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1.
J Nutr Health Aging ; 27(7): 571-577, 2023.
Article in English | MEDLINE | ID: mdl-37498104

ABSTRACT

BACKGROUND: Independently, malnutrition and delirium in older hospitalised adults is prevalent. However, there is limited evidence on the association between these two conditions in older hospitalised adults with chronic kidney disease (CKD). OBJECTIVES: To determine the association between malnutrition and delirium in older CKD patients admitted to intensive care units (ICU). METHODS: This data linkage study utilised administrative data from New South Wales (NSW) hospitals in Australia between 2017 and 2020.Admitted patient data was linked with Cause of Death Unit Record File, and NSW Registry of Deaths (RBD). The study population comprised all CKD patients aged 65 and over admitted to ICUs. Descriptive statistics were used to summarise patient characteristics. Binary logistic tested for association between malnutrition and delirium. RESULTS: The study population included 748 CKD patients with a total 948 admissions in the study period. The International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) was used to code for all outcomes and comorbidities. The incidence of delirium was 15.5% (n=141) and malnutrition was recorded in 11.3% (n=103) across all admissions. The adjusted odds ratio (OR) of a delirium diagnosis was 2.07 (95% CI: 1.27-3.39) for CKD patients that were malnourished compared to non-malnourished CKD patients. CONCLUSIONS: This study showed a significant association between delirium and malnutrition in older CKD patients admitted to ICU. Management of malnutrition could be critical in reducing the risk of delirium in older hospitalized patients with CKD. Additionally, more education and awareness around delirium and its association with malnutrition are needed in clinical practice.


Subject(s)
Delirium , Malnutrition , Renal Insufficiency, Chronic , Delirium/epidemiology , Delirium/ethnology , Malnutrition/complications , Malnutrition/epidemiology , Humans , Intensive Care Units , Male , Female , Middle Aged , Aged , Aged, 80 and over , Risk Factors , Routinely Collected Health Data
2.
Epidemiol Infect ; 145(11): 2324-2329, 2017 08.
Article in English | MEDLINE | ID: mdl-28545598

ABSTRACT

Routine, passive surveillance systems tend to underestimate the burden of communicable diseases such as dengue. When empirical methods are unavailable, complimentary opinion-based or extrapolative methods have been employed. Here, an expert Delphi panel estimated the proportion of dengue captured by the Indonesian surveillance system, and associated health system parameters. Following presentation of medical and epidemiological data and subsequent discussions, the panel made iterative estimates from which expansion factors (EF), the ratio of total:reported cases, were calculated. Panelists estimated that of all symptomatic Indonesian dengue episodes, 57·8% (95% confidence interval (CI) 46·6-59·8) enter healthcare facilities to seek treatment; 39·3% (95% CI 32·8-42·0) are diagnosed as dengue; and 20·3% (95% CI 16·1-24·3) are subsequently reported in the surveillance system. They estimated most hospitalizations occur in the public sector, while ~55% of ambulatory episodes are seen privately. These estimates gave an overall EF of 5·00; hospitalized EF of 1·66; and ambulatory EF of 34·01 which, when combined with passive surveillance data, equates to an annual average (2006-2015) of 612 005 dengue cases, and 183 297 hospitalizations. These estimates are lower than those published elsewhere, perhaps due to case definitions, local clinical perceptions and treatment-seeking behavior. These findings complement global burden estimates, support health economic analyses, and can be used to inform decision-making.


Subject(s)
Dengue/epidemiology , Hospitalization/statistics & numerical data , Population Surveillance , Delphi Technique , Dengue/prevention & control , Dengue/virology , Humans , Indonesia/epidemiology
3.
Asia Pac J Public Health ; 29(1): 7-16, 2017 Jan.
Article in English | MEDLINE | ID: mdl-28198645

ABSTRACT

We described and quantified epidemiologic trends in dengue disease burden in 5 Asian countries (Indonesia, Thailand, Malaysia, Philippines, and Vietnam) and identified and estimated outbreaks impact over the last 3 decades. Dengue surveillance data from 1980 to 2010 were retrieved from DengueNet and from World Health Organization sources. Trends in incidence, mortality, and case fatality rate (CFR) were systematically analyzed using annual average percent change (AAPC), and the contribution of epidemic years identified over the observation period was quantified. Over the 30-year period, incidence increased in all countries (AAPC 1980-2010: 6.7% in Thailand, 10.4% in Vietnam, 12.0% in Indonesia, 18.1% in Malaysia, 24.4% in Philippines). Mortality also increased in Indonesia, Malaysia, and Philippines (AAPC: 6.8%, 7.0%, and 29.2%, respectively), but slightly decreased in Thailand and Vietnam (AAPC: -1.3% and -2.5%), and CFR decreased in all countries (AAPC: -4.2% to -8.3%). Epidemic years, despite representing less than a third of the observation period, contributed from 1 to 3 times more cases versus nonepidemic years. Implementation of more sensitive surveillance methods over the study period may have contributed to a reporting or ascertainment bias in some countries. Nonetheless, these data support the urgent need for novel, integrated, or otherwise effective dengue prevention and control tools and approaches.


Subject(s)
Dengue/epidemiology , Population Surveillance , Asia, Southeastern/epidemiology , Dengue/mortality , Humans , Incidence
4.
Med Inform (Lond) ; 21(4): 317-26, 1996.
Article in English | MEDLINE | ID: mdl-9179835

ABSTRACT

A robust, hand-held, patient-oriented insulin regimen optimizer (POIRO) has been developed. Relevant information is entered by selecting appropriate items from choices displayed on a touch-sensitive screen rather than a conventional keyboard. All data items are recorded, together with their time and date of entry, and may be recalled at any time with glucose values displayed graphically to provide an overview of glycaemic control. When requested, an integral, hybrid, statistical and rule-based expert system program uses all available data to suggest an optimum insulin dose within physician determined, pre-set limits. POIRO has been formally evaluated in a randomized crossover pilot trial, comparing two 3 week periods with and without decision support, in six patients with type 1 diabetes. Mean (SE) pre-prandial blood glucose levels were significantly lower during the period when decision support was available (7.5 (0.4) versus 8.9 (0.4) mmol/l, p = 0.015) with no increase in the frequency or severity of hypoglycaemia. The device, which was well received by the patients, may offer a relatively inexpensive method of providing expert diabetic advice at a distance. The persistence of improved glycaemic control, even after decision support was switched off, suggests the device could be used intermittently by patients and may have educational value.


Subject(s)
Blood Glucose Self-Monitoring , Diabetes Mellitus, Type 1/drug therapy , Drug Therapy, Computer-Assisted/instrumentation , Expert Systems , Hypoglycemic Agents/administration & dosage , Insulin/administration & dosage , Algorithms , Analysis of Variance , Cross-Over Studies , Humans , Patient Satisfaction , Pilot Projects , User-Computer Interface
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