KEYWORDS: Wegener granulomatosis; Young girl; Cyclophophamide; cANCA.
METHODS: A double-blind, parallel-group randomised controlled trial was carried out. The intervention group received oral care with chlorhexidine 0.2%, while the control group received routine oral care with thymol. Nurses provided oral care with assigned solutions of 20 mL once daily over seven days. Oral cavity assessment using the Brief Oral Health Status Examination form was performed before each oral care procedure. Data on medication received and the subsequent development of aspiration pneumonia was recorded. An oral swab was performed on Day 7 to obtain specimens to test for colonisation.
RESULTS: The final sample consisted of 35 (control) and 43 (intervention) patients. Chlorhexidine was effective in reducing oral colonisation compared to routine oral care with thymol (p < 0.001). The risk of oral bacterial colonisation was nearly three times higher in the thymol group compared to the chlorhexidine group.
CONCLUSION: The use of chlorhexidine 0.2% significantly reduced oral colonisation and is recommended as an easier and more cost-effective alternative for oral hygiene.
METHODS: A stochastic model of Ers is integrated into the VENT protocol from previous works to develop the SiVENT protocol, to account for both intra- and inter-patient variability. A cohort of 20 virtual MV patients based on retrospective patient data are used to validate the performance of this method for volume-controlled (VC) ventilation. A performance evaluation was conducted where the SiVENT and VENT protocols were implemented in 1080 instances each to compare the two protocols and evaluate the difference in reduction of possible MV settings achieved by each.
RESULTS: From an initial number of 189,000 possible MV setting combinations, the VENT protocol reduced this number to a median of 10,612, achieving a reduction of 94.4% across the cohort. With the integration of the stochastic model component, the SiVENT protocol reduced this number from 189,000 to a median of 9329, achieving a reduction of 95.1% across the cohort. The SiVENT protocol reduces the number of possible combinations provided to the user by more than 1000 combinations as compared to the VENT protocol.
CONCLUSIONS: Adding a stochastic model component into a model-based approach to selecting MV settings improves the ability of a decision support system to recommend patient-specific MV settings. It specifically considers inter- and intra-patient variability in respiratory elastance and eliminates potentially harmful settings based on clinically recommended pressure thresholds. Clinical input and local protocols can further reduce the number of safe setting combinations. The results for the SiVENT protocol justify further investigation of its prediction accuracy and clinical validation trials.
METHODS: Two stochastic models (SM2 and SM3) were developed using retrospective patient respiratory elastance (Ers) from two clinical cohorts which were averaged over time intervals of 10 and 30 min respectively. A stochastic model from a previous study (SM1) was used to benchmark performance. The stochastic models were clinically validated on an independent retrospective clinical cohort of 14 patients. Differences in predictive ability were evaluated using the difference in percentile lines and cumulative distribution density (CDD) curves.
RESULTS: Clinical validation shows all three models captured more than 98% (median) of future Ers data within the 5th - 95th percentile range. Comparisons of stochastic model percentile lines reported a maximum mean absolute percentage difference of 5.2%. The absolute differences of CDD curves were less than 0.25 in the ranges of 5 systems, providing guided, personalised, and safe MV treatment.