Recent temporal trends, characteristics and outcomes of patients with non-COVID-19 community-acquired pneumonia at two tertiary hospitals in Australia: an observational study.

BACKGROUND: Community-acquired pneumonia (CAP) leads to considerable morbidity and mortality globally. However, data on CAP burden in Australia, especially during the coronavirus disease 2019 (COVID-19) pandemic, are limited. AIMS: We characterised and assessed clinical outcomes of non-COVID-19 CAP hospitalisations over a 6-year period at two major hospitals in South Australia. METHODS: All non-COVID-19 CAP hospitalisations were identified using the International Statistical Classification of Diseases and Related Health Problems, Tenth revision, Australian modification (ICD-10-AM) codes, between 1 January 2018 and 31 December 2023, at two tertiary hospitals in Adelaide. Clinical outcomes included in-hospital and 30-day mortality, length of stay (LOS) in, intensive care unit (ICU) admission and 30-day readmissions. Multilevel regression models were utilised to identify predictors of clinical outcomes. RESULTS: Over the 6-year period, there were 7853 non-COVID-19 CAP hospitalisations, with a temporal increase from 100 per 100 000 population in 2018 to 208 per 100 000 population in 2023 (P < 0.001). The mean (SD) age was 75.1 (17.6) years, and 54.6% were males. The mean age declined over time (P < 0.05), while other characteristics remained stable. Streptococcus pneumoniae was the most commonly identified bacterium (21.8% of cases). In-hospital mortality occurred in 7.8% of patients, with 30-day mortality and readmission rates of 14.3% and 16.9% respectively. LOS declined significantly during the pandemic years; however, mortality remained stable over time. Frailty status, malnutrition and number of comorbidities significantly predicted 30-day mortality and LOS, in addition to pneumonia severity and ICU admission. CONCLUSIONS: There has been an increasing trend of hospitalisations for non-COVID-19 CAP during the COVID-19 pandemic, with a concomitant trend towards shorter LOS and no significant shift in other clinical outcomes.

Comparing Outcomes of Community-Acquired Pneumonia Patients Discharged from General Medicine and Respiratory Units in Australia: A Propensity Score-Matched Analysis.

Background/Objectives: Community-acquired pneumonia (CAP) is a common emergency presentation in Australia, with the choice of admitting specialty unit often influenced by pneumonia severity and comorbidities. However, it remains unclear whether there are between-specialty differences in patient characteristics and outcomes. We sought to address this issue by investigating the characteristics and outcomes of CAP patients admitted to General Medicine (GM) versus Respiratory units. Methods: This retrospective observational study utilised data from the two largest metropolitan hospitals in South Australia, encompassing all non-COVID-19-related CAP admissions throughout 2021 to 2023. The hospital length of stay (LOS), in-patient and 30-day mortality, and 30-day readmission rates were assessed by propensity score matching (PSM) using 17 variables. Results: Of the 3004 cases of non-COVID-19 CAP admitted across the two hospitals during the study period, 2673 (71.8%) were admitted under GM units and 331 (9.1%) under Respiratory units. GM patients were, on average, a decade older, presented with a significantly higher burden of comorbidities, exhibited a greater prevalence of frailty, and had higher pneumonia severity compared to those admitted under a Respiratory unit (p < 0.05). Unadjusted analysis revealed a shorter median LOS among GM-admitted patients (5.9 vs. 4.1 days, p < 0.001). After PSM adjustment, patients admitted under the Respiratory units had an 8-fold higher odds of a longer LOS compared to GM (adjusted odds ratio [aOR] 8.53, 95% CI 1.96-37.25, p = 0.004). Other clinical outcomes were comparable between the two groups. Conclusions: Our findings indicate that GM units compared to Respiratory units provide efficient and safe care for patients requiring hospitalisation for CAP.

The value of distinguishing patients with isolated subsegmental pulmonary embolism presenting to two tertiary hospitals in Australia: an observational study.

Isolated-subsegmental-pulmonary-embolism (SSPE) is increasingly diagnosed with the use of computed-tomography-pulmonary-angiogram (CTPA). There remains clinical equipoise for management of SSPE with previous studies not accounting for frailty while determining clinical outcomes. Clinical outcomes among patients with isolated SSPE were compared with those with a more proximal PE after accounting for frailty and other risk-factors. This study included all patients with a positive CTPA for pulmonary embolism (PE) admitted between 2017 and 2021 to two Australian-tertiary-hospitals. Frailty was determined by use of the hospital-frailty-risk-score (HFRS). Competing-risk-analysis and Cox-proportional hazard models determined the cumulative-risk of VTE and mortality within 3 months and 1 year of index PE event after adjustment for frailty and other variables. Of 334 patients with positive CTPA for PE, 111 (33.2%) had isolated-SSPE. The mean (SD) age was 64.3 (17.7) years, 50.9% were males and 9.6% were frail. The risk of recurrent VTE within 3-months (0.9% vs. 1.8%, P = 0.458) and within 1-year of follow-up (2.7% vs. 6.3%, P = 0.126) did not differ significantly between patients with isolated SSPE and those with more proximal PE. After adjusted analyses, the cumulative-incidence of recurrent VTE was not different among patients with isolated SSPE within 1 year of index event [subdistribution-hazard-ratio (HR) 0.84, 95% CI 0.19 to 3.60]. Similarly, mortality within 1 year of index event was also not different between the two groups (aHR 1.72, 95% CI 0.92-3.23). The prevalence of SSPE was 33.2% and even after adjustment for frailty these patients had no different clinical outcomes than those with proximal PE.

Impact of Malnutrition on Clinical Outcomes of Acutely Hospitalised Heart Failure Patients at Two Tertiary Hospitals in Australia: An Observational Study.

BACKGROUND: Malnutrition is common in patients with heart failure (HF) but is often neglected, despite guidelines suggesting that all hospitalised patients should undergo nutritional screening within 24-hours of admission. AIMS: This study investigated the nutritional screening rates and determined the immediate and long-term clinical outcomes in patients with HF admitted at two tertiary hospitals in Australia. METHODS: Nutritional screening was assessed by the Malnutrition Universal Screening Tool (MUST) completion rates. Patients were classified into two categories based on their MUST scores (0=low malnutrition risk and ≥1=at risk of malnutrition). Propensity-score-matching (PSM) was used to match 20 variables depending upon the risk of malnutrition. Clinical outcomes included the days-alive-and-out-of-hospital at 90 days of discharge (DAOH90), length of hospital stay, in-hospital, 30-day and 180-day mortality and 30-day readmissions. RESULTS: There were 5,734 HF admissions between 2013-2020, of whom, only 789 (13.8%) patients underwent MUST screening. The mean (SD) age was 76.2 (14.0) years and 51.9% were males. Five-hundred and fifty-four (554) (70.2%) patients were at low malnutrition risk and 235 (29.8%) at risk of malnutrition. In HF patients, who were at risk of malnutrition, the DAOH90 were lower by 5.9 days (95% CI -11.49 to -0.42, p=0.035) and 180-day mortality was significantly worse (coefficient 0.10, 95% CI 0.02-0.18, p=0.007) compared to those who were at low risk of malnutrition. However, other clinical outcomes were similar between the two groups. CONCLUSION: Nutrition screening is poor in hospitalised HF patients and long-term but not short-term clinical outcomes were worse in malnourished HF patients.

Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital.

Background and aims: Medication usage varies according to prescribing behavior, professional recommendations, and the introduction of new drugs. Local surveillance of medication usage may be useful for understanding and comparing prescribing practices by healthcare providers, particularly in countries such as Australia that are in the process of enhancing nationwide data linkage programs. We sought to investigate the utility of electronic hospital admission data to investigate local trends in medication use, to determine similarities and differences with other Australian studies, and to identify areas for targeted interventions. Methods: We performed a retrospective longitudinal analysis using combined data from a hospital admissions administrative dataset from a large tertiary teaching hospital in Adelaide, South Australia and a hospital administrative database documenting medication usage matched for the same set of patients. All adult admissions over a 12-year period, between 1 January 2007 and 31st December 2018, were included in the study population. Medications were categorized into 21 pre-defined drug classes of interest according to the ATC code list 2021. Results: Of the 692,522 total admissions, 300,498 (43.4%) had at least one recorded medication. The overall mean number of medications for patients that were medicated increased steadily from a mean (SD) of 5.93 (4.04) in 2007 to 7.21 (4.98) in 2018. Results varied considerably between age groups, with the older groups increasing more rapidly. Increased medication usage was partly due to increased case-complexity with the mean (SD) Charlson comorbidity index increasing from 0.97 (1.66) in 2007-to-2012 to 1.17 (1.72) in 2013-to-2018 for medicated patients. Of the 21 medication classes, 15 increased (p < 0.005), including antithrombotic agents; OR = 1.18 [1.16-1.21], proton pump inhibitors; OR = 1.14 [1.12-1.17], statins; OR = 1.12; [1.09-1.14], and renin-angiotensin system agents; OR = 1.06 [1.04-1.08], whilst 3 decreased (p < 0.005) including anti-inflammatory drugs (OR = 0.55; 99.5% CI = 0.53-0.58), cardiac glycosides (OR = 0.81; 99.5% CI = 0.78-0.86) and opioids (OR = 0.82; 99.5% CI = 0.79-0.83). The mean number of medications for all admissions increased between 2007 and 2011 and then declined until 2018 for each age group, except for the 18-to-35-year-olds. Conclusion: Increased medication use occurred in most age groups between 2007 and 2011 before declining slightly even after accounting for increased comorbidity burden. The use of electronic hospital admission data can assist with monitoring local medication trends and the effects of initiatives to enhance the quality use of medicines in Australia.

Benefits of heart failure-specific pharmacotherapy in frail hospitalised patients: a cross-sectional study.

OBJECTIVES: Up to 50% of heart failure (HF) patients may be frail and have worse clinical outcomes than non-frail patients. The benefits of HF-specific pharmacotherapy (beta-blockers, ACE-inhibitors/angiotensin-receptor-blockers and mineralocorticoid-receptor-antagonist) in this population are unclear. This study explored whether HF-specific pharmacotherapy improves outcomes in frail hospitalised HF patients. DESIGN: Observational, multicentre, cross-sectional study. SETTINGS: Tertiary care hospitals. PARTICIPANTS: One thousand four hundred and six hospitalised frail HF patients admitted between 1 January 2013 and 31 December 2020. MEASURES: The Hospital Frailty Risk Score (HFRS) determined frailty status and patients with HFRS ≥5 were classified as frail. The primary outcomes included the days alive and out of hospital (DAOH) at 90 days following discharge, 30-day and 180-day mortality, length of hospital stay (LOS) and 30-day readmissions. Propensity score matching (PSM) compared clinical outcomes depending on the receipt of HF-specific pharmacotherapy. RESULTS: Of 5734 HF patients admitted over a period of 8 years, 1406 (24.5%) were identified as frail according to the HFRS and were included in this study. Of 1406 frail HF patients, 1025 (72.9%) received HF-specific pharmacotherapy compared with 381 (27.1%) who did not receive any of these medications. Frail HF patients who did not receive HF-specific pharmacotherapy were significantly older, with higher creatinine and brain natriuretic peptide but with lower haemoglobin and albumin levels (p<0.05) when compared with those frail patients who received HF medications. After PSM frail patients on treatment were more likely to have an increased DAOH (coefficient 16.18, 95% CI 6.32 to 26.04, p=0.001) than those who were not on treatment. Both 30-day (OR 0.30, 95% CI 0.23 to 0.39, p<0.001) and 180-day mortality (OR 0.43, 95% CI 0.33 to 0.54, p<0.001) were significantly lower in frail patients on HF treatment but, there were no significant differences in LOS and 30-day readmissions (p>0.05). CONCLUSION: This study found an association between the use of HF-specific pharmacotherapy and improved clinical outcomes in frail HF hospitalised patients when compared to those who were not on treatment. TRIAL REGISTRATION NUMBER: ANZCTRN383195.

Validity of the Malnutrition Universal Screening Tool for Evaluation of Frailty Status in Older Hospitalised Patients.

The malnutrition-universal-screening-tool (MUST) is commonly used for screening malnutrition in hospitalised patients but its utility in the detection of frailty is unknown. This study determined the utility of MUST in detection of frailty in older hospitalised patients. This prospective-study enrolled 243 patients ⩾65 years in a tertiary-teaching hospital in Australia. Patients with a MUST score of ⩾1 were classified as at-risk of malnutrition. Frailty status was determined by the Edmonton-Frail-Scale (EFS) and patients with an EFS score of >8 were classified as frail. We validated the MUST against the EFS by plotting a receiver-operating-characteristic-curve (ROC) curve and area-under-the-curve (AUC) was determined. The mean (SD) age was 83.9 (6.5) years and 126 (51.8%) were females. The EFS determined 149 (61.3%) patients as frail, while 107 (44.1%) patients were at-risk of malnutrition according to the MUST. There was a positive linear but weak association between the MUST and the EFS scores (Pearson's correlation coefficient= .22, 95% CI .12- .36, p < .001). The sensitivity, specificity, positive and negative predictive value of MUST in the detection of frailty was 51%, 67%, 78.5% and 37%, respectively and the AUC was .59 (95% CI .53-.65, p < .001). The MUST is moderately sensitive in detection of frailty in older-hospitalised patients.

The impact of standardised goals of care documentation on the use of cardiopulmonary resuscitation, mechanical ventilation, and intensive care unit admissions in older patients: a retrospective observational analysis.

Background In South Australian hospitals, 'Do Not Resuscitate' orders have been replaced by '7-Step Pathway Acute Resuscitation Plans', a standardised form and approach that encourages shared decision-making while providing staff with clarity about goals of care. This initiative has led to increased rates of documentation about treatment preferences, including 'Not-For-Cardiopulmonary Resuscitation'. Aim To quantify any effect of the 7-Step Pathway form versus previous 'Do Not Resuscitate' orders on cardiopulmonary resuscitation, mechanical ventilation, and/or intensive care unit admission during hospitalisation. Methods We completed a retrospective, observational study in two Australian tertiary hospitals using interrupted time-series analysis. We examined the number of medical inpatients aged 70 years and over who received one or more Intensive Treatments-cardiopulmonary resuscitation, mechanical ventilation, or intensive care unit admission-in the 2 years before and 2 years after the introduction of the form. Results There were 2759 Intensive Treatments across 66 051 inpatient admissions; 1304/32 489 (4.0%) pre-intervention and 1455/33 562 post-intervention (4.3%). Sub-group analysis of those who died in hospital showed 400/1669 (24%) received Intensive Treatments pre-intervention and 382/1624 post-intervention (24%). Interrupted time-series analysis suggested that the intervention did not significantly alter Intensive Treatments over time at Hospital 1 and was associated with a significant slowing of the already decreasing use of Intensive Treatments at Hospital 2. Among patients who died in hospital, there was minimal change at either site. Conclusions There was no reduction in Intensive Treatments in older medical inpatients following the introduction of standardised goals of care documentation.

External Validation of the Hospital Frailty-Risk Score in Predicting Clinical Outcomes in Older Heart-Failure Patients in Australia.

Frailty is common in older hospitalised heart-failure (HF) patients but is not routinely assessed. The hospital frailty-risk score (HFRS) can be generated from administrative data, but it needs validation in Australian health-care settings. This study determined the HFRS scores at presentation to hospital in 5735 HF patients ≥ 75 years old, admitted over a period of 7 years, at two tertiary hospitals in Australia. Patients were classified into 3 frailty categories: HFRS < 5 (low risk), 5−15 (intermediate risk) and >15 (high risk). Multilevel multivariable regression analysis determined whether the HFRS predicts the following clinical outcomes: 30-day mortality, length of hospital stay (LOS) > 7 days, and 30-day readmissions; this was determined after adjustment for age, sex, Charlson index and socioeconomic status. The mean (SD) age was 76.1 (14.0) years, and 51.9% were female. When compared to the low-risk HFRS group, patients in the high-risk HFRS group had an increased risk of 30-day mortality and prolonged LOS (adjusted OR (aOR) 2.09; 95% CI 1.21−3.60) for 30-day mortality, and an aOR of 1.56 (95% CI 1.01−2.43) for prolonged LOS (c-statistics 0.730 and 0.682, respectively). Similarly, the 30-day readmission rate was significantly higher in the high-risk HFRS group when compared to the low-risk group (aOR 1.69; 95% CI 1.06−2.69; c-statistic = 0.643). The HFRS, derived at admission, can be used to predict ensuing clinical outcomes among older hospitalised HF patients.

Relationship between Vitamin C Deficiency and Cognitive Impairment in Older Hospitalised Patients: A Cross-Sectional Study.

Vitamin C is a powerful antioxidant and facilitates neurotransmission. This study explored association between vitamin C deficiency and cognitive impairment in older hospitalised patients. This prospective study recruited 160 patients ≥ 75 years admitted under a Geriatric Unit in Australia. Cognitive assessment was performed by use of the Mini-Mental-State-Examination (MMSE) and patients with MMSE scores <24 were classified as cognitively-impaired. Fasting plasma vitamin C levels were determined using high-performance-liquid-chromatography. Patients were classified as vitamin C deficient if their levels were below 11 micromol/L. Logistic regression analysis was used to determine whether vitamin C deficiency was associated with cognitive impairment after adjustment for various covariates. The mean (SD) age was 84.4 (6.4) years and 60% were females. A total of 91 (56.9%) were found to have cognitive impairment, while 42 (26.3%) were found to be vitamin C deficient. The mean (SD) MMSE scores were significantly lower among patients who were vitamin C deficient (24.9 (3.3) vs. 23.6 (3.4), p-value = 0.03). Logistic regression analysis suggested that vitamin C deficiency was 2.9-fold more likely to be associated with cognitive impairment after adjustment for covariates (aOR 2.93, 95% CI 1.05−8.19, p-value = 0.031). Vitamin C deficiency is common and is associated with cognitive impairment in older hospitalised patients.

Prevalence, characteristics and risk factors of frequently readmitted patients to an internal medicine service.

BACKGROUND: Unplanned hospital readmissions (HRA), which have been used as key performance index of healthcare quality, are becoming more prevalent. They are associated with substantial financial burden to hospital systems and considerable impacts on patients' physical and mental health. Patients with frequent readmissions are not well studied. AIMS: To determine the prevalence, characteristics and risk factors associated with frequent readmissions (FRA) to an internal medicine service at a tertiary public hospital. METHOD: A retrospective observational study was conducted at an internal medicine service in a tertiary teaching hospital between 1 January 2010 and 30 June 2016. FRA was defined as four or more readmissions within 12 months of discharge from the index admission (IA). Demographic and clinical characteristics and potential risk factors were evaluated. RESULTS: A total of 50 515 patients was included; 1657 (3.3%) had FRA and were associated with nearly 2.5 times higher in 12-month mortality rates. They were older, had higher rates of indigenous Australians (3.2%), more disadvantaged status (index of relative socio-economic disadvantage decile of 5.3) and more comorbidities (mean Charlson comorbidity index 1.4) in comparison, to infrequent readmission group. The mean length of hospital stay during the IA was 6 days for FRA group (21.4% staying more than 7 days) with higher incidence of discharge against medical advice (2.0% higher). Intensive care unit admission rate was 6.6% for FRA group compared with 3.9% for infrequent readmission group. Multivariate analysis showed mental disease and disorders, neoplastic, alcohol/drug use and alcohol/drug-induced organic mental disorders are associated with FRA. CONCLUSION: The risk factors associated with FRA were older age, indigenous status, being socially disadvantaged, having higher comorbidities and discharging against medical advice. Conditions that lead to FRA were mental disorders, alcohol/drug use and alcohol/drug-induced organic mental disorders and neoplastic disorders.

Trends in Frailty and Use of Evidence-Based Pharmacotherapy for Heart Failure in Australian Hospitalised Patients: An Observational Study.

Frailty increases morbidity and mortality in heart failure (HF) patients. Current risk-adjustment models do not include frailty-status and the relationship between frailty and pharmacotherapy is unclear. This study explored trends in frailty over time and its relationship with prescription of heart failure specific pharmacotherapy in hospitalised HF patients. We used the Hospital Frailty Risk Score (HFRS) to determine frailty status of patients ≥18 years admitted between 2015-2019 at two tertiary hospitals in Australia. Patients with an HFRS ≥ 5 were classified as frail. In the 3706 patients with a mean (SD) age of 76.1 (14.4) years, 876 (23.6%) were classified as frail. HFRS was weakly correlated with age (r = 0.16) and Charlson-index (r = 0.35) (both p values < 0.001). Whilst frailty was more common in older HF patients (28.9% of patients ≥80 years), 15.1% of patients ≤65 years of age were also found to be frail. The proportion of frail patients increased from 19.4% in 2015 to 29.2% in 2019 despite no significant change in age during this period. The proportion of patients who received heart failure specific pharmacotherapy decreased from 86.7% in 2015 to 82.9% in 2019 (p value = 0.03) and frail patients were significantly less likely to be prescribed HF specific pharmacotherapy than non-frail patients (77.4% vs. 85.9%, p < 0.001).

The Impact of Morbid Obesity on the Health Outcomes of Hospital Inpatients: An Observational Study.

Morbid obesity poses a significant burden on the health-care system. This study determined whether morbid obesity leads to worse health-outcomes in hospitalised patients. This retrospective-study examined nutritional data of all inpatients aged 18-79 years, with a body-mass-index (BMI) ≥ 18.5 kg/m2 admitted over a period of 4 years at two major hospitals in Australia. Patients were divided into 3 groups for comparison: normal/overweight (BMI 18.5-29.9 kg/m2), obese (BMI 30-39.9 kg/m2) and morbidly-obese (BMI ≥ 40 kg/m2). Outcome measures included length-of-hospital-stay (LOS), in-hospital mortality, and 30-day readmissions. Multilevel-mixed-effects regression was used to compare clinical outcomes between the groups after adjustment for potential confounders. Of 16,579 patients, 1004 (6.1%) were classified as morbidly-obese. Morbidly-obese patients had a significantly longer median (IQR) LOS than normal/overweight patients (5 (2, 12) vs. 5 (2, 11) days, p value = 0.012) and obese-patients (5 (2, 12) vs. 5 (2, 10) days, p value = 0.036). After adjusted-analysis, morbidly-obese patients had a higher incidence of a longer LOS than normal/overweight patients (IRR 1.04; 95% CI 1.02-1.07; p value < 0.001) and obese-patients (IRR 1.13; 95% CI 1.11-1.16; p value < 0.001). Other clinical outcomes were similar between the different groups. Morbid obesity leads to a longer LOS in hospitalised patients but does not adversely affect other clinical outcomes.

The overlap of frailty and malnutrition in older hospitalised patients: An observational study.

BACKGROUND AND OBJECTIVES: Frailty and malnutrition are geriatric syndromes with common risk-factors. Limited studies have investigated these two conditions simultaneously in hospitalised patients. This study investigated the overlap of frailty and malnutrition in older hospitalised patients. METHODS AND STUDY DESIGN: This prospective study enrolled 263 patients ≥65 years in a tertiary-teaching hospital in Australia. Frailty status was assessed by use of the Edmonton-Frail-Scale (EFS) and malnutrition risk was determined by use of the Malnutrition Universal Screening Tool (MUST). Patients were divided into four categories for comparison: normal, at malnutrition- risk only, frail-only and both frail and at malnutrition risk. Multivariable regression models compared clinical outcomes: length of hospital stay (LOS), in-hospital mortality, health-related quality of life (HRQoL) and 30- day readmissions after adjustment for age, sex, Charlson comorbidity index (CCI) and living-status. RESULTS: The mean (SD) age was 84.1 (6.6) years and 51.2% were females. The prevalence of patients who were at malnutrition- risk only was 14.8%, frailty only 27.8% and 33.5% were both frail and at malnutrition-risk. Frail-only patients were more likely to be older, from a nursing home and with a higher CCI than malnourished only patients. Frail patients had a worse HRQoL (coefficient -0.08, 95% -0.0132--0.031, p=0.002) and were more likely to have a longer LOS (coefficient 5.91, 95% CI 0.77-11.14, p=0.024) than patients at-risk of malnutrition. Other clinical outcomes were similar between the two groups. CONCLUSIONS: There is a substantial overlap of frailty and malnutrition in older hospitalised patients and frailty is associated with worse clinical outcomes than malnutrition.

Prevalence of Hypovitaminosis C and its Relationship with Frailty in Older Hospitalised Patients: A Cross-Sectional Study.

Frailty is common in older hospitalised patients and may be associated with micronutrient malnutrition. Only limited studies have explored the relationship between frailty and vitamin C deficiency. This study investigated the prevalence of vitamin C deficiency and its association with frailty severity in patients ≥75 years admitted under a geriatric unit. Patients (n = 160) with a mean age of 84.4 ± 6.4 years were recruited and underwent frailty assessment by use of the Edmonton Frail Scale (EFS). Patients with an EFS score <10 were classified as non-frail/vulnerable/mildly frail and those with ≥10 as moderate-severely frail. Patients with vitamin C levels between 11-28 µmol/L were classified as vitamin C depleted while those with levels <11 µmol/L were classified as vitamin C deficient. A multivariate logistic regression model determined the relationship between vitamin C deficiency and frailty severity after adjustment for various co-variates. Fifty-seven (35.6%) patients were vitamin C depleted, while 42 (26.3%) had vitamin C deficiency. Vitamin C levels were significantly lower among patients who were moderate-severely frail when compared to those who were non-frail/vulnerable/mildly frail (p < 0.05). After adjusted analysis, vitamin C deficiency was 4.3-fold more likely to be associated with moderate-severe frailty (aOR 4.30, 95% CI 1.33-13.86, p = 0.015). Vitamin C deficiency is common and is associated with a greater severity of frailty in older hospitalised patients.

Nutritional risk assessed by the Malnutrition Universal Screening Tool as a predictor of frailty in acutely hospitalised older patients: An observational study.

BACKGROUND AND OBJECTIVES: Frailty and malnutrition are overlapping geriatric syndromes and leads to poor clinical outcomes in older patients. This study determined whether Malnutrition Universal Screening Tool (MUST) can predict frailty in older hospitalised patients. METHODS AND STUDY DESIGN: This prospective study recruited 243 patients ≥65 years in a tertiary-teaching hospital in Australia. Frailty assessment was performed by use of the Edmonton-Frail-Scale (EFS), while malnutrition-risk was determined by use of the MUST. Patients with an EFS score >8 were classified as frail, while patients with a MUST score of 1 as at moderate malnutritionrisk and ≥2 as at high malnutrition-risk. Multivariable logistic regression determined whether malnutrition-risk predicts frailty after adjustment for various co-variates. RESULTS: The mean (SD) age was 83.9 (6.5) years) and 126 (51.9%) were females. One-hundred and forty-nine (61.3%) patients were classified as frail, while 66 (27.2%) were found to be at high malnutrition-risk according to the MUST. Frail patients were more likely to be older with a higher Charlson-index and on polypharmacy than non-frail patients. Patients who were at high malnutrition- risk were more likely to be living alone and on vitamin D supplementation than those at low malnutritionrisk. Patients who were at a high malnutrition-risk but not those who were at moderate malnutrition-risk, were more likely to be deemed frail (aOR 2.6, 95% CI 1.2-5.5, p=0.015) when compared to those who were at low malnutrition-risk. CONCLUSIONS: Only patients who were classified as at high malnutrition-risk according to the MUST are more likely to be deemed frail.

Effectiveness of Oseltamivir in reducing 30-day readmissions and mortality among patients with severe seasonal influenza in Australian hospitalized patients.

BACKGROUND: Worldwide, seasonal influenza causes significant mortality and poses a significant economic burden. Oseltamivir is an effective treatment, but benefits beyond immediate hospitalization are unknown. METHODS: This retrospective multicenter study included adult hospitalized influenza patients from two major teaching hospitals in Australia. Patients who received Oseltamivir <48 h of admission (prompt-treatment group) were compared with those who either did not receive treatment or if treatment was delayed by >48 h (delayed/no-treatment group). Propensity-score matching was used to balance confounders between two groups. Primary outcomes included 30-day readmissions, 30-day mortality, composite-outcome (30-day mortality and readmissions), in-hospital mortality, and hospital length of stay (LOS). RESULTS: Between January 2016-March 2020, 1828 adult patients mean (SD) age 66.4 (20.1), 52.9% females, were hospitalized with influenza. Four hundred and forty-eight (24.5%) received prompt-treatment with Oseltamivir, while 1380 (75.5%) patients were in the delayed/no-treatment group. The median (IQR) time from onset of symptoms to the administration of Oseltamivir was three (1-5) days. The propensity-score model included 245 matched patients in each group (standardized mean difference of <10%). Both 30-day readmissions and the composite-outcome were, respectively, 5.7% (P = 0.03) and 6.5% (P = 0.02) lower in patients who received prompt-treatment with Oseltamivir when compared to the delayed/no-treatment group. LOS showed a significant reduction, and in-hospital mortality showed a trend towards improvement among patients who received prompt-treatment when compared to the other group. CONCLUSIONS: Early administration of Oseltamivir was associated with a reduction in 30-days readmissions and composite-outcome of 30-day readmissions and mortality in adult hospitalized influenza patients when compared to delayed/no-treatment.

Prognostic impact of high sensitive troponin in predicting 30-day mortality among patients admitted to hospital with influenza.

BACKGROUND: Worldwide, seasonal influenza causes significant mortality and severe infections may cause cardiac injury. High-sensitive-troponins (hsTnT) are sensitive and specific markers of myocardial damage. This study investigated the prognostic impact of hsTnT on 30-day mortality in hospitalised influenza patients. METHODS: This retrospective study included influenza patients ≥ 18 years, who had hsTnT performed during admission in two tertiary-hospitals in South Australia. Diagnosis of influenza was confirmed by polymerase-chain-reaction (PCR) test and hsTnT > 14 ng/L with a change of > 20% during admission was considered to be indicative of acute-cardiac injury. Clinical characteristics, complications and 30-day mortality were compared among four groups of patients: hsTnT unavailable, hsTnT negative, chronically elevated hsTnT and acutely elevated hsTnT. Cox-proportional hazard regression determined the hazard of death at 30-days following hospital discharge after adjustment for co-variates. RESULTS: Between January 2016 -March 2020, 1828 influenza patients, mean age 66.4 years, were hospitalised. Troponin results were available for 617 (47.7%) patients, of whom, 62 (10%) had acute myocardial injury and 232 (37.6%) had chronic hsTnT elevation. Both inpatient and 30-day mortality were significantly higher among patients with acute (P < 0.001) and chronic hsTnT (P < 0.001) when compared to other groups. When compared to patients with negative hsTnT, acute but not chronic hsTnT elevation was significantly associated with 30-day mortality after adjustment for various co-variates (HR 8.30, 1.80-17.84, P value = 0.013). CONCLUSIONS: This is the largest available analysis of cardiac-specific biomarker hsTnT in patients with influenza. An acutely elevated hsTnT was associated with 30-day mortality among hospitalised influenza patients.

Clinical characteristics and outcomes of influenza A and B virus infection in adult Australian hospitalised patients.

BACKGROUND: Influenza B is often perceived as a less severe strain of influenza. The epidemiology and clinical outcomes of influenza B have been less thoroughly investigated in hospitalised patients. The aims of this study were to describe clinical differences and outcomes between influenza A and B patients admitted over a period of 4 years. METHODS: We retrospectively collected data of all laboratory confirmed influenza patients ≥18 years at two tertiary hospitals in South Australia. Patients were confirmed as influenza positive if they had a positive polymerase-chain-reaction (PCR) test of a respiratory specimen. Complications during hospitalisation along with inpatient mortality were compared between influenza A and B. In addition, 30 day mortality and readmissions were compared. Logistic regression model compared outcomes after adjustment for age, Charlson index, sex and creatinine levels. RESULTS: Between January 2016-March 2020, 1846 patients, mean age 66.5 years, were hospitalised for influenza. Of whom, 1630 (88.3%) had influenza A and 216 (11.7%) influenza B. Influenza B patients were significantly younger than influenza A. Influenza A patients were more likely be smokers with a history of chronic obstructive pulmonary disease (COPD) and ischaemic heart disease (IHD) than influenza B. Complications, including pneumonia and acute coronary syndrome (ACS) were similar between two groups, however, septic shock was more common in patients with influenza B. Adjusted analyses showed similar median length of hospital stay (LOS), in hospital mortality, 30-day mortality and readmissions between the two groups. CONCLUSIONS: Influenza B is less prevalent and occurs mostly in younger hospitalised patients than influenza A. Both strains contribute equally to hospitalisation burden and complications. TRIAL REGISTRATION: Australia and New Zealand Clinical Trial Registry (ANZCR) no ACTRN12618000451202 date of registration 28/03/2018.

Characteristics and clinical outcomes of index versus non-index hospital readmissions in Australian hospitals: a cohort study.

Objective Risk factors and clinical outcomes of non-index hospital readmissions (readmissions to a hospital different from the previous admission) have not been studied in Australia. The present study compared characteristics and clinical outcomes between index and non-index hospital readmissions in the Australian healthcare setting. Methods This retrospective cohort study included medical admissions from 2012 to 2016 across all major public hospitals in South Australia. Readmissions within 30 day to all public hospitals were captured using electronic health information system. In-hospital mortality and readmission length of hospital stay (LOS) were compared, along with 30-day mortality and subsequent readmissions among patients readmitted to index or non-index hospitals. Results Of 114105 index admissions, there were 20539 (18.0%) readmissions. Of these, 17519 (85.3%) were index readmissions and 3020 (14.7%) were non-index readmissions. Compared with index readmissions, patients in the non-index readmissions group had a lower Charlson comorbidity index, shorter LOS and fewer complications during the index admission and were more likely to be readmitted with a different diagnosis to the index admission. No difference in in-hospital mortality was observed, but readmission LOS was shorter and 30-day mortality was higher among patients with non-index readmissions. Conclusion A substantial proportion of patients experienced non-index hospital readmissions. Non-index hospital readmitted patients had no immediate adverse outcomes, but experienced worse 30-day outcomes. What is known about the topic? A significant proportion of unplanned hospital readmissions occur to non-index hospitals. North American studies suggest that non-index hospital readmissions are associated with worse outcomes for patients due to discontinuity of care, medical reconciliation and delayed treatment. Limited studies have determined factors associated with non-index hospital readmissions in Australia, but whether such readmissions lead to adverse clinical outcomes is unknown. What does this paper add? In the Australian healthcare setting, 14.7% of patients were readmitted to non-index hospitals. Compared with index hospital readmissions, patients admitted to non-index hospitals had a lower Charlson comorbidity index, a shorter index LOS and fewer complications during the index admission. At the time of readmission there was no differences in discharge summary completion rates between the two groups. Unlike other studies, the present study found no immediate adverse outcomes for patients readmitted to non-index hospitals, but 30-day outcomes were worse than for patients who had an index hospital readmission. What are the implications for practitioners? Non-index hospital readmissions may not be totally preventable due to factors such as ambulance diversions stemming from emergency department overcrowding and prolonged emergency department waiting times. Patients should be advised to re-present to hospital in case they experience recurrence or relapse of a medical condition, and preferably should be readmitted to the same hospital to prevent discontinuity of care.