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1. World Association of Sleep Medicine (WASM) 2016 standards for recording and scoring leg movements in polysomnograms developed by a joint task force from the International and the European Restless Legs Syndrome Study Groups (IRLSSG and EURLSSG)

Author

Ferri, R., Fulda, S., Allen, R.P., Zucconi, M., Bruni, O., Chokroverty, S., Ferini-Strambi, L., Frauscher, B., Garcia-Borreguero, D., Hirshkowitz, M., Högl, B., Inoue, Y., Jahangir, A., Manconi, M., Marcus, C.L., Picchietti, D.L., Plazzi, G., Winkelman, J.W., and Zak, R.S.

Published
2016
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4. Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals

Author

Leisman, DE, Harhay, MO, Lederer, DJ, Abramson, M, Adjei, AA, Bakker, J, Ballas, ZK, Barreiro, E, Bell, SC, Bellomo, R, Bernstein, JA, Branson, RD, Brusasco, V, Chalmers, JD, Chokroverty, S, Citerio, G, Collop, NA, Cooke, CR, Crapo, JD, Donaldson, G, Fitzgerald, DA, Grainger, E, Hale, L, Herth, FJ, Kochanek, PM, Marks, G, Moorman, JR, Ost, DE, Schatz, M, Sheikh, A, Smyth, AR, Stewart, I, Stewart, PW, Swenson, ER, Szymusiak, R, Teboul, J-L, Vincent, J-L, Wedzicha, JA, Maslove, DM, Leisman, DE, Harhay, MO, Lederer, DJ, Abramson, M, Adjei, AA, Bakker, J, Ballas, ZK, Barreiro, E, Bell, SC, Bellomo, R, Bernstein, JA, Branson, RD, Brusasco, V, Chalmers, JD, Chokroverty, S, Citerio, G, Collop, NA, Cooke, CR, Crapo, JD, Donaldson, G, Fitzgerald, DA, Grainger, E, Hale, L, Herth, FJ, Kochanek, PM, Marks, G, Moorman, JR, Ost, DE, Schatz, M, Sheikh, A, Smyth, AR, Stewart, I, Stewart, PW, Swenson, ER, Szymusiak, R, Teboul, J-L, Vincent, J-L, Wedzicha, JA, and Maslove, DM

Abstract

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of "modifiable risk factors", measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.

Published
2020

5. Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals

Author

Leisman, D, Harhay, M, Lederer, D, Abramson, M, Adjei, A, Bakker, J, Ballas, Z, Barreiro, E, Bell, S, Bellomo, R, Bernstein, J, Branson, R, Brusasco, V, Chalmers, J, Chokroverty, S, Citerio, G, Collop, N, Cooke, C, Crapo, J, Donaldson, G, Fitzgerald, D, Grainger, E, Hale, L, Herth, F, Kochanek, P, Marks, G, Moorman, J, Ost, D, Schatz, M, Sheikh, A, Smyth, A, Stewart, I, Stewart, P, Swenson, E, Szymusiak, R, Teboul, J, Vincent, J, Wedzicha, J, Maslove, D, Leisman, Daniel E, Harhay, Michael O, Lederer, David J, Abramson, Michael, Adjei, Alex A, Bakker, Jan, Ballas, Zuhair K, Barreiro, Esther, Bell, Scott C, Bellomo, Rinaldo, Bernstein, Jonathan A, Branson, Richard D, Brusasco, Vito, Chalmers, James D, Chokroverty, Sudhansu, Citerio, Giuseppe, Collop, Nancy A, Cooke, Colin R, Crapo, James D, Donaldson, Gavin, Fitzgerald, Dominic A, Grainger, Emma, Hale, Lauren, Herth, Felix J, Kochanek, Patrick M, Marks, Guy, Moorman, J Randall, Ost, David E, Schatz, Michael, Sheikh, Aziz, Smyth, Alan R, Stewart, Iain, Stewart, Paul W, Swenson, Erik R, Szymusiak, Ronald, Teboul, Jean-Louis, Vincent, Jean-Louis, Wedzicha, Jadwiga A, Maslove, David M, Leisman, D, Harhay, M, Lederer, D, Abramson, M, Adjei, A, Bakker, J, Ballas, Z, Barreiro, E, Bell, S, Bellomo, R, Bernstein, J, Branson, R, Brusasco, V, Chalmers, J, Chokroverty, S, Citerio, G, Collop, N, Cooke, C, Crapo, J, Donaldson, G, Fitzgerald, D, Grainger, E, Hale, L, Herth, F, Kochanek, P, Marks, G, Moorman, J, Ost, D, Schatz, M, Sheikh, A, Smyth, A, Stewart, I, Stewart, P, Swenson, E, Szymusiak, R, Teboul, J, Vincent, J, Wedzicha, J, Maslove, D, Leisman, Daniel E, Harhay, Michael O, Lederer, David J, Abramson, Michael, Adjei, Alex A, Bakker, Jan, Ballas, Zuhair K, Barreiro, Esther, Bell, Scott C, Bellomo, Rinaldo, Bernstein, Jonathan A, Branson, Richard D, Brusasco, Vito, Chalmers, James D, Chokroverty, Sudhansu, Citerio, Giuseppe, Collop, Nancy A, Cooke, Colin R, Crapo, James D, Donaldson, Gavin, Fitzgerald, Dominic A, Grainger, Emma, Hale, Lauren, Herth, Felix J, Kochanek, Patrick M, Marks, Guy, Moorman, J Randall, Ost, David E, Schatz, Michael, Sheikh, Aziz, Smyth, Alan R, Stewart, Iain, Stewart, Paul W, Swenson, Erik R, Szymusiak, Ronald, Teboul, Jean-Louis, Vincent, Jean-Louis, Wedzicha, Jadwiga A, and Maslove, David M

Abstract

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of "modifiable risk factors", measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.

Published
2020

12. Control of confounding and reporting of results in causal inference studies.

Author

Adjei A.A., Branson R.D., Chalmers J.D., Marshall R., Maslove D.M., Ost D.E., Punjabi N.M., Schatz M., Smyth A.R., Stewart P.W., Suissa S., Akdis C.A., Azoulay E., Bakker J., Ballas Z.K., Bardin P.G., Barreiro E., Bellomo R., Bernstein J.A., Brusasco V., Buchman T.G., Chokroverty S., Collop N.A., Crapo J.D., Fitzgerald D.A., Hale L., Hart N., Herth F.J., Iwashyna T.J., Jenkins G., Kolb M., Marks G.B., Mazzone P., Moorman J.R., Murphy T.M., Noah T.L., Reynolds P., Riemann D., Russell R.E., Sheikh A., Sotgiu G., Swenson E.R., Szczesniak R., Szymusiak R., Teboul J.-L., Vincent J.-L., Lederer D.J., Bell S.C., Adjei A.A., Branson R.D., Chalmers J.D., Marshall R., Maslove D.M., Ost D.E., Punjabi N.M., Schatz M., Smyth A.R., Stewart P.W., Suissa S., Akdis C.A., Azoulay E., Bakker J., Ballas Z.K., Bardin P.G., Barreiro E., Bellomo R., Bernstein J.A., Brusasco V., Buchman T.G., Chokroverty S., Collop N.A., Crapo J.D., Fitzgerald D.A., Hale L., Hart N., Herth F.J., Iwashyna T.J., Jenkins G., Kolb M., Marks G.B., Mazzone P., Moorman J.R., Murphy T.M., Noah T.L., Reynolds P., Riemann D., Russell R.E., Sheikh A., Sotgiu G., Swenson E.R., Szczesniak R., Szymusiak R., Teboul J.-L., Vincent J.-L., Lederer D.J., and Bell S.C.

Published
2019

14. 0771 THE NATIONAL SLEEP FOUNDATION’S SLEEP HEALTH INDEX

Author

Knutson, KL, primary, Phelan, J, additional, Paskow, M, additional, Roach, A, additional, Whiton, K, additional, Langer, G, additional, Hillygus, D, additional, Broughton, WA, additional, Chokroverty, S, additional, Lichstein, K, additional, Weaver, T, additional, and Hirshkowitz, M, additional

Published
2017
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15. Sleep and stroke

Author

Montagna, P, Chokroverty, S, Montagna, P ( P ), Chokroverty, S ( S ), Bassetti, C L, Hermann, D M, Montagna, P, Chokroverty, S, Montagna, P ( P ), Chokroverty, S ( S ), Bassetti, C L, and Hermann, D M

Abstract

Sleep–wake functions and respiration depend upon the integrity of neuronal networks in the brainstem and cerebral hemispheres. Following stroke, sleep–wake disorders (SWDs) and sleep-disordered breathing (SDB) are frequently observed as a direct or indirect (e.g., pain, depression, medications) consequence of acute focal brain damage. About one-third of stroke patients present with SWD – mostly as insomnia or hypersomnia (excessive daytime sleepiness, fatigue, increased sleep needs). Severe SWDs are often seen after thalamic or brainstem stroke, are linked with neuropsychiatric and psychological deficits, and have a less favorable functional outcome. The relationship between stroke characteristics (topography, severity, outcome), sleep electroencephalographic changes and SWD is complex. In severe/persisting SWD, hypnotics, dopaminergic drugs, and stimulants can be used. About half of patients have SDB, mostly in the form of obstructive sleep apnea (OSA). OSA represents both a risk factor and a consequence of stroke. The presence of OSA has been linked with poorer outcome. Continuous positive airway pressure is the treatment of choice for OSA. Oxygen and other forms of ventilation may be helpful in central forms of SDB.

Published
2011

16. Editor’s corner

Author

Chokroverty S

Subjects
medicine.medical_specialty, Pediatrics, business.industry, Family medicine, Milestone (project management), medicine, Alternative medicine, General Medicine, business, Sleep medicine
Published
2009

22. Validation of the International Restless Legs Syndrome Study Group rating scale for restless legs syndrome

Author

Walters, As, Lebrocq, C, Dhar, A, Hening, W, Rosen, R, Allen, Rp, Trenkwalder, C, Adler, C, Newman, S, Reiners, C, Aksu, M, Buchholz, D, Hening, Wa, Anderson, M, Mosko, S, Ancoli-Israel, S, Jimenez, Wb, Hallett, M, Bassetti, C, Clavadetscher, S, Bliwise, Dl, Gurecki, P, Rye, Db, Broch, Ll, Zak, R, Chokroverty, S, Coccagna, G, Lugaresi, E, Miele, F, Montagna, P, Plazzi, G, Provini, F, de Mello MT, Tufik, S, de Weerd AW, Rijsman, Rm, Ehrenberg, B, Eisensehr, I, Ekbom, K, Ljungdahl, A, Garcia-Borreguero, D, Larrosa, O, Hirsch, L, Hogl, B, Horiguchi, J, Hornyak, M, Voderholzer, U, Kryger, M, Skomrow, R, Lipinski, Jf, Masood, A, Phillips, B, Oertel, Wh, Stiasny, K, O'Keeffe, S, Oldani, A, Zucconi, M, Ondo, Wg, Picchietti, D, Poceta, Js, Rich, Gb, Scrima, L, Shafor, R, Sharon, D, Silber, M, Smith, R, Wetter, Tc, Winkelmann, J, Vanek, Z, and Wagner, M

Subjects
Adult, medicine.medical_specialty, Psychometrics, International Cooperation, Severity of Illness Index, 03 medical and health sciences, 0302 clinical medicine, Rating scale, Restless Legs Syndrome, mental disorders, Criterion validity, Medicine, Humans, 030212 general & internal medicine, Restless legs syndrome, Reliability (statistics), Aged, Aged, 80 and over, business.industry, Reproducibility of Results, General Medicine, Middle Aged, medicine.disease, 3. Good health, Assessment, Factor analysis, Psycchometrics, Reliability, Validity, BTBD9, Convergent validity, Case-Control Studies, Physical therapy, Clinical Global Impression, business, Gabapentin enacarbil, 030217 neurology & neurosurgery, medicine.drug
Abstract

BACKGROUND There is a need for an easily administered instrument which can be applied to all patients with restless legs syndrome (RLS) to measure disease severity for clinical assessment, research, or therapeutic trials. The pathophysiology of RLS is not clear and no objective measure so far devised can apply to all patients or accurately reflect severity. Moreover, RLS is primarily a subjective disorder. Therefore, a subjective scale is at present the optimal instrument to meet this need. METHODS Twenty centers from six countries participated in an initial reliability and validation study of a rating scale for the severity of RLS designed by the International RLS study group (IRLSSG). A ten-question scale was developed on the basis of repeated expert evaluation of potential items. This scale, the IRLSSG rating scale (IRLS), was administered to 196 RLS patients, most on some medication, and 209 control subjects. RESULTS The IRLS was found to have high levels of internal consistency, inter-examiner reliability, test-retest reliability over a 2-4 week period, and convergent validity. It also demonstrated criterion validity when tested against the current criterion of a clinical global impression and readily discriminated patient from control groups. The scale was dominated by a single severity factor that explained at least 59% of the pooled item variance. CONCLUSIONS This scale meets performance criteria for a brief, patient completed instrument that can be used to assess RLS severity for purposes of clinical assessment, research, or therapeutic trials. It supports a finding that RLS is a relatively uniform disorder in which the severity of the basic symptoms is strongly related to their impact on the patient's life. In future studies, the IRLS should be tested against objective measures of RLS severity and its sensitivity should be studied as RLS severity is systematically manipulated by therapeutic interventions.

Published
2003

23. Restless legs syndrome: Diagnostic criteria, special considerations, and epidemiology. A report from the restless legs syndrome diagnosis and epidemiology workshop at the National Institutes of Health

Author

Allen, R. P., Picchietti, D., Hening, W. A., Trenkwalder, C., Walters, A. S., Montplaisi, J., Bara-Jimenez, W., Becker, P., Bell, G., Berger, K., Bliwise, D. L., Brooks, D., Consens, F., Earley, C. J., Ehrenberg, B. L., Foley, D., Murray, C. F., Garcia-Borreguero, D., Hallett, M., Hornyak, M., Hunt, C. E., Kushida, C., Kurth, T., Launer, L., Monjan, A., Nichols, P., Rye, D. B., Sharon, D., Streiner, D. L., Winkelman, J. W., Winkelmann, J., Zak, R., Adler, C., Benes, H., Chokroverty, S., Ekbom, K., Frauscher, B., Hogl, B., Kryger, M., Montagna, P., Oertel, W., Plazzi, G., Poceta, J. S., Silber, M., Stiasny, K., Tolosa, E., Tufik, S., de Mello, M. T., and Zucconi, M.

Subjects
Consensus, Movement disorder, Neurologic disorder, Periodic limb movement disorder, Periodic limb movements of sleep, Sleep, Sleep disorder
Published
2003

39. The official World Association of Sleep Medicine (WASM) standards for recording and scoring periodic leg movements in sleep (PLMS) and wakefulness (PLMW) developed in collaboration with a task force from the International Restless Legs Syndrome Study Group (IRLSSG)

Author

ZUCCONI, M, primary, FERRI, R, additional, ALLEN, R, additional, BAIER, P, additional, BRUNI, O, additional, CHOKROVERTY, S, additional, FERINISTRAMBI, L, additional, FULDA, S, additional, GARCIABORREGUERO, D, additional, and HENING, W, additional

Published
2006
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