The impact of the COVID-19 pandemic on 397 631 elective dental admissions among the under-25s in England: a retrospective study.

BACKGROUND: COVID-19 caused widespread disruptions to health services worldwide, including reductions in elective surgery. Tooth extractions are among the most common reasons for elective surgery among children and young people (CYP). It is unclear how COVID-19 affected elective dental surgeries in hospitals over multiple pandemic waves at a national level. METHODS: Elective dental tooth extraction admissions were selected using Hospital Episode Statistics. Admission trends for the first 14 pandemic months were compared with the previous five years and results were stratified by age (under-11s, 11-16s, 17-24s). RESULTS: The most socioeconomically deprived CYP comprised the largest proportion of elective dental tooth extraction admissions. In April 2020, admissions dropped by >95%. In absolute terms, the biggest reduction was in April (11-16s: -1339 admissions, 95% CI -1411 to -1267; 17-24s: -1600, -1678 to -1521) and May 2020 (under-11s: -2857, -2962 to -2752). Admissions differed by socioeconomic deprivation for the under-11s (P < 0.0001), driven by fewer admissions than expected by the most deprived and more by the most affluent during the pandemic. CONCLUSION: Elective tooth extractions dropped most in April 2020, remaining below pre-pandemic levels throughout the study. Despite being the most likely to be admitted, the most deprived under-11s had the largest reductions in admissions relative to other groups.

Impact of the COVID-19 pandemic on the clinical management trends for acute appendicitis among the under-25s: a retrospective study.

OBJECTIVE: To describe the COVID-19 pandemic's impact on acute appendicitis management on children and young people (CYP). DESIGN: Retrospective cohort study. SETTING: All English National Health Service hospitals. PATIENTS: Acute appendicitis admissions (all, simple, complex) by CYP (under-5s, 5-9s, 10-24s). EXPOSURE: Study pandemic period: February 2020-March 2021. Comparator pre-pandemic period: February 2015-January 2020. MAIN OUTCOME MEASURES: Monthly appendicectomy and laparoscopic appendicectomy rate trends and absolute differences between pandemic month and the pre-pandemic average. Proportions of appendicitis admissions comprising complex appendicitis by hospital with or without specialist paediatric centres were compared. RESULTS: 101 462 acute appendicitis admissions were analysed. Appendicectomy rates fell most in April 2020 for the 5-9s (-18.4% (95% CI -26.8% to -10.0%)) and 10-24s (-28.4% (-38.9% to -18.0%)), driven by reductions in appendicectomies for simple appendicitis. This was equivalent to -54 procedures (-68.4 to -39.6) and -512 (-555.9 to -467.3) for the 5-9s and 10-24s, respectively. Laparoscopic appendicectomies fell in April 2020 for the 5-9s (-15.5% (-23.2% to -7.8%)) and 10-24s (-44.8% (-57.9% to -31.6%) across all types, which was equivalent to -43 (-56.1 to 30.3) and -643 (-692.5 to -593.1) procedures for the 5-9s and 10-24s, respectively. A larger proportion of complex appendicitis admissions were treated within trusts with specialist paediatric centres during the pandemic. CONCLUSIONS: For CYP across English hospitals, a sharp recovery followed a steep reduction in appendicectomy rates in April 2020, due to concerns with COVID-19 transmission. This builds on smaller-sized studies reporting the immediate short-term impacts.

Risk prediction of mortality for patients with heart failure in England: observational study in primary care.

AIMS: Many risk prediction models have been proposed for heart failure (HF), but few studies have used only information available to general practitioners (GPs) in primary care electronic health records (EHRs). We describe the predictors and performance of models built from GP-based EHRs in two cohorts of patients 10 years apart. METHODS AND RESULTS: Linked primary and secondary care data for incident HF cases in England were extracted from the Clinical Practice Research Datalink for 2001-02 and 2011-12. Time-to-event models for all-cause mortality were developed using a long list of potential baseline predictors. Discrimination and calibration were calculated. A total of 5966 patients in 156 general practices were diagnosed in 2001-02, and 12 827 patients in 331 practices were diagnosed in 2011-12. The 5-year survival rate was 40.0% in 2001-02 and 40.2% in 2011-12, though the latter population were older, frailer, and more comorbid; for 2001-02, the 10-year survival was 20.8% and 15-year survival 11.1%. Consistent predictors included age, male sex, systolic blood pressure, body mass index, GP domiciliary visits before diagnosis, and some comorbidities. Model performance for both time windows was modest (c = 0.70), but calibration was generally excellent in both time periods. CONCLUSIONS: Information routinely available to UK GPs at the time of diagnosis of HF gives only modest predictive accuracy of all-cause mortality, making it hard to decide on the type, place, and urgency of follow-up. More consistent recording of data relevant to HF (such as echocardiography and natriuretic peptide results) in GP EHRs is needed to support accurate prediction of healthcare needs in individuals with HF.

Factors associated with, and variations in, COVID-19 hospital death rates in England's first two waves: observational study.

OBJECTIVES: To assess patient-level and hospital-level predictors of death and variation in death rates following admission for COVID-19 in England's first two waves after accounting for random variation. To quantify the correlation between hospitals' first and second wave death rates. DESIGN: Observational study using administrative data. SETTING: Acute non-specialist hospitals in England. PARTICIPANTS: All patients admitted with a primary diagnosis of COVID-19. PRIMARY AND SECONDARY OUTCOMES: In-hospital death. RESULTS: Hospital Episode Statistics (HES) data were extracted for all acute hospitals in England for COVID-19 admissions from March 2020 to March 2021. In wave 1 (March to July 2020), there were 74 484 admissions and 21 883 deaths (crude rate 29.4%); in wave 2 (August 2020 to March 2021), there were 165 642 admissions and 36 040 deaths (21.8%). Wave 2 patients were younger, with more hypertension and obesity but lower rates of other comorbidities. Mortality improved for all ages; in wave 2, it peaked in December 2020 at 24.2% (lower than wave 1's peak) but halved by March 2021. In multiple multilevel modelling combining HES with hospital-level data from Situational Reports, wave 2 and wave 1 variables significantly associated with death were mostly the same. The median odds ratio for wave 1 was just 1.05 and for wave 2 was 1.07. At 99.8% control limits, 3% of hospitals were high and 7% were low funnel plot outliers in wave 1; these figures were 9% and 12% for wave 2. Four hospitals were (low) outliers in both waves. The correlation between hospitals' adjusted mortality rates between waves was 0.45 (p<0.0001). Length of stay was similar in each wave. CONCLUSIONS: England's first two COVID-19 waves were similar regarding predictors and moderate interhospital variation. Despite the challenges, variation in death rates and length of stay between hospitals was modest and might be accounted for by unobserved patient factors.

Patient-level and hospital-level variation and related time trends in COVID-19 case fatality rates during the first pandemic wave in England: multilevel modelling analysis of routine data.

BACKGROUND: A report suggesting large between-hospital variations in mortality after admission for COVID-19 in England attracted much media attention but used crude rates. We aimed to quantify these variations between hospitals and over time during England's first wave (March to July 2020) and assess available patient-level and hospital-level predictors to explain those variations. METHODS: We used administrative data for England, augmented by hospital-level information. Admissions were extracted with COVID-19 codes. In-hospital death was the primary outcome. Risk-adjusted mortality ratios (standardised mortality ratios) and interhospital variation were calculated using multilevel logistic regression. Early-wave (March to April) and late-wave (May to July) periods were compared. RESULTS: 74 781 admissions had a primary diagnosis of COVID-19, with 21 984 in-hospital deaths (29.4%); the 30-day total mortality rate was 28.8%. The crude in-hospital death rate fell in all ages and overall from 32.9% in March to 13.4% in July. Patient-level predictors included age, male gender, non-white ethnic group (early period only) and several comorbidities (obesity early period only). The only significant hospital-level predictor was daily COVID-19 admissions in the late period; we did not find a relation with staff absences for COVID-19, mechanical ventilation bed occupancies, total bed occupancies or bed occupancies for COVID-19 admissions in either period. Just 4 (3%) and 2 (2%) hospitals were high, and 5 (4%) and 0 hospitals were low funnel plot mortality outliers at 3 SD for early and late periods, respectively, after risk adjustment. We found no strong correlation between early and late hospital-level mortality (r=0.17, p=0.06). CONCLUSIONS: There was modest variation in mortality following admission for COVID-19 between English hospitals after adjustment for risk and random variation, in marked contrast to early media reports. Early-period mortality did not predict late-period mortality.

Changes in heart failure management and long-term mortality over 10 years: observational study.

OBJECTIVES: To estimate the long-term survival of two cohorts of people diagnosed with heart failure 10 years apart and to assess differences in patient characteristics, clinical guideline compliance and survival by diagnosis setting. METHODS: Data for patients aged 18 and over with a new diagnosis of heart failure in the Clinical Practice Research Datalink in 2001-2002 (5966 patients in 156 practices) and 2011-2012 (12 827 patients in 331 practices). Survival rates since diagnosis were described using Kaplan-Meier plots. Compliance with national guidelines was summarised. RESULTS: 2011/2012 patients were older than those diagnosed a decade before, with lower blood pressure and cholesterol but more comorbidity and healthcare contacts. For those diagnosed in 2001/2002, the 5-year survival was 40.0% (40.2% in the 2011/2012 cohort), 10-year survival was 20.8%, and 15-year survival 11.1%. Improvement in survival between the two time periods was seen only in those diagnosed in primary care (5-year survival 46.0% vs 57.4%, compared with 33.9% and 32.6% for hospital-diagnosed patients).Beta-blocker use rose from 24.3% to 39.1%; renin-angiotensin system blockers rose from 31.8% to 54.3% (both p<0.001). There was little change for loop diuretics and none for thiazide diuretics. For the 9963 patients with symptoms recorded by their general practitioner before diagnosis, brain natriuretic peptide (BNP) testing was low, but echocardiogram use rose from 8.3% to 19.3%, and specialist referral rose from 7.2% to 24.6% (all p<0.001). CONCLUSIONS: The 10 years saw some long-term survival gains but only modest improvement in national clinical guideline compliance, from a low baseline, despite the introduction of national initiatives.

Five-year outcomes following left ventricular assist device implantation in England.

OBJECTIVE: Implant rates of mechanical circulatory supports such as left ventricular assist devices (LVAD) have steadily increased in the last decade. We assessed the utility of administrative data to provide information on hospital use and outcomes. METHODS: Using 2 years of national hospital administrative data for England linked to the death register, we identified all patients with an LVAD and extracted hospital activity for 5 years before and after the LVAD implantation date. RESULTS: In the two index years April 2011 to March 2013, 157 patients had an LVAD implanted. The mean age was 50.9 (SD 15.4), and 78.3% were men. After 5 years, 92 (58.6%) had died; the recorded cause of death was noncardiovascular in 67.4%. 42 (26.8%) patients received a heart±lung transplantation. Compared with the 12 months before implantation, the 12 months after but not including the month of implantation saw falls in total inpatient and day case admissions, a fall in admissions for heart failure (HF), a rise in non-HF admissions, a fall in emergency department visits not ending in admission and a rise in outpatient appointments (all per patient at risk). Postimplantation complications were common in the subsequent 5 years: 26.1% had a stroke, 23.6% had a device infection and 13.4% had a new LVAD implanted. CONCLUSIONS: Despite patients' young age, their mortality is high and their hospital use and complications are common in the 5 years following LVAD implantation. Administrative data provide important information on resource use in this patient group.

Five-year survival and use of hospital services following ICD and CRT implantation: comparing real-world data with RCTs.

AIMS: Guidelines recommend the use of an implantable cardioverter-defibrillator (ICD) and/or cardiac resynchronization therapy (CRT) device based on the results of randomized controlled trials (RCTs), typically with selected patients and short follow-up. METHODS AND RESULTS: We describe the 5 year survival rate and use of hospital services following ICD and CRT implantation in England from April 2011 to March 2013 using the national hospital administrative database covering emergency department visits, inpatient admissions, and clinic appointments, linked to the national death register. Five-year survival was 64% after ICD implantation and 58% after CRT implantation, with median survival times of 6.8 and 6.2 years, respectively. Hospital use was high in both device groups, for the 5 years prior and after implantation, peaking around the implantation date. Most hospital activity was not primarily related to heart failure. Healthcare costs were dominated by admissions, but emergency department and clinic activity were both high. Only the CRT group saw total per-patient costs fall after the index month (implantation), driven by a slight fall in the heart failure admission rate. Patients were typically older than in the trials, but with similar co-morbidity except for substantially more atrial fibrillation and less dementia. Survival and device complications were similar to the RCTs. CONCLUSIONS: Clinical and cost-effectiveness assessments of ICD and CRT implantation are supported by real-world data, although the prevalence of atrial fibrillation remains substantially higher than in the RCTs.