Pulse signal contains a wealth of biological and pathological information. However, it is susceptible to the influence of various factors which results in poor signal quality, and causes the device to generate false alarms. First the pulse signals are processing into discrete symbols, and then compare the test signal with the pulse template by using Dynamic Time Warping (DTW) to get the threshold for which can be used to find the interference segment of the test signal. By analyzing the DTW distance of the pulse signal, we can get the interference degree of the signal, then the quality level of the plus signal can be defined by the relationship between the interference degree and quality of the signal. The 1 055 group pulse signals provided by MIMIC II physiological database are used to train and test the signal quality assessment algorithms, and compared with other existing algorithms. The results show that the algorithms can accurately detect interference segments in pulse signal and reflect the quality of it.
Algorithms ; Heart Rate ; Humans ; Pulse ; Signal Processing, Computer-Assisted

Pulse signal contains a wealth of biological and pathological information. However, it is susceptible to the influence of various factors which results in poor signal quality, and causes the device to generate false alarms. First the pulse signals are processing into discrete symbols, and then compare the test signal with the pulse template by using Dynamic Time Warping (DTW) to get the threshold for which can be used to find the interference segment of the test signal. By analyzing the DTW distance of the pulse signal, we can get the interference degree of the signal, then the quality level of the plus signal can be defined by the relationship between the interference degree and quality of the signal. The 1 055 group pulse signals provided by MIMICⅡphysiological database are used to train and test the signal quality assessment algorithms, and compared with other existing algorithms. The results show that the algorithms can accurately detect interference segments in pulse signal and reflect the quality of it.

AIM: To describe and evaluate the clinical characteristics, treatment management and clinical outcomes of ceftazidime-avibactam (CZA) in the treatment of patients with multidrug-resistant gram-negative bacterial (MDR-GNB) infections. METHODS: A retrospective cohort study was performed on patients hospitalized in the Affiliated Hospital of Xuzhou Medical University from September 2019 to December 2021. Adult patients who received CZA for ≥ 72 hours consecutively were eligible for inclusion. The primary outcome was clinical failure, defined as a composite of 30-day all-cause mortality, microbiological failure and / or failure to resolve or improve signs and symptoms of infection during treatment with CZA. RESULTS: A total of 198 patients with MDR-GNB infections were described and evaluated, including 132 in the carbapenem-resistant Enterobatceriaceae (CRE) cohort and 66 in the Pseudomonas spp. cohort. The main infection sites were lung infection (92.42%), abdominal infection (10.61%), and intracranial infection (10.61%), among which 63 patients (31.82%) were positive for blood culture. Clinical failure, 30-day all-cause mortality and microbiological failure occurred in 61 (30.81%), 33(16.67%) and 11(5.56%) patients, respectively. Body mass index (BMI), acute physiology and chronic health evaluation scoring system (APACHE Ⅱ) and polymicrobial infections were positively associated with clinical outcome failureadjusted OR 1.109, 95%CI 1.017, 1.209; adjusted OR 1.071, 95%CI 1.015, 1.129; adjusted OR 2.844, 95%CI 1.391, 5.814, however, initiation of CZA within 48 hours of admission was protective (adjusted OR 0.424, 95%CI 0.205, 0.879). A total of 15 patients had adverse reactions possibly related to CZA, including 2 cases of rash, 6 cases of nausea and vomiting, and 7 cases of antibiotic-related diarrhea. CONCLUSION: CZA can be used to treat infections caused by a range of MDR-GNB, including Pseudomonas spp. and CRE.