors that can occur in the tracker and for drift from the detector. The experimental results show that the proposed algorithm combining CNN and optical flow can detect and trace multiple objects in a video stream, and can carry out robust detection and tracing even in a complex environment.
Journal Article
Safety and efficacy of the European Society of Cardiology 0/1-hour algorithm for diagnosis of myocardial infarction: systematic review and meta-analysis
ObjectiveThe European Society of Cardiology (ESC) 0/1 hour algorithm has been primarily validated in Europe, America and Australasia with less knowledge of its performance outside of these settings. We aim to evaluate the performance of the ESC 0/1 hour algorithm across different contexts.MethodsWe searched PubMed, Embase, Scopus, Web of Science and the Cochrane Central Register of Controlled Trials for relevant studies published between 1 January 2008 and 31 May 2019. The primary outcome was index myocardial infarction and the secondary outcome was major adverse cardiac event or mortality. A bivariate random-effects meta-analysis was used to derive the pooled estimate of each outcome.ResultsA total of 11 014 patients from 10 cohorts were analysed for the primary outcome. The algorithm based on high-sensitivity cardiac troponin (hs-cTn)T (Roche), hs-cTnI (Abbott) and hs-cTnI (Siemens) had pooled sensitivity of 98.4% (95% CI=95.1% to 99.5%), 98.1% (95% CI=94.6% to 99.3%) and 98.7% (95% CI=97.3% to 99.3%), respectively. The algorithm based on hs-cTnT (Roche) and hs-cTnI (Siemens) had pooled specificity of 91.2% (95% CI=86.0% to 94.6%) and 95.9% (95% CI=94.1% to 97.2%), respectively. Among patients in the rule-out category, the pooled mortality rate at 30 days and at 1 year was 0.1% (95% CI=0.0% to 0.4%) and 0.8% (95% CI=0.5% to 1.2%), respectively. Among patients in the observation zone, the pooled mortality rate was 0.7% (95% CI=0.3% to 1.2%) at 30 days but increased to 8.1% (95% CI=6.1% to 10.4%) at 1 year, comparable to the mortality rate in the rule-in group.ConclusionThe ESC 0/1 hour algorithm has high diagnostic accuracy but may not be sufficiently safe if the 1% miss-rate for myocardial infarction is desired.PROSPERO registration numberCRD42019142280.
Journal Article
Impact of sodium-glucose cotransporter-2 inhibitors on heart failure and mortality in patients with cancer
ObjectivesSodium-glucose cotransporter-2 inhibitors (SGLT2i) reduce heart failure (HF) in at-risk patients and may possess antitumour effects. We examined the effect of SGLT2i on HF and mortality among patients with cancer and diabetes.MethodsThis was a retrospective propensity score-matched cohort study involving adult patients with type 2 diabetes mellitus diagnosed with cancer between January 2010 and December 2021. The primary outcomes were hospitalisation for incident HF and all-cause mortality. The secondary outcomes were serious adverse events associated with SGLT2i.ResultsFrom a total of 8640 patients, 878 SGLT2i recipients were matched to non-recipients. During a median follow-up of 18.8 months, SGLT2i recipients had a threefold lower rate of hospitalisation for incident HF compared with non-SGLT2i recipients (2.92 vs 8.95 per 1000 patient-years, p=0.018). In Cox regression and competing regression models, SGLT2i were associated with a 72% reduction in the risk of hospitalisation for HF (HR 0.28 (95% CI: 0.11 to 0.77), p=0.013; subdistribution HR 0.32 (95% CI: 0.12 to 0.84), p=0.021). The use of SGLT2i was also associated with a higher overall survival (85.3% vs 63.0% at 2 years, p<0.001). The risk of serious adverse events such as hypoglycaemia and sepsis was similar between the two groups.ConclusionsThe use of SGLT2i was associated with a lower rate of incident HF and prolonged overall survival in patients with cancer with diabetes mellitus.
Journal Article
The Practice of Wearing Surgical Masks during the COVID-19 Pandemic
Before the 2003 severe acute respiratory syndrome coronavirus epidemic in Taiwan, only persons with open tuberculosis wore masks in public. Respiratory virus shedding in exhaled breath and efficacy of face masks. COVID-19 and the risk to health care workers: a case report.
Journal Article
Diagnostic and prognostic value of presepsin and procalcitonin in non-infectious organ failure, sepsis, and septic shock: a prospective observational study according to the Sepsis-3 definitions
Background
We investigated the diagnostic and prognostic value of presepsin among patients with organ failure, including sepsis, in accordance with the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).
Methods
This prospective observational study included 420 patients divided into three groups: non-infectious organ failure (n = 142), sepsis (n = 141), and septic shock (n = 137). Optimal cut-off values of presepsin to discriminate between the three groups were evaluated using receiver operating characteristic curve analysis. We determined the optimal cut-off value of presepsin levels to predict mortality associated with sepsis and performed Kaplan–Meier survival curve analysis according to the cut-off value. Cox proportional hazards model was performed to determine the risk factors for 30-day mortality.
Results
Presepsin levels were significantly higher in sepsis than in non-infectious organ failure cases (
p
< 0.001) and significantly higher in patients with septic shock than in those with sepsis (
p
= 0.002). The optimal cut-off value of the presepsin level to discriminate between sepsis and non-infectious organ failure was 582 pg/mL (p < 0.001) and between sepsis and septic shock was 1285 pg/mL (
p
< 0.001). The optimal cut-off value of the presepsin level for predicting the 30-day mortality was 821 pg/mL (
p
= 0.005) for patients with sepsis. Patients with higher presepsin levels (≥ 821 pg/mL) had significantly higher mortality rates than those with lower presepsin levels (< 821 pg/mL) (log-rank test;
p
= 0.004). In the multivariate Cox proportional hazards model, presepsin could predict the 30-day mortality in sepsis cases (hazard ratio, 1.003; 95% confidence interval 1.001–1.005;
p
= 0.042).
Conclusions
Presepsin levels could effectively differentiate sepsis from non-infectious organ failure and could help clinicians identify patients with sepsis with poor prognosis. Presepsin was an independent risk factor for 30-day mortality among patients with sepsis and septic shock.
Journal Article
