The Hospital Frailty Risk Score and outcomes in head and neck cancer surgery.

OBJECTIVE: This study aimed to assess if the Hospital Frailty Risk Score (HFRS) could predict outcomes for older people undergoing head and neck procedures. DESIGN: A retrospective cohort study of patients admitted between April 2008 and February 2020, undergoing head and neck procedures defined as major resections using procedural codes. SETTING: The analysis was performed using data from the NHS Secondary Uses Service (SUS) electronic database. PARTICIPANTS: A number of 7479 patients were selected based on an age of 75 years and above and an admission associated with a diagnostic code associated with a head and neck cancer. Based on HFRS, 5153 patients were risk-stratified into mild, moderate, and severe frailty risk. MAIN OUTCOME MEASURES: The relationships between frailty risk and length of stay, readmission rate, and mortality were quantified using descriptive statistics. RESULTS: Severely frail patients had a median length of stay of 9 days compared to 3 for mildly frail patients. Twenty-seven percentage of severely frail patients were readmitted within 30 days of surgery. Rising levels of frailty correlate with a higher risk of death following surgery which is maintained in longer term mortality at 1 year and until the data were extracted in March 2022. Fifty percentage of moderately frail patients and 66% of severely frail patients had died in hospital by the end of the study period. CONCLUSION: The results quantify the relationship between frailty and adverse health outcomes. This information could be used to identify those that might benefit from holistic assessment, aid prognostication, commissioning, and service planning.

The Hospital Frailty Risk Score-outcomes in specialised services.

BACKGROUND: Frailty is increasingly used to risk stratify older people, but across specialised services there is no standardised approach. The aim of this study was to assess if the Hospital Frailty Risk Score (HFRS) could describe outcomes for older people within English specialised services. DESIGN: A retrospective cohort study was performed using the Secondary Uses Service (SUS) electronic database for people aged 75 or older admitted between April 2017 and March 2018. METHODS: Based on HFRS, the populations were risk stratified into mild, moderate and severe frailty risk. The relationships with length of stay, readmission rate, mortality and some selected condition specific treatment complications were quantified using descriptive statistics. RESULTS: Very few individuals (<2%) could not be risk stratified for frailty risk. Frailty was differentially distributed across the specialties; around one-third had mild frailty; another third had moderate frailty and one-quarter severe frailty. Increasing frailty risk was associated with increased length of stay for the index admission, more days in hospital in the year following intervention and increased risk of dying in hospital. Severe frailty was a powerful discriminator of the risk of death; between 25 and 40% of those with severe frailty risk died at 30 months across all specialties. CONCLUSIONS: This study demonstrates the first application of the HFRS to a national dataset to describe service outcomes and mortality for older people undergoing a range of specialised interventions. This information could be used to identify those that might benefit from holistic assessment, aid prognostication, commissioning and service planning.

Identification of patients undergoing chronic kidney replacement therapy in primary and secondary care data: validation study based on OpenSAFELY and UK Renal Registry.

Objective: To validate primary and secondary care codes in electronic health records to identify people receiving chronic kidney replacement therapy based on gold standard registry data. Design: Validation study using data from OpenSAFELY and the UK Renal Registry, with the approval of NHS England. Setting: Primary and secondary care electronic health records from people registered at 45% of general practices in England on 1 January 2020, linked to data from the UK Renal Registry (UKRR) within the OpenSAFELY-TPP platform, part of the NHS England OpenSAFELY covid-19 service. Participants: 38 745 prevalent patients (recorded as receiving kidney replacement therapy on 1 January 2020 in UKRR data, or primary or secondary care data) and 10 730 incident patients (starting kidney replacement therapy during 2020), from a population of 19 million people alive and registered with a general practice in England on 1 January 2020. Main outcome measures: Sensitivity and positive predictive values of primary and secondary care code lists for identifying prevalent and incident kidney replacement therapy cohorts compared with the gold standard UKRR data on chronic kidney replacement therapy. Agreement across the data sources overall, and by treatment modality (transplantation or dialysis) and personal characteristics. Results: Primary and secondary care code lists were sensitive for identifying the UKRR prevalent cohort (91.2% (95% confidence interval (CI) 90.8% to 91.6%) and 92.0% (91.6% to 92.4%), respectively), but not the incident cohort (52.3% (50.3% to 54.3%) and 67.9% (66.1% to 69.7%)). Positive predictive values were low (77.7% (77.2% to 78.2%) for primary care data and 64.7% (64.1% to 65.3%) for secondary care data), particularly for chronic dialysis (53.7% (52.9% to 54.5%) for primary care data and 49.1% (48.0% to 50.2%) for secondary care data). Sensitivity decreased with age and index of multiple deprivation in primary care data, but the opposite was true in secondary care data. Agreement was lower in children, with 30% (295/980) featuring in all three datasets. Half (1165/2315) of the incident patients receiving dialysis in UKRR data had a kidney replacement therapy code in the primary care data within three months of the start date of the kidney replacement therapy. No codes existed whose exclusion would substantially improve the positive predictive value without a decrease in sensitivity. Conclusions: Codes used in primary and secondary care data failed to identify a small proportion of prevalent patients receiving kidney replacement therapy. Codes also identified many patients who were not recipients of chronic kidney replacement therapy in UKRR data, particularly dialysis codes. Linkage with UKRR kidney replacement therapy data facilitated more accurate identification of incident and prevalent kidney replacement therapy cohorts for research into this vulnerable population. Poor coding has implications for any patient care (including eligibility for vaccination, resourcing, and health policy responses in future pandemics) that relies on accurate reporting of kidney replacement therapy in primary and secondary care data.

The risk of colorectal cancer in individuals with mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene: An English population-based study.

BACKGROUND: Studies have demonstrated a higher risk of developing colorectal cancer (CRC) in individuals with Cystic Fibrosis (CF), and also a potentially increased risk in carriers of cystic fibrosis transmembrane conductance regulator (CFTR) mutations. Life expectancy for those with CF is rising, increasing the number at risk of developing CRC. METHODS: The incidence of CRC amongst individuals with CF was calculated using data from CORECT-R and linked UK CF Registry and Secondary User Services (SUS) data. Crude, age-specific and age-standardised rates were compared to those without CF. The presence of CFTR mutations in individuals with CRC was assessed using 100,000 Genomes Project data. FINDINGS: The crude incidence rate of CRC in the CF population was 0.29 per 1,000 person-years (28 cases). The CF population were significantly younger than those without (median age at CRC diagnosis 52 years versus 73 years; p<0·01). When age-adjusted, there was a 5-fold increased CRC incidence amongst individuals with CF compared to those without (SIR 5.0 95%CI 3.2-6.9). When compared to other population studies the overall prevalence of CFTR mutations in the CRC population was significantly higher than expected (p<0·01). INTERPRETATION: CF is linked to an increased risk of CRC. The incidence of CFTR mutations in the CRC population is higher than would be expected, suggesting an association between CFTR function and CRC risk. Further research is needed to develop effective screening strategies for these populations. FUNDING: Cancer Research UK (grants C23434/A23706 & C10674/A27140).

The association between frailty risk and COVID-19-associated all-mortality in hospitalised older people: a national cohort study.

INTRODUCTION: Frailty has emerged as an important construct to support clinical decision-making during the COVID-19 pandemic. However, doubts remain related to methodological limitations of published studies. METHODS: Retrospective cohort study of all people aged 75 + admitted to hospital in England between 1 March 2020 and 31 July 2021. COVID-19 and frailty risk were captured using International Classification of Disease-10 (ICD-10) diagnostic codes. We used the generalised gamma model to estimate accelerated failure time, reporting unadjusted and adjusted results. RESULTS: The cohort comprised 103,561 individuals, mean age 84.1, around half female, 82% were White British with a median of two comorbidities. Frailty risk was distributed approximately 20% low risk and 40% each at intermediate or high risk. In the unadjusted survival plots, 28-day mortality was almost 50% for those with an ICD-10 code of U071 (COVID-19 virus identified), and 25-35% for those with U072 (COVID-19 virus not identified). In the adjusted analysis, the accelerated failure time estimates for those with intermediate and high frailty risk were 0.63 (95% CI 0.58-0.68) and 0.67 (95% CI 0.62-0.72) fewer days alive respectively compared to those with low frailty risk with an ICD-10 diagnosis of U072 (reference category). CONCLUSION: In older people with confirmed COVID-19, both intermediate and high frailty risk were associated with reduced survival compared to those with low frailty risk.