Statistical analysis of a cluster-randomized clinical trial on adult general intensive care units in Brazil: TELE-critical care verSus usual Care On ICU PErformance (TELESCOPE) trial

Otavio Ranzani, Adriano José Pereira, Maura Cristina Dos Santos, Thiago Domingos Corrêa, Leonardo Jose Rolim Ferraz, Eduardo Cordioli, Renata Albaladejo Morbeck, Otávio Berwanger, Lúbia Caus de Morais, Guilherme Schettino, Alexandre Biasi Cavalcanti, Regis Goulart Rosa, Rodrigo Santos Biondi, Jorge Ibrain Figueira Salluh, Luciano César Pontes de Azevedo, Ary Serpa Neto, Danilo Teixeira Noritomi, Otavio Ranzani, Adriano José Pereira, Maura Cristina Dos Santos, Thiago Domingos Corrêa, Leonardo Jose Rolim Ferraz, Eduardo Cordioli, Renata Albaladejo Morbeck, Otávio Berwanger, Lúbia Caus de Morais, Guilherme Schettino, Alexandre Biasi Cavalcanti, Regis Goulart Rosa, Rodrigo Santos Biondi, Jorge Ibrain Figueira Salluh, Luciano César Pontes de Azevedo, Ary Serpa Neto, Danilo Teixeira Noritomi

Abstract

Objective: The TELE-critical Care verSus usual Care On ICU PErformance (TELESCOPE) trial aims to assess whether a complex telemedicine intervention in intensive care units, which focuses on daily multidisciplinary rounds performed by remote intensivists, will reduce intensive care unit length of stay compared to usual care.

Methods: The TELESCOPE trial is a national, multicenter, controlled, open label, cluster randomized trial. The study tests the effectiveness of daily multidisciplinary rounds conducted by an intensivist through telemedicine in Brazilian intensive care units. The protocol was approved by the local Research Ethics Committee of the coordinating study center and by the local Research Ethics Committee from each of the 30 intensive care units, following Brazilian legislation. The trial is registered with ClinicalTrials. gov (NCT03920501). The primary outcome is intensive care unit length of stay, which will be analyzed accounting for the baseline period and cluster structure of the data and adjusted by prespecified covariates. Secondary exploratory outcomes included intensive care unit performance classification, in-hospital mortality, incidence of nosocomial infections, ventilator-free days at 28 days, rate of patients receiving oral or enteral feeding, rate of patients under light sedation or alert and calm, and rate of patients under normoxemia.

Conclusion: According to the trial's best practice, we report our statistical analysis prior to locking the database and beginning analyses. We anticipate that this reporting practice will prevent analysis bias and improve the interpretation of the reported results.ClinicalTrials.gov registration: NCT03920501.

Conflict of interest statement

Conflicts of interest: None.

Figures

Figure 1
Figure 1
Time periods of 30 units in the TELESCOPE trial. IRB - Research Ethics Committee. * From April, the data collection will continue until hospital outcome or 90-days post-intensive care unit admission. The intervention will be maintained in the whole unit until the last included patient is discharged from the intensive care unit. The waiting period was the period when the intensive care units completed their baseline period of two months and were waiting for more blocks to complete their 2-month period to be randomized as a block.

References

    1. Adhikari NK, Fowler RA, Bhagwanjee S, Rubenfeld GD. Critical care and the global burden of critical illness in adults. Lancet. 2010;376(9749):133946.
    1. Ranzani OT, Bastos LS, Gelli JG, Marchesi JF, Baião F, Hamacher S, et al. Characterisation of the first 250,000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data. Lancet Respir Med. 2021;9(4):407–418.
    1. Veras RP, Oliveira M. Aging in Brazil: the building of a healthcare model. Cienc Saude Colet. 2018;23(6):1929–1936.
    1. GBD 2016 Brazil Collaborators Burden of disease in Brazil, 1990-2016: a systematic subnational analysis for the Global Burden of Disease Study 2016. Lancet. 2018;392(10149):760–775.
    1. Valley TS, Noritomi DT. ICU beds: less is more? Yes. Intensive Care Med. 2020;46(8):1594–1596.
    1. Lane D, Ferri M, Lemaire J, McLaughlin K, Stelfox HT. A systematic review of evidence-informed practices for patient care rounds in the ICU. Crit Care Med. 2013;41(8):2015–2029.
    1. Kim MM, Barnato AE, Angus DC, Fleisher LA, Fleisher LF, Kahn JM. The effect of multidisciplinary care teams on intensive care unit mortality. Arch Intern Med. 2010;170(4):369–376.
    1. Pronovost PJ, Angus DC, Dorman T, Robinson KA, Dremsizov TT, Young TL. Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA. 2002;288(17):2151–2162.
    1. Wilcox ME, Adhikari NK. The effect of telemedicine in critically ill patients: systematic review and meta-analysis. Crit Care. 2012;16(4):R127.
    1. Young LB, Chan PS, Lu X, Nallamothu BK, Sasson C, Cram PM. Impact of telemedicine intensive care unit coverage on patient outcomes: a systematic review and meta-analysis. Arch Intern Med. 2011;171(6):498506.
    1. Noritomi DT, Ranzani OT, Ferraz LJ, Dos Santos MC, Cordioli E, Albaladejo R, Serpa Neto A, Correa TD, Berwanger O, de Morais LC, Schettino G, Cavalcanti AB, Rosa RG, Biondi RS, Salluh JI, Azevedo LC, Pereira AJ, TELESCOPE Trial Investigators TELE-critical Care verSus usual Care On ICU PErformance (TELESCOPE): protocol for a cluster-randomised clinical trial on adult general ICUs in Brazil. BMJ Open. 2021;11(6):e042302
    1. Harhay MO, Ratcliffe SJ, Small DS, Suttner LH, Crowther MJ, Halpern SD. Measuring and analyzing length of stay in critical care trials. Med Care. 2019;57(9):e53–e59.
    1. Rapoport J, Teres D, Lemeshow S, Gehlbach S. A method for assessing the clinical performance and cost-effectiveness of intensive care units: a multicenter inception cohort study. Crit Care Med. 1994;22(9):1385–1391.
    1. Rothen HU, Stricker K, Einfalt J, Bauer P, Metnitz PG, Moreno RP, et al. Variability in outcome and resource use in intensive care units. Intensive Care Med. 2007;33(8):1329–1336.
    1. Moreno RP, Metnitz PG, Almeida E, Jordan B, Bauer P, Campos RA, Iapichino G, Edbrooke D, Capuzzo M, Le Gall JR, SAPS 3 Investigators SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med. 2005;31(10):1345–1355.
    1. Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) Bloodstream Infection Event (Central LineAssociated Bloodstream Infection and Non-central Line Associated Bloodstream Infection) 2018. Available from: .
    1. Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) Pneumonia (Ventilator-associated [VAP] and non-ventilator-associated Pneumonia [PNEU]) Event. 2018. Available from: .
    1. Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) Urinary Tract Infection (Catheter-Associated Urinary Tract Infection [CAUTI] and Non-Catheter-Associated Urinary Tract Infection [UTI]) and Other Urinary System Infection [USI]) Events. 2018. Available from: .
    1. Carter BR, Hood K. Balance algorithm for cluster randomized trials. BMC Med Res Methodol. 2008;8:65.
    1. Richards-Belle A, Mouncey PR, Wade D, Brewin CR, Emerson LM, Grieve R, Harrison DA, Harvey S, Howell D, Mythen M, Sadique Z, Smyth D, Weinman J, Welch J, Rowan KM, POPPI Trial Investigators Psychological Outcomes following a nurse-led Preventative Psychological Intervention for critically ill patients (POPPI): protocol for a cluster-randomised clinical trial of a complex intervention. BMJ Open. 2018;8(2):e020908
    1. Associação de Medicina Intensiva Brasileira (AMIB) Brazilian ICUs Project. Profile of the ICUs. 2018. [cited 2018 Sep 1]. Available from: .
    1. Soares M, Bozza FA, Angus DC, Japiassú AM, Viana WN, Costa R, et al. Organizational characteristics, outcomes, and resource use in 78 Brazilian intensive care units: the ORCHESTRA study. Intensive Care Med. 2015;41(12):2149–2160.
    1. Ranzani OT, Simpson ES, Augusto TB, Cappi SB, Noritomi DT, AMIL Critical Care Group Evaluation of a minimal sedation protocol using ICU sedative consumption as a monitoring tool: a quality improvement multicenter project. Crit Care. 2014;18(5):580.
    1. Eldridge SM, Ashby D, Kerry S. Sample size for cluster randomized trials: effect of coefficient of variation of cluster size and analysis method. Int J Epidemiol. 2006;35(5):1292–1300.
    1. Hemming K, Kasza J, Hooper R, Forbes A, Taljaard M. A tutorial on sample size calculation for multiple-period cluster randomized parallel, cross-over and stepped-wedge trials using the Shiny CRT Calculator. Int J Epidemiol. 2020;49(3):979–995.
    1. Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393.
    1. Madley-Dowd P, Hughes R, Tilling K, Heron J. The proportion of missing data should not be used to guide decisions on multiple imputation. J Clin Epidemiol. 2019;110:63–73.
    1. Hemming K, Taljaard M, Forbes A. Analysis of cluster randomised stepped wedge trials with repeated cross-sectional samples. Trials. 2017;18(1):101.
    1. Copas AJ, Hooper R. Cluster randomised trials with different numbers of measurements at baseline and endline: sample size and optimal allocation. Clin Trials. 2020;17(1):69–76.
    1. Hussey MA, Hughes JP. Design and analysis of stepped wedge cluster randomized trials. Contemp Clin Trials. 2007;28(2):182–191.
    1. Leyrat C, Morgan KE, Leurent B, Kahan BC. Cluster randomized trials with a small number of clusters: which analyses should be used? Int J Epidemiol. 2018;47(1):321–331.
    1. Hernán MA, Robins JM. Per-protocol analyses of pragmatic trials. N Engl J Med. 2017;377(14):1391–1398.
    1. Agbla SC, De Stavola B, DiazOrdaz K. Estimating cluster-level local average treatment effects in cluster randomised trials with non-adherence. Stat Methods Med Res. 2020;29(3):911–933.
    1. Harhay MO, Ratcliffe SJ, Halpern SD. Measurement error due to patient flow in estimates of intensive care unit length of stay. Am J Epidemiol. 2017;186(12):1389–1395.
    1. Wolkewitz M, Cooper BS, Bonten MJ, Barnett AG, Schumacher M. Interpreting and comparing risks in the presence of competing events. BMJ. 2014;349:g5060.
    1. Campbell MK, Piaggio G, Elbourne DR, Altman DG, CONSORT Group Consort 2010 statement: extension to cluster randomised trials. BMJ. 2012;345:e5661.

Source: PubMed

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