Early Detection Of Infection Research Articles

Artificial Intelligence and Neutrosophic Machine learning in the Diagnosis and Detection of COVID 19

The world has always suffered and from diseases and epidemics, and the coronavirus is one of the most dangerous viruses that threatened human life that requires the use of all scientific methods and means to respond to it and reduce its spread by early detection of infections and taking necessary measures In view of the significant role that artificial intelligence plays in most fields of science, it has become one of the most important scientific methods used to resolve complex issues and has been harnessed in medical diagnosis, one of the most complex areas. Many AI and machine learning algorithms have been used to diagnose and detect diseases in general and coronavirus in particular. The support vector machine (svm) machine algorithm was one of the most important algorithms in this area and is one of the most effective compilations used in the knowledge extraction process In spite of all this, the results they present remain incomplete because classification issues do not deal with cognitive uncertainties such as ambiguity, neutrality and inconsistency associated with perception of human thinking, This adversely affects the work of a classic support vector machine and affects the accurate diagnosis of the disease To solve this problem, we have done this research using a Neutrosophic Support Vector Machine because it takes into account all possible cases during the study of the sample and it reduces the impact of extreme values. This increases the accuracy of the results when diagnosing coronavirus symptoms. The study was conducted according to the following steps: 1. We extract features from chest radiographs based on GLCM 2. We form a neutrosophic dataset. 3. We train Neutrosophic Support Machine N-SVM on new data. 4. We record the results. Comparing the results, we got using the upgraded N-SVM algorithm with the classic SVM algorithm results we found that it gives a more accurate diagnosis of the disease.

Avoid the Possibility of Remove of Osteosynthesis Device Secondary to Infection of the Lumbar Region

Infections after spinal surgery are one of the battles and a cause for concern for any spinal surgeon. For its prevention, it is necessary to control the previous situation of the patients, strict prophylaxis protocols in the operating room and mechanisms for early detection of infection. Acting at these three levels will allow us to reduce the rate of post-surgical spine infections and avoid new interventions and more suffering for our patients. We present the use of a product that tries to avoid the need to remove the implant in the event of a wound infection.

Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine

Bacterial infections can affect the skin, lungs, blood, and brain, and are among the leading causes of mortality globally. Early infection detection is critical in diagnosis and treatment but is a time- and work-consuming process taking several days, creating a hitherto unmet need to develop simple, rapid, and accurate methods for bacterial detection at the point of care. The most frequent type of bacterial infection is infection of the urinary tract. Here, we present a wireless-enabled, portable, potentiometric sensor for E. coli. E. coli was chosen as a model bacterium since it is the most common cause of urinary tract infections. The sensing principle is based on reduction of Prussian blue by the metabolic activity of the bacteria, detected by monitoring the potential of the sensor, transferring the sensor signal via Bluetooth, and recording the output on a laptop or a mobile phone. In sensing of bacteria in an artificial urine medium, E. coli was detected in ~4 h (237 ± 19 min; n = 4) and in less than 0.5 h (21 ± 7 min, n = 3) using initial E. coli concentrations of ~103 and 105 cells mL-1, respectively, which is under or on the limit for classification of a urinary tract infection. Detection of E. coli was also demonstrated in authentic urine samples with bacteria concentration as low as 104 cells mL-1, with a similar response recorded between urine samples collected from different volunteers as well as from morning and afternoon urine samples.

The potential of non-movement behavior observation method for detection of sick broiler chickens.

The poultry industry, which produces excellent sources of protein, suffers enormous economic damage from diseases. To solve this problem, research is being conducted on the early detection of infection according to the behavioral characteristics of poultry. The purpose of this study was to evaluate the potential of a non-movement behavior observation method to detect sick chickens. Forty 1-day-old Ross 308 males were used in the experiments, and an isolator equipped with an Internet Protocol (IP) camera was fabricated for observation. The chickens were inoculated with Salmonella enterica serovar Gallinarum A18-GCVP-014, the causative agent of fowl typhoid (FT), at 14 days of age, which is a vulnerable period for FT infection. The chickens were continuously observed with an IP camera for 2 weeks after inoculation, chickens that did not move for more than 30 minutes were detected and marked according to the algorithm. FT infection was confirmed based on clinical symptoms, analysis of cardiac, spleen and liver lesion scores, pathogen re-isolation, and serological analysis. As a result, clinical symptoms were first observed four days after inoculation, and dead chickens were observed on day six. Eleven days after inoculation, the number of clinical symptoms gradually decreased, indicating a state of recovery. For lesion scores, dead chickens scored 3.57 and live chickens scored 2.38. Pathogens were re-isolated in 37 out of 40 chickens, and hemagglutination test was positive in seven out of 26 chickens. The IP camera applied with the algorithm detected about 83% of the chickens that died in advance through non-movement behavior observation. Therefore, observation of non-movement behavior is one of the ways to detect infected chickens in advance, and it appears to have potential for the development of remote broiler management system.

Discrepancy of C-Reactive Protein, Procalcitonin and Interleukin-6 at Hospitalization: Infection in Patients with Normal C-Reactive Protein, Procalcitonin and High Interleukin-6 Values.

C-reactive protein (CRP) or procalcitonin (PCT) alone has limitations in the early detection of infection or inflammation due to shortcomings in specificity and varied cut-off values. Recently, interleukin (IL)-6 has been assessed, but it is not known to what extent the three values are homogeneous in reality. This retrospective study was conducted with two large datasets (discrepancy set with results within 24 h of admission [7149 patients] and follow-up set until 2 weeks of hospital stay [5261 tests]) consisting of simultaneous examinations of CRP, PCT, and IL-6 between January 2015 and August 2021. The specific discrepant group (n = 102, 1.4%) with normal CRP (<10 mg/L) and PCT (<0.1 ng/mL) and high IL-6 (≥100 pg/mL) values was extracted from the discrepancy set. Dimensionality reduction and visualization were performed using Python. The three markers were not clearly clustered after t-distributed stochastic neighbor embedding. Pearson's correlation coefficients between two markers were substantially low (0.23-0.55). Among the high normalized IL-6 levels (≥0.5) (n = 349), 17.8% and 38.7% of CRP and PCT levels were very low (≤0.01). 9.2% and 13.4% of normal CRP (n = 1522) had high PCT (≥0.5 ng/mL) and IL-6 (≥100 pg/mL) values, respectively. Infection and bacteremia among 102 patients occurred in 36 (35.3%) and 9 (8.8%) patients, respectively. In patients with bacteremia, IL-6 was the first to increase, followed by PCT and CRP. Our study revealed that CRP, PCT, and IL-6 levels were considerably discrepant, which could be misinterpreted if only CRP tests are performed.

Protecting the environment from pollution through early detection of infections on crops using the deep belief network in paddy

Paddy is the staple food for more than 50% of 138 billion Indian population. Inorder to meet with the growing demand, farmers often resort to application of synthetic fertilizers and plant protection chemicals indiscriminately. Rice is susceptible to diseases, pests, and nutrient deficiencies likewise other crops. Ignorant about the reasons for damage farmers apply synthetic chemicals that too in exorbitant rates. Excessive use of these chemical molecules alters the soil characteristics and causes environmental pollution as well. As a result, entire eco system gets affected. To overcome this, it is necessary to identify the reason for damage early and necessary treatments should be done in the beginning stages itself. Early detection can be done by assessing the leaves and culm of paddy. Assessment by naked eye may misinterpret symptoms and if artificial intelligence is used such misinterpretations can be minimised. This study proposes an automatic classification system using artificial intelligence and image processing for identification of diseased, pest infested and nutrient deficient crop using symptoms exhibited in the leaves and culm of paddy. Kaggle data set was being used to test the performance of the proposed classification system for metrics specificity, precision, sensitivity, F1-score and accuracy. The proposed work provides a specificity, precision, sensitivity, F1-score and accuracy of 97.1%, 97.6%, 96.2%, 96.8%, and 98.1% respectively. The evaluation results indicate that the proposed algorithm outperforms other recent rice leaf disease, pest and nutrient deficiency classification algorithms. Thus, precise identification of reasons for infection allows farmers to use specific control methods with less toxic chemicals or through eco-friendly methods. Thus, environmental pollution and soil characteristics can be saved and in turn can save the environment and its creatures.

ASSESSMENT AND EVALUATING THE KNOWLEDGE OF A SAMPLE OF PRIMARY SCHOOL TEACHERS ON SAFETY MEASURES AND FIRST AID IN THE SCHOOL ENVIRONMENT (FIELD STUDY)

The current research aims to evaluate the knowledge of a sample of primary school teachers from different disciplines in The City of Baghdad, where the size of the random research sample (50 teachers) distributed on both sides of al-Karkh and Al-Rasafa, About safety measures and first aid and their role in implementing those measures and carrying out first aid for students in the event of accidents within the school environment and then arranging the transfer of the injured person to the nearest hospital within the geographical area of the school, The aim of the research was also to evaluate that knowledge by making recommendations and suggestions. The descriptive analytical method of the research sample vocabulary was adopted using the resolution tool that set its questions to achieve the above-mentioned research objectives. Hence the scheduling and presentation of research data and the adoption of the percentage as a statistical means of research and then presenting the findings and conclusions followed by a review of the most important recommendations and proposals that may contribute to raising the efficiency and role of primary school teachers in the field of health, safety and accident prevention, as well as early detection of infection swells among pupils, Finally, the research was appendixed to the most important sources used, which were used to record search information‎‎.‎

Cytomegalovirus infection in pregnant women - threats, diagnosis and treatment

Cytomegalovirus is one of the most widespread DNA viruses, with 90% of women of childbearing age in Poland infected with it. Infection poses a risk to the mother as well as the fetus, as the virus can cross the placenta and damage the fetus. The purpose of this paper is to review scientific publications from 2017-2022, which describe the course of cytomegalovirus infection in pregnant women, the risks to the mother and fetus associated with the infection, methods of diagnosing the infection in the pregnant woman and the fetus, as well as treatment of cytomegalovirus infection and directions for vaccine research.
 The most common complications of congenital cytomegalovirus infection include hearing loss, mental developmental delays and miscarriage. The infection can be detected in the pregnant woman by immunological testing, while polymerase chain reaction is used in the fetus and newborn. Early detection of infection in a pregnant woman allows the implementation of treatment which includes ganciclovir, valganciclovir, acyclovir and valacyclovir. A vaccine against cytomegalovirus has not been developed. Particularly important in the prevention of infection is to conduct educational activities regarding the routes of transmission of the virus and the consequences of congenital infection for the fetus.
 Cytomegalovirus infections among pregnant women. It is important to monitor fetal development and possibly diagnose for congenital CMV infection in case of abnormalities, and the best diagnostic method is polymerase chain reaction testing. For the treatment of congenital CMV infection, acyclovir and valacyclovir are preferred, and therapy should be implemented for specific indications. Attention should be paid to educating women about infections caused by cytomegalovirus.

A click chemistry amplified nanopore assay for ultrasensitive quantification of HIV-1 p24 antigen in clinical samples

Despite major advances in HIV testing, ultrasensitive detection of early infection remains challenging, especially for the viral capsid protein p24, which is an early virological biomarker of HIV-1 infection. Here, To improve p24 detection in patients missed by immunological tests that dominate the diagnostics market, we show a click chemistry amplified nanopore (CAN) assay for ultrasensitive quantitative detection. This strategy achieves a 20.8 fM (0.5 pg/ml) limit of detection for HIV-1 p24 antigen in human serum, demonstrating 20~100-fold higher analytical sensitivity than nanocluster-based immunoassays and clinically used enzyme-linked immunosorbent assay, respectively. Clinical validation of the CAN assay in a pilot cohort shows p24 quantification at ultra-low concentration range and correlation with CD4 count and viral load. We believe that this strategy can improve the utility of p24 antigen in detecting early infection and monitoring HIV progression and treatment efficacy, and also can be readily modified to detect other infectious diseases.

The Prognosis of Diabetic Foot Ulcer is Independent of age? A Comparative Analysis of the Characteristics of Patients with Diabetic Foot Ulcer in Different age Groups: A Cross-Sectional Study from China.

Background: With younger onset age of type 2 diabetes mellitus (T2DM), the incidence of diabetic foot ulcer (DFU) in young and middle-aged adults is also increasing. Elucidating the distinctive characteristics of DFU in different ages and exploring the influence of age on the prognosis of DFU are crucial to the improvement of DFU treatments. Methods: 684 patients hospitalized for DFU in the department of endocrinology were recruited and assigned into the young and middle-aged group (age <65 years old) and the elderly group (age ≥65 years old). Demographic data and clinical features were compared between two groups. Results: Compared with the elderly group, the young and middle-aged group had higher proportion of males (72.3% vs 49.6%, P < .01) and smokers (52.5% vs 35.8%, P < .01), shorter duration of diabetes mellitus (155 months vs 196 months, P < .01), higher levels of glycosylated hemoglobin (9.3% vs 8.7%, P < .01), lower ratio of ankle-brachial index <0.9 (25.8% vs 51.1%, P < .01) and higher levels of c-reactive protein and erythrocyte sedimentation rate (14 mg/L vs 10 mg/L, P < .05; 36 mm/h vs 30 mm/h, P < .05). The prevalence of diabetic peripheral neuropathy and Wagner Grade were similar in two groups. Of note, the prognosis was similar in different age groups, as there were no significant differences in the healing rate (59.7% vs 60.1%, P > .05), healing time (30 days vs 22 days, P > .05) and minor amputation rate (11.9% vs 8.7%, P > .05). Conclusions: We found that no evidence to suggest a better prognosis with younger DFU patients. Compared with elderly ones, young and middle-aged patients were characterized by a higher proportion of smoking, worse glycemic control, higher inflammatory biomarkers but less severe lower limb ischemia, indicating that smoking cessation, strict blood glucose control and early detection of infection were crucial for improving the prognosis of young and middle-aged diabetic DFU patients.

POS-103 THE SPECTRUM OF POST-TRANSPLANT INFECTIOUS COMPLICATIONS AND THEIR DETERMINANTS IN A TERTIARY CARE FROM NORTHERN INDIA

Infections account for a substantial proportion of morbidity and mortality in kidney transplant recipients, especially so, in developing countries in the tropics. Existing regional protocols for screening and early detection of infections both pre- and post- transplant can be enhanced by gaining additional insights into the clinical spectrum and determinants of these infections in kidney transplant recipients. The aim of the present study is to present the clinical spectrum of bacterial, viral and fungal infections in kidney transplant recipients in the last five years, and study the determinants of these infections.

Detecting early physiologic changes through cardiac implantable electronic device data among patients with COVID-19

BackgroundCardiac implantable electronic devices (CIEDs) may enable early identification of COVID-19 to facilitate timelier intervention.ObjectiveTo characterize early physiologic changes associated with the onset of acute COVID-19 infection, as well as during and after acute infection, among patients with CIEDs.MethodsCIED sensor data from March 2020 to February 2021 from 286 patients with a CIED were linked to clinical data from electronic health records. Three cohorts were created: known COVID-positive (n = 20), known COVID-negative (n = 166), and a COVID-untested control group (n = 100) included to account for testing bias. Associations between changes in CIED sensors from baseline (including HeartLogic index, a composite index predicting worsening heart failure) and COVID-19 status were evaluated using logistic regression models, Wilcoxon signed rank tests, and Mann-Whitney U tests.ResultsSignificant differences existed between the cohorts by race, ethnicity, CIED device type, and medical admissions. Several sensors changed earlier for COVID-positive vs COVID-negative patients: HeartLogic index (mean 16.4 vs 9.2 days [P = .08]), respiratory rate (mean 8.5 vs 3.9 days [P = .01], and activity (mean 8.2 vs 3.5 days [P = .008]). Respiratory rate during the 7 days before testing significantly predicted a positive vs negative COVID-19 test, adjusting for age, sex, race, and device type (odds ratio 2.31 [95% confidence interval 1.33–5.13]).ConclusionPhysiologic data from CIEDs could signal early signs of infection that precede clinical symptoms, which may be used to support early detection of infection to prevent decompensation in this at-risk population.

Different outcomes of Canid alphaherpesvirus 1 infection in a litter of puppies: The silent viral spread

AbstractCanid alphaherpesvirus 1 causes worldwide infection with different outcomes in neonatal puppies and adults, followed by latency. Here, we report the varied outcomes of Canid alphaherpesvirus 1 infection in a Dalmatian litter of 12 puppies in Italy. The diagnosis of Canid alphaherpesvirus 1 was obtained by polymerase chain reaction on internal organs of one of the dead puppies. Another three puppies (one stillborn and two dead within the first 3 days of life) were not investigated (owner's request). Based on a positive result, an epidemiological investigation was performed. The outcome of the infection was particularly variable within the litter (one dead puppy, three healthy polymerase chain reaction‐positive and another five virologically negative puppies). The present case report indicates the relevance of early detection of infection, how the features of herpetic infection can vary in the same litter and how viral spread can be underestimated in asymptomatic dogs. Effective control of Canid alphaherpesvirus 1 infection should include hygienic measures and screening tests, especially in situations in which dogs, even asymptomatic, are mixed.

C-Reactive Protein Velocity (CRPv) as a New Biomarker for the Early Detection of Acute Infection/Inflammation.

C-reactive protein (CRP) is considered a biomarker of infection/inflammation. It is a commonly used tool for early detection of infection in the emergency room or as a point-of-care test and especially for differentiating between bacterial and viral infections, affecting decisions of admission and initiation of antibiotic treatments. As C-reactive protein is part of a dynamic and continuous inflammatory process, a single CRP measurement, especially at low concentrations, may erroneously lead to a wrong classification of an infection as viral over bacterial and delay appropriate antibiotic treatment. In the present review, we introduce the concept of C-reactive protein dynamics, measuring the velocity of C-reactive protein elevation, as a tool to increase this biomarker’s diagnostic ability. We review the studies that helped define new metrics such as estimated C-reactive protein velocity (velocity of C-reactive protein elevation from symptoms’ onset to first C-reactive protein measurement) and the measured C-reactive protein velocity (velocity between sequential C-reactive protein measurements) and the use of these metrics in different clinical scenarios. We also discuss future research directions for this novel metric.

Silent Infection of Highly Pathogenic Avian Influenza Virus (H5N1) Clade 2.3.4.4b in a Commercial Chicken Broiler Flock in Italy.

From October 2021 to January 2022, different incursions of clade 2.3.4.4b H5N1 HPAIV (Highly Pathogenic Avian Influenza Virus) occurred in several Italian regions with its main diffusion in Densely Poultry Populated Areas (DPPAs) of north-eastern Italy. Monitoring and control activities applied in the affected area clearly evidenced that turkeys and broilers were the most affected species, although several flocks of broilers at times resulted HPAIV H5N1 infected in absence of increased mortality and/or clinical signs. Thus, an approach based on sampling dead birds was adopted in the broiler sector to improve the early detection of infection; this protocol allowed us to confirm that 15 farms were HPAIV-infected with birds ready to be delivered to the slaughterhouse. The aim of this report is to describe the results of the diagnostic activities carried out in one HPAIV H5N1-infected broiler farm, three days after laboratory confirmation during the pre-movement testing without showing increased mortality or clinical signs. Thus, clinical signs, daily cumulative mortality rate (CMR), virus shedding, seroconversion, pathobiology of clade 2.3.4.4b H5N1 HPAIV as well as Avian Influenza Viruses (AIVs) environmental contamination were thoroughly examined in the infected holding. Such in-depth investigation demonstrated low infection prevalence in live birds, low environmental contamination, no seroconversion for AIVs, gross and microscopic findings compatible with systemic infection with peracute death in H5N1 HPAIV-infected birds.

Passive Sweat Based Electrochemical Sensor for Rapid Detection of IL-6

Introduction: Portable, on demand biosensing has become a key element for rapid detection of disease, particularly conditions that progress rapidly, such as infections and trauma in response to injury. Severe infections or internal traumas caused by injury can rapidly progress from the moment of onset, often before a patient has started to show symptoms, leading to progressive organ damage. In order to promptly get access to treatment, rapid testing for infection/trauma is necessary for individuals who experience a physical injury. When a person undergoes a traumatic injury, the immune system releases inflammatory cytokines, such as Interleukin-6 (IL6), in response. These cytokines induce inflammation at the site of injury as a defense mechanism against infection and further injury. The inflammatory cytokines are excreted through sweat at levels detectable by an electrochemical sensor. Using a portable, sweat-collecting electrochemical sensor, we have developed a sweat-based sensor that can detect IL6 within ultralow volumes of sweat (1-5 ul) at concentrations as low as 1 pg/ml, for rapid, noninvasive detection of infection and traumatic injury. Materials and Methods: The electrochemical sensor consists of zinc oxide electrodes on a flexible substrate. IL6 antibodies were immobilized onto the sensor surface using a thiol linker chemistry. Sensor response was measured using Electrochemical Impedance Spectroscopy (EIS) of synthetic sweat dosed with concentrations of IL6 within their physiological ranges. The spike dosing results were verified by a human study, where subjects induced IL6 elevation in their sweat. Results and Discussion: Sensor response to IL6 spike doses in synthetic sweat showed a dose dependent response to concentration of IL6, as illustrated by the Nyquist plot for sensor response to IL6 in Figure 1. These results were verified by the sensor response to pre- and post-exercise sweat of human subjects, which demonstrates an increase in IL6 levels after 10 minutes of anaerobic exercise for all subjects. This increase in IL6 post-exercise was shown to be significant for all subjects with 95% confidence using a paired T test. Conclusion: This study presents a noninvasive electrochemical sensor for rapid and early detection of infection or traumatic injury in response to a physical injury. The sensor exhibits a dose dependent response to IL6, a marker expressed at the time of injury. Sensor capability was demonstrated with human sweat pre- and post-exercise, in order to simulate the conditions following a traumatic injury, for which a significant increase in sensor response post-exercise was observed. Figure 1. Nyquist plot of Electrochemical Impedance Spectroscopy assay of IL6 in synthetic sweat. Figure 1

Feasibility of detecting apple scab infections using low-cost sensors and interpreting radiation interactions with scab lesions

ABSTRACT Apple scab is a disease caused by the fungus Venturia inaequalis (Cke.) Wint. which can spread rapidly throughout orchards diminishing tree productivity and causing huge losses in marketable fruit. Efficient orchard reconnaissance and early detection of infections can inform fungicide applications for effective disease control and a range of new low-cost sensors offer a means of imaging orchards as the basis of scab detection. This study evaluates the potential contribution of three imaging devices: a multispectral (VIS-NIR) camera, thermal camera and a 3D sensor, for the detection of scab on young apple plants. In a controlled experiment, apple seedings were infected with scab and disease progression was imaged daily under natural illumination conditions in a glasshouse with minimal image processing. Whilst the thermal and 3D sensors images were deemed unsuitable for scab detection, the high-resolution multispectral imagery was exceptionally effective, with the NIR band (800–1000 nm) permitting the earliest scab detection due to the substantially lower reflectance of the fungal structures of V. inaequalis relative to healthy leaf tissue. We offer a model of near-infrared radiation interactions with the fungus and leaf interactions to explain reflectance characteristics of scab-infected leaves throughout the growth cycle of the pathogen. The simple, low-cost remote-sensing approach developed here holds considerable promise for providing timely information on tree infection to improve the efficiency of apple scab disease management routines.

Decision support-tools for early detection of infection in older people (aged> 65 years): a scoping review

BackgroundInfection is more frequent, and serious in people aged > 65 as they experience non-specific signs and symptoms delaying diagnosis and prompt treatment. Monitoring signs and symptoms using decision support tools (DST) is one approach that could help improve early detection ensuring timely treatment and effective care.ObjectiveTo identify and analyse decision support tools available to support detection of infection in older people (> 65 years).MethodsA scoping review of the literature 2010–2021 following Arksey and O’Malley (2005) framework and PRISMA-ScR guidelines. A search of MEDLINE, Cochrane, EMBASE, PubMed, CINAHL, Scopus and PsycINFO using terms to identify decision support tools for detection of infection in people > 65 years was conducted, supplemented with manual searches.ResultsSeventeen papers, reporting varying stages of development of different DSTs were analysed. DSTs largely focussed on specific types of infection i.e. urine, respiratory, sepsis and were frequently hospital based (n = 9) for use by physicians. Four DSTs had been developed in nursing homes and one a care home, two of which explored detection of non- specific infection.ConclusionsDSTs provide an opportunity to ensure a consistent approach to early detection of infection supporting prompt action and treatment, thus avoiding emergency hospital admissions. A lack of consideration regarding their implementation in practice means that any attempt to create an optimal validated and tested DST for infection detection will be impeded. This absence may ultimately affect the ability of the workforce to provide more effective and timely care, particularly during the current covid-19 pandemic.

ID:16381 To Explant or Not to Explant: Differentiating Between IPG Pocket Hematoma and Infection

Infection is a known complication of spinal cord stimulator (SCS) implantation and has an estimated incidence of 2.4 to 3.1%. Most present as pocket infections and the feared complication of epidural abscess is rare. However, there is a paucity of data in the literature regarding the incidence of IPG pocket hematomas which share signs and symptoms with infection. While early detection of infection is based on physical examination, laboratory values, and imaging, these can all have significant overlap with IPG hematomas.

Trend of Perioperative CRP (C-Reactive Protein) Levels in Non-Infected Total Knee Arthroplasty

The aim of this prospective study was to define the perioperative trend of C-reactive protein (CRP) in non-infected total knee arthroplasty (TKA). CRP was evaluated in 42 patients the day before surgery and 4 and 30 days after surgery. Functional and radiological evaluation was scheduled for 3, 6, and 12 months after surgery. Preoperatively, the median CRP was 3.2 mg/L (IQR,3.2-4.2) (reference range, 0-5 mg/L); 4 and 30 days after surgery, it measured 57.6 mg/L (IQR,36.1-96.4) and 5.3 mg/L (IQR,3.0-11.8), respectively. There were significant differences between the CRP preoperatively and 4 days after surgery (p<0.001) and between CPR levels 4 and 30 days after surgery (p<0.001) but not between CRP values preoperatively and 30 days after surgery (p=0.181). Higher preoperative CRP was associated to heart disease and chronic renal failure (r=0.329, p=0.036, and r=0.437, p=0.004, respectively). Four days after surgery, higher CRP was associated to older patients (r=0.311, p=0.048). In summary, 30 days after primary non-infected TKA, CRP levels were comparable to preoperative values. Older age and comorbidities should be carefully evaluated using postoperative CRP as diagnostic marker for the early detection of infection.