Component network meta-analysis identifies the most effective components of psychological preparation for adults undergoing surgery under general anesthesia

Journal of Clinical Epidemiology

Volumn 98, Issue , 2018, Pages 105-116

  Freeman, Suzanne C ^a,b   Scott, Neil W ^b   Powell, Rachael ^c   Johnston, Marie ^b   Sutton, Alex J ^a   Cooper, Nicola J ^a  

^a UNIVERSITY OF LEICESTER   (United Kingdom)

^b UNIVERSITY OF ABERDEEN   (United Kingdom)

^c UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Bayesian; Complex interventions; Component; Network meta analysis; Psychological preparation; Surgery

Indexed keywords

ADULT; AFFECT; ANXIETY; COCHRANE LIBRARY; DEPRESSION; EMOTION; GENERAL ANESTHESIA; HUMAN; LENGTH OF STAY; META ANALYSIS; NETWORK META-ANALYSIS; OUTCOME ASSESSMENT; PAIN; PRIORITY JOURNAL; PSYCHOLOGICAL ASPECT; REVIEW; SURGERY; PATIENT EDUCATION; POSTOPERATIVE PAIN; PREOPERATIVE CARE; PROBABILITY; PROCEDURES; PSYCHOLOGY; STATISTICAL MODEL; TREATMENT OUTCOME;

ADULT; AFFECT; ANESTHESIA, GENERAL; HUMANS; LENGTH OF STAY; MODELS, STATISTICAL; NETWORK META-ANALYSIS; PAIN, POSTOPERATIVE; PATIENT EDUCATION AS TOPIC; PREOPERATIVE CARE; PROBABILITY; SURGICAL PROCEDURES, OPERATIVE; SYSTEMATIC REVIEWS AS TOPIC; TREATMENT OUTCOME;

EID: 85044153371     PISSN: 08954356     EISSN: 18785921     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2018.02.012     Document Type: Review

References (40)

1. Craig, P., Dieppe, P., Macintyre, S., Michie, S., Nazareth, I., Petticrew, M., et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ, 337, 2008, a1655.
2. Lewin, S., Hendry, M., Chandler, J., Oxman, A.D., Michie, S., Shepperd, S., et al. Assessing the complexity of interventions within systematic reviews: development, content and use of a new tool (iCAT_SR). BMC Med Res Methodol, 17, 2017, 76.
3. Lu, G., Ades, A.E., Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med 23 (2004), 3105–3124.
4. Caldwell, D.M., Ades, A.E., Higgins, J.P.T., Simultaneous comparison of multiple treatments: combining direct and indirect evidence. BMJ 331 (2005), 1897–1900.
5. Welton, N.J., Caldwell, D.M., Adamopoulos, E., Vedhara, K., Mixed treatment comparison meta-analysis of complex interventions: psychological interventions in coronary heart disease. Am J Epidemiol 169 (2009), 1158–1165.
6. Mills, E.J., Druyts, E., Ghement, I., Puhan, M.A., Pharmacotherapies for chronic obstructive pulmonary disease: a multiple treatment comparison meta-analysis. Clin Epidemiol 3 (2011), 107–129.
7. Mills, E.J., Thorlund, K., Ioannidis, J.P., Calculating additive treatment effects from multiple randomized trials provides useful estimates of combination therapies. J Clin Epidemiol 65 (2012), 1282–1288.
8. Thorlund, K., Mills, E., Stability of additive treatment effects in multiple treatment comparison meta-analysis: a simulation study. Clin Epidemiol 4 (2012), 75–85.
9. Powell, R., Scott, N.W., Manyande, A., Bruce, J., Vogele, C., Byrne-Davis, L.M., et al. Psychological preparation and postoperative outcomes for adults undergoing surgery under general anaesthesia. Cochrane Database Syst Rev, 2016, CD008646.
10. Johnston, M., Vögele, C., Benefits of psychological preparation for surgery: a meta-analysis. Ann Behav Med 15:4 (1993), 245–256.
11. Arpino, L., Iavarone, A., Parlato, C., Moraci, A., Prognostic role of depression after lumbar disc surgery. Neurol Sci 25:3 (2004), 145–147.
12. Bruce, J., Thornton, A.J., Scott, N.W., Marfizo, S., powell, R., Johnston, M., et al. Chronic preopoerative pain and psychological robustness predict acute postoperative pain outcomes after surgery for breast cancer. Br J Cancer 107 (2012), 937–946.
13. Granot, M., Ferber, S.G., The roles of pain catastrophizing and anxiety in the prediction of postoperative pain intensity - a prospective study. Clin J Pain 21:5 (2005), 429–445.
14. Munafò, M.R., Stevenson, J., Anxiety and surgical recovery - Reinterpreting the literature. J Psychosomatic Res 51:4 (2001), 589–596.
15. Rainville, P., Bao, Q.V.H., Chrétien, P., Pain-related emotions modulate experimental pain perception and autonomic responses. Pain 118 (2005), 306–318.
16. van Middendorp, H., Lumley, M., Jacobs, J.W.G., Bijilsma, J.W.J., Geenen, R., The effects of anger and sadness on clinical pain reports and experimentally-induced pain thresholds in women with and without fibromyalgia. Arthritis Care Res (Hoboken) 62:10 (2010), 1370–1376.
17. Maple, H., Joseph, C., Lee, V., Simmonds, S., Weinman, J., Mamode, N., Stress predicts the trajectory of wound healing in living kidney donors as measured by high-resolution ultrasound. Brain Behav Immun 43 (2015), 19–26.
18. Walburn, J., Vedhara, K., Hankins, M., Rixon, L., Weinman, J., Psychological stress and wound healing in humans: a systematic review and meta-analysis. J Psychosomatic Res 67:3 (2009), 253–271.
19. Achana, F.A., Cooper, N.J., Dias, S., Lu, G., Rice, S.J.C., Kendrick, D., et al. Extending methods for investigating the relationship between treatment effect and baseline risk from pairwise meta-analysis to network meta-analysis. Stat Med 32 (2013), 752–771.
20. de Bruin, M., Viechtbauer, W., Hospers, H.J., Schaalma, H.P., Kok, G., Standard care quality determines treatment outcomes in control groups of HAART-adherence intervention studies: implications for the interpretation and comparison of intervention effects. Health Psychol 28:6 (2009), 668–674.
21. Ma, Y.I., Qin, L.J., Han, Z.F., Relaxation training on stress response to abdominal surgery [[original title in Chinese script]]. Chin J Nurs (Zhonghua Hu Li Za Zhi) 31:7 (1996), 377–380.
22. Guo, P., East, L., Arthur, A., A preoperative education intervention to reduce anxiety and improve recovery among Chinese cardiac patients: a randomized controlled trial. Int J Nurs Stud 49:2 (2012), 129–137.
23. Ashton, C. Jr., Whitworth, G.C., Seldomridge, J.A., Shapiro, P.A., Weinberg, A.D., Michler, R.E., et al. Self-hypnosis reduces anxiety following coronary artery bypass surgery. A prospective, randomized trial. J Cardiovasc Surg 38:1 (1997), 69–75.
24. Felton, G., Huss, K., Payne, E.A., Srsic, K., Preoperative nursing intervention with the patient for surgery: outcomes of three alternative approaches. Int J Nurs Stud 13:2 (1976), 83–96.
25. Giraudet-Le Quintrec, J., Coste, J., Vastel, L., Pacault, V., Jeanne, L., Lamas, J., et al. Positive effect of patient education for hip surgery: a randomized trial. Clin Orthop Relat Res(414), 2003, 112–120.
26. Lim, L., Chow, P., Wong, C.Y., Chung, A., Chan, Y.H., Wong, W.K., et al. Doctor-patient communication, knowledge, and question prompt lists in reducing preoperative anxiety - a randomized control study. Asian J Surg 34:4 (2011), 175–180.
27. Bitterli, R., Sieben, J.M., Hartmann, M., De Bruin, E.D., Pre-surgical sensorimotor training for patients undergoing total hip Replacement: a randomised controlled trial. Int J Sports Med 32:9 (2011), 725–732.
28. Coslow, B.I.F., Eddy, M.E., Effects of preoperative ambulatory gynecological education: clinical outcomes and patient satisfaction. J PeriAnesthesia Nurs 13:1 (1998), 4–10.
29. Wells, N., The effect of relaxation on postoperative muscle tension and pain. Nurs Res 31:4 (1982), 236–238.
30. Deeks, J.J., Higgins, J.P.T., Altman, D.G., Chapter 9: Analysing data and undertaking meta-analyses. Higgins, J.P.T., Green, S., (eds.) Cochrane Handbook for Systematic Reviews of Interventions, 2008, John Wiley & Sons, Chichester (UK).
31. Dias, S., Welton, N.J., Sutton, A.J., Ades, A.E., NICE DSU Technical Support Document 2: a generalised linear modelling framework for pairwise and network meta-analysis of randomised controled trials. 2011, NICE Decision Support Unit, University of Sheffield, Sheffield, UK last updated September 2016.
32. Salanti, G., Ades, A.E., Ioannidis, J.P., Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol 64 (2011), 163–171.
33. Mills, E.J., Thorlund, K., Ioannidis, J.P., Demystifying trial networks and network meta-analysis. BMJ, 346, 2013, f2914.
34. Cohen, J., Statistical power analysis for the behavioural sciences. Second edition, 1988, Lawrence Erlbaum Associates, USA.
35. Nikolakopoulou, A., Mavridis, D., Salanti, G., Planning future studies based on the precision of network meta-analysis results. Stat Med 35 (2016), 978–1000.
36. McAlister, F.A., Straus, S.E., Sackett, D.L., Altman, D.G., Analysis and reporting of factorial trials - a Systematic review. JAMA 289 (2003), 2545–2553.
37. Del Giovane, C., Vacchi, L., Mavridis, D., Filippini, G., Salanti, G., Network meta-analysis models to account for variability in treatment definitions: application to dose effects. Stat Med 32 (2013), 25–39.
38. Bucher, H.C., Guyatt, G.H., Griffith, L.E., Walter, S.D., The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol 50 (1997), 683–691.
39. Lu, G., Ades, A.E., Assessing evidence inconsistency in mixed treatment comparisons. J Am Stat Assoc 101 (2006), 447–459.
40. Salanti, G., Higgins, J.P.T., Ioannidis, J.P.A., Evaluation of networks of randomized trials. Stat Methods Med Res 17 (2007), 279–301.