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STATISTICS
Year : 2017  |  Volume : 8  |  Issue : 4  |  Page : 187-191

Common pitfalls in statistical analysis: Measures of agreement

Priya Ranganathan1, CS Pramesh2, Rakesh Aggarwal3
1 Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India
2 Department of Surgical Oncology, Tata Memorial Centre, Mumbai, Maharashtra, India
3 Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

Date of Web Publication5-Oct-2017

Correspondence Address:
Priya Ranganathan
Department of Anaesthesiology, Tata Memorial Centre, Ernest Borges Road, Parel, Mumbai - 400 012, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


Read associated Erratum: Erratum: Common pitfalls in statistical analysis: Measures of agreement with this article

DOI: 10.4103/picr.PICR_123_17

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   Abstract 


Agreement between measurements refers to the degree of concordance between two (or more) sets of measurements. Statistical methods to test agreement are used to assess inter-rater variability or to decide whether one technique for measuring a variable can substitute another. In this article, we look at statistical measures of agreement for different types of data and discuss the differences between these and those for assessing correlation.

Keywords: Agreement, biostatistics, concordance


How to cite this article:
Ranganathan P, Pramesh C S, Aggarwal R. Common pitfalls in statistical analysis: Measures of agreement. Perspect Clin Res 2017;8:187-91

How to cite this URL:
Ranganathan P, Pramesh C S, Aggarwal R. Common pitfalls in statistical analysis: Measures of agreement. Perspect Clin Res [serial online] 2017 [cited 2023 Mar 25];8:187-91. Available from: http://www.picronline.org/text.asp?2017/8/4/187/215973




   Introduction Top


Often, one is interested in knowing whether measurements made by two (sometimes more than two) different observers or by two different techniques produce similar results. This is referred to as agreement or concordance or reproducibility between measurements. Such analysis looks at pairs of measurements, either both categorical or both numeric, with each pair having been made on one individual (or a pathology slide, or an X-ray).

Superficially, these data may appear to be amenable to analysis using methods used for 2 × 2 tables (if the variable is categorical) or correlation (if numeric), which we have discussed previously in this series.[1],[2] However, a closer look would show that this is not true. In those methods, the two measurements on each individual relate to different variables (e.g., exposure and outcome, or height and weight, etc), whereas in the “agreement” studies, the two measurements relate to the same variable (e.g., chest radiographs rated by two radiologists or hemoglobin measured by two methods).


   What Is Agreement? Top


Let us consider the case of two examiners A and B evaluating answer sheets of 20 students in a class and marking each of them as “pass” or “fail,” with each examiner passing half the students. [Table 1] shows three different situations that may happen. In situ ation 1 in this table, eight students receive a “pass” grade from both the examiners, eight receive a “fail” grade from both the examiners, and four receive pass grade from one examiner but “fail” grade from the other (two passed by A and the other two by B). Thus, the two examiners' results agree for 16/20 students (agreement = 16/20 = 0.80, disagreement = 4/20 = 0.20). This seems quite good. However, this fails to take into account that some of the grades may have been guesswork and that the agreement may have occurred just by chance.
Table 1: Results of 20 students, each evaluated independently by two examiners

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Let us now consider a hypothetical situation where examiners do exactly this, i.e., assign grades by tossing a coin; heads = pass, tails = fail [Table 1], Situation 2]. In that case, one would expect 25% (=0.50 × 0.50) of students to receive pass grade from both and another 25% to receive “fail” grade from both – an overall “expected” agreement rate for “pass” or “fail” of 50% (=0.25 + 0.25 = 0.50). Hence, the observed agreement rate (80% in situ ation 1) needs to be interpreted keeping in mind that 50% agreement was expected purely by chance. These examiners could have bettered this by 50% (best possible agreement minus the agreement expected by chance = 100%−50% =50%), but achieved only 30% (observed agreement minus the agreement expected by chance = 80%−50% =30%). Thus, their real performance in being concordant is 30%/50% = 60%.

Of course, they could theoretically have performed worse than what was expected by chance. For instance, in situ ation 3 [Table 1], even though each of them passed 50% of students, their grades agreed for only 4 of the 20 students – far fewer than that expected even by chance!

It is important to note that, in each of the three situations in [Table 1], the pass percentages for the two examiners are equal, and if the two examiners are compared using a usual 2 × 2 test for paired data (McNemar's test), one would find no difference between their performances; by contrast, the inter-observer agreement in the three situations is widely different. The basic concept to be understood here is that “agreement” quantifies the concordance between the two examiners for each of the “pairs” of scores and not the similarity of the overall pass percentage between the examiners.


   Methods Used to Measure Agreement Top


The statistical methods used to assess agreement vary depending on the type of variable being studied and the number of observers between whom agreement is sought to be assessed. These are summarized in [Table 2] and discussed below.
Table 2: Methods used for assessment of agreement between observers depending on the type of variable measured and the number of observers

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   Assessing Agreement between Measurements of Categorical Variables Top


Two observers assessing the same binary outcome (Cohen's kappa)

Cohen's kappa (κ) calculates inter-observer agreement taking into account the expected agreement by chance as follows:

κ = (observed agreement [Po] – expected agreement [Pe])/(1-expected agreement [Pe]).

In the above example [Table 1], Situation 1], Cohen's k = (0.80 − 0.50)/(1 − 0.50) = 0.30/0.50 = 0.60.

The κ statistic can take values from − 1 to 1, and is interpreted somewhat arbitrarily as follows: 0 = agreement equivalent to chance; 0.10–0.20 = slight agreement; 0.21–0.40 = fair agreement; 0.41–0.60 = moderate agreement; 0.61–0.80 = substantial agreement; 0.81–0.99 = near-perfect agreement; and 1.00 = perfect agreement. Negative values indicate that the observed agreement is worse than what would be expected by chance. An alternative interpretation offered is that kappa values below 0.60 indicate a significant level of disagreement.

Cohen's κ can also be used when the same rater evaluates the same patients at two time points (say 2 weeks apart) or, in the example above, grades the same answer sheets again after 2 weeks. Its limitations are: (i) it does not take into account the magnitude of differences, making it unsuitable for ordinal data, (ii) it cannot be used if there are more than two raters, and (iii) it does not differentiate between agreement for positive and negative findings – which may be important in clinical situations (e.g., wrongly diagnosing a disease versus wrongly excluding it may have different consequences).

Variations of Cohen's κ

Weighted kappa

For ordinal data, where there are more than two categories, it is useful to know if the ratings by different raters varied by a small degree or by a large amount. For example, microbiologists may rate bacterial growth on culture plates as: none, occasional, moderate, or confluent. Here, ratings of a particular plate by two reviewers as “occasional” and “moderate,” respectively, would imply a lower level of discordance than if these ratings were “no growth” and “confluent,” respectively. The weighted Kappa statistic takes this difference into account. It thus yields a higher value when the raters' responses correspond more closely, with the maximum scores for perfect agreement; conversely, a larger difference in two ratings provides a lower value of weighted kappa. Techniques for assigning weightage to the difference between categories (linear, quadratic) can vary.

Fleiss' kappa

This method is used when ratings by more than two observers are available for either binary or ordinal data.


   Assessing Agreement between Measurements of Continuous Variables Top


Two methods are available for assessing agreement between measurements of a continuous variable across observers, instruments, time points, etc. One of these, namely intra-class correlation coefficient (ICC), provides a single measure of the extent of agreement, and the other, namely Bland–Altman plot, in addition, provides a quantitative estimate of how closely the values from two measurements lie.

Intra-class correlation coefficient

Let us think of two ophthalmologists measuring intraocular pressure using a tonometer. Each patient will thus have two readings – one by each observer. ICC provides an estimate of overall concordance between these readings. It is somewhat akin to “analysis of variance” in that it looks at the between-pair variances expressed as a proportion of the total variance of the observations (i.e., the total variability in “2n” observations, which would be expected to be the sum of within- and between-pair variances). The ICC can take a value from 0 to 1, with 0 indicating no agreement and 1 indicating perfect agreement.

Bland–Altman plots

When two instruments or techniques are used to measure the same variable on a continuous scale, the Bland–Altman plots can be used to estimate agreement. This plot is a scatter plot of the difference between the two measurements (Y-axis) against the average of the two measurements (X-axis). Thus, it provides a graphical display of bias (mean difference between the two observers or techniques) with 95% limits of agreement. The latter are given by the formula:

Limits of agreement = mean observed difference ± 1.96 × standard deviation of observed differences.

Consider a situation where we wish to assess the agreement between hemoglobin measurements (in g/dL) using a bedside hemoglobinometer and the formal photometric laboratory technique in ten persons [Table 3]. The Bland–Altman plot for these data shows the difference between the two methods for each person [Figure 1]. The mean difference between the values is 1.07 g/dL (with standard deviation of 0.36 g/dL), and the 95% limits of agreement are 0.35–1.79. What this implies is that hemoglobin level of a particular person measured by photometry could vary from that measured by the bedside method from as little as 0.35 g/dL higher to as much as 1.79 g/dL higher (this is the case for 95% of individuals; for 5% of individuals, variations could be outside these limits). This obviously means that the two techniques cannot be used as substitutes for one another. Importantly, there is no uniform criterion for what constitutes acceptable limits of agreement; this is a clinical decision and depends on the variable being measured.
Table 3: Hemoglobin measurements in ten patients using two different methods

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Figure 1: Bland–Altman plot for data shown in Table 3. The upper and lower limits of agreement are generally drawn at 1.96 (roughly 2) standard deviations (of observed inter-observer differences) above and below the line representing the mean difference (solid line); these dotted lines are expected to enclose 95% of the observed inter-observer differences

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   Points to Remember Top


Correlation versus agreement

As alluded to above, correlation is not synonymous with agreement. Correlation refers to the presence of a relationship between two different variables, whereas agreement looks at the concordance between two measurements of one variable. Two sets of observations, which are highly correlated, may have poor agreement; however, if the two sets of values agree, they will surely be highly correlated. For instance, in the hemoglobin example, even though the agreement is poor, the correlation coefficient between values from the two methods is high [Figure 2]; (r = 0.98). The other way to look at it is that, though the individual dots are not fairly close to the dotted line (least square line;[2] indicating good correlation), these are quite far from the solid black line, which represents the line of perfect agreement ([Figure 2]: the solid black line). In case of good agreement, the dots would be expected to fall on or near this (the solid black) line.
Figure 2: Scatter plot showing correlation between hemoglobin measurements from two methods for data shown in Table 3 and Figure 1. The dotted line is a trend line (least squares line) through the observed values, and the correlation coefficient is 0.98. However, the individual dots are far away from the line of perfect agreement (solid black line)

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Use of paired tests to assess agreement

For all the three situations shown in [Table 1], the use of McNemar's test (meant for comparing paired categorical data) would show no difference. However, this cannot be interpreted as an evidence of agreement. The McNemar's test compares overall proportions; therefore, any situation where the overall proportion of pass/fail by the two examiners is similar (e.g., situations 1, 2, and 3 in [Table 1]) would result in a lack of difference. Similarly, the paired t-test compares mean difference between two observations in a group. It can therefore be nonsignificant if the average difference between the paired values is small, even though the differences between two observers for individuals are large.


   Suggested Reading Top


The readers are referred to the following papers that feature measures of agreement:

  1. Qureshi et al. compared the grade of prostatic adenocarcinoma as assessed by seven pathologists using a standard system (Gleason's score).[3] Concordance between each pathologist and the original report and between pairs of pathologists was determined using Cohen's kappa. It is a useful example. However, we feel that, Gleason's score being an ordinal variable, weighted kappa might have been a more appropriate choice
  2. Carlsson et al. looked at inter- and intra-observer variability in Hand Eczema Extent Score in patients with hand eczema.[4] Inter- and intra-observer reliability was assessed using the ICC
  3. Kalantri et al. looked at the accuracy and reliability of pallor as a tool for detecting anemia.[5] They concluded that “Clinical assessment of pallor can rule out and modestly rule in severe anemia.” However, the inter-observer agreement for detecting pallor was very poor (kappa values = 0.07 for conjunctival pallor and 0.20 for tongue pallor) which means that pallor is an unreliable sign for diagnosing anemia.


Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Ranganathan P, Pramesh CS, Aggarwal R. Common pitfalls in statistical analysis: Logistic regression. Perspect Clin Res 2017;8:148-51.  Back to cited text no. 1
  [Full text]  
2.
Aggarwal R, Ranganathan P. Common pitfalls in statistical analysis: The use of correlation techniques. Perspect Clin Res 2016;7:187-90.  Back to cited text no. 2
[PUBMED]  [Full text]  
3.
Qureshi A, Lakhtakia R, AL Bahri M, Al Haddabi I, Saparamadu A, Shalaby A, et al. Gleason's grading of prostatic adenocarcinoma: Inter-observer variation among seven pathologists at a tertiary care center in Oman. Asian Pac J Cancer Prev 2016;17:4867-8.  Back to cited text no. 3
    
4.
Carlsson A, Svensson Š, Anderson CD, Baranovskaya I, Hindsén-Stenström M, Holt I, et al. Scoring of hand eczema: Good reliability of hand eczema extent score (HEES). Acta Derm Venereol 2017;97:193-7.  Back to cited text no. 4
    
5.
Kalantri A, Karambelkar M, Joshi R, Kalantri S, Jajoo U. Accuracy and reliability of pallor for detecting anaemia: A hospital-based diagnostic accuracy study. PLoS One 2010;5:e8545.  Back to cited text no. 5
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]


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BMJ Open. 2022; 12(6): e052209
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46 Prevalence of non-diabetic kidney disease and inability of clinical predictors to differentiate it from diabetic kidney disease: results from a prospectively performed renal biopsy study
Madhurima Basu, Smartya Pulai, Subhasis Neogi, Mainak Banerjee, Nitai P Bhattacharyya, Sanghamitra Sengupta, Pradip Mukhopadhyay, Arpita Ray Chaudhury, Sujoy Ghosh
BMJ Open Diabetes Research & Care. 2022; 10(6): e003058
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47 Development of a new version of the Bristol Stool Form Scale: translation, content validity, face validity, and reliability of the Persian version
Nasim Shokouhi, Samira Mohammadi, Zeenat Ghanbari, Ali Montazeri
BMJ Open Gastroenterology. 2022; 9(1): e001017
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48 Examination of New Electrocardiographic Repolarization Markers in Diabetic Patients with Noncritical Coronary Artery Disease
Müjgan Gürler, Mehmet Inanir, Anca Daniela Farcas
International Journal of Clinical Practice. 2022; 2022: 1
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49 Evaluation of methods to distinguish trips from activities in walking and cycling GPS data
Elmira Berjisian, Alexander Bigazzi
Transportation Research Part C: Emerging Technologies. 2022; 137: 103588
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50 How is vowel production in Italian affected by geminate consonants and stress patterns?
Lucia COLOMBO, Michela INFANTI, Joanne ARCIULI
Journal of Child Language. 2022; : 1
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51 A genotyping by sequencing approach can disclose Apis mellifera population genomic information contained in honey environmental DNA
Samuele Bovo, Valerio Joe Utzeri, Anisa Ribani, Valeria Taurisano, Giuseppina Schiavo, Luca Fontanesi
Scientific Reports. 2022; 12(1)
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52 Reducing gender bias in household consumption data: Implications for food fortification policy
Helen Harris-Fry, Lauren Lamson, Katelyn Roett, Elizabeth Katz
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53 Masseter muscle volume as a disease marker in adult-onset myotonic dystrophy type 1
Agata Oliwa, Clarissa Hocking, Mark J Hamilton, John McLean, Sarah Cumming, Bob Ballantyne, Ravi Jampana, Cheryl Longman, Darren G Monckton, Maria Elena Farrugia
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54 Subtyping intestinal metaplasia in patients with chronic atrophic gastritis: an interobserver variability study
Julia M. Lerch, Rish K. Pai, Ian Brown, Anthony J. Gill, Dhanpat Jain, Bence Kovári, Ryoji Kushima, Kieran Sheahan, Tomas Slavik, Amitabh Srivastava, Gregory Y. Lauwers, Cord Langner
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55 Spatial covariance analysis of FDG-PET and HMPAO-SPECT for the differential diagnosis of dementia with Lewy bodies and Alzheimer's disease
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56 Evaluating Agreement between Clinic and Patient-Reported Outcomes for Weight and Comorbidities at 1 Year Following Bariatric Surgery
Arielle Grieco, Meridith E. Greene, Clifford Y. Ko, Mark E. Cohen, Kimberly Evans-Labok, Teresa Fraker, Matthew M. Hutter
Surgery for Obesity and Related Diseases. 2022;
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57 Just teasing! - Infants' and toddlers' understanding of teasing interactions and its effect on social bonding
Livia Colle, Gerlind Grosse, Tanya Behne, Michael Tomasello
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58 CT measures of femoral and tibial version and rotational position of femoral and tibial components of knee replacements: limitations in reliability and suitability for routine clinical practice
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59 A standardized method to measure the membranous urethral length (MUL) on MRI of the prostate with high inter- and intra-observer agreement
Hans Veerman, Marinus J. Hagens, Caroline M. Hoeks, Henk G. van der Poel, Pim J. van Leeuwen, André N. Vis, Stijn W. T. J. P. Heijmink, Ivo G. Schoots, Margriet C. de Haan, Thierry N. Boellaard
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60 Long-term Reported Outcomes Following Primary Laparoscopic Sleeve Gastrectomy
Nasser Sakran, Kim Soifer, Keren Hod, Shiri Sherf-Dagan, Sharon Soued, Yafit Kessler, Dana Adelson, Reut Biton, J. N. Buchwald, David Goitein, Asnat Raziel
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61 Effectiveness of Mobile-Based Mindfulness Interventions in Improving Mindfulness Skills and Psychological Outcomes for Adults: a Systematic Review and Meta-regression
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62 Are We Agreed? Self- Versus Proxy-Reporting of Paediatric Health-Related Quality of Life (HRQoL) Using Generic Preference-Based Measures: A Systematic Review and Meta-Analysis
Diana Khanna, Jyoti Khadka, Christine Mpundu-Kaambwa, Kiri Lay, Remo Russo, Julie Ratcliffe, Nancy Devlin, Richard Norman, Rosalie Viney, Julie Ratcliffe, Kim Dalziel, Brendan Mulhern, Harriet Hiscock, Deborah Street, Gang Chen, Tessa Peasgood, Cate Bailey, Christine Mpundu-Kaambwa, Alice Yu, Mina Bahrampour, Renee Jones, Rachel O’Loughlin, Yiting Luo, Alex van Heusden, Xiuqin Xiong, Diana Khanna, Ashwini De Silva
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63 Ecological Momentary Assessment: A Systematic Review of Validity Research
Lesleigh Stinson, Yunchao Liu, Jesse Dallery
Perspectives on Behavior Science. 2022;
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64 Managing Boundary Uncertainty in Diagnosing the Patients of Rural Area Using Fuzzy and Rough Set
Sayan Das, Jaya Sil
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65 Exploring Worker Experience as a Predictor of Routine and Non-routine Safety Performance Outcomes in the Mining Industry
Cassandra L. Hoebbel, Emily J. Haas, Margaret E. Ryan
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66 Agreement and Correlation Between Different Topical Corticosteroid Potency Classification Systems
Alexa C. Bowie, Mina Tadrous, Alexander Egeberg, Jane Harvey, Stephanie J. Lax, Jacob P. Thyssen, Aaron M. Drucker
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67 Transvaginal Two-Dimensional Ultrasound Evaluation as a Screening Tool for Levator ani Muscle Avulsion in Postpartum Women
Yue Wang, HuiFang Wang
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68 Limitations of laparoscopy to assess the peritoneal cancer index and eligibility for cytoreductive surgery with HIPEC in peritoneal metastasis
Can Yurttas, Lisa Überrück, Giorgi Nadiradze, Alfred Königsrainer, Philipp Horvath
Langenbeck's Archives of Surgery. 2022;
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69 External validation of the deep learning system “SpineNet” for grading radiological features of degeneration on MRIs of the lumbar spine
Alexandra Grob, Markus Loibl, Amir Jamaludin, Sebastian Winklhofer, Jeremy C. T. Fairbank, Tamás Fekete, François Porchet, Anne F. Mannion
European Spine Journal. 2022;
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70 Ultrasonography: an interesting imaging method for ligament assessment during the acute phase of closed elbow injuries
Romain Bilger, Pierre Laumonerie, Hugo Barret, Franck Lapègue, Pierre Mansat, Nicolas Sans, Marie Faruch-Bilfeld
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71 An Evaluation of Parent and Teacher Discrepancies on an Adaptive Behavior Measure for Youth with Autism Spectrum Disorder, Intellectual Disability, and Global Developmental Delay
Mallory A. Stevens, Kimberly J. Selders, Olivia Jeckel, Valerie Brownfield, Kerri P. Nowell
Journal of Autism and Developmental Disorders. 2022;
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72 Evaluation of the quality of ‘do not use’ medication abbreviation audits: a key enabler to successful implementation of audit and feedback
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International Journal of Clinical Pharmacy. 2021;
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73 Determining leaf nutrient concentrations in citrus trees using UAV imagery and machine learning
Lucas Costa, Sudip Kunwar, Yiannis Ampatzidis, Ute Albrecht
Precision Agriculture. 2021;
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74 Prognostic and predictive impact of stroma cells defined by PDGFRb expression in early breast cancer: results from the randomized SweBCG91RT trial
Carina Strell,Axel Stenmark Tullberg,Reidunn Jetne Edelmann,Lars Andreas Akslen,Per Malmström,Mårten Fernö,Erik Holmberg,Arne Östman,Per Karlsson
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75 Correlation does not imply agreement: A cautionary tale for researchers and reviewers
Christopher Edwards,Heather Allen,Crispen Chamunyonga
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76 The Rosenberg view and coronal stress radiographs give similar measurements of articular cartilage height in knees with osteoarthritis
Jacob F. Mortensen,Andreas Kappel,Lasse E. Rasmussen,Svend E. Østgaard,Anders Odgaard
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77 The reliability of radiographic measures of total ankle replacement position: an analysis from the OARS cohort
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78 Comparing video observation to electronic topography device as a method for measuring cigarette puffing behavior
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79 MRI in the Assessment of TMJ-Arthritis in Children with JIA; Repeatability of a Newly Devised Scoring System
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Academic Radiology. 2021;
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80 Detection of EGFR mutations in liquid biopsy samples using allele-specific quantitative PCR: A comparative real-world evaluation of two popular diagnostic systems
Adam Szpechcinski,Maciej Bryl,Piotr Wojcik,Grzegorz Czyzewicz,Emil Wojda,Piotr Rudzinski,Katarzyna Duk,Joanna Moes-Sosnowska,Krystyna Maszkowska-Kopij,Renata Langfort,Aleksander Barinow-Wojewodzki,Joanna Chorostowska-Wynimko
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81 Incorporating personal-device-based point-of-care ultrasound into obstetric care: a validation study
Cecilia B. Leggett, Mariam Naqvi, Tania F. Esakoff, Marcio A. Diniz, Melissa S. Wong
American Journal of Obstetrics and Gynecology. 2021;
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82 Absence of relevant clinical effects of SARS-COV-2 on the affinity of hemoglobin for O2 in patients with COVID-19
Sergi Pascual-Guàrdia, Antoni Ferrer, Óscar Díaz, Antonio O. Caguana, Elvira Tejedor, Salomé Bellido-Calduch, Diego A. Rodríguez-Chiaradia, Joaquim Gea
Archivos de Bronconeumología (English Edition). 2021;
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83 Ausencia de efectos clínicos destacables del SARS-CoV-2 sobre la afinidad de la hemoglobina por el O2 en pacientes con COVID-19
Sergi Pascual-Guàrdia,Antoni Ferrer,Óscar Díaz,Antonio O. Caguana,Elvira Tejedor,Salomé Bellido-Calduch,Diego A. Rodríguez-Chiaradia,Joaquim Gea
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84 Teledermatología en Chile: experiencia de su implementación temprana
Diego Aragón-Caqueo,Montserrat Arceu,Gonzalo Aragón-Caqueo,Kathalina Zamora,Denis Tom,José Luis Gatica
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85 Minor migrants’ age estimation: Comparison of two dental methods
Francesco Lupariello,Alessandro Gabriele,Federica Mirri,Giuliana Mattioda,Emilio Nuzzolese,Giancarlo Di Vella
Forensic Science International: Synergy. 2021; 3: 100134
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86 Development and Initial Evaluation of Psychometric Properties of a Pain Competence Assessment Tool (PCAT)
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The Journal of Pain. 2021;
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87 Clinical Simulation Model of Fibrinogen Decline During Hemorrhage in Major Noncardiac Surgery
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88 Wearable technology-delivered lifestyle intervention amongst adults with overweight and obese: A systematic review and meta-regression
Sai Ho Wong, Zhen Yang Abel Tan, Ling Jie Cheng, Siew Tiang Lau
International Journal of Nursing Studies. 2021; : 104163
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89 Cariprazine and akathisia, restlessness, and extrapyramidal symptoms in patients with bipolar depression
Leslie Citrome,Lakshmi N. Yatham,Mehul D. Patel,Ágota Barabássy,Arlene Hankinson,Willie R. Earley
Journal of Affective Disorders. 2021; 288: 191
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90 Beyond Percent Correct: Measuring Change in Individual Picture Naming Ability
Grant M. Walker, Alexandra Basilakos, Julius Fridriksson, Gregory Hickok
Journal of Speech, Language, and Hearing Research. 2021; : 1
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91 Functional Communication Abilities in Youth With Cerebral Palsy: Association With Impairment Profiles and School-Based Therapy Goals
Clare Koopmans, Ashley Sakash, Jennifer Soriano, Helen L. Long, Katherine C. Hustad
Language, Speech, and Hearing Services in Schools. 2021; : 1
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92 Disentangling the Psycholinguistic Loci of Anomia with Cognitive Psychometric Models
Grant M. Walker
Seminars in Speech and Language. 2021; 42(03): 256
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93 Accuracy and Safety of Image-Guided Freehand Pin Placement in Canine Cadaveric Vertebrae
Eva S. Samer,Franck Forterre,Justus M.K. Rathmann,Veronika M. Stein,Christina M. Precht,Julien Guevar
Veterinary and Comparative Orthopaedics and Traumatology. 2021;
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94 Are subjective measures the answer to assess physical inactivity on a daily basis in patients with resistant hypertension?
Susana Lopes,José Mesquita-Bastos,Catarina Garcia,Daniela Figueiredo,Pedro Carvalho,José Oliveira,Jorge Polónia,Alberto Jorge Alves,Fernando Ribeiro
Journal of Human Hypertension. 2021;
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95 Bioelectrical impedance analysis versus quantitative computer tomography and anthropometry for the assessment of body composition parameters in China
Qian Qin,Yang Yang,Jingfeng Chen,Yaojun Jiang,Ang Li,Meng Huang,Yihan Dong,Shoujun Wang,Suying Ding
Scientific Reports. 2021; 11(1)
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96 Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images
Mansooreh Montazerin,Zahra Sajjadifar,Elias Khalili Pour,Hamid Riazi-Esfahani,Tahereh Mahmoudi,Hossein Rabbani,Hossein Movahedian,Alireza Dehghani,Mohammadreza Akhlaghi,Rahele Kafieh
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97 Interclinician agreement on the recognition of selected respiratory clinical signs in dogs and cats with abnormal breathing patterns
M. Domínguez-Ruiz, C.R. Reinero, A. Vientos-Plotts, M.E. Grobman, D. Silverstein, K. Le Boedec
The Veterinary Journal. 2021; 277: 105760
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98 High PDGFRb Expression Predicts Resistance to Radiotherapy in DCIS within the SweDCIS Randomized Trial
Carina Strell,Dick Folkvaljon,Erik Holmberg,Aglaia Schiza,Viktoria Thurfjell,Per Karlsson,Jonas Bergh,Troy Bremer,Lars A. Akslen,Fredrik Wärnberg,Arne Östman
Clinical Cancer Research. 2021; 27(12): 3469
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99 Early perceptions and behavioural responses during the COVID-19 pandemic: a cross-sectional survey of UK adults
Christina Atchison,Leigh Robert Bowman,Charlotte Vrinten,Rozlyn Redd,Philippa Pristerà,Jeffrey Eaton,Helen Ward
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100 Chest radiograph-based artificial intelligence predictive model for mortality in community-acquired pneumonia
Jessica Quah,Charlene Jin Yee Liew,Lin Zou,Xuan Han Koh,Rayan Alsuwaigh,Venkataraman Narayan,Tian Yi Lu,Clarence Ngoh,Zhiyu Wang,Juan Zhen Koh,Christine Ang,Zhiyan Fu,Han Leong Goh
BMJ Open Respiratory Research. 2021; 8(1): e001045
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101 Primer on binary logistic regression
Jenine K Harris
Family Medicine and Community Health. 2021; 9(Suppl 1): e001290
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102 A Pilot Study of Detecting Individual Sleep Apnea Events Using Noncontact Radar Technology, Pulse Oximetry, and Machine Learning
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103 Autism spectrum disorder and obstetric optimality: a twin study and meta-analysis of sibling studies
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Journal of Child Psychology and Psychiatry. 2021;
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104 Validation of a novel patient-operated device for measuring skin barrier function in atopic dermatitis
Erin E. Grinich,Christina Topham,Dylan Haynes,Janice Chung,Emile Latour,Eric L. Simpson
Skin Research and Technology. 2021;
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105 Dynamics of methylated cell-free DNA in the urine of non-small cell lung cancer patients
Sander Bach,Birgit M.M. Wever,Mark A. van de Wiel,Joris D. Veltman,Sayed M.S. Hashemi,Geert Kazemier,Idris Bahce,Renske D.M. Steenbergen
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106 Validation of the telephone-based assessment of locomotion ability after stroke
Patrick R. Avelino,Lucas R. Nascimento,Kênia K.P. Menezes,Ruani A. Tenório,Gabriela N. Cândido,Isabela S. Christovão,Luci F. Teixeira-Salmela
International Journal of Rehabilitation Research. 2021; 44(1): 88
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107 A Novel Application of the Modified Angoff Method to Rate Case Difficulty in Simulation-Based Research
Melissa N. Joseph, Jungsoo Chang, Samuel G. Buck, Marc A. Auerbach, Ambrose H. Wong, Thomas D. Beardsley, Philip M. Reeves, Jessica M. Ray, Leigh V. Evans
Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare. 2021; 16(6): e142
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108 Karnofsky Performance Score—Failure to Thrive as a Frailty Proxy?
Margaret R. Stedman,Daniel J. Watford,Glenn M. Chertow,Jane C. Tan
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109 Evaluating the influence of action- and subject-specific factors on chimpanzee action copying
Alba Motes-Rodrigo,Roger Mundry,Josep Call,Claudio Tennie
Royal Society Open Science. 2021; 8(2): 200228
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110 Phone-based monitoring to evaluate health policy and program implementation in Kenya
Paul G Ashigbie,Peter C Rockers,Richard O Laing,Howard J Cabral,Monica A Onyango,John Mboya,Daniella Arends,Veronika J Wirtz
Health Policy and Planning. 2021;
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111 Distinguishing sleep from wake with a radar sensor: a contact-free real-time sleep monitor
Hanne Siri Amdahl Heglum,Håvard Kallestad,Daniel Vethe,Knut Langsrud,Trond Sand,Morten Engstrøm
Sleep. 2021;
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112 What’s in a name? The meaning of sustainability to destination managers
Julia N. Albrecht,Marco Haid,Wiebke Finkler,Peter Heimerl
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113 A smartphone application to objectively monitor music listening habits in adolescents
Danique E. Paping,Jantien L. Vroegop,Simone P. C. Koenraads,Carlijn M.P. le Clercq,André Goedegebure,Robert J. Baatenburg de Jong,Marc P. van der Schroeff
Journal of Otolaryngology - Head & Neck Surgery. 2021; 50(1)
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114 Self-collected and clinician-collected anal swabs show modest agreement for HPV genotyping
Racheal S. Dube Mandishora,Trine B. Rounge,Megan Fitzpatrick,Irene Kraus Christiansen,Ole Herman Ambur,Sonja Lagström,Babill Stray-Pedersen,Massimo Tommasino,Joel Palefsky,Zvavahera M. Chirenje,Michael Scheurer
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115 Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies
Pairash Saiviroonporn,Kanchanaporn Rodbangyang,Trongtum Tongdee,Warasinee Chaisangmongkon,Pakorn Yodprom,Thanogchai Siriapisith,Suwimon Wonglaksanapimon,Phakphoom Thiravit
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116 Relationship between women’s decision-making power over their own health care and use of modern contraception in the Democratic Republic of the Congo: a cross-sectional secondary data analysis
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BMC Women's Health. 2021; 21(1)
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117 Validating Ellipsoid Zone Area Measurement With Multimodal Imaging in Choroideremia
Yi Zhai,Sarah Oke,Ian M. MacDonald
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118 An Intervention-Related Comparison of Preschoolers’ Scores on the TGMD-2 and TGMD-3
Kara K. Palmer,Katherine M. Chinn,Katherine Q. Scott-Andrews,Leah E. Robinson
Perceptual and Motor Skills. 2021; 128(4): 1354
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119 Response to Letter to the Editor Titled Remote Fiberoptic Nasopharyngolaryngoscopy in the Pediatric Population: Methodological Issues on Reliability and Accuracy
Lauren E. Miller,Adva Buzi,Rachel S. Rogers,Lisa M. Elden
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120 Characteristics of Acute Childhood Illness Apps for Parents: Environmental Scan
James Benoit, Lisa Hartling, Michelle Chan, Shannon Scott
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121 Impact of Guidelines on Hypertension Control in the Elderly
Del Pinto Rita, Mirela Dobre, Silvia Pagliacci, Claudio Ferri
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122 A Critical Overview of Systematic Reviews of Chemotherapy for Advanced and Locally Advanced Pancreatic Cancer using both AMSTAR2 and ROBIS as Quality Assessment Tools
Amit Dang, Surendar Chidirala, Prashanth Veeranki, B.N. Vallish
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123 Efficacy and Safety of EGFR Inhibitors in the Treatment of EGFRPositive NSCLC Patients: A Meta-Analysis
Amit Dang, Sumit Dang, B.N. Vallish
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124 Inhabiting the Body(ies) in Female Soccer Players: The Protective Role of Positive Body Image
Débora Godoy-Izquierdo,Isabel Díaz
Frontiers in Psychology. 2021; 12
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125 Galectin-3 Binding Protein, Depression, and Younger Age Were Independently Associated With Alexithymia in Adult Patients With Type 1 Diabetes
Eva O. Melin,Ralph Svensson,Jonatan Dereke,Magnus Hillman
Frontiers in Psychiatry. 2021; 12
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126 Development of a Colic Scoring System to Predict Outcome in Horses
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127 Assessment of a Rapid Semi-Quantitative Immunochromatographic Test for the Evaluation of Transfer of Passive Immunity in Calves
Pauline Delhez,Elise Meurette,Emilie Knapp,Léonard Theron,Georges Daube,Anne-Sophie Rao
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128 Breast Mass Classification Using Diverse Contextual Information and Convolutional Neural Network
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129 Inter-Reader Agreement of Diffusion-Weighted Magnetic Resonance Imaging for Breast Cancer Detection: A Multi-Reader Retrospective Study
Filippo Pesapane,Anna Rotili,Silvia Penco,Marta Montesano,Giorgio Maria Agazzi,Valeria Dominelli,Chiara Trentin,Maria Pizzamiglio,Enrico Cassano
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130 A Functional Network Model of the Metastasis Suppressor PEBP1/RKIP and Its Regulators in Breast Cancer Cells
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131 Prevalence and Associated Factors of Psychological Distress and Burnout among Medical Students: Findings from Two Campuses
Nik Muhammad Arif Nik Ahmad,Nurhanis Syazni Roslan,Shaiful Bahari Ismail,Ramyashilpa D. Nayak,Muhamad Ridzuan Jamian,Alya Syahmina Mohamad Ali Roshidi,Teh Chen Edward,Muhammad Aiman Kamal,Muhammad Mujaahid Mohd Amin,Shukri Shaari,Muhammad Fikri Shaharudin Basri
International Journal of Environmental Research and Public Health. 2021; 18(16): 8446
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132 Myelin Quantification in White Matter Pathology of Progressive Multiple Sclerosis Post-Mortem Brain Samples: A New Approach for Quantifying Remyelination
Marije J. D. Huitema, Eva M. M. Strijbis, Antonio Luchicchi, John G. J. M. Bol, Jason R. Plemel, Jeroen J. G. Geurts, Geert J. Schenk
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133 Smart Determination of Gold Content in PCBs of Waste Mobile Phones by Coupling of XRF and AAS Techniques
Nicolò Maria Ippolito,Gianmaria Belardi,Valentina Innocenzi,Franco Medici,Loris Pietrelli,Luigi Piga
Processes. 2021; 9(9): 1618
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134 Genetik Algoritma Yaklasimiyla Öznitelik Seçimi Kullanilarak Makine Ögrenmesi Algoritmalari ile Kalp Hastaligi Tahmini
Berna VATANSEVER, Hakan AYDIN, Ali ÇETINKAYA
Journal of Scientific Technology and Engineering Research. 2021;
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135 Levels of Urgency for Orthopaedic Procedures: Reliability and Adoption of a Consensus-driven Classification
Edward Y. Cheng, David M. Matson, Kyle D. Morgenstern, Julie Agel, Paul Hoogervorst
Journal of the American Academy of Orthopaedic Surgeons. 2021; 29(21): e1078
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136 Introduction to Artificial Intelligence and Machine Learning for Pathology
James H. Harrison,John R. Gilbertson,Matthew G. Hanna,Niels H. Olson,Jansen N. Seheult,James M. Sorace,Michelle N. Stram
Archives of Pathology & Laboratory Medicine. 2021; 145(10): 1228
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137 Validation of a Low-Cost Electrocardiography (ECG) System for Psychophysiological Research
Ruth Erna Wagner,Hugo Plácido da Silva,Klaus Gramann
Sensors. 2021; 21(13): 4485
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138 Validity of an inertial system for measuring velocity, force, and power during hamstring exercises performed on a flywheel resistance training device
Rodrigo Martín-San Agustín,Mariana Sánchez-Barbadora,José A. García-Vidal
PeerJ. 2020; 8: e10169
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139 CancerGram: An Effective Classifier for Differentiating Anticancer from Antimicrobial Peptides
Michal Burdukiewicz,Katarzyna Sidorczuk,Dominik Rafacz,Filip Pietluch,Mateusz Bakala,Jadwiga Slowik,Przemyslaw Gagat
Pharmaceutics. 2020; 12(11): 1045
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140 A Pilot Study of the Reliability and Agreement of Heart Rate, Respiratory Rate and Short-Term Heart Rate Variability in Elite Modern Pentathlon Athletes
Bartosz Hoffmann,Andrew A. Flatt,Luiz Eduardo Virgilio Silva,Marcel Mlynczak,Rafal Baranowski,Ewelina Dziedzic,Bozena Werner,Jakub S. Gasior
Diagnostics. 2020; 10(10): 833
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141 Geospatial analysis of environmental noise levels in a residential area in Lagos, Nigeria
Rose Anthony Alani, Olajomi Mary Ogunmoyela, Chukwuma John Okolie, Olagoke Emmanuel Daramola
Noise Mapping. 2020; 7(1): 223
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142 CT Angiography in Evaluating Large-Vessel Occlusion in Acute Anterior Circulation Ischemic Stroke: Factors Associated with Diagnostic Error in Clinical Practice
B.A.C.M. Fasen,R.J.J. Heijboer,F.-J.H. Hulsmans,R.M. Kwee
American Journal of Neuroradiology. 2020;
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143 Real world safety of bevacizumab in cancer patients: A systematic literature review of case reports
Amit Dang,P. Jagan Mohan Venkateshwara Rao,Ravi Kishore,B.N. Vallish
International Journal of Risk & Safety in Medicine. 2020; : 1
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144 Reliability of P3 Event-Related Potential During Working Memory Across the Spectrum of Cognitive Aging
Hannes Devos,Jeffrey M. Burns,Ke Liao,Pedram Ahmadnezhad,Jonathan D. Mahnken,William M. Brooks,Kathleen Gustafson
Frontiers in Aging Neuroscience. 2020; 12
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145 Rapid Administration of High-Dose Intravenous Methylprednisolone Improves Visual Outcomes After Optic Neuritis in Patients With AQP4-IgG-Positive NMOSD
Tetsuya Akaishi,Takayuki Takeshita,Noriko Himori,Toshiyuki Takahashi,Tatsuro Misu,Ryo Ogawa,Kimihiko Kaneko,Juichi Fujimori,Michiaki Abe,Tadashi Ishii,Kazuo Fujihara,Masashi Aoki,Toru Nakazawa,Ichiro Nakashima
Frontiers in Neurology. 2020; 11
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146 Predicting Poor Outcome Before Endovascular Treatment in Patients With Acute Ischemic Stroke
Lucas A. Ramos,Manon Kappelhof,Hendrikus J. A. van Os,Vicky Chalos,Katinka Van Kranendonk,Nyika D. Kruyt,Yvo B. W. E. M. Roos,Aad van der Lugt,Wim H. van Zwam,Irene C. van der Schaaf,Aeilko H. Zwinderman,Gustav J. Strijkers,Marianne A. A. van Walderveen,Mariekke J. H. Wermer,Silvia D. Olabarriaga,Charles B. L. M. Majoie,Henk A. Marquering
Frontiers in Neurology. 2020; 11
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147 Accuracy and Reliability of the Visual Assessment of Patellar Tracking
Matthew J. Best,Miho J. Tanaka,Shadpour Demehri,Andrew J. Cosgarea
The American Journal of Sports Medicine. 2020; 48(2): 370
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148 Disclosing Main authors and Organisations collaborations in bioprinting through network maps analysis
Leonardo Azael García-García,Marisela Rodríguez-Salvador
Journal of Biomedical Semantics. 2020; 11(1)
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149 Evaluation of intra- and interobserver reliability in the assessment of the ‘critical trochanter angle’
Sebastian Serong,Moritz Schutzbach,Ivica Zovko,Marcus Jäger,Stefan Landgraeber,Marcel Haversath
European Journal of Medical Research. 2020; 25(1)
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150 Predicting Metastatic Potential in Pheochromocytoma and Paraganglioma: A Comparison of PASS and GAPP Scoring Systems
Heather Wachtel,Troy Hutchens,Ezra Baraban,Lauren E Schwartz,Kathleen Montone,Zubair Baloch,Virginia LiVolsi,Lauren Krumeich,Douglas L Fraker,Katherine L Nathanson,Debbie L Cohen,Lauren Fishbein
The Journal of Clinical Endocrinology & Metabolism. 2020; 105(12)
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151 Comparison of radiographer interobserver image registration variability using cone beam CT and MR for cervix radiotherapy
John Rodgers,Rosie Hales,Lee Whiteside,Jacqui Parker,Louise McHugh,Anthea Cree,Marcel van Herk,Ananya Choudhury,Peter Hoskin,Alan McWilliam,Cynthia L Eccles
The British Journal of Radiology. 2020; : 20200169
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152 Brucellosis in food-producing animals in Mosul, Iraq: A systematic review and meta-analysis
Mohammad O. Dahl,Roy Martin Roop
PLOS ONE. 2020; 15(7): e0235862
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153 Assessing the Importance and Cognition Level of ACCE’s Student Learning Outcomes: Industry, Educator, and Student Perceptions
Mohammed S. Hashem M. Mehany,Richard Gebken
International Journal of Construction Education and Research. 2020; : 1
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154 Predictors of volitional motor recovery with epidural stimulation in individuals with chronic spinal cord injury
Samineh Mesbah,Tyler Ball,Claudia Angeli,Enrico Rejc,Nicholas Dietz,Beatrice Ugiliweneza,Susan Harkema,Maxwell Boakye
Brain. 2020;
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155 Disc-fovea Angle Is Associated With Visual Field Defect Location in Patients With Glaucoma
Ricardo Y. Abe,Alexis G. Matos,Carolina P.B. Gracitelli,Tiago S. Prata,Guilherme B. Ribeiro,Jayter S. Paula
Journal of Glaucoma. 2020; 29(10): 964
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156 Test-retest reliability of a self-reported physical activity environment instrument for use in rural settings
Verity Cleland,Anna Timperio,Melanie J. Sharman,James Dollman
Australian Journal of Rural Health. 2020; 28(2): 168
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157 Tooth Shade Preferences among the General Public
Balqees Almufleh,Elham Emami,Aliaa Al-Khateeb,Stefano Del Monte,Faleh Tamimi
Journal of Prosthodontics. 2020;
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158 Comparison of a rapid immunochromatographic test with a chemiluminescence immunoassay for detection of anti-SARS-CoV-2 IgM and IgG
Claudia Colomba,Marcello Ciaccio,Giulia Bivona,Luisa Agnello,Rosaria Vincenza Giglio,Bruna Lo Sasso,Caterina Maria Gambino
Biochemia medica. 2020; 30(3): 475
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159 Alchemical Hydration Free-Energy Calculations Using Molecular Dynamics with Explicit Polarization and Induced Polarity Decoupling: An On–the–Fly Polarization Approach
Braden D. Kelly,William R. Smith
Journal of Chemical Theory and Computation. 2020;
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160 A Simple Method for Including Polarization Effects in Solvation Free Energy Calculations When Using Fixed-Charge Force Fields: Alchemically Polarized Charges
Braden D. Kelly,William R. Smith
ACS Omega. 2020;
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161 Enhanced oral hygiene interventions as a risk mitigation strategy for the prevention of non-ventilator-associated pneumonia: a systematic review and meta-analysis
Poolakkad S. Satheeshkumar,Stefania Papatheodorou,Stephen Sonis
British Dental Journal. 2020; 228(8): 615
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162 Fibroblasts in urothelial bladder cancer define stroma phenotypes that are associated with clinical outcome
Artur Mezheyeuski,Ulrika Segersten,Lina Wik Leiss,Per-Uno Malmström,Jiri Hatina,Arne Östman,Carina Strell
Scientific Reports. 2020; 10(1)
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163 Using open-source software and digital imagery to efficiently and objectively quantify cover density of an invasive alien plant species
Julien Carlier,Eithne Davis,Sara Ruas,Dolores Byrne,Joseph M. Caffrey,Neil E. Coughlan,Jaimie T.A. Dick,Frances E. Lucy
Journal of Environmental Management. 2020; 266: 110519
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164 Clinical Competence Assessed Using Simulation: Development of a Standardized Tool to Assess Nutrition-Focused Physical Exam Skill Competence for Registered Dietitian Nutritionists
Elizabeth L. MacQuillan,Jennifer Ford,Kristin Baird
Journal of Nutrition Education and Behavior. 2020;
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165 Predicting Mid-Air Gestural Interaction with Public Displays based on Audience Behaviour
Vito Gentile,Mohamed Khamis,Fabrizio Milazzo,Salvatore Sorce,Alessio Malizia,Florian Alt
International Journal of Human-Computer Studies. 2020; : 102497
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166 Self-Determination Theory to observe healthcare professionals’ counselling in chronic care encounters: development of the COUNSEL-CCE tool
Veerle Duprez,Leen Haerens,Dorien Wuyts,Sofie Verhaeghe,Regina Van Zanten,Emma K. Massey,Ann Van Hecke
Patient Education and Counseling. 2020;
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167 Validation of sleep stage classification using non-contact radar technology and machine learning (Somnofy®)
Ståle Toften,Ståle Pallesen,Maria Hrozanova,Frode Moen,Janne Grønli
Sleep Medicine. 2020;
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168 Deep learning to find colorectal polyps in colonoscopy: A systematic literature review
Luisa F. Sánchez-Peralta,Luis Bote-Curiel,Artzai Picón,Francisco M. Sánchez-Margallo,J. Blas Pagador
Artificial Intelligence in Medicine. 2020; 108: 101923
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169 Agroview: Cloud-based application to process, analyze and visualize UAV-collected data for precision agriculture applications utilizing artificial intelligence
Yiannis Ampatzidis,Victor Partel,Lucas Costa
Computers and Electronics in Agriculture. 2020; 174: 105457
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170 Zur Reliabilität von Wearable Devices am Beispiel einer Premium Multisport-Smartwatch
Matthias Wagner,Florian Engel,Kristina Klier,Saskia Klughardt,Franziska Wallner,Alissa Wieczorek
German Journal of Exercise and Sport Research. 2020;
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171 Comparison of three equations for estimating low-density lipoprotein-cholesterol in the rural northeastern region of Thailand
Sirawich Sonsok,Pongdech Sarakarn,Pattara Sanchaisuriya
Journal of Clinical Laboratory Analysis. 2020;
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172 The power of knowledge about dementia in Latin America across health professionals working on aging
Agustin Ibanez, Daniel Flichtentrei, Eugenia Hesse, Martin Dottori, Ailin Tomio, Andrea Slachevsky, Cecilia M Serrano, Christian Gonzalez-Billaut, Nilton Custodio, Claudia Miranda, Julian Bustin, Marcelo Cetckovitch, Fernando Torrente, Loreto Olavarria, Tomas Leon, Barbara Costa Beber, Sonia Bruki, Claudia K. Suemoto, Ricardo Nitrini, Bruce L. Miller, Jennifer S. Yokoyama
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring. 2020; 12(1)
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173 Self and parent-proxy rated health-related quality of life (HRQoL) in youth with obesity: are parents good surrogates?
Delicia Shu Qin Ooi,Kah Yin Loke,Cindy Wei Li Ho,Yvonne Yijuan Lim,Veronica Tay,Vijaya Karuppiah,Andrew Anjian Sng,Lester Yousheng Lai,Yung Seng Lee,Konstadina Griva
Quality of Life Research. 2020;
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174 Standardization and reproducibility of sonographic stomach position grades in fetuses with congenital diaphragmatic hernia
Eniola R. Ibirogba,Victoria Arruga Novoa Y Novoa,Laura F. Sutton,Allan E. Neis,Amber M. Marroquin,Tracey M. Coleman,Kathleen A. Praska,Tamara A. Freimund,Krystal L. Ruka,Vicki L. Warzala,Haleh Sangi-Haghpeykar,Rodrigo Ruano
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175 Do magnetic resonance imaging abnormalities of the non-dominant wrist correlate with ulnar-sided wrist pain in elite tennis players?
Sidney M. Levy,Machar Reid,Anne-Marie Montgomery,Elissa Botterill,Stephanie A. Kovalchik,Melanie Omizzolo,Frank Malara,Timothy O. Wood,Gregory A. Hoy,Andrew H. Rotstein
Skeletal Radiology. 2019;
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176 Methodological aspects when assessing the inter-rater reliability of medication error classification – A response to a letter to editor
Anna-Riia Holmström
Research in Social and Administrative Pharmacy. 2019;
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177 Lobular neoplasia and invasive lobular breast cancer: Inter-observer agreement for histological grading and subclassification
Nora Schaumann,Mieke Raap,Laura Hinze,Luisa Rieger,Christian M. Schürch,Wiebke Antonopoulos,Stefanie Avril,Till Krech,Maximilian Dämmrich,Gian Kayser,Florian Puls,Florian Länger,Marianne Tinguely,Hans Kreipe,Matthias Christgen
Pathology - Research and Practice. 2019; : 152611
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178 Prediction of Alkanolamine pKa Values by Combined Molecular Dynamics Free Energy Simulations and ab Initio Calculations
Javad Noroozi,William R. Smith
Journal of Chemical & Engineering Data. 2019;
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179 Applicability of a field portable X-ray fluorescence for analyzing elemental concentration of waste samples
Jouni Havukainen,Jaana Hiltunen,Liisa Puro,Mika Horttanainen
Waste Management. 2019; 83: 6
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180 Classifications in Brief
Hamza Murtaza,Connor W. Sullivan
Clinical Orthopaedics and Related Research. 2019; 477(12): 2798
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181 Reply to “Diagnostic Value of CT in Detecting Peripheral Zone Prostate Cancer: Methodologic Issues to Avoid Misinterpretation”
Paraskevi A. Vlachou
American Journal of Roentgenology. 2019; 213(6): W298
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182 Validity of Wrist-Worn Activity Trackers for Estimating VO2max and Energy Expenditure
Stefanie Passler,Julian Bohrer,Lukas Blöchinger,Veit Senner
International Journal of Environmental Research and Public Health. 2019; 16(17): 3037
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183 Investigation of Cervical Tumor Biopsies for Chromosomal Loss of Heterozygosity (LOH) and Microsatellite Instability (MSI) at the HLA II Locus in HIV-1/HPV Co-infected Women
Ramadhani Chambuso,Evelyn Kaambo,Lynette Denny,Clive M. Gray,Anna-Lise Williamson,Monika Migdalska-Sek,Gloudi Agenbag,George Rebello,Raj Ramesar
Frontiers in Oncology. 2019; 9
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