ASHA journals
36 files

Voice rehabilitation after total laryngectomy (Tawfik et al., 2021)

journal contribution
posted on 2021-06-29, 20:58 authored by Gehad Mohamed Tawfik, Omar Mohamed Makram, Ahmad Helmy Zayan, Sherief Ghozy, Peter Samuel Eid, Mona Hanafy Mahmoud, Abdelaziz Abdelaal, Seif Mahmoud Abdelghany, Ahmed M. Sayed, To Kim Sang, Mahmoud Kassem, Quoc Le Minh Ho, Heba Hussien Eltanany, Amira Farghaly Ali, Osama Gamal Sweiny, Khaled Essam Elsherbiny, Amr G. Shafik, Kenji Hirayama, Nguyen tien HuyNguyen tien Huy
Purpose: Our aim was to assess the different voice prostheses (VPs) to identify the most efficient, safest, patient-tailored, longest lifetime, and inexpensive VPs and assess the different factors affecting their quality.
Method: In September 2017, 15 databases were searched to include all randomized controlled trials. A new search was done in May 2019 to include all other study design articles, which include all the new-era VPs subtypes. Network meta-analysis (NMA) was applied to all 27 outcomes, besides NMA overall and partial order setting was done by using Hasse scatter plots. p values were used in NMA, where the best VPs are approaching one and the least approaches zero. Meta-analysis was done for the rest of the outcomes.
Results: Two hundred one articles were eligible for inclusion in our study (N = 11,918). Provox-2 was significantly the most efficient and safest device concerning the most patient preference (odds ratio [OR] = 33.88 [0.65, 1762.24]; p = .92), the least dislodgement (risk ratio [RR] = 0.27 [0.13, 0.57]; p = .79), the least airflow resistance (RR = 0.42 [0.08, 2.11]; p = .84), the least granulation formation (RR = 0.73 [0.02, 26.32]; p = .60), and the least VPs’ inaccurate size (RR = 0.77 (0.23, 2.61); p = .66). Heat and moisture exchanger addition showed a significant increase in maximum phonation time and breathing experience, with p values (1 and .59), respectively. While heat and moisture exchanger addition showed a significant decline in stoma cleaning frequency, coughing frequency, forced expectoration, sputum production, sleeping problems, and loosening of adhesive, with p values (.99, .72, .69, .96, 1, and .96), respectively, Groningen low resistance and Nijdam were considered the worst devices with both overall mean p value of .44.
Conclusions: Provox-2 is considered the best choice as being the most preferable for patients, with the least airflow resistance, dislodgment, granulation formation, and prosthesis inaccurate size. Groningen low resistance and Nijdam were considered the worst devices according to our analysis.

Supplemental Figures
S1. Risk of bias assessment summary.
S2. Risk of bias assessment graph of included randomized controlled trials.
S3. Network meta-analysis for Replacements frequency of each device.
S4. Network meta-analysis for Duration lifetime of each device.
S5. Network meta-analysis for Air flow resistance of each device.
S6. Network meta-analysis for Maximum phonation time of each device.
S7. Network meta-analysis for Leakage rate of each device.
S8. Network meta-analysis for Speech rate of each device.
S9. Network meta-analysis for Patient device preference of each device.
S10. Network meta-analysis for Stoma cleaning of each device.
S11. Network meta-analysis for Breathing problems of each device.
S12. Network meta-analysis for Coughing Frequency of each device.
S13. Network meta-analysis for Forced expectorations of each device.
S14. Network meta-analysis for Sputum production of each device.
S15. Network meta-analysis for Sleeping problems of each device.
S16. Network meta-analysis for Loosening of adhesive of each device.
S17. Network meta-analysis for Increase phonatory effort of each device.
S18. Network meta-analysis for Voice speech quality of each device.
S19. Network meta-analysis for Fundamental Frequency of each device.
S20. Network meta-analysis for Voice Loudness of each device.
S21. Network meta-analysis for Speech Intelligibility of each device.
S22. Network meta-analysis for Stoma stenosis of each device.
S23. Network meta-analysis for Dislodgement of each device.
S24. Network meta-analysis for Fistula problems of each device.
S25. Network meta-analysis for Granulation of each device.
S26. Network meta-analysis for Breathing Experience of each device.
S27. Network meta-analysis for Prosthesis inaccurate size of each device.
S28. Network meta-analysis for Prosthesis deterioration of each device.
S29. Network meta-analysis for Follow-up survival rate of each device.
S30A. Meta-analysis for Aspiration pneumonia rate of each device.
S30B. Meta-analysis for Fungal colonization rate of each device.
S31A. Meta-analysis for Experience with speaking rate of each device.
S31B. Meta-analysis for Skin irritation rate of each device.

Supplemental Tables
S1. PRISMA 2009 Checklist.
S2. Detailed search strategy for each database search.
S3. Detailed definitions of each outcome in the study.
S4. All equations used in data extraction.
S5. Baseline characteristics of the patients in the included studies.

Tawfik, G. M., Makram, O. M., Zayan, A. H., Ghozy, S., Eid, P. S., Mahmoud, M. H., Abdelaal, A., Abdelghany, S. M., Sayed, A. M., Sang, T. K., Kassem, M., Ho, Q. L. M., Eltanany, H. H., Ali, A. F., Sweiny, O. G., Elsherbiny, K. E., Shafik, A. G., Hirayama, K., & Huy, N. T. (2021). Voice rehabilitation by voice prostheses after total laryngectomy: A systematic review and network meta-analysis for 11,918 patients. Journal of Speech, Language, and Hearing Research. Advance online publication.