The following information is available to be viewed/ printed in Adobe Acrobat pdf format. I. Statement of Purpose A. About the Uniform Requirements B. Potential Users of the Uniform Requirements C. How to Use the Uniform Requirements II. Ethical Considerations in the Conduct and Reporting of Research A. Authorship and Contributorship 1. Byline Authors 2. Contributors Listed in Acknowledgments B. Editorship 1. The Role of the Editor 2. Editorial Freedom C. Peer Review D. Conflicts of Interest 1. Potential Conflicts of Interest Related to Individual Authors’ Commitments 2. Potential Conflicts of Interest Related to Project Support 3. Potential Conflicts of Interest Related to Commitments of Editors, Journal Staff, or Reviewers E. Privacy and Confidentiality 1. Patients and Study Participants 2. Authors and Reviewers F. Protection of Human Subjects and Animals in Research III. Publishing and Editorial Issues Related to Publication in Biomedical Journals A. Obligation to Publish Negative Studies B. Corrections, Retractions, and “Expressions of Concern” C. Copyright D. Overlapping Publications 1. Duplicate Submission 2. Redundant Publication 3. Acceptable Secondary Publication 4. Competing Manuscripts based on the Same Study a. Differences in Analysis or Interpretation b. Differences in Reported Methods or Results 5. Competing Manuscripts Based on the Same Database E. Correspondence F. Supplements, Theme Issues, and Special Series G. Electronic Publishing H. Advertising I. Medical Journals and the General Media J. Obligation to Register Clinical Trials IV. Manuscript Preparation and Submission A. Preparing a Manuscript for Submission to Biomedical Journals 1. a. General Principles b. Reporting Guidelines for Specific Study Designs 2. Title page 3. Conflict-of-interest Notification Page 4. Abstract and

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Successful Scientific Writing: Excerpts from “Uniform requirements for manuscripts submitted to biomedical journals: Writing and editing for biomedical publication”

Breast is best

The Bland-Altman method has been widely used for assessing agreement between two methods of measurement. However, it remains unsolved about sample size estimation. We propose a new method of sample size estimation for Bland-Altman agreement assessment. According to the Bland-Altman method, the conclusion on agreement is made based on the width of the confidence interval for LOAs (limits of agreement) in comparison to predefined clinical agreement limit. Under the theory of statistical inference, the formulae of sample size estimation are derived, which depended on the pre-determined level of α, β, the mean and the standard deviation of differences between two measurements, and the predefined limits. With this new method, the sample sizes are calculated under different parameter settings which occur frequently in method comparison studies, and Monte-Carlo simulation is used to obtain the corresponding powers. The results of Monte-Carlo simulation showed that the achieved powers could coincide with the pre-determined level of powers, thus validating the correctness of the method. The method of sample size estimation can be applied in the Bland-Altman method to assess agreement between two methods of measurement.

https://www.degruyter.com/downloadpdf/j/ijb.2016.12.issue-2/ijb-2015-0039/ijb-2015-0039.xml

Sample Size for Assessing Agreement between Two Methods of Measurement by Bland-Altman Method.

Wearable sensors are promising instruments for conducting both laboratory and ambulatory research in psychophysiology. However, scholars should be aware of their measurement error and the conditions in which accuracy is achieved. This study aimed to assess the accuracy of a wearable sensor designed for research purposes, the E4 wristband (Empatica, Milan, Italy), in measuring heart rate (HR), heart rate variability (HRV), and skin conductance (SC) over five laboratory conditions widely used in stress reactivity research (seated rest, paced breathing, orthostatic, Stroop, speech task) and two ecological conditions (slow walking, keyboard typing). Forty healthy participants concurrently wore the wristband and two gold standard measurement systems (i.e., electrocardiography and finger SC sensor). The wristband accuracy was determined by evaluating the signal quality and the correlations with and the Bland-Altman plots against gold standard-derived measurements. Moreover, exploratory analyses were performed to assess predictors of measurement error. Mean HR measures showed the best accuracy over all conditions. HRV measures showed satisfactory accuracy in seated rest, paced breathing, and recovery conditions but not in dynamic conditions, including speaking. Accuracy was diminished by wrist movements, cognitive and emotional stress, nonstationarity, and larger wrist circumferences. Wrist SC measures showed neither correlation nor visual resemblance with finger SC signal, suggesting that the two sites may reflect different phenomena. Future studies are needed to assess the responsivity of wrist SC to emotional and cognitive stress. Limitations and implications for laboratory and ambulatory research are discussed.

Stressing the accuracy: Wrist‐worn wearable sensor validation over different conditions

The Bland–Altman Limits of Agreement is a popular and widespread means of analyzing the agreement of two methods, instruments, or raters in quantitative outcomes. An agreement analysis could be reported as a stand-alone research article but it is more often conducted as a minor quality assurance project in a subgroup of patients, as a part of a larger diagnostic accuracy study, clinical trial, or epidemiological survey. Consequently, such an analysis is often limited to brief descriptions in the main report. Therefore, in several medical fields, it has been recommended to report specific items related to the Bland–Altman analysis. The present study aimed to identify the most comprehensive and appropriate list of items for such an analysis. Seven proposals were identified from a MEDLINE/PubMed search, three of which were derived by reviewing anesthesia journals. Broad consensus was seen for the a priori establishment of acceptability benchmarks, estimation of repeatability of measurements, description of the data structure, visual assessment of the normality and homogeneity assumption, and plotting and numerically reporting both bias and the Bland–Altman Limits of Agreement, including respective 95% confidence intervals. Abu-Arafeh et al. provided the most comprehensive and prudent list, identifying 13 key items for reporting (Br. J. Anaesth. 2016, 117, 569–575). An exemplification with interrater data from a local study accentuated the straightforwardness of transparent reporting of the Bland–Altman analysis. The 13 key items should be applied by researchers, journal editors, and reviewers in the future, to increase the quality of reporting Bland–Altman agreement analyses.

Reporting Standards for a Bland-Altman Agreement Analysis: A Review of Methodological Reviews.

Background and objectivesTo carry out a cross-sectional survey of the medical literature on laboratory research papers published later than 2012 and available in the common search engines (PubMed, ...

https://journals.sagepub.com/doi/pdf/10.1177/0004563214553438

Reporting standards for Bland–Altman agreement analysis in laboratory research: a cross-sectional survey of current practice

To compare sodium and potassium levels in children as done with Blood Gas Analyzer (BGA) at point of care testing in pediatric ICU vs. that done in laboratory electrolyte analyzer. This prospective method comparison study was done from February to April 2012 in Pediatric ICU of tertiary care hospital at Delhi. Sixty consecutive patients were tested during the period. Paired blood samples for venous blood gas to be tested on BGA and serum electrolytes to be tested on auto-analyzers (AA) were taken as per standard technique. Data was collected and 59 paired samples were analyzed for sodium and potassium levels. They were analyzed according to CLSI document EP15-A2 using ACB method comparison software. Mean sodium measured on the BGA was 132.8 ± 12.2 mmol/L where as measured by AA was 141.5 ± 11.1 mmol/L. The mean difference between the two was −8.76 mmol/L (p < 0.001). The difference was statistically significant in all three subgroups of hypernatremia, isonatremia and hyponatremia (p < 0.001). Potassium level in BGA was 3.53 ± 0.81 mmol/L and AA was 4.28 ± 1.05 mmol/L. The mean difference between the BGA and AA was −0.75 mmol/L (p < 0.0001). The difference was statistically significant in patients with normokalemia and hyperkalemia (p < 0.0001). The difference was non significant in patients with hypokalemia (p = 0.051). Blood gas analyzers underestimates Na + and K + values if sampling is done using liquid sodium heparin and if all other potential pre-analytical errors of testing are taken care of. The Bland Altman’s analysis in the present study showed a significant systematic bias and very wide limits of agreement for both sodium and potassium, which is not clinically acceptable.

A comparative study on reliability of point of care sodium and potassium estimation in a pediatric intensive care unit.

Objectives We conducted a systematic review and meta-analysis of literature to determine if the publication of the Consolidated Standards of Reporting Trials (CONSORT) abstract guideline in 2008 was followed by change in reporting quality of randomized controlled trial (RCT) abstracts. Study design and settings Evaluations were included if they compared reporting quality of RCT abstracts before and after the publication of CONSORT-abstract guideline. The literature search was performed (January 2008 to April 2017) in Medline (Ovid), EMbase, CINAHL plus and Cochrane methodologies register. We assessed study validity with a special validity tool, adapted from a previous Cochrane review. Results Initial search identified 4142 articles, of which total 10 evaluations including 5184 abstracts were included. Total 22 outcomes related to individual items of CONSORT-abstract guideline were assessed, and 14 showed significant effect sizes favoring CONSORT-abstract guideline. Despite significant effect size, the overall post-CONSORT reporting (PCR) was suboptimal for ten items: title (RR = 1.40, 95% CI 1.23 to 1.59, PCR = 53.4%), participants (RR = 1.58, 95% CI 1.11 to 2.26, PCR = 24.5%), primary outcome (RR = 1.12, 95% CI 1.02 to 1.23, PCR = 65%), blinding (RR = 2.13, 95% CI 1.20 to 3.76, PCR = 13.9%), trial status (RR = 1.81, 95% 1.39 to 2.35, PCR = 10.6%), numbers analyzed (RR = 1.51, 95% CI 1.15 to 1.98, PCR = 26.5%), outcome (RR = 1.40, 95% 1.05 to 1.86, PCR = 21.9%), effect size and precision (RR = 1.59, 95% CI 1.15 to 2.19, PCR = 58.9%), harms (RR = 1.24, 95% CI 1.04 to 1.48, PCR = 41.8%), trial registration (RR = 2.02, 95% CI 1.63 to 2.50, PCR = 33.8%). Three items with favorable effect size in addition had wide CIs: randomization (RR = -4.28, 95% CI 1.56 to 11.75, PCR = -3.3%), allocation concealment (RR = -19.89, 95% CI 1.54 to 256.69, PCR = -5.7%), and funding (RR = -22.61, 95% CI 8.13 to 62.67, PCR = -11.32%). Conclusion The change in reporting quality of RCT abstracts is far from satisfactory, as evidenced by suboptimal post-CONSORT rates and wide CIs of effect sizes for majority of improved items. Mere publication of CONSORT-abstract guideline, without strict endorsement has failed to translate into good quality abstracts.

Reporting quality of trial abstracts-improved yet suboptimal: A systematic review and meta-analysis

An interrupted time series analysis showed suboptimal improvement in reporting quality of trial abstract

To find a correlation between inferior vena cava (IVC) diameters, IVC compressibility index (CI) and central venous pressure (CVP). Prospective observational study was done at pediatric intensive care unit (PICU) of Kalawati Saran Children’s Hospital (KSCH). Fifty children aged 5-18 y, presenting with shock were enrolled for the study. IVC diameters, CI and relevant clinical data were noted at enrollment, 30 min, 1 h, 6 h, and 12 h. Central line was placed at the time of admission. Of 50 children enrolled, 28 were boys, with a mean age of 11 y. More than 80% of cases were diagnosed as septic shock. Mean maximum and minimum IVC diameter of 8.3 ± 2 mm and 3.7 ± 1.7 mm, respectively CI 58.2 ± 7% and CVP of 5.4 ± 1.5 cm of H2O was observed at admission. CVP and IVC diameters showed a serial improvement with treatment; CI showed a serial decrease with treatment. Heart rate (HR) and systolic blood pressure (SBP) also showed a serial improvement at 12 h (p < 0.05). CVP showed a positive correlation with IVC diameter (r +0.312; p < 0.05), and a negative correlation with CI (r −0.343; p < 0.05). Effective fluid resuscitation improves IVC diameters with a decrease in CI. IVC diameter has a positive correlation to CVP and CI has a negative correlation to CVP.

Sandeep Kumar Kanwal

Papers

Reporting standards for Bland–Altman agreement analysis in laboratory research: a cross-sectional survey of current practice

A comparative study on reliability of point of care sodium and potassium estimation in a pediatric intensive care unit.

Reporting quality of trial abstracts-improved yet suboptimal: A systematic review and meta-analysis

An interrupted time series analysis showed suboptimal improvement in reporting quality of trial abstract

The Correlation Between Inferior Vena Cava Diameter Measured by Ultrasonography and Central Venous Pressure.