Detection Of Wound Infection Research Articles

A Scoping Review of 'Smart' Dressings for Diagnosing Surgical Site Infection: A Focus on Arthroplasty.

Early diagnosis and treatment of surgical wound infection can be challenging. This is especially relevant in the management of periprosthetic joint infection: early detection is key to success and reducing morbidity, mortality and resource use. 'Smart' dressings have been developed to detect parameters suggestive of infection. This scoping review investigates the current status of the field, limited to devices tested in animal models and/or humans, with a focus on their application to arthroplasty. The literature was searched using MEDLINE/PubMed and Embase databases from 2000 to 2023. Original articles assessing external sensing methods for the detection of wound infection in animal models or human participants were included. Sixteen articles were eligible. The results were broadly divided by sensing method: colorimetric, electrochemical and fluorescence/photothermal responses. Six of the devices detected more than one parameter (multimodal), while the rest were unimodal. The most common parameters examined were temperature and pH. Most 'smart' dressings focused on diagnosing infection in chronic wounds, and none were tested in humans with wound infections. There is limited late-stage research into using dressing sensors to diagnose wound infection in post-surgical patients. Future research should explore this to enable inpatient and remote outpatient monitoring of post-operative wounds to detect wound infection.

Battery-Free and Multifunctional Microfluidic Janus Wound Dressing with Biofluid Management, Multi-Indicator Monitoring, and Antibacterial Properties.

The sophisticated environment of chronic wounds, characterized by prolonged exudation and recurrent bacterial infections, poses significant challenges to wound recovery. Recent advancements in multifunctional wound dressings fall short of providing comprehensive, accurate, and comfortable treatment. To address these issues, a battery-free and multifunctional microfluidic Janus wound dressing (MM-JWD) capable of three functions, including exudate management, antibacterial properties, and multiple indications of wound infection detection, has been developed. During the treatment, the fully soft microfluidic Janus membrane not only demonstrated stable unidirectional fluid transport capabilities under various skin deformations for a longer period but also provided antibacterial effects through surface treatment with chitosan quaternary ammonium salts and poly(vinyl alcohol). Furthermore, integrating multiple colorimetric sensors within the Janus membrane's microchannels and a dual-layer structure enabled simultaneous monitoring of the wound's pH, uric acid, and temperature. The monitoring was facilitated by smartphone recognition of color changes in the sensors. In vivo and in vitro tests confirmed the exudate management, antibacterial, and sensing capabilities of the MM-JWD, proving its efficacy in monitoring and promoting the healing of wounds. Overall, this study provides a valuable method for the design of multifunctional wound dressings for chronic wound care.

Early versus delayed dressing removal after primary closure of clean and clean contaminated wounds: an observational study

Background: Traditionally, surgical dressings have remained untouched for several days after surgery. However, recent research is exploring the potential benefits of removing dressings sooner. Early removal may offer advantages like quicker detection of infection and improved patient comfort, but it's crucial to determine if it affects healing rates or patient satisfaction compared to the traditional delayed approach. Methods: A year-long cohort study investigated the efficacy of early (within 48 hours) versus delayed dressing removal 150 post-surgical patients who were divided into two respective groups. Data analysis was performed using statistical software. Results: Early and delayed dressing removal showed no significant difference in wound complications (p-values > 0.05 for both Chi-square and t-tests). However, patient satisfaction was lower in the early removal group (97 dissatisfied vs 143 satisfied in delayed removal). While the study found no objective benefit to delayed removal, it suggests patients were less satisfied with early removal. Conclusions: Although there were no statistically significant results between the early and delayed removal of dressing, early removal of dressing had the advantage of cost effectiveness, early detection of wound infection and decreased duration of hospital stay in patients.

Developing Porous Microneedles Patch for the Detection of Wound Infections

AbstractWound infections caused by invasive pathogens become an increasing global challenge health. Porous microneedles (MNs) present distinctive advantages for non‐invasive and in situ detection of wound infections, enabling the extraction of interstitial fluid, skin sweat, saliva and other biological samples. Consequently, porous MNs find widespread acceptance in medical detection, drug delivery, and monitoring physiological indicators. Based on these advantages, the emerging clinical applications and classifications of MNs is first introduced, covering mechanical strength, methods for antibody probe modification onto porous MNs, and signal amplification techniques for biomarkers analysis. At the same time, the specific applications of immunology and electrochemistry on porous MNs, introducing methods to enhance the detection signal of target molecules, such as rolling circle amplification, gold/silver nanoparticles, fluorescence amplification origami microneedle and so on is try to summarized. The improvement of detection sensitivity is realized by integrating various signal amplification strategies and diverse detection methods. Meanwhile, it is briefly illustrated applications in wound detections. Finally, challenges and future prospects of using porous MNs for detection in practical applications is discussed.

Digital tools for post-discharge surveillance of surgical site infection.

Conduct a scoping review on the development and use of digital tools for post-discharge surgical site infection surveillance. Scoping review. Science Direct, PubMed, Embase, Literatura Latino-Americana e do Caribe em Ciências da Saúde and Cumulative Index to Nursing and Allied Health Literature were searched from 2013 to May 2022. Six intellectual property registries were reviewed from 2013 to 2022. The review followed the Joanna Briggs Institute model, and included intellectual property records (applications, prototypes and software) and scientific articles published in any language on the development and/or testing of digital tools for post-discharge surveillance of surgical site infection among surgical patients aged 18 and over. One intellectual property record and 13 scientific articles were identified, covering 10 digital tools. The intellectual property record was developed and registered by a China educational institution in 2018. The majority of manuscripts were prospective cohort studies and randomized clinical trials, published between 2016 and 2022, and more than half were conducted in the United States. The population included adult patients undergoing cardiac, thoracic, vascular, abdominal, arthroplasty and caesarean surgery. The main functionalities of the digital tools were the previously prepared questionnaire, the attachment of a wound image, the integrated Web system and the evaluation of data by the health team, with post-discharge surgical site infection surveillance time between 14 and 30 days after surgery. Digital tools show promise for the surveillance of surgical site infection, collaborating with the early detection of wound infection. Mobile technology was favourable for detecting surgical site infections, reducing unnecessary visits to the health service, and increasing patient satisfaction. Technological advances in the health area open new perspectives for post-discharge surveillance of surgical site infection. WHAT IS ALREADY KNOWN?: There is underreporting of surgical site infections due to difficulties related to traditional methods of post-discharge surveillance. The use of digital tools within surgical site infection surveillance is increasing. Benefits of using digital tools within surgical site infection surveillance have been reported. WHAT HAS THIS STUDY ADDED TO OUR KNOWLEDGE?: This scoping review is one of the first to analyse the development and use of digital tools for post-discharge surveillance of surgical site infection in different countries. The main functionalities of digital tools are: structured questionnaires; attachment of wound images; integrated web systems; and evaluation of data by professionals. The use of mobile technology is favourable for detecting surgical site infections with a reduction in costs from face-to-face consultations and increased patient satisfaction. WHERE AND ON WHOM WILL THE RESEARCH HAVE AN IMPACT?: Healthcare providers can successfully use digital tools for surgical site infection post-discharge surveillance. Remote monitoring can reduce unnecessary patient visits to healthcare facilities. Policy makers can study how to implement digital platforms for remote patient monitoring. PRISMA statement for Scoping Reviews (PRISMA-ScR). No patient or public contribution. The study protocol was registered in the OSF (https://doi.org/10.17605/OSF.IO/BA8D6).

Array Optimization Based on Weighted and Hilbert–Schmidt Schemes of Multisensor Detection System

This paper presents a novel sensor array optimization scheme for multisensor electronic nose detection system. A system architecture with multisensor is first proposed to implement the medical detection, including the bacterial culture medium detection and animal wound infection detection. The system efficiency is evaluated by comparing with the field asymmetric ion mobility spectrometry (FAIMS) system. To further improve the detection effect and reduce the number of sensors of the electronic nose system, we then derive two sensor array optimization procedures based on factor analysis and Hilbert-Schmidt independence criterion, respectively. Specifically, the weighted factor analysis method and non-weighted factor analysis method are proposed via factor analysis. Besides, the Hilbert-Schmidt independence criterion optimization design of linear kernel function and Gaussian kernel function are also exploited. The experiment results highlight that compared with the existing approaches, the proposed weighted factor analysis optimization method and Hilbert-Schmidt independence criterion optimization method (Gaussian kernel function) can achieve a significant system performance.

Smart Dual-Sensor Wound Dressing for Monitoring Cutaneous Wounds.

Managing slow-healing wounds and associated complications is challenging, time-consuming, and expensive. Systematic collection, analysis, and dissemination of correct wound status data are critical for enhancing healing outcomes and reducing complications. However, traditional data collection approaches are often neither accurate nor user-friendly and require diverse skill levels, resulting in the collection of inconsistent and unreliable data. As an advancement to the authors' previously developed hydrogel-based smart wound dressing, here is reported an enhancedintegration of drug delivery and sensing (pH and glucose) modules for accelerated treatment and continuous monitoring of cutaneous wounds. In the currentstudy, growth factor delivery modules and an array of colorimetric glucose sensors are incorporated into the dressing to promote wound healing and extend the dressing's utility for diabetic wound treatment. Furthermore, the efficacy of the wound dressing in monitoring infection and supporting wound healing via antibiotic and growth factor delivery is investigated in mice models. The updated dressing reveals excellent healing benefits on non-infected and infected wounds, as well as real-time monitoring and early detection of wound infection.

Wearable battery-free smart bandage with peptide functionalized biosensors based on MXene for bacterial wound infection detection

Wound infection is a life-threatening healthcare issue that can cause severe pain, sepsis, and even amputation. Herein, to address the challenges of point-of-care wound analysis, a battery-free, wireless, and wearable smart bandage was developed for bacterial virulence factors detection. Typical biomarkers, sortase A and pyocyanin, corresponding to two major types of bacterial infection, Gram-positive Staphylococcus aureus and Gram-negative Pseudomonas aeruginosa, were detected with electrochemical differential pulse voltammetry. Ti3C2Tx MXene was applied to the electrode to enhance the sensitivity. Pyocyanin could transfer electrons with the electrode for sensing due to its redox characteristics, while a peptide labeled with the electroactive ferrocene was customized for the specific recognition of sortase A. The integration of near field communication module realized wireless energy harvesting and data transmission with the smartphone. The fully integrated system demonstrated good linearity and high sensitivity, with wide detection ranges of 1 pg/mL to 100 ng/mL for sortase A, and 1 μM to 100 μM for pyocyanin. Furthermore, the animal studies indicated the effectiveness of the smart bandage for multi-biomarker profiling of wound. This wearable system provides a noninvasive, convenient, and efficient platform for in situ bacterial virulence factors detection, offering great potential for the management of the infected wound.

Myeloperoxidase-based in-vitro test strip sensor for early detection of wound infections at the patient´s bedside

Early and precise identification of wound infection is still challenging to prevent and mitigate the onset of upcoming infections. Recently we have developed a sensor system based on the neutrophil-derived enzyme myeloperoxidase (MPO) and applied flow-based fluidics to allow the reliable detection of wound infection at a very early stage. However, still no easily applicable devices with low instrumental effort to enable early and accurate detection of wound infections at the patient´s bedside are available. We aimed to advance this preceding MPO- and flow-based sensor into an MPO-based in-vitro test strip sensor applying drop-based fluidics to be used at the patient´s bedside. Further, we aimed to implement a proof-of-concept one-point-calibration approach to improve the precision of the test strip sensor and to reduce heterogeneities deriving from sensor production. To change the fluidic concept of the preceding sensor system from flow-based to drop-based the composition of the functionalization solution was adapted. Further, two proof-of-concept one-point-calibration approaches were implemented and compared regarding sensor performance and applicability. Results showed a good correlation between sensor current and MPO concentration which proved the ability of the novel in-vitro test strip sensor to reliably detect wound infection at an early stage. Further, two proof-of-concept one-point-calibration approaches were successfully implemented, and one of these two was favored over the other due to its easier handling properties. This easily applicable in-vitro test strip sensor for early and accurate detection of wound infection at the bedside holds great promise to significantly improve wound management and to promote effective, rapid point-of-care diagnostics.

Rapid Colorimetric Detection of Wound Infection with a Fluidic Paper Device.

Current procedures for the assessment of chronic wound infection are time-consuming and require complex instruments and trained personnel. The incidence of chronic wounds worldwide, and the associated economic burden, urge for simple and cheap point-of-care testing (PoCT) devices for fast on-site diagnosis to enable appropriate early treatment. The enzyme myeloperoxidase (MPO), whose activity in infected wounds is about ten times higher than in non-infected wounds, appears to be a suitable biomarker for wound infection diagnosis. Herein, we develop a single-component foldable paper-based device for the detection of MPO in wound fluids. The analyte detection is achieved in two steps: (i) selective immunocapture of MPO, and (ii) reaction of a specific dye with the captured MPO, yielding a purple color with increasing intensity as a function of the MPO activity in infected wounds in the range of 20–85 U/mL. Ex vivo experiments with wound fluids validated the analytic efficiency of the paper-based device, and the results strongly correlate with a spectrophotometric assay.

Paper-Based Interleukin-6 Test Strip for Early Detection of Wound Infection.

The early stage of wound infection is always non-specific. Prompt intervention may help to prevent the wound from worsening. We developed a new protocol, based on previous research, that employs a paper-based IL-6 test strip used in combination with a spectrum-based optical reader to detect IL-6 in normal tissue (n = 19), acute wounds (n = 31), and chronic wounds (n = 32). Our data indicated the presence of significantly higher levels of IL-6 in acute wound tissues, but no significant difference in serum CRP. Receiver operating characteristics were used to determine clinical sensitivity and specificity of tissue IL-6 and systemic CRP. The area under the curve values were 0.87 and 0.63, respectively. The cut-off value of 30 pg/mL for IL-6 provided good sensitivity (75.0%) and superior specificity (88.9%). We found a high correlation between the IL-6 test strip and conventional ELISA results (R2 = 0.85, p < 0.001), and good agreement was also observed according to Bland-Altman analysis. We showed a promising role of tissue IL-6 to help early diagnosis of wound infection when clinical symptoms were non-specific. The advantages of this wound detection protocol included minimal invasiveness, small sample requirements, speed, sample preparation ease, and user-friendliness. This methodology could help care providers quickly clarify wound infection status and implement timely, optimal management.

Rapid, label-free pathogen identification system for multidrug-resistant bacterial wound infection detection on military members in the battlefield.

US military service members experiencing combat-related wounds have higher risk of infection by multidrug-resistant bacteria. The gold standard culture-based antimicrobial susceptibility testing (AST) is not feasible in the battlefield environment. Thus, a rapid deployable system for bacteria identification and AST directly from wound sample is urgently needed. We report the potential of a Rapid, Label-free Pathogen Identification (RAPID) diagnostic system based on ATR-FTIR method to detect and distinguish multi-drug resistant strains for six different species in the ESKAPEE group. Our RAPID system combines sample processing on-broad to isolate and enrich bacteria cells from wound sample, ATR-FTIR measurement to detect antimicrobial-induced bacterial cell spectral changes, and machine learning model for automated, objective, and quantitative spectral analysis and unknown sample classification. Based on experimental results, our RAPID system is a promising technology for label-free, sensitive (104 cfu/mL from mixture), species-specific (> 95% accuracy), rapid (< 10 min for identification, ~ 4 hours for AST) bacteria detection directly from wound samples.

Study on Sensor Array Optimization of Medical Electronic Nose for Wound Infection Detection

In order to improve the detection effect and simplify the number of sensors of electronic nose system for wound infection detection, the sensor arrays are optimized based on Hilbert-Schmidt independence criterion (HSIC) in this brief. Specifically, the HSIC optimization algorithm of Gaussian kernel function is exploited. The criterion of Hilbert-Schmidt independence is obtained by empirical estimation of norm of Hilbert-Schmidt cross-covariance operator. The main idea of its application in sensor array optimization is that the larger the empirical norm estimates of Hilbert-Schmidt cross-covariance operator, the stronger the correlation between sensor features and labels, the greater the role of sensor features in classification and recognition. The experimental results show that the HSIC optimization method (Gaussian kernel function) performs better than the linear discriminant analysis (LDA) method and the principal component analysis (PCA).

A soft intelligent dressing with pH and temperature sensors for early detection of wound infection.

Wound infection is a common clinical problem. Traditional detection methods can not provide infection early warning information in time. With the development of flexible electronics, flexible wearable devices have been widely used in the field of intelligent monitoring. Here, we describe the development of a soft wound infection monitoring system with pH sensors and temperature sensors. The measurement range of pH was 4–10, the fitting accuracy was 99.8%, and the response time was less than 6 s. The temperature sensor array showed good accuracy and short response times in the range of 30 °C to 40 °C. A series of in vitro tests and the use of a rat model of Staphylococcus aureus infection confirmed that this flexible detection system can monitor the pH and temperature changes occurring in the early stage of infection, which provides an effective reference for clinical application.

Wearable Sensors for the Detection of Biomarkers for Wound Infection.

Infection represents a major complication that can affect wound healing in any type of wound, especially in chronic ones. There are currently certain limitations to the methods that are used for establishing a clinical diagnosis of wound infection. Thus, new, rapid and easy-to-use strategies for wound infection diagnosis need to be developed. To this aim, wearable sensors for infection diagnosis have been recently developed. These sensors are incorporated into the wound dressings that are used to treat and protect the wound, and are able to detect certain biomarkers that can be correlated with the presence of wound infection. Among these biomarkers, the most commonly used ones are pH and uric acid, but a plethora of others (lactic acid, oxygenation, inflammatory mediators, bacteria metabolites or bacteria) have also been detected using wearable sensors. In this work, an overview of the main types of wearable sensors for wound infection detection will be provided. These sensors will be divided into electrochemical, colorimetric and fluorimetric sensors and the examples will be presented and discussed comparatively.

A wireless and battery-free wound infection sensor based on DNA hydrogel.

The confluence of wireless technology and biosensors offers the possibility to detect and manage medical conditions outside of clinical settings. Wound infections represent a major clinical challenge in which timely detection is critical for effective interventions, but this is currently hindered by the lack of a monitoring technology that can interface with wounds, detect pathogenic bacteria, and wirelessly transmit data. Here, we report a flexible, wireless, and battery-free sensor that provides smartphone-based detection of wound infection using a bacteria-responsive DNA hydrogel. The engineered DNA hydrogels respond selectively to deoxyribonucleases associated with pathogenic bacteria through tunable dielectric changes, which can be wirelessly detected using near-field communication. In a mouse acute wound model, we demonstrate that the wireless sensor can detect physiologically relevant amounts of Staphylococcus aureus even before visible manifestation of infection. These results demonstrate strategies for continuous infection monitoring, which may facilitate improved management of surgical or chronic wounds.

Ubiquitination Flow Repressors: Enhancing Wound Healing of Infectious Diabetic Ulcers through Stabilization of Polyubiquitinated Hypoxia-Inducible Factor-1α by Theranostic Nitric Oxide Nanogenerators.

Current treatments for diabetic ulcers (DUs) remain unsatisfactory due to the risk of bacterial infection and impaired angiogenesis during the healing process. The increased degradation of polyubiquitinated hypoxia-inducible factor-1α (HIF-1α) compromises wound healing efficacy. Therefore, the maintenance of HIF-1α protein stability might help treat DU. Nitric oxide (NO) is an intrinsic biological messenger that functions as a ubiquitination flow repressor and antibacterial agent; however, its clinical application in DU treatment is hindered by the difficulty in controlling NO release. Here, an intelligent near-infrared (NIR)-triggered NO nanogenerator (SNP@MOF-UCNP@ssPDA-Cy7/IR786s, abbreviated as SNP@UCM) is presented. SNP@UCM represses ubiquitination-mediated proteasomal degradation of HIF-1α by inhibiting its interaction with E3 ubiquitin ligases under NIR irradiation. Increased HIF-1α expression in endothelial cells by SNP@UCM enhances angiogenesis in wound sites, promoting vascular endothelial growth factor (VEGF) secretion and cell proliferation and migration. SNP@UCM also enables early detection of wound infections and ROS-mediated killing of bacteria. The potential clinical utility of SNP@UCM is further demonstrated in infected full-thickness DU model under NIR irradiation. SNP@UCM is the first reported HIF-1α-stabilizing advanced nanomaterial, and further materials engineering might offer a facile, mechanism-based method for clinical DU management.

Battery‐Free and Wireless Smart Wound Dressing for Wound Infection Monitoring and Electrically Controlled On‐Demand Drug Delivery

AbstractReal‐time monitoring wound status and providing timely therapies with smart wound dressing is a promising way to treat wound infections and accelerate the healing process. Herein, to establish a closed‐loop monitoring and treatment system, a fully integrated, battery‐free, and wireless smart wound dressing for wound infection detection and on‐demand drug delivery is developed using flexible electronics. The smart wound dressing integrated with the near field communication module can realize wireless power harvest and data transmission, on‐site signal processing, and drug delivery control, through the miniaturized circuit and smartphone. The temperature, pH, and uric acid of the wound is detected simultaneously by the developed sensors to assess wound conditions. Meanwhile, the drug delivery electrode in the dressing is used to provide on‐demand infection treatment by the electrically controlled antibiotics delivery. Through in vitro antibacterial experiments and in situ animal studies, it is shown that the dressing can effectively inhibit bacterial growth and accelerate wound healing, which fully validates its effectiveness in the wound treatment. Utilizing the advantages of near‐field communication and flexible electronics, the battery‐free and integrated design of sensing and treatment provides a promising solution for the development of a closed‐loop biomedical system integrating monitoring, diagnosis, and therapy.

Toward a Closed Loop, Integrated Biocompatible Biopolymer Wound Dressing Patch for Detection and Prevention of Chronic Wound Infections.

Chronic wound infections represent a significant burden to healthcare providers globally. Often, chronic wound healing is impeded by the presence of infection within the wound or wound bed. This can result in an increased healing time, healthcare cost and poor patient outcomes. Thus, there is a need for dressings that help the wound heal, in combination with early detection of wound infections to support prompt treatment. In this study, we demonstrate a novel, biocompatible wound dressing material, based on Polyhydroxyalkanoates, doped with graphene platelets, which can be used as an electrochemical sensing substrate for the detection of a common wound pathogen, Pseudomonas aeruginosa. Through the detection of the redox active secondary metabolite, pyocyanin, we demonstrate that a dressing can be produced that will detect the presence of pyocyanin across clinically relevant concentrations. Furthermore, we show that this sensor can be used to identify the presence of pyocyanin in a culture of P. aeruginosa. Overall, the sensor substrate presented in this paper represents the first step toward a new dressing with the capacity to promote wound healing, detect the presence of infection and release antimicrobial drugs, on demand, to optimized healing.

A Unified Framework for Automatic Detection of Wound Infection with Artificial Intelligence

Background: The surgical wound is a unique problem requiring continuous postoperative care, and mobile health technology is implemented to bridge the care gap. Our study aim was to design an integrated framework to support the diagnosis of wound infection. Methods: We used a computer-vision approach based on supervised learning techniques and machine learning algorithms, to help detect the wound region of interest (ROI) and classify wound infection features. The intersection-union test (IUT) was used to evaluate the accuracy of the detection of color card and wound ROI. The area under the receiver operating characteristic curve (AUC) of our model was adopted in comparison with different machine learning approaches. Results: 480 wound photographs were taken from 100 patients for analysis. The average value of IUT on the validation set with fivefold stratification to detect wound ROI was 0.775. For prediction of wound infection, our model achieved a significantly higher AUC score (83.3%) than the other three methods (kernel support vector machines, 44.4%; random forest, 67.1%; gradient boosting classifier, 66.9%). Conclusions: Our evaluation of a prospectively collected wound database demonstrates the effectiveness and reliability of the proposed system, which has been developed for automatic detection of wound infections in patients undergoing surgical procedures.