| Literature DB >> 28629318 |
Vanessa R Y Hollaar1,2,3, Gert-Jan van der Putten4,5,6, Claar D van der Maarel-Wierink4,7, Ewald M Bronkhorst8, Bert J M de Swart9,10, Nico H J Creugers5.
Abstract
BACKGROUND: Dysphagia and potential respiratory pathogens in the oral biofilm are risk factors for aspiration pneumonia in nursing home residents. The aim of the study was to examine if the daily application of 0.05% chlorhexidine oral rinse solution is effective in reducing the incidence of aspiration pneumonia in nursing home residents with dysphagia. Associations between background variables (age, gender, dysphagia severity, care dependency, medication use, number of medical diagnoses, teeth and dental implants, and wearing removable dentures) and the incidence of aspiration pneumonia were also examined.Entities:
Keywords: Aspiration pneumonia; Chlorhexidine; Dysphagia; Nursing home; Oral health care; Oral hygiene care; Pneumonia
Mesh:
Substances:
Year: 2017 PMID: 28629318 PMCID: PMC5477106 DOI: 10.1186/s12877-017-0519-z
Source DB: PubMed Journal: BMC Geriatr ISSN: 1471-2318 Impact factor: 3.921
Fig. 1Flow chart of multicenter study
Numbers of participants or gender and mean (Mean ± SD) age, FOIS-level, CDS-score, and numbers of diseases and medications in each group at baseline
| Intervention | Control | Total | |
|---|---|---|---|
| Number of participants | 52 | 51 | 103 |
| Number of men / women | 25/27 | 26/25 | 51/52 |
| Age | 79.4 ± 8.9 | 81.7 ± 9.03 | 80.5 ± 9.0 |
| FOIS-level | 4.8 ± 1.5 | 4.9 ± 1.5 | 4.8 ± 1.5 |
| CDS-score | 38.0 ± 16.6 | 35.0 ± 15.0 | 36.5 ± 15.8 |
| Number of diseases | 4.7 ± 2.4 | 4.3 ± 2.2 | 4.5 ± 2.3 |
| Number of medication | 8.6 ± 3.7 | 9.6 ± 3.6 | 9.0 ± 3.7 |
Number of participants with a certain oral status determined by their oral examination at baseline
| Intervention | Control | Total | |
|---|---|---|---|
| Dentulous, including participants with | 14 | 19 | 33 (32%) |
| Natural teeth | 6 | 11 | 17 |
| Dental implant(s) | 4 | 1 | 5 |
| Partial prosthesis | 1 | 1 | 2 |
| Removable denture | 3 | 4 | 7 |
| Removable denture and partial prosthesis | 0 | 2 | 2 |
| Mean number of teeth | 15.1 ± 7.9 | 14.6 ± 7.1 | 14.9 ± 7.3 |
| Edentulous, including participants with | 38 | 32 | 70 (68%) |
| Complete removable dentures | 29 | 30 | 59 |
| Complete removable dentures with dental implants | 5 | 1 | 6 |
| Not wearing dentures | 4 | 1 | 5 |
Number and percentages (%) of participants who participated for one year, dropped out or died during the study period and incidence of pneumonia, including dropouts and mortality in each group
| Intervention | Control | Total | |
|---|---|---|---|
| Included 1 year | 15 (29) | 34 (67) | 49 (48) |
| Dropout | 23 (44) | 1 (2) | 24 (23) |
| Mortality | 14 (27) | 16 (31) | 30 (29) |
| Pneumonia | 12 (23) | 14 (27) | 26 (25) |
| Included 1 year | 3 (25) | 7 (50) | 10 (38) |
| Dropout | 1 (8) | 0 | 1 (4) |
| Mortality | 8 (67) | 7 (50) | 15(58) |
Fig. 2Pneumonia free survival by group status. Legends: Intervention - - - -. Control ─
Results of Cox regression analysis for group and FOIS-level of the risk of the incidence of pneumonia and Cox’s multivariate proportional hazards regression model of possible risk factors for pneumonia after correction for group and FOIS-level presented as hazard ratio (HR), 95% confidence interval (95% CI) and P-value
| HR | 95% CI |
| |
|---|---|---|---|
| Group (Intervention / Control) | 0.800a | [0.368–1.737] | 0.572 |
| FOIS-level | 0.804a | [0.656 – 0.986] | 0.036 |
| Age | 0.990 | [0.943–1.039] | 0.684 |
| Gender | 1.017 | [0.469–2.205] | 0.965 |
| CDS-score | 0.976 | [0.948–1.006] | 0.118 |
| Number of diseases | 1.046 | [0.873–1.253] | 0.628 |
| Number of used medication | 1.087 | [0.977–1.210] | 0.127 |
| Oral status (edentulous/dentate) | 1.526 | [0.702–3.319] | 0.286 |
| Number of teeth | 1.002 | [0.923–1.089] | 0.956 |
| Dental implants (yes/no) | 1.104 | [0.247–4.941] | 0.897 |
| Removable denture (yes/no) | 1.057 | [0.236–4.725] | 0.942 |
aHR-ranges for Group from 0.664 to 0.939 and HR-ranges for FOIS-level from 0.738 to 0.920 in the nine different Cox’s multivariate proportional hazards regression models with possible risk factors