Nutritional Status of older patients attending Cork University Dental School and Hospital

Objectives: This study aimed to gather data on the nutritional status of older patients attending Cork University Dental School and Hospital for treatment in the Restorative Department. Information was also collected about the medical status of the patients including the prevalence of self-reported xerostomia.
Methods: Data was collected by a self-completion questionnaire followed by a brief clinical examination. Nutritional Status was measured using the short version of the Mini Nutritional Assessment (MNA) which recorded patients’ Body Mass Index (BMI). The MNA consists of 6 parameters (including questions relating to patients’ history and anthropometric data) with a maximum total of 14 points. Scores of 12-14 indicate “normal nutritional status” whilst those between 8 and 11 indicate a patient “at risk of malnutrition”. Scores lower than 8 are an indication a patient who is “malnourished”. All patients attending Cork University Dental School and Hospital aged 65 years and older were invited to participate in the study.

Results: A total of 22 subjects participated in this study. Twelve patients were partially dentate with 10 edentulous. The results from the MNA indicate that 11 patients were of “normal nutritional status” with 11 patients identified as being “at risk of malnutrition”. None of the subjects were “malnourished”. Edentate patients generally recorded lower MNA scores than partially dentate patients. In total, 9 patients reported experiencing xerostomia with 8 indicating that they needed to sip liquids to aid swallowing but only 3 had difficulty swallowing food.

Conclusion: This small study indicates that a number of the older patients attending Cork University Dental School and Hospital for dental care may be “at risk of malnutrition”. These findings suggest that nutritional advice and dental care should both be included in an overall package of care for older patients.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

A modified method for measuring antibiotic use in healthcare settings: implications for antibiotic stewardship and benchmarking

Objectives: To determine whether adjusting the denominator of the common hospital antibiotic use measurement unit (defined daily doses/100 bed-days) by including age-adjusted comorbidity score (100 bed-days/age-adjusted comorbidity score) would result in more accurate and meaningful assessment of hospital antibiotic use. 

Methods: The association between the monthly sum of age-adjusted comorbidity and monthly antibiotic use was measured using time-series analysis (January 2008 to June 2012). For the purposes of conducting internal benchmarking, two antibiotic usage datasets were constructed, i.e. 2004-07 (first study period) and 2008-11 (second study period). Monthly antibiotic use was normalized per 100 bed-days and per 100 bed-days/age-adjusted comorbidity score. 

Results: Results showed that antibiotic use had significant positive relationships with the sum of age-adjusted comorbidity score (P = 0.0004). The results also showed that there was a negative relationship between antibiotic use and (i) alcohol-based hand rub use (P = 0.0370) and (ii) clinical pharmacist activity (P = 0.0031). Normalizing antibiotic use per 100 bed-days contributed to a comparative usage rate of 1.31, i.e. the average antibiotic use during the second period was 31% higher than during the first period. However, normalizing antibiotic use per 100 bed-days per age-adjusted comorbidity score resulted in a comparative usage rate of 0.98, i.e. the average antibiotic use was 2% lower in the second study period. Importantly, the latter comparative usage rate is independent of differences in patient density and case mix characteristics between the two studied populations. 

Conclusions: The proposed modified antibiotic measure provides an innovative approach to compare variations in antibiotic prescribing while taking account of patient case mix effects. 

The Coxian phase-type distribution as a contribution to the multilevel model of in-hospital mortality

This paper presents multilevel models that utilize the Coxian phase-type distribution in order to be able to include a survival component in the model. The approach is demonstrated by modeling patient length of stay and in-hospital mortality in geriatric wards in Italy. The multilevel model is used to provide a means of controlling for the existence of possible intra-ward correlations, which may make patients within a hospital more alike in terms of experienced outcome than patients coming from different hospitals, everything else being equal. Within this multilevel model we introduce the use of the Coxian phase-type distribution to create a covariate that represents patient length of stay or stage (of hospital care). Results demonstrate that the use of the multilevel model for representing the in-patient mortality is successful and further enhanced by the inclusion of the Coxian phase-type distribution variable (stage covariate).

A Conditional Approach for Modelling Patient Re-admissions in Hospital using a mixture of Coxian phase-type distributions incorporating Bayes Theorem

The number of elderly patients requiring hospitalisation in Europe is rising. With a greater proportion of elderly people in the population comes a greater demand for health services and, in particular, hospital care. Thus, with a growing number of elderly patients requiring hospitalisation competing with non-elderly patients for a fixed (and in some cases, decreasing) number of hospital beds, this results in much longer waiting times for patients, often with a less satisfactory hospital experience. However, if a better understanding of the recurring nature of elderly patient movements between the community and hospital can be developed, then it may be possible for alternative provisions of care in the community to be put in place and thus prevent readmission to hospital. The research in this paper aims to model the multiple patient transitions between hospital and community by utilising a mixture of conditional Coxian phase-type distributions that incorporates Bayes' theorem. For the purpose of demonstration, the results of a simulation study are presented and the model is applied to hospital readmission data from the Lombardy region of Italy.

Medication Reconciliation at Discharge from Hospital: A Systematic Review of the Quantitative Literature

Medicines reconciliation is a way to identify and act on discrepancies in patients’ medical histories and it is found to play a key role in patient safety. This review focuses on discrepancies and medical errors that occurred at point of discharge from hospital. Studies were identified through the following electronic databases: PubMed, Sciences Direct, EMBASE, Google Scholar, Cochrane Reviews and CINAHL. Each of the six databases was screened from inception to end of January 2014. To determine eligibility of the studies; the title, abstract and full manuscript were screened to find 15 articles that meet the inclusion criteria. The median number of discrepancies across the articles was found to be 60%. In average patient had between 1.2–5.3 discrepancies when leaving the hospital. More studies also found a relation between the numbers of drugs a patient was on and the number of discrepancies. The variation in the number of discrepancies found in the 15 studies could be due to the fact that some studies excluded patient taking more than 5 drugs at admission. Medication reconciliation would be a way to avoid the high number of discrepancies that was found in this literature review and thereby increase patient safety.