Interobserver Bias Research Articles

Clinical spectrum and prevalence of temporomandibular joint disorder: A hospital-basedanalysis

Objective: The objective of this study was to determine frequency of temporomandibular joint disorders and its severity among patients presenting with complaints of pain at tempo mandibular joint. Materials and methods: A total of 205 patients were selected in this study, the research has been done in unit of oral and maxillofacial surgery at darul-sehat hospital, Karachi. Patients, age 18 to 40 years, with history of diabetes, hypertension, habits of pan/chalia and smoking presented with complain of pain at temporomandibular joint for a period of two weeks were recruited in study. Patients with history of bone & neurological disorder, taking immunosuppressant drug, trauma or surgery of temporomandibular joint were excluded from study. Examinations were carried out by single researcher to ensure the continuity and reliability of answers and interpretation of results. This will also help to eliminate inter-observer biases. Data gathered using a questionnaire and analyzed using SPSS software version 20. Results: A total of 205 patients which fulfilled the inclusion criteria were included in the study, including 99(48.3%) males and 106(51.7%) females. The age ranged from 18-40 years were included, belonging to age 15-20 years n=73(35.3%), 21-25 years n=65(31.4%), 26-30 years n=2(1%), 31-35 years n=60 (29%), and 36-40% years n=5 (2.4%). Around 42 (20.5%) patients had history of hypertension while 40 (19.5%) had diabetes, for which they were taking their medicines. History of smoking was seen among 38 (18.5%) patients.Disease was categorized as mild in 98 (47.8%) patients, moderate in 88 (42.9%) patients and severe in 19 (9.3%) patients. Around 158 (77.1%) had unilateral and 47 (22.9%) had bilateral disorder. Out of 205 patients most of them had temporomandibular joint disorder 192(93.7%). Conclusion: temporomandibular joint disorder is most common cause of orofacial pain and requires thorough knowledge and adequate examination to diagnose the disorder.

Flow cytometric analysis for Ki67 assessment in formalin-fixed paraffin-embedded breast cancer tissue

BackgroundPathologists commonly employ the Ki67 immunohistochemistry labelling index (LI) when deciding appropriate therapeutic strategies for patients with breast cancer. However, despite several attempts at standardizing the Ki67 LI, inter-observer and inter-laboratory bias remain problematic. We developed a flow cytometric assay that employed tissue dissociation, enzymatic treatment and a gating process to analyse Ki67 in formalin-fixed paraffin-embedded (FFPE) breast cancer tissue.ResultsWe demonstrated that mechanical homogenizations combined with thrombin treatment can be used to recover efficiently intact single-cell nuclei from FFPE breast cancer tissue. Ki67 in the recovered cell nuclei retained reactivity against the MIB-1 antibody, which has been widely used in clinical settings. Additionally, since the method did not alter the nucleoskeletal structure of tissues, the nuclei of cancer cells can be enriched in data analysis based on differences in size and complexity of nuclei of lymphocytes and normal mammary cells. In a clinical study using the developed protocol, Ki67 positivity was correlated with the Ki67 LI obtained by hot spot analysis by a pathologist in Japan (rho = 0.756, P < 0.0001). The number of cancer cell nuclei subjected to the analysis in our assay was more than twice the number routinely checked by pathologists in clinical settings.ConclusionsThe findings of this study showed the application of this new flow cytometry method could potentially be used to standardize Ki67 assessments in breast cancer.

A spatiotemporal comparison of interobserver error in vegetation sampling

AbstractQuestionsWe asked how interobserver error in sampling vegetation (excluding trees) varied over time, space and habitat type; determined whether there were any obvious correlates of observer error; and evaluated evidence of bias among observers.LocationNine national park units in the Midwestern USA.MethodsWe quantified observer error in the context of a long‐term monitoring program employing three observers, evaluating interobserver error across 11 locations in the Midwestern USA over five years. The vegetation (excluding trees) was sampled independently by two teams of observers at prairie and woodland locations (n = 94 plots total).ResultsTotal pseudoturnover ranged between 20.2% and 22.1% at prairie locations, and between 16.8% and 28.6% at woodland locations. The overlooking component of pseudoturnover accounted for 75% or more of total pseudoturnover, with misidentification and cautious components each contributing 19% or less of the total, depending on location. The percentage of comparisons in which both observers recorded the same cover class ranged from 71.3% to 78.5% at the prairie locations and 56.9% to 85.6% at woodland locations. When observers did not agree on cover class, they were off by more than one class less than 6% of the time. Overlooking error was more likely to occur for species with less cover, while estimation error was more likely to occur for species with greater cover. A bias existed among observers, as the least experienced observer recorded 6.2%–11.8% more species than the other two observers. Interobserver bias also existed for rates of estimation error, as one observer consistently recorded higher cover classes.ConclusionsObserver error is a pervasive aspect of vegetation sampling. Continued training and experience yielded limited increases in precision. Elements of the sampling design probably reduced observer error to a certain degree, although some level of interobserver error in vegetation surveys is unavoidable.

A resonance frequency analysis to investigate the impact of implant size on primary and secondary stability.

Recent years have seen a rise in the usage of dental implants to restore lost teeth. The stability of a dental implant is the main factor in determining its success. Implant stability is influenced by various factors. Several approaches have been employed clinically to evaluate stability at different time intervals. One non-invasive way to assess implant stability is by resonance frequency analysis. Utilizing the resonance frequency analysis method, this study seeks to understand how implant length and diameter affect primary and secondary stability. The current prospective study was conducted in the Prosthodontics Department of Institute of Dentistry, CMH Lahore Medical College. The duration of the study was six months. A total of 90 implants of sizes 4.5 x 8.5 mm and 4 x 10mm were placed. Resonance frequency measurements were recorded using Osstell™ AB device for primary stability at implant insertion and at 12 weeks for secondary stability. All the measurements were carried out by only one of the researchers to minimize inter-observer bias. The average primary stability was 70.33±6.60, and the average secondary stability was 71.43±5.44. The data was stratified for age, gender, and implant site, and the mean primary and secondary stability of both sizes didn't show any statistically significant differences. Without forfeiting implant stability, both implant sizes (4 x 10mm and 4.5 x 8.5mm) can be used interchangeably, depending on available space and anatomical constraints.

Role of Renal Sonography in the Diagnosis of Chronic Kidney Disease

Aim: to use sonographic imaging in grading CKD and assess the serum creatinine, renal longitudinal size,parenchymal thickness and compare these parameters based upon ultrasonographic grade.Material and Methods: Present cross-sectional; study was conducted at the Department of Radiology, Tertiary Care Teaching Institute of India for the duration of 1 year. There are 120 participants with CKD in the research.All patients received a questionnaire, and a thorough clinical examination was done. Each participant underwent sector curved array transducer of 3.5–5 MHz ultrasound images of their liver and kidneys. Low tissue harmonic and speckle reduction imaging techniques are used to measure the echogenicity of the kidney and liver while reducing interobserver bias. In all the participants, the mean values of both the kidneys renal longitudinal size and parenchymal thickness were calculated. Renal cortical echogenicity was compared and graded with the echogenicity of the liver and renal medulla.Results: The mean age of the CKD patients was found to be 45.23 ± 06.05 years. It was found that 50 patientshad Grade 1, 40 patients had Grade 2, 20 patients had Grade 3 and 10 patients had Grade 4. The results showed that, when the comparison was done, serum creatinine was found to be significant among echogenicity grades with ANOVA. when the comparison was done; the mean longitudinal size was found to be significant among echogenicity. On comparison was found to be mean Parenchymal thickness was found to be significant among echogenicity grades.Conclusion: Renal cortical echogenicity and its grading in relation to longitudinal length, parenchymal thickness, and cortical thickness in CKD patients are the best sonographic parameters that correlate with blood creatinine. It is possible to use renal cortical echogenicity as a metric of renal function since it has the benefit of being irreversible in compared to serum creatinine levels.

CRABEL Score Assessment for Oral Surgery Excision Biopsy Case Notes of Oral Squamous Cell Carcinoma.

Background Oral surgical records contain all the information regarding a patient, including their history, clinical findings, diagnostic test results, pre-and postoperative care, progress, and medication. Notes that are properly drafted will help the physician argue that the course of therapy is appropriate. Several tools have been created for auditing clinical records; one such tool that may be used for any inpatient specialty is the CRABEL score system developed by CRAwford-BEresford-Lafferty. Aims This research aimed to evaluate the oral surgical records using the CRABEL scoring system for quality assessment. Materials and methods The case audit was performed from June 2023 to February 2024 for all Excisional biopsy cases of Oral Squamous Cell Carcinoma. Relevant data was retrieved from the Dental Information Archival Software (DIAS) of Saveetha Dental College and Hospitals, Chennai. It was evaluated by two independent oral pathologists trained in CRABEL scores. Two consecutive case records were evaluated. Fifty points were given for each case record. Scoring was given according to initial clerking (10 points), subsequent entries (30 points), consent (5 points), and discharge summary (5 points). The total score was calculated by subtracting the total deduction from 100 to give the final score. The mean scores of the case records were calculated. A descriptive statistical analysis was done with Statistical Package for Social Sciences (SPSS version 23.0; IBM Inc., Armonk, New York). Inter-observer agreement and reliability assessment were made using Kappa statistics. Results From the DIAS in that period, the data of 52 cases were retrieved and reviewed. There was no proof of a reference source in the audited records, and one deduction was made to the reference score in the initial clerking, and the effective score was 98 out of 100. The mean values of 52 case records were also 98 out of 100. The observed kappa score was 1.0. There was no inter-observer bias in the scoring criteria. Both observers also gave the same scoring. Conclusion Our study illustrates that oral surgery case records in our institution were found to be accurate, as they maintained 98% of the CRABEL score value. Frequent audit cycles will help in standardizing and maintaining the quality of oral surgery case records.

Value of Automatically Derived Full Thrombus Characteristics: An Explorative Study of Their Associations with Outcomes in Ischemic Stroke Patients.

(1) Background: For acute ischemic strokes caused by large vessel occlusion, manually assessed thrombus volume and perviousness have been associated with treatment outcomes. However, the manual assessment of these characteristics is time-consuming and subject to inter-observer bias. Alternatively, a recently introduced fully automated deep learning-based algorithm can be used to consistently estimate full thrombus characteristics. Here, we exploratively assess the value of these novel biomarkers in terms of their association with stroke outcomes. (2) Methods: We studied two applications of automated full thrombus characterization as follows: one in a randomized trial, MR CLEAN-NO IV (n = 314), and another in a Dutch nationwide registry, MR CLEAN Registry (n = 1839). We used an automatic pipeline to determine the thrombus volume, perviousness, density, and heterogeneity. We assessed their relationship with the functional outcome defined as the modified Rankin Scale (mRS) at 90 days and two technical success measures as follows: successful final reperfusion, which is defined as an eTICI score of 2b-3, and successful first-pass reperfusion (FPS). (3) Results: Higher perviousness was significantly related to a better mRS in both MR CLEAN-NO IV and the MR CLEAN Registry. A lower thrombus volume and lower heterogeneity were only significantly related to better mRS scores in the MR CLEAN Registry. Only lower thrombus heterogeneity was significantly related to technical success; it was significantly related to a higher chance of FPS in the MR CLEAN-NO IV trial (OR = 0.55, 95% CI: 0.31-0.98) and successful reperfusion in the MR CLEAN Registry (OR = 0.88, 95% CI: 0.78-0.99). (4) Conclusions: Thrombus characteristics derived from automatic entire thrombus segmentations are significantly related to stroke outcomes.

Detecting unitary synaptic events with machine learning

Spontaneously occurring miniature excitatory postsynaptic currents (mEPSCs) are fundamental electrophysiological events produced by quantal vesicular transmitter release at synapses. Their analysis can provide important information regarding pre- and postsynaptic function. However, the small signal relative to recording noise requires expertise and considerable time for their identification. Furthermore, many mEPSCs smaller than ~8 pA are not well resolved (e.g., those produced at distant synapses or synapses with few receptor channels). Here, we describe an automated approach to detect mEPSCs using a machine learning-based tool. This method, which can be easily generalized to other one-dimensional signals, eliminates inter-observer bias, provides an estimate of its sensitivity and specificity and permits reliable detection of small (e.g., 5 pA) spontaneous unitary synaptic events.

Deep-learning-based diagnosis and grading of vesicoureteral reflux: A novel approach for improved clinical decision-making

Background/Aim: Vesicoureteral reflux (VUR) is a condition that causes urine to flow in reverse, from the bladder back into the ureters and occasionally into the kidneys. It becomes a vital cause of urinary tract infections. Conventionally, VUR’s severity is evaluated through imaging via voiding cystourethrography (VCUG). However, there is an unresolved debate regarding the precise timing and type of surgery required, making it crucial to classify VUR grades uniformly and accurately. This study’s primary purpose is to leverage machine learning, particularly convolutional neural network (CNN), to effectively identify and classify VUR in VCUG images. The aspiration is to diminish classification discrepancies between different observers and to create an accessible tool for healthcare practitioners. Methods: We utilized a dataset of 59 VCUG images with diagnosed VUR sourced from OpenI. These images were independently classified by two seasoned urologists according to the International Reflux Classification System. We utilized TensorFlow, Keras, and Jupyter Notebook for data preparation, segmentation, and model building. The CNN Inception V3 was employed for transfer learning, while data augmentation was used to improve the model’s resilience. Results: The deep-learning model attained exceptional accuracy rates of 95% and 100% in validation and training, respectively, after six cycles. It effectively categorized VUR grades corresponding to the global classification system. Matplotlib tracked loss and accuracy values, while Python-based statistical analysis assessed the model’s performance using the F1-score. Conclusion: The study’s model effectively categorized images, including those of vesicoureteral reflux, which has significant implications for treatment decisions. The application of this artificial intelligence model may help reduce interobserver bias. Additionally, it could offer an objective method for surgical planning and treatment outcomes.

Evaluating intra and inter-observer bias in the cosmetic rating for random vs. serial assessment of breast photographs

BackgroundThis study was done to assess inter and intra-rater bias in rating of cosmesis, when breast photographs were evaluated serially or randomly by a panel of six members having varying years of experience. MethodsCosmetic assessment was done subjectively for 175 images [of 50 unilateral breast cancer patients for whom at least 3 images were collected], that were arranged serially from baseline to follow up in chronological order termed ‘serial assessment setting’ [SAS]. For ‘random assessment setting’ [RAS], all images was randomly arranged for assessment. Objectively assessment was also done using BCCT.core. Kappa index was calculated for agreement between the RAS and SAS rating for the 3 panellists' groups and with BCCT.core. ResultsGood agreement [kappa 0.659] was found between the mean panel cosmetic scores for both SAS and RAS. Fair agreement was found when subjective RAS [k = 0.301] and SAS [k = 0.343] scores were compared with the BCCT.core, which was highest for the most experienced panellists with SAS k = 0.387 and RAS k = 0.436. Both SAS and RAS had good intra-rater reliability. ConclusionsSAS improves the agreement with BCCT.core rating and may be used if validated in a larger cohort. The clinical experience of the panellist impacts cosmetic rating and must be considered before forming a panel.

The use of deep learning enables high diagnostic accuracy in detecting syndesmotic instability on weight-bearing CT scanning.

Delayed diagnosis of syndesmosis instability can lead to significant morbidity and accelerated arthritic change in the ankle joint. Weight-bearing computed tomography (WBCT) has shown promising potential for early and reliable detection of isolated syndesmotic instability using 3D volumetric measurements. While these measurements have been reported to be highly accurate, they are also experience-dependent, time-consuming, and need a particular 3D measurement software tool that leads the clinicians to still show more interest in the conventional diagnostic methods for syndesmotic instability. The purpose of this study was to increase accuracy, accelerate analysis time, and reduce interobserver bias by automating 3D volume assessment of syndesmosis anatomy using WBCT scans. A retrospective study was conducted using previously collected WBCT scans of patients with unilateral syndesmotic instability. One-hundred and forty-four bilateral ankle WBCT scans were evaluated (48 unstable, 96 control). We developed three deep learning models for analyzing WBCT scans to recognize syndesmosis instability. These three models included two state-of-the-art models (Model 1-3D Convolutional Neural Network [CNN], and Model 2-CNN with long short-term memory [LSTM]), and a new model (Model 3-differential CNN LSTM) that we introduced in this study. Model 1 failed to analyze the WBCT scans (F1 score = 0). Model 2 only misclassified two cases (F1 score = 0.80). Model 3 outperformed Model 2 and achieved a nearly perfect performance, misclassifying only one case (F1 score = 0.91) in the control group as unstable while being faster than Model 2. In this study, a deep learning model for 3D WBCT syndesmosis assessment was developed that achieved very high accuracy and accelerated analytics. This deep learning model shows promise for use by clinicians to improve diagnostic accuracy, reduce measurement bias, and save both time and expenditure for the healthcare system. II.

Morphological variability or inter-observer bias? A methodological toolkit to improve data quality of multi-researcher datasets for the analysis of morphological variation.

The investigation of morphological variation in animals is widely used in taxonomy, ecology, and evolution. Using large datasets for meta-analyses has dramatically increased, raising concerns about dataset compatibilities and biases introduced by contributions of multiple researchers. We compiled morphological data on 13 variables for 3073 individual mouse lemurs (Cheirogaleidae, Microcebus spp.) from 25 taxa and 153 different sampling locations, measured by 48 different researchers. We introduced and applied a filtering pipeline and quantified improvements in data quality (Shapiro-Francia statistic, skewness, and excess kurtosis). The filtered dataset was then used to test for genus-wide sexual size dimorphism and the applicability of Rensch's, Allen's, and Bergmann's rules. Our pipeline reduced inter-observer bias (i.e., increased normality of data distributions). Inter-observer reliability of measurements was notably variable, highlighting the need to reduce data collection biases. Although subtle, we found a consistent pattern of sexual size dimorphism across Microcebus, with females being the larger (but not heavier) sex. Sexual size dimorphism was isometric, providing no support for Rensch's rule. Variations in tail length but not in ear size were consistent with the predictions of Allen's rule. Body mass and length followed a pattern contrary to predictions of Bergmann's rule. We highlighted the usefulness of large multi-researcher datasets for testing ecological hypotheses after correcting for inter-observer biases. Using genus-wide tests, we outlined generalizable patterns of morphological variability across all mouse lemurs. This new methodological toolkit aims to facilitate future large-scale morphological comparisons for a wide range of taxa and applications.

Empty stomach together with menstrual bleeding as predictors of committed suicides among women of reproductive age: What a primary physician must know.

Women of reproductive age group (WoRAG) are among the most vulnerable groups to suicide in India. The present study intended to develop a mathematical model to differentiate suicides from homicides among WoRAG. It was a cross-sectional study based on a record review of autopsy at Patna, India, from 2016 to 2021. The cause of deaths was ascertained by autopsies and other records independently by two investigators to reduce the interobserver bias. Independent variables were tested with confirmed suicides to calculate statistically significant association. These variables were further used for developing prediction models for the suicides by multivariate logistic regression analysis. Out of total of 520 autopsies of WoRAG performed by investigators, the cause of death has been confirmed for 62. Of them, 30 were confirmed as suicides. In univariate analysis, suicides were associated with the menstrual bleed (OR 35 CI 6.9,179), gastric emptying (OR 3.9 CI 1.2,12.8), hanging, poisoning, and drowning as mode of death (OR 435 CI 37.4,5061.9). By logistic regression, three prediction models were built to predict suicide; Model I: gastric emptying, Model II: menstrual bleed, and Model III: including both. The area under the curve (AUC) for Models I, II, and III was 0.67 (95%CI 0.34,0.99), 0.92 (95%CI 0.75,1.00), and 0.94 (95%CI 0.82,1.00), respectively. The AUC of Model III differs significantly from that of Model I (P value 0.03) but not with Model II (P value 0.11). Menstrual bleed, gastric emptying, and mode of death may be used as a supplement tool in ascertaining the cause of death among WoRAG in medical and legal proceedings.

Fully automatic estimation of global left ventricular systolic function using deep learning in transoesophageal echocardiography.

To improve monitoring of cardiac function during major surgery and intensive care, we have developed a method for fully automatic estimation of mitral annular plane systolic excursion (auto-MAPSE) using deep learning in transoesophageal echocardiography (TOE). The aim of this study was a clinical validation of auto-MAPSE in patients with heart disease. TOE recordings were collected from 185 consecutive patients without selection on image quality. Deep-learning-based auto-MAPSE was trained and optimized from 105 patient recordings. We assessed auto-MAPSE feasibility, and agreement and inter-rater reliability with manual reference in 80 patients with and without electrocardiogram (ECG) tracings. Mean processing time for auto-MAPSE was 0.3 s per cardiac cycle/view. Overall feasibility was >90% for manual MAPSE and ECG-enabled auto-MAPSE and 82% for ECG-disabled auto-MAPSE. Feasibility in at least two walls was ≥95% for all methods. Compared with manual reference, bias [95% limits of agreement (LoA)] was -0.5 [-4.0, 3.1] mm for ECG-enabled auto-MAPSE and -0.2 [-4.2, 3.6] mm for ECG-disabled auto-MAPSE. Intra-class correlation coefficient (ICC) for consistency was 0.90 and 0.88, respectively. Manual inter-observer bias [95% LoA] was -0.9 [-4.7, 3.0] mm, and ICC was 0.86. Auto-MAPSE was fast and highly feasible. Inter-rater reliability between auto-MAPSE and manual reference was good. Agreement between auto-MAPSE and manual reference did not differ from manual inter-observer agreement. As the principal advantages of deep-learning-based assessment are speed and reproducibility, auto-MAPSE has the potential to improve real-time monitoring of left ventricular function. This should be investigated in relevant clinical settings.

Traversing Their Path to the Peripheral Smear: The Journey of Traumatized Red Blood Cells.

Background Thrombotic microangiopathy encompasses a wide range of conditions, of which thrombotic thrombocytopenic purpura being a medical emergency requires prompt intervention, with schistocytes being a reliable morphological indicator of microvascular injury. However, there are conditions other than thrombotic microangiopathic anemia where schistocytes can be seen in large numbers. These nonthrombotic microangiopathic conditions are broadly grouped under cytoskeletal abnormalities, mechanical damage, and thermal injuries. Automated methods in schistocyte evaluation have shown varied reproducibility requiring manual identification. International Council for Standardization in Hematology (ICSH) recommends standardized morphological criteria and quantitative assessment as a percentage after counting at least 1,000 red blood cells in optimal areas of smear to reduce interobserver variability. Objectives The aim of this study was to evaluate and quantitate schistocytes in thrombotic microangiopathic and nonthrombotic microangiopathic groups using ICSH guidelines and to evaluate interobserver reproducibility of manual schistocyte count. Materials and Methods Overall, 157 peripheral blood smears showing schistocytes were studied by two independent observers using ICSH recommendations on light microscopy. The hematological findings were correlated with clinical diagnosis and other relevant investigations. Results Schistocytes were observed in five cases of thrombotic microangiopathic anemia and 152 cases of nonthrombotic microangiopathic anemia. Schistocyte count in thrombotic microangiopathic anemia and nonthrombotic microangiopathic anemia groups with mean (±standard deviation) value was 2.28 ± 2.65% and 0.76 ± 0.67%, respectively ( p < 0.001). The correlation coefficient between the two observers was 0.59 (confidence interval = 0.966-1.346) showing an excellent agreement on the reproducibility of schistocytes by application of ICSH guidelines. Conclusion Percentage of schistocytes more than 1% is a robust morphological indicator for diagnosis of thrombotic microangiopathic anemia in adults. Strict application of ICSH guidelines reduces interobserver bias.

A study on calcification, variability of the stylo-mandibular ligament, or styloid process with regard to clinical parameters among United Arab Emirates population

Aim: The styloid process (SP) is often considered elongated when it is longer than 33 mm. The aim of this study is to assess the prevalence of the elongated styloid process (ESP) among dental patients and the role of dental pathology as a possible etiological factor. Materials and Methods: In total, 2000 consecutive panoramic radiographs of normal people were retrieved from the College of Dentistry, Ajman University, Ajman, UAE, during the 2-year study period. Two calibrated observers evaluated the radiographs to minimize interobserver bias and error. A caliper was used to measure the length (in millimeters of the ESPs directly on the radiographs from the caudal margin of the tympanic plate to the tip of the SP). The ESP was considered present when the measurements were ≥30 mm. Results: This study indicates that the prevalence of the ESP was about 6.9% among the patients who attended the dental school clinic. Of the 2000 panoramic radiographs reviewed, ESP could be measured in 100 cases at least on one side. There was a significant difference between distributions on the left and right sides. The distribution also depends significantly on age and gender. The incidence of related symptoms was higher than that reported in previous studies. Conclusions: The incidence of ESP among dental patients was estimated to be 6.9%, more prevalent among the elderly compared to the young people and bilateral. Odds ratio (OR) in favor of developing ESP in males is 2.378 times more than that in females. In contrast, the OR in favor of having unilateral ESP in males is less than that in females by 0.284.

Inter-observer variance and agreement of wildlife information extracted from camera trap images

Camera traps are a popular tool in terrestrial wildlife research due to their low costs, easy operability, and usefulness for studying a wide array of species and research questions. The vast numbers of images they generate often require multiple human data extractors, yet accuracy and inter-observer variance are rarely considered. We compared results from 10 observers who processed the same set of multi-species camera trap images (n = 11,560) from seven sites. We quantified inter-observer agreement and variance for (1) the number of mammals identified, (2) the number of images saved, (3) species identification accuracy and the types of mistakes made, and (4) counts of herbivore groups and individuals. We analysed the influence of observer experience, species distinctiveness and camera location. Observers varied significantly regarding image processing rates, the number of mammals found and images saved, and species misidentifications. Only one observer detected all 22 mammals (range: 18–22, n = 10). Experienced observers processed images up to 4.5 times faster and made less mistakes regarding species detection and identification. Missed species were mostly small mammals (56.5%) while misidentifications were most common among species with low phenotypic distinctiveness. Herbivore counts had high to very high variances with mainly moderate agreement across observers. Observers differed in how they processed images and what they recorded. Our results raise important questions about the reliability of data extracted by multiple observers. Inter-observer bias, observer-related variables, species distinctiveness and camera location are important considerations if camera trapping results are to be used for population estimates or biodiversity assessments.

The optimal dose of oral tranexamic acid in melasma: A network meta-analysis.

Melasma is a chronic skin condition that adversely impacts quality of life. Although many therapeutic modalities are available there is no single best treatment for melasma. Oral tranexamic acid has been used for the treatment of this condition but its optimal dose is yet to be established. We used network meta-analysis to determine the optimal dose of oral tranexamic acid for the treatment of melasma. We conducted a comprehensive search of all studies of oral tranexamic acid for the treatment of melasma up to September 2020 using PubMed, EMBASE and the Cochrane Library database. The quality of the studies was evaluated using the Jadad score and the Cochrane's risk of bias assessment tool. Only high quality randomised controlled trials were selected. Some studies lacked standard deviation of changes from baseline and these were estimated using the correlation coefficient obtained from another similar study. A total of 92 studies were identified of which 6 randomized controlled trials comprising 599 patients were included to form 3 pair-wise network comparisons. The mean age of the patients in these studies ranged from 30.3 to 46.5 years and the treatment duration ranged from 8 to 12 weeks. The Jadad scores ranged from 5 to 8. The optimal dose and duration of oral tranexamic acid was estimated to be 750 mg per day for 12 consecutive weeks. Some confounding factors might not have been described in the original studies. Although clear rules were followed, the Melasma Area and Severity Index and the modified Melasma Area and Severity Index were scored by independent physicians and hence inter-observer bias could not be excluded. Oral tranexamic acid is a promising drug for the treatment of melasma. This is the first network meta-analysis to determine the optimal dose of this drug and to report the effects of different dosages. The optimal dose is 250 mg three times per day for 12 weeks, but 250 mg twice daily may be an acceptable option in poorly adherent patients. Our findings will allow physicians to balance drug effects and medication adherence. Personalized treatment plans are warranted.

Using the Axial Oblique View of Computed Tomography (CT) in Evaluating Femoral Anteversion: A Comparative Cadaveric Study.

Twenty-five cadaveric adult femora’s anteversion angles were measured to develop a highly efficient and reproducible femoral anteversion measurement method using computed tomography (CT). Digital photography captured the proximal femur’s two reference lines, head-to-neck (H-N) and head-to-greater trochanter (H-G). Six reference lines (A/B in transverse section; C, axial oblique section; D/E, conventional 3D reconstruction; and M, volumetric 3D reconstruction) from CT scans were used. The posterior condylar line was used as a distal femoral reference. As measured with the H-N and H-G lines, the anteversion means were 10.43° and 19.50°, respectively. Gross anteversion measured with the H-G line had less interobserver bias (ICC; H-N = 0.956, H-G = 0.982). The 2D transverse and volumetric 3D CT sections’ B/M lines were consistent with the H-N line (p: B = 0.925, M = 0.122) and the 2D axial oblique section’s C line was consistent with the H-G line (p < 0.1). The D/E lines differed significantly from the actual gross images (p < 0.05). Among several CT scan femoral anteversion measurement methods, the novel anteversion angle measurement method using CT scans’ axial oblique section was approximated with actual gross femoral anteversion angle from the femoral head to the greater trochanter.

Superior reproducibility and repeatability in automated quantitative pupillometry compared to standard manual assessment, and quantitative pupillary response parameters present high reliability in critically ill cardiac patients.

Quantitative pupillometry is part of multimodal neuroprognostication of comatose patients after out-of-hospital cardiac arrest (OHCA). However, the reproducibility, repeatability, and reliability of quantitative pupillometry in this setting have not been investigated. In a prospective blinded validation study, we compared manual and quantitative measurements of pupil size. Observer and device variability for all available parameters are expressed as mean difference (bias), limits of agreement (LoA), and reliability expressed as intraclass correlation coefficients (ICC) with a 95% confidence interval. Fifty-six unique quadrupled sets of measurement derived from 14 sedated and comatose patients (mean age 70±12 years) were included. For manually measured pupil size, inter-observer bias was -0.14±0.44 mm, LoA of -1.00 to 0.71 mm, and ICC at 0.92 (0.86-0.95). For quantitative pupillometry, we found bias at 0.03±0.17 mm, LoA of -0.31 to 0.36 mm and ICCs at 0.99. Quantitative pupillometry also yielded lower bias and LoA and higher ICC for intra-observer and inter-device measurements. Correlation between manual and automated pupillometry was better in larger pupils, and quantitative pupillometry had less variability and higher ICC, when assessing small pupils. Further, observers failed to detect 26% of the quantitatively estimated abnormal reactivity with manual assessment. We found ICC >0.91 for all quantitative pupillary response parameters (except for latency with ICC 0.81-0.91). Automated quantitative pupillometry has excellent reliability and twice the reproducibility and repeatability than manual pupillometry. This study further presents novel estimates of variability for all quantitative pupillary response parameters with excellent reliability.