Factors Associated With Infections From Peripheral Venous Catheters in Older Patients in the ICU and Exploration of Preventive Measures.

Context: Intensive care units (ICUs) have the highest incidence of hospital-acquired infections. An in-depth understanding of the factors associated with PVIN infections may be the best way to prevent and control PVIN infections. Objective: The study aimed to investigate the factors associated with peripheral venous indwelling needle (PVIN) infections in older patients in the intensive care unit (ICU) and to use the findings to develop targeted preventive-care measures. Design: The research team conducted a prospective observational study of factors influencing PVIN infections and a prospective randomized controlled study of targeted nursing care. Setting: The studies took place at the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China. Participants: For the first study, participants were 121 patients admitted to the hospital's ICU between April 2018 and June 2020, and for a second analysis, participants were 92 ICU patients admitted between December 2020 and March 2022. The first group took part in an analysis of the factors influencing PFIN infections and the second in a comparison of a targeted nursing intervention and routine care. Groups: For the first analysis, the research team divided the 121 participants into two groups: (1) a control group with 69 participants who didn't develop a PVIN infection and (2) an observation group with 52 participants who developed a PVIN infection. For the second analysis, the team randomly assigned the 92 participants to one of two groups: (1) 46 participants to a targeted nursing group who received care focused on preventing PVIN infections, and (2) 46 participants to a conventional group receiving routine care. Outcome Measures: For the first analysis, the research team carried out logistic regression analysis to assess the factors related to PVIN infections, including the incidence of PVIN infections, durations of PVIN retention, ICU stays, and lengths of hospital stay (LOS). For the second analysis, the research team: (1) measured changes in blood glucose and inflammatory factor levels at baseline and postintervention and (2) conducted a nursing satisfaction survey upon patients' discharges. Results: For the first study, logistic multiple regression analysis revealed that the durations of catheter retention of ≥7d, a number of punctures ≥2 times, a duration of antibiotic administration of ≥14d, and Acute Physiology and Chronic Health Evaluation (APACHE II) scores were independent risk factors for PVIN infections in older patients in an ICU (all P < .001). After implementing targeted nursing strategies for the second study, the targeted care group had a significantly lower incidence of PVIN infections (P < .001), shorter duration of PVIN retention (P < .001), shorter ICU stay (P < .001), and shorter LOS (P < .001) compared to those of the conventional group. Additionally, the intervention group showed significantly lower fasting plasma glucose (FPG) and 2h postprandial plasma glucose (2hPG) levels, with P < .001 and P = .002, respectively; significantly lower interleukin-1 beta (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNF-α) levels, with P < .001, P < .001, and P = .001, respectively; and significantly higher nursing satisfaction postintervention (P = .036). Conclusions: The duration of catheterization, antibiotic administration, and APACHE II scores were independent risk factors for PVIN infections in older patients in the ICU. Implementing targeted care based on those factors can effectively prevent PVIN infections in ICU patients and improve patient satisfaction, demonstrating high clinical practicality.

A denoising method of ECG signal based on variational autoencoder and masked convolution.

Wearable electrocardiogram (ECG) equipment can realize continuous monitoring of cardiovascular diseases, but these devices are more susceptible to interference from various noises, which will seriously reduce the diagnostic correctness. In this work, a novel noise reduction model for ECG signals is proposed based on variational autoencoder and masked convolution. The variational Bayesian inference is conducted to capture the global features of the ECG signals by encouraging the approximate posterior of the latent variables to fit the prior distribution, and we use the skip connection and feature concatenation to realize the information interaction across the channels. To strengthen the connection of local features of the ECG signals, the masked convolution module is used to extract local feature information, which supplement the global features and the noise reduction performance of whole model can be greatly improved. Experiments are carried out on the MIT-BIH arrythmia database, and the results display that the performance metrics of signal-to-noise ratio (SNR) and root mean square error (RMSE) are significantly improved compared with other approaches while causing less signal distortion.

An Energy-Efficient MAC Protocol for Medical Emergency Monitoring Body Sensor Networks.

Medical emergency monitoring body sensor networks (BSNs) monitor the occurrence of medical emergencies and are helpful for the daily care of the elderly and chronically ill people. Such BSNs are characterized by rare traffic when there is no emergency occurring, high real-time and reliable requirements of emergency data and demand for a fast wake-up mechanism for waking up all nodes when an emergency happens. A beacon-enabled MAC protocol is specially designed to meet the demands of medical emergency monitoring BSNs. The rarity of traffic is exploited to improve energy efficiency. By adopting a long superframe structure to avoid unnecessary beacons and allocating most of the superframe to be inactive periods, the duty cycle is reduced to an extremely low level to save energy. Short active time slots are interposed into the superframe and shared by all of the nodes to deliver the emergency data in a low-delay and reliable way to meet the real-time and reliable requirements. The interposition slots can also be used by the coordinator to broadcast network demands to wake-up all nodes in a low-delay and energy-efficient way. Experiments display that the proposed MAC protocol works well in BSNs with low emergency data traffic.

A MAC protocol for medical monitoring applications of wireless body area networks.

Targeting the medical monitoring applications of wireless body area networks (WBANs), a hybrid medium access control protocol using an interrupt mechanism (I-MAC) is proposed to improve the energy and time slot utilization efficiency and to meet the data delivery delay requirement at the same time. Unlike existing hybrid MAC protocols, a superframe structure with a longer length is adopted to avoid unnecessary beacons. The time slots are mostly allocated to nodes with periodic data sources. Short interruption slots are inserted into the superframe to convey the urgent data and to guarantee the real-time requirements of these data. During these interruption slots, the coordinator can break the running superframe and start a new superframe. A contention access period (CAP) is only activated when there are more data that need to be delivered. Experimental results show the effectiveness of the proposed MAC protocol in WBANs with low urgent traffic.

Outage Probability of MRC for κ-µ Shadowed Fading Channels under Co-Channel Interference.

In this paper, exact closed-form expressions are derived for the outage probability (OP) of the maximal ratio combining (MRC) scheme in the κ-µ shadowed fading channels, in which both the independent and correlated shadowing components are considered. The scenario assumes the received desired signals are corrupted by the independent Rayleigh-faded co-channel interference (CCI) and background white Gaussian noise. To this end, first, the probability density function (PDF) of the κ-µ shadowed fading distribution is obtained in the form of a power series. Then the incomplete generalized moment-generating function (IG-MGF) of the received signal-to-interference-plus-noise ratio (SINR) is derived in the closed form. By using the IG-MGF results, closed-form expressions for the OP of MRC scheme are obtained over the κ-µ shadowed fading channels. Simulation results are included to validate the correctness of the analytical derivations. These new statistical results can be applied to the modeling and analysis of several wireless communication systems, such as body centric communications.