Kappa Statistic Value Research Articles

Correlation of Immunohistochemical Biomarkers and Differential Staining Techniques to Investigate the Role of Subepithelial Hyalinization in the Aggressiveness of Odontogenic Keratocyst.

Odontogenic Keratocysts (OKCs) are known for their aggressive behavior along with rapid expansion. Subepithelial hyalinization (SEH) is one of the causes of recurrence. The ability to predict this biological behaviorhistologically may help medical experts choose the best course of action. To investigate the aggressiveness of odontogenic keratocyst caused by SEH and its recurrence tendency in the north Indian population, this study will link differential staining methods with immunohistochemistry biomarkers that can be used in routine investigative procedures. Consequently, the evaluation and grading of SEH were established by measuring from the basement membrane to the extent of connective tissue. The levels were correlated to Ki67, Alcian blue, and O -safranine for validation. Forty OKCs were examined for the histological investigation of SEH using the immunohistochemical marker Ki67 and differential staining with O-safranine and Alcian Blue. The histological trait of separation of epithelium from the connective tissue interface due to SEH was noted. SEH-positive cases that were evaluated with Ki67, had increased proliferative activity. The differential staining techniques were validated with Ki67, cross-tabulations in SPSS, and kappa statistic value was given to analyze the results. Spearman's rank correlation was done between Ki67 vs Alcian blue and O-Safranine. A p value of less than < 0.05 was considered statistically significant. In SEH-positive cases, a higher proliferative index was observed. Additionally, histological metrics were statistically significantly higher in SEH-positive cases. Consequently, SEH is a reliable histopathological indicator in OKC for predicting recurrence. The presence of SEH indicates that OKCs are more likely to recur.

Molecular and serological prevalence of Leptospira spp. among slaughtered cattle and associated risk factors in the Bahr El Ghazal region of South Sudan

IntroductionLeptospirosis is a neglected emerging and zoonotic disease reported worldwide. This study sought to determine the molecular and serological prevalence of Leptospira spp. and the associated risk factors in slaughtered cattle from the Bahr El Ghazal region of South Sudan.Materials and methodsBetween January 16th and February 25th, 2023, blood and urine samples were collected from 402 cattle at the Lokoloko Municipal Slaughterhouse in Western Bahr El-Ghazal State. Serum samples were tested using the microscopic agglutination test (MAT), with a panel of 12 serovars (sv) from 12 serogroups (sg) and 4 species (spp) of Leptospira spp. These serovars had been previously identified in Sudan and the East African region. Simultaneously, 400 corresponding urine samples were screened using qualitative real-time polymerase chain reaction (PCR) to detect the shedding of Leptospira spp. in urine. To identify the associated risk factors, the age, sex, breed and body condition score of each sampled cattle was noted at the time of sampling and subsequently analysed using logistic regression models.ResultsAmong the 402 serum samples screened, a substantial 81.8% (329/402, 95% CI 77.9–85.3) displayed seropositivity for Leptospira spp. with a MAT titre ≥ 100. The prevalence of urine shedding determined by PCR was 6% (23/400, 95% CI 3.8–8.4), while probable recent leptospirosis with a MAT ≥ 1:800 was observed in 33.1% (133/402, 95% CI 28.6–37.8) of the cattle. Multiple reactions were detected in 34.8% (140/402, 95% CI 30.6–39.5) serum samples. The seropositivity was against L. borgpetersenii sg. Tarassovi (78.6%; 316/402, 95% CI 74.4–82.3), followed by L. borgpetersenii sg. Ballum at 20.4% (82/402, 95% CI, 16.7–24.4%), L. kirschneri sg. Autumnalis At 8.7% (35/402, 95% CI 5.7–11.7), L. interrogans sg. of Pomona at 7.0% (28/402, 95% CI 4.5–9.5), and L. interrogans sg. Hebdomadis was 5.0% (20/402, 95% CI 2.8–7.2). Several risk factors are associated with seropositivity. Older animals (≥ 2 years) had 2.0 times greater odds (95% CI 1.14–3.5) of being seropositive than younger animals (< 2 years), P-value = 0.016. Female animals demonstrated 2.1 times greater odds (95% CI 1.2–3.6) of seropositivity than males did (P-value = 0.008). Additionally, Felata/Mbororo cattle exhibited 2.4 times greater odds (95% CI 1.3–4.5) of being seropositive than did local Nilotic cattle (P-value = 0.005). The agreement between the MAT and PCR results was poor, as indicated by a kappa statistic value of 0.001 and a P-value of 0.913. But there was a moderate agreement between MAT high titres ≥ 800 and PCR positivity with a kappa statistic value = 0.501 and a P-value < 0.001.ConclusionIn addition to the high seroprevalence, Leptospira spp. were found in the urine of slaughtered cattle, suggesting that leptospirosis is endemic to the study area. This finding underscores the significance of cattle as potential sources of infection for slaughterhouse workers, the general public, and other animal species. To address this issue effectively in the Bahr El Ghazal Region and South Sudan, a comprehensive strategy involving a multidisciplinary approach is essential to minimize disease among animals, hence reducing potential zoonotic risks to humans.

Spatio-temporal land use and land cover change assessment: Insights from the Ouémé River Basin

The rapid increase in population and urban development are exacerbating the transformation of natural environments into unnatural forms. While detailed assessment of the environment is beneficial for efficient ecosystem system management, it can also be time and resources-consuming. This study aimed to map and quantify the spatio-temporal changes in land use and land cover (LULC) using the Ouémé River Basin as a case study. The supervised classification in Google Earth Engine (GEE) cloud-computing platform was employed to distinguish Landsat images for 1986, 2000, 2015 and 2023 into forest areas, settlements/bare lands, savanna areas (woodlands), agricultural lands and water bodies. Analysis of the LULC changes revealed that savanna areas and woodlands which were predominant in the basin in 1986 have steadily declined by 24 % in area in 2023. Forest areas have diminished by 4.3 % at an annual rate of 4 %. Agricultural lands have however grown exponentially by 28 % since 1986, with a more rapid increase between 2015 and 2023 at an annual rate of 3.7 %, driven by rising food demand due to population growth within and around the basin. Settlements and bare areas tripled in area, reflecting a similar trend to Benin's urban population growth. Accuracy statistics of the LULC classification showed overall accuracy and kappa statistic values above 90 % and 86 %, respectively, indicating the admirable performance and reliability of the Simple Composite Landsat algorithm for image composition, and the Random Forest Classifier for LULC classification approach applied in this study. The approach also demonstrates the robustness and potential of LULC mapping in large and complex ecosystems using the GEE cloud-based remote sensing tool, which is underutilized in the study area. Overall, the LULC trends provide beneficial insights useful to policy-makers and any other stakeholders involved in sustainable ecosystem management planning in the basin.

Psychometric Evaluation of the Bahasa Malaysia Version of the Lymphedema Functioning, Disability, and Health Questionnaire for Upper Limb Lymphedema in Patients with Breast Cancer-Related Lymphedema.

Background: Breast cancer-related lymphedema (BCRL) is the most prevalent comorbidity that occurs following breast cancer treatments and has negative impact on the patients' quality of life (QoL). The Lymphedema Functioning, Disability, and Health Questionnaire for Upper Limb Lymphedema (Lymph-ICF-UL) is a valid and reliable instrument in assessing the QoL of patients with BCRL. However, the Bahasa Malaysia (BM) version is not available yet. This study aimed to translate the Lymph-ICF-UL into BM and to evaluate its validity and reliability. Methods and Results: A forward-backward translation was performed based on Sousa's guideline, and then, the face, content, construct validity, internal consistency, and test-retest reliability were tested. Face validity was assessed by five patients, and content validity was evaluated by six experts. Then, construct validity and internal validity were assessed in 107 patients. Finally, test-retest reliability was analyzed in 21 patients. Two items were eliminated following suggestions from the patients and experts. All patients found the scoring system and items clear and relevant. The results showed sufficient content validity index and modified kappa statistics value. Confirmatory factor analysis showed acceptable fit indices. Cronbach's alpha values ranged from 0.67 to 0.95, intraclass correlation coefficient ranged from 0.88 to 0.99, standard error measurement was 2.29-6.15, and the Bland-Altman plot showed an agreement between two test occasions. Conclusion: These results suggested that the Lymph-ICF-UL BM has good validity and reliability in evaluating the QoL of patients with BCRL in Malaysia.

Time Efficiency, Reliability, and User Satisfaction of the Tooth Memo App for Recording Oral Health Information: Cross-Sectional Questionnaire Study.

Digitalizing oral health data through an app can help manage the extensive data obtained through oral health surveys. The Tooth Memo app collects data from oral health surveys and personal health information. This study aims to evaluate the evaluate the time efficiency, reliability, and user satisfaction of the Tooth Memo app. There are 2 sections in the Tooth Memo app: oral health survey and personal oral health record. For the oral health survey section of the Tooth Memo app, different data entry methods were compared and user satisfaction was evaluated. Fifth-year dental students had access to the oral health survey section in the Tooth Memo app during their clinical work. The time required for data entry, analysis, and summary of oral health survey data by 3 methods, that is, pen-and-paper (manual), Tooth Memo app on iOS device, and Tooth Memo app on Android device were compared among 3 data recorders who entered patients' information on decayed, missing, and filled permanent teeth (DMFT) index and community periodontal index (CPI), which were read aloud from the database of 103 patients by another dental personnel. The interobserver reliability of the 3 different data-entering procedures was evaluated by percent disagreement and kappa statistic values. Laypeople had access to the personal oral health record section of this app, and their satisfaction was evaluated through a Likert scale questionnaire. The satisfaction assessments for both sections of the Tooth Memo app involved the same set of questions on the app design, usage, and overall satisfaction. Of the 103 dental records on DMFT and CPI, 5.2% (177/3399) data points were missing in the manual data entries, but no data on tooth status were missing in the Android and iOS methods. Complete CPI information was provided by all 3 methods. Transferring data from paper to computer took an average of 55 seconds per case. The manual method required 182 minutes more than the iOS or Android methods to clean the missing data and transfer and analyze the tooth status data of 103 patients. The users, that is, 109 fifth-year dental students and 134 laypeople, expressed high satisfaction with using the Tooth Memo app. The overall satisfaction with the oral health survey ranged between 3 and 10, with an average (SD) of 7.86 (1.46). The overall satisfaction with the personal oral health record ranged between 4 and 10, with an average (SD) of 8.09 (1.28). The Tooth Memo app was more efficacious than manual data entry for collecting data of oral health surveys. Dental personnel as well as general users reported high satisfaction when using this app.

AI in the ED: Assessing the efficacy of GPT models vs. physicians in medical score calculation

Background and aimsArtificial Intelligence (AI) models like GPT-3.5 and GPT-4 have shown promise across various domains but remain underexplored in healthcare. Emergency Departments (ED) rely on established scoring systems, such as NIHSS and HEART score, to guide clinical decision-making. This study aims to evaluate the proficiency of GPT-3.5 and GPT-4 against experienced ED physicians in calculating five commonly used medical scores. MethodsThis retrospective study analyzed data from 150 patients who visited the ED over one week. Both AI models and two human physicians were tasked with calculating scores for NIH Stroke Scale, Canadian Syncope Risk Score, Alvarado Score for Acute Appendicitis, Canadian CT Head Rule, and HEART Score. Cohen's Kappa statistic and AUC values were used to assess inter-rater agreement and predictive performance, respectively. ResultsThe highest level of agreement was observed between the human physicians (Kappa = 0.681), while GPT-4 also showed moderate to substantial agreement with them (Kappa values of 0.473 and 0.576). GPT-3.5 had the lowest agreement with human scorers. These results highlight the superior predictive performance of human expertise over the currently available automated systems for this specific medical outcome. Human physicians achieved a higher ROC-AUC on 3 of the 5 scores, but none of the differences were statistically significant. ConclusionsWhile AI models demonstrated some level of concordance with human expertise, they fell short in emulating the complex clinical judgments that physicians make. The study suggests that current AI models may serve as supplementary tools but are not ready to replace human expertise in high-stakes settings like the ED. Further research is needed to explore the capabilities and limitations of AI in emergency medicine.

Land cover change analysis of buffer areas in New Capital City of Nusantara, Indonesia: A cellular automata approach on satellite imageries data

The proposed plan to move Indonesia's capital city to the New Capital City of Nusantara in East Kalimantan Province undoubtedly requires careful efforts to ensure food supply for the population. Population migration to the new capital may pose a food security challenge. To address this fundamental issue, one of the most crucial approaches is to establish buffer areas that can support the food needs of the new capital. The currently existing official Area Sampling Frame survey conducted by the government to assess food vulnerability faced several limitations, including weather conditions, field terrain variations, and high cost. In this study, we propose the utilization of remote sensing satellite imagery data in buffer areas to analyze changes and predict future land cover, which can provide valuable data for assessing food availability. We investigate the integration of a Cellular Automata method with the two most popular analytical methods of classical Logistic Regression and data-driven Artificial Neural Networks, known as CA-LR and CA-ANN, to identify and map land cover changes in the new capital buffer zones. Our findings reveal that both combined methods, CA-LR and CA-ANN, yield fairly promising results, with correctness and kappa statistic values exceeding 80%. Prediction results indicate that buffer areas are predominantly covered by trees, while built-up areas are still limited. The flooded vegetation cover, including rice fields, is predicted to decrease by 2024. This should be a matter of concern for stakeholders, considering the construction of the new capital city is still ongoing and the number of migrants is expected to keep rising.

A new method for fully automated detection of algae blooms in Antarctica using Sentinel-2 satellite images

The melting of Antarctic glaciers has become a significant issue as a result of global climate change. Algae on the Antarctic ice/snow is an important part of terrestrial photosynthetic organisms. Monitoring and tracking these algal blooms is crucial for understanding the melting of glaciers in the region. Due to the climatic and natural conditions of the region, traveling to and arranging logistics for monitoring and observing snow algae in the Antarctic continent becomes extremely challenging. To overcome these challenges, a novel algorithm has been developed and designed to automatically detect and analyze green algae (Chlorella sp.) from satellite images. Leveraging the vast and free available data from the Sentinel-2 satellite, the algorithm utilizes its high spectral resolution capabilities, capturing invaluable information from various spectral bands. The algorithm was formulated based on the image obtained on February 28, 2017, where green algae formations were intensively seen in the Ryder Bay. The algorithm was developed based on rule-based detection of algae, with the usage of reflection values from the areas where ground truth was established on this date. The developed algorithm was coded and tested using Python version 3.9. The accuracy analysis of the algorithm was conducted using overall accuracy (OA), F1 score, and Kappa statistical test. As a result of the analysis, the OA, F1 score, and Kappa statistic values were calculated as %91, %88.82-%95.27, and 0.901, respectively.

Monitoring dan Klasifikasi Kualitas Air Kolam Ikan Gurami Berbasis Internet of Things Menggunakan Metode Naive Bayes

Ministry of Marine Affairs and Fisheries (KKP) noted that Indonesia produced 56,539 tons of gourami fish in the second quarter of 2022 High market demand and economical selling prices encourage farmers to cultivate gourami fish. In cultivating gourami fish there are several obstacles, for example, disease caused by poor water quality. Water quality is the main parameter in the success of gourami fish farming. This research aims to develop a water quality monitoring system based on the Internet of Things. The system prototype uses a temperature sensor (DS18B20), Ph sensor (dfrobot SEN0161), turbidity sensor (dfrobot SEN0189), flowmeter, and ultrasonic sensor (JSN-SR04) as input. The Arduino Mega R3 microcontroller is the processor and the Oled module (SSD1306) is the output. Thingboard is a cloud server that functions as sensor data monitoring. Temperature sensor testing results (DS18B20) average error 0.48%, Ph(dfrobot SEN0161) sensor testing average error 0.64%, ultrasonic sensor testing (JSN-SR04) average error 7.83%, testing Turbidity sensors can measure the level of water turbidity. Next, the water quality parameter data is processed using the Naïve Bayes algorithm method for classifying the water quality of gourami ponds. The results of this classification obtained an accuracy of 99.94% a Kappa Statistics value of 0.9989 and a Mean Absolute Error of 0.0003

Evaluation of an immunochromatographic serologic test to detect the presence of anti-Toxoplasma gondii antibodies in cats.

Toxoplasmosis is a protozoan disease caused by Toxoplasma gondii. Different T. gondii confirmatory techniques, including serologic methods, are available to detect the presence of the parasite. Among serology techniques, immunochromatographic rapid testing could be a reliable alternative to serologic laboratory techniques. This study evaluated a commercial immunochromatographic test (FASTest TOXOPLASMA g) in seronegative and seropositive cats. Two indirect immunofluorescence antibody reference tests, an in-house technique, and a commercial test were used to classify 292 feline serum samples. The rapid test was evaluated in different groups of cats, including healthy seronegative cats (n=121), seropositive cats with variable anti-Toxoplasma antibodies (n=146), and cats with positive serologic results for other pathogens (n=25). The sensitivity, specificity, accuracy, receiver operating characteristic curves, and kappa statistics were analyzed as performance measures. Of the 292 samples, 146 were classified as T. gondii seropositive and 146 as T. gondii seronegative. Concordant results were obtained for all samples using immunofluorescence antibody tests. The diagnostic measures of this rapid test showed 98.63% sensitivity and 100% specificity, and 99.32% accuracy. The kappa statistics value was 0.986, and the area under the receiver operating characteristic curve was 0.993. This rapid test showed diagnostic measurements similar to those of traditional quantitative serologic methods. In situations where laboratory techniques are not available, this test, under clinical conditions, could be a useful alternative to obtain accurate results rapidly.

Lipoarabinomannan (LAM)—a potential biomarker for the diagnosis of tuberculosis from the urine of infected elephants

The spread of tuberculosis (TB) in Asian countries is mainly due to co-existence and close association of humans with elephants and other domestic livestock. Infected animals tend to shed the organism in the preclinical period which risks the transmission of the infection from animals to humans and vice versa. Since tuberculosis infection is chronic and lack specific clinical signs, diagnosis remains challenging. The present study focuses on the utilization of lipoarabinomannan (LAM), a glycolipid for the detection of TB infection in elephants. Usage of urine as the biological sample for the diagnosis makes it more advantageous. Seroprevalence of tuberculosis (TB) in elephants in Kerala were found to be 37.2% (n = 86) using Chembio DPP VetTB assay. Nine (10.46%) out of 86 elephants were positive for AFB and 29 (33.7%) out of 86 elephants were positive for LAM antigen. On comparison of efficiency of LF-LAM assay with that of DPP VetTB assay, LF-LAM assay had a sensitivity of 90.63%, specificity 100%, positive predictive value 100%, negative predictive value 94.7%, accuracy 95.51%, and kappa statistic value 0.924 (p value < 0.001). On comparison of LF-LAM with traditional acid fast staining method, LF-LAM assay had the sensitivity of 100%, specificity 74.03%, positive predictive value 31%, negative predictive value 100%, accuracy 76.74%, and kappa statistic value 0.374 (p value < 0.001). The presence of Mycobacterium tuberculosis was confirmed in trunk wash sample using PCR targeting gene IS6110, at 245 bp amplicon size and 25 seropositive elephants (78.2%) were confirmed positive. Custom sequencing and phylogenetic analysis revealed that the isolate obtained was Mycobacterium tuberculosis. This study in elephants prove that TB LAM Ag (LF-LAM) can be used as potent biomarker for diagnosis of tuberculosis in elephants.

In silico investigation of acyclovir derivatives potency against herpes simplex virus

Herpes simplex virus (HSV) is a major human pathogen, sub-divided into two types: HSV-1 which causes oral and perioral infections and HSV-2 which causes genital herpes. The global disease burden is high with 67% and 11% of the World's population being infected with HSV-1 and HSV-2 respectively. Acyclovir, an FDA approved drug, is a synthetic purine nucleoside analogue used for the treatment of HSV infections. The drug acts via the viral encoded thymidine kinase and competitively inhibits viral DNA polymerase. Emerging HSV resistance to acyclovir and lack of approved vaccines necessitates need for effective strategies to circumvent the viral infection. Derivatives of acyclovir were modelled using computer aided drug design techniques through Chemsketch and drugability determined based on Lipinski's Ro5 where a Python filtering code was created and derivatives with zero non-violations were selected. Putative biological targets were determined through network pharmacology and validated through gene ontology. Molecular docking with known and putative targets was done to determine the binding affinities of the acyclovir derivatives. Based on enzyme inhibition scores, pharmacokinetics prediction was done on Molinspiration while pharmacodynamics predictions were done on AdmetSAR based on bioavailability scores. Thirty acyclovir derivatives were modelled of which 22 had zero non-violations. 2-[(3, 6-dihydro-9H-purin-9-yl)methoxy]ethan-1-ol) had the highest enzyme inhibition score at 1.0 compared to 0.84 for acyclovir. The molecule was further optimized generating (2‐[(6‐methyl‐6,9‐dihydro‐3H‐purin‐9‐yl)methoxy]ethan‐1‐ol which had a better bioavailability and a higher blood brain barrier value of 0.9880 indicating possible better patient tolerance. 2‐[(6‐methyl‐6,9‐dihydro‐3H‐purin‐9‐yl)methoxy]ethan‐1‐ol had an enzyme inhibition score of 0.90 and binding energies of -5.1 kcal/mol when docked against thymidine kinase. The intra-viral HSV PPI network was analysed and DNA replication helicase (UL5) and serine /threonine-protein kinase (US3) were selected due to functional similarity with thymidine kinase with kappa statistics value of 0.30 and 0.24 respectively. Gene enrichment analysis indicated that the biological targets UL5 and US3 had a significant P value of 0.62 based on Benjamin Correction at P<0.05. The study recommends in vitro and in vivo validation of this novel compound and molecular validation of the two new potential biological targets for possible development of new anti-herpes therapeutic compounds.

Simultaneous depiction of clot and MRA using 1 min phase contrast angiography in acute ischemic patients

[Background and Purpose] Clot location and range predict clinical outcomes for acute ischemic stroke (AIS). We developed a new technique for visualizing occlusion clots, namely, the DEpicting blood clot and MRA using Phase contrast angiography with Image Calculation for Thrombectomy (DEPICT) method. The purpose of this study was to assess the clinical usefulness of DEPICT.[Methods] We used DEPICT in 36 AIS patients to obtain MRA and black blood images with 1-min phase contrast angiography (PCA). We created the black blood images by subtracting the MRA from the T1WI using the source image of PCA. We evaluated the motion artifact, detectability of clot, and precision in location and range compared these to that of susceptibility vessel sign in T2*WI and measured contrast ration (CR) of clot between the cistern and brain tissue. Motion artifact was visually evaluated using a 3-point scale. Detectability and precision of the location and range of occlusion clots were assessed by comparison with findings from digital subtraction angiography (DSA). Gwet's AC1 and kappa statistics were used to assess inter-observer agreement.[Results] DEPICT showed significant robustness for motion artifact compared with T2*WI (p = 0.0026, Wilcoxon signed-rank test). DEPICT showed 100% detectability for the clot. Further, DEPICT showed higher Gwet's AC1 and kappa statistic values with DSA than T2*WI. CR demonstrated a positive value.[Conclusions] DEPICT technique based on 1-min PCA offers both MRA and black blood T1W images that can be used to accurately evaluate both location and range of the clot.

Usefulness of Sōna Aspergillus Galactomannan LFA with digital readout as diagnostic and as screening tool of COVID-19 associated pulmonary aspergillosis in critically ill patients. Data from a multicenter prospective study performed in Argentina.

COVID-19-associated pulmonary aspergillosis (CAPA) incidence varies depending on the country. Serum galactomannan quantification is a promising diagnostic tool since samples are easy to obtain with low biosafety issues. A multicenter prospective study was performed to evaluate the CAPA incidence in Argentina and to assess the performance of the lateral flow assay with digital readout (Sōna Aspergillus LFA) as a CAPA diagnostic and screening tool. The correlation between the values obtained with Sōna Aspergillus LFA and Platelia® EIA was evaluated. In total, 578 serum samples were obtained from 185 critically ill COVID patients. CAPA screening was done weekly starting from the first week of ICU stay. Probable CAPA incidence in critically ill patients was 10.27% (19/185 patients when LFA was used as mycological criteria) and 9% (9/100 patients when EIA was used as mycological criteria). We found a very good correlation between the two evaluated galactomannan quantification methods (overall agreement of 92.16% with a Kappa statistic value of 0.721). CAPA diagnosis (>0.5 readouts in LFA) were done during the first week of ICU stay in 94.7% of the probable CAPA patients. The overall mortality was 36.21%. CAPA patients' mortality and length of ICU stay were not statistically different from for COVID (non-CAPA) patients (42.11 vs 33.13% and 29 vs 24 days, respectively). These indicators were lower than in other reports. LFA-IMMY with digital readout is a reliable tool for early diagnosis of CAPA using serum samples in critically ill COVID patients. It has a good agreement with Platelia® EIA.Lay SummaryThe incidence of COVID-associated pulmonary aspergillosis (CAPA) in critically-ill Argentinian patients was established (10.27%). Serum galactomannan quantification was useful as a screening tool for this mycosis. A good agreement between Platelia® EIA and Sōna Aspergillus LFA is reported.

Using the cobweb classification system as a digital location system for the neurologic compression in cervical degenerative disease.

ObjectiveTo provide the cobweb classification system (CCS) for the precise digital location and description of the neurological compression in cervical degenerative disease (CDD), and the reliability and the clinical subgroup analysis of the system were tested and analyzed.MethodsThe CCS consisted of three parts: compression zones (1‐12), degrees (a, b) and ossification (s, m, h). Computerized tomography (CT) and magnetic resonance imaging (MRI) images from 238 CDD patients were reviewed. All compression cases were classified by five independent reviewers with varied clinical experience in spine surgery. The reliability of the CCS was tested by calculating the kappa (κ) statistics value. Finally, 74 patients with anterior cervical surgery treatment were enrolled for the clinical subgroup analysis.ResultsFor the small compression, including single and double compression zones, there was a good interobserver reliability between the reviewers (κ coefficient = .855, P < .001). For the large compression with three or more involved zones, there was a fair reliability between the reviewers (κ coefficient = .696, P < .001). The whole intraobserver reliability was good (κ coefficient = .923, P < .001). For clinical practice, the operative time in the large compression and the m/h group was significantly longer than the small compression and the s group, respectively (P < .05), and the blood loss in the m/h group was significantly increased as well (P < .01). Though the preoperative Japanese Orthopedic Association score in Group b was lower than Group a (P < .05), all patients had achieved significant clinical improvement at last follow‐up.ConclusionsThe CCS can be used to provide detailed and objective descriptions of the location, extent, and severity of neurological compressions in CDD with satisfactory reliability. Surgeons should pay more attention to the patient with large zone, degree b, and ossification compression, because the operation may be more challenging.

Comparison between Urine and Cervical High-Risk HPV Tests for Japanese Women with ASC-US.

Most uterine cervical cancers are caused by the persistent infection of the high-risk human papillomavirus (hrHPV). Thus, the hrHPV-DNA test, which examines specimens from the cervix, is the standard screening method as well as cytology in western countries. Urine sampling for the hrHPV-DNA test would be easier and help improving screening rates. This study prospectively investigated the concordance between urine and cervical hrHPV tests for patients with atypical squamous cells of undetermined significance (ASC-US) in cervical cytology. We recruited 338 women with the cytologic diagnosis of ASC-US and performed hrHPV-DNA tests to both samples from the uterine cervix and first void urine, using the Cobas 4800 system. In all hrHPV genotypes, the simple concordance rate was 90.8% (307/338) and the Kappa statistic value was 0.765, which shows substantial concordance. The positive concordance rate was 70.5% (74/105), which was the rate excluding women who had negative results in both tests. When limited to types 16 and 18, the simple concordance rate was 98.8% (334/338), and the Kappa statistical value was calculated to be 0.840, which showed almost perfect concordance. The positive concordance rate resulted in 81.8% (18/22). We conclude that the urine hrHPV-DNA test could substitute the cervical test in women with ASC-US.

Digital mapping of soil classes using spatial extrapolation with imbalanced data

Digital mapping of soil classes using the extrapolation approach is timesaving, economically cheap, and helps collecting soil data from areas with difficult sampling. However, it has not been explored widely enough for digital mapping of soil classes. This study seeks to evaluate and compare several machine learning and regression algorithms for the extrapolation of soil sub-groups. Also the issue of imbalanced number of observations was addressed and oversampling technique was applied on the minority soil class to improve the models performance. The study area is located in central north Iran with 84 and 72 soil profiles sampled in the donor and recipient areas, respectively. A set of various environmental covariates including remotely sensed data, digital elevation model derivatives and geomorphology map were used as explanatory variables for predicting soil classes. Results showed that among eleven investigated models, C5.0 decision tree (DT), random forest (RF) and multinomial logistic regression (MNL) had the highest overall accuracy of 46%, 42% and 38%, respectively, for the extrapolation of soil classes. Also the Kappa statistic values for these models were 0.30, 0.24 and 0.22, respectively. Oversampling of the minority soil class led to an increase in overall accuracy for some of the models with the highest ones being DT = 53% and RF = 50%. Also, the Kappa value for DT and RF models increased to 0.39 and 0.35, respectively. In addition, oversampling of the minority soil class led to the prevention of losing this class in the final map.

Optimization of a Loop-Mediated Isothermal Amplification Assay as a Point-of-Care Tool for the Detection of Wuchereria bancrofti in Human Blood in Tana River Delta, Kenya.

Introduction Accurate detection of filarial parasites in humans and vectors is essential for the implementation and evaluation of Global and National Programs to eliminate lymphatic filariasis. Immunological methods to detect infection are available; however, cross-reactivity issues have been reported in most of them. Nucleic acid-based molecular assays offer high levels of specificity and sensitivity and can be used to detect the infections. Methods In this study, we evaluated loop-mediated isothermal amplification (LAMP) tests to amplify Wuchereria bancrofti DNA in patients' blood. The amplicons were tested by both pH-sensitive dyes for enhanced visual detection and agarose gel electrophoresis. A closed-tube LAMP assay was also evaluated. Cohen's Kappa statistics was used for statistical analysis of the assays. 125 patients consented for blood sampling which were used for clinical analysis of LAMP assays with the PCR method used as the “gold standard.” Results The sensitivity of the evaluated Wuchereria bancrofti LAMP was 92.3%, with a specificity of 97.3% and kappa statistics value of 0.84, which is in a strong agreement. Conclusion In this study, LAMP assays coupled with fluorescence dye detection have been found to be suitable for diagnosis and monitoring of Wuchereria bancrofti infections in the Kenyan population.

Point-of-care ultrasound for the evaluation of venous cannula position in neonatal extracorporeal membrane oxygenation.

To assess the ability of point-of-care ultrasound (POCUS) to identify venous cannula position in neonates on extracorporeal membrane oxygenation (ECMO) and compare withconventional imaging. Retrospective review of 37 infants on ECMO with 51 POCUS studies between January 2017 and October 2019. Studies were reviewed for identification of venous cannula location and compared with plain radiography and echocardiography. Kappa statistic and predictive values were calculated. Venous cannula tip position was identified in 90% of POCUS studies. Fifty percent of the cannula tips were malpositioned. Plain radiography, the most commonly used method for evaluating tip position, showed poor agreement (57%) with POCUS (kappa 0.13). There was substantial agreement (89%) between echocardiography and POCUS (kappa 0.78). This study provides preliminary evidence that POCUS is more accurate than plain radiography for the evaluation of ECMO venous cannula position. Adoption of this practice may prevent potentially catastrophic ECMO complications.

Performance Assessment of Ensemble Learning Model for Prediction of Cardiac Disease Among Smokers Based on HRV Features

Smoking impacts the pattern of heart rate variability (HRV); HRV therefore acts as a predictor of cardiac diseases (CD). In this study, to predict CD non-invasively among smokers, ensemble machine learning methods have been used. A single model is created based on ensemble voting classifier with a combined boosting technique to improve the accuracy of predictive model. The final ensemble model shows an accuracy of 95.20%, precision of 97.27%, sensitivity of 92.35%, specificity of 98.07%, F1 score of 0.95, AUC of 0.961, MCE of 0.0479, kappa statistics value of 0.9041, and MSE of 0.2189. The obtained accuracy by using the proposed method is the highest value achieved so far for the prediction of CD among smokers using HRV data.