Dataset Information

Survival and new-onset morbidity after critical care admission for acute pancreatitis in Scotland: a national electronic healthcare record linkage cohort study.

ABSTRACT:

Introduction

Severe acute pancreatitis (AP) requiring critical care admission (ccAP) impacts negatively on long-term survival.

Objective

To document organ-specific new morbidity and identify risk factors associated with premature mortality after an episode of ccAP.

Design

Cohort study.

Setting

Electronic healthcare registries in Scotland.

Participants

The ccAP cohort included 1471 patients admitted to critical care with AP between 1 January 2008 and 31 December 2010 followed up until 31 December 2014. The population cohort included 3450 individuals from the general population of Scotland frequency-matched for age, sex and social deprivation.

Methods

Record linkage of routinely collected electronic health data with population matching.

Primary and secondary outcome measures

Patient demographics, comorbidity (Charlson Comorbidity Index), acute physiology, organ support and other critical care data were linked to records of mortality (death certificate data) and new-onset morbidity. Kaplan-Meier and Cox regression analyses were used to identify risk factors associated with mortality.

Results

310 patients with AP died during the index admission. Outcomes were not ascertained for five patients, and the deprivation quintile was not known for six patients. 340 of 1150 patients in the resulting postdischarge ccAP cohort died during the follow-up period. Greater comorbidity measured by the Charlson score, prior to ccAP, negatively influenced survival in the hospital and after discharge. The odds of developing new-onset diabetes mellitus after ccAP compared with the general population were 10.70 (95% CI 5.74 to 19.94). A new diagnosis of myocardial infarction, stroke, heart failure, liver disease, peptic ulcer, renal failure, cancer, peripheral vascular disease and lung disease was more frequent in the ccAP cohort than in the general population.

Conclusions

The persistent deleterious impact of severe AP on long-term outcome and survival is multifactorial in origin, influenced by pre-existing patient characteristics and acute episode features. Further mechanistic and epidemiological investigation is warranted.

SUBMITTER: Ventre C

PROVIDER: S-EPMC6303604 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Survival and new-onset morbidity after critical care admission for acute pancreatitis in Scotland: a national electronic healthcare record linkage cohort study.

Ventre Chiara C Nowell Sian S Graham Catriona C Kidd Doug D Skouras Christos C Mole Damian J DJ

BMJ open 20181214 12

<h4>Introduction</h4>Severe acute pancreatitis (AP) requiring critical care admission (ccAP) impacts negatively on long-term survival.<h4>Objective</h4>To document organ-specific new morbidity and identify risk factors associated with premature mortality after an episode of ccAP.<h4>Design</h4>Cohort study.<h4>Setting</h4>Electronic healthcare registries in Scotland.<h4>Participants</h4>The ccAP cohort included 1471 patients admitted to critical care with AP between 1 January 2008 and 31 Decembe ...[more]

PMID: 30552270

Similar Datasets

Project description:BackgroundMultimorbidity is common in women across the life course. Preterm birth is the single biggest cause of neonatal mortality and morbidity. We aim to estimate the prevalence of multimorbidity in pregnant women and to examine the association between maternal multimorbidity and PTB.MethodsThis is a retrospective cohort study using electronic health records from the Scottish Morbidity Records. All pregnancies among women aged 15 to 49 with a conception date between 1 January 2014 and 31 December 2018 were included. Multimorbidity was defined as the presence of two or more pre-existing long-term physical or mental health conditions, and complex multimorbidity as the presence of four or more. It was calculated at the time of conception using a predefined list of 79 conditions published by the MuM-PreDiCT consortium. PTB was defined as babies born alive between 24 and less than 37 completed weeks of gestation. We used Generalised Estimating Equations adjusted for maternal age, socioeconomic status, number of previous pregnancies, BMI, and smoking history to estimate the effect of maternal pre-existing multimorbidity. Absolut rates are reported in the results and tables, whilst Odds Ratios (ORs) are adjusted (aOR).ResultsThirty thousand five hundred fifty-seven singleton births from 27,711 pregnant women were included in the analysis. The prevalence of pre-existing multimorbidity and complex multimorbidity was 16.8% (95% CI: 16.4-17.2) and 3.6% (95% CI: 3.3-3.8), respectively. The prevalence of multimorbidity in the youngest age group was 10.2%(95% CI: 8.8-11.6), while in those 40 to 44, it was 21.4% (95% CI: 18.4-24.4), and in the 45 to 49 age group, it was 20% (95% CI: 8.9-31.1). In women without multimorbidity, the prevalence of PTB was 6.7%; it was 11.6% in women with multimorbidity and 15.6% in women with complex multimorbidity. After adjusting for maternal age, socioeconomic status, number of previous pregnancies, Body Mass Index (BMI), and smoking, multimorbidity was associated with higher odds of PTB (aOR = 1.64, 95% CI: 1.48-1.82).ConclusionsMultimorbidity at the time of conception was present in one in six women and was associated with an increased risk of preterm birth. Multimorbidity presents a significant health burden to women and their offspring. Routine and comprehensive evaluation of women with multimorbidity before and during pregnancy is urgently needed.

Project description:BackgroundCOVID-19 has overwhelmed health services across the world; its global death toll has exceeded 5.3 million and continues to grow. There have been almost 15 million cases of COVID-19 in the UK. The need for rapid accurate identification, appropriate clinical care and decision making, remains a priority for UK ambulance service. To support identification and conveyance decisions of patients presenting with COVID-19 symptoms the Scottish Ambulance Service introduced the revised Medical Priority Dispatch System Protocol 36, enhanced physician led decision support and prehospital clinical guidelines. This study aimed to characterise the impact of these changes on the pathways and outcomes of people attended by the SAS) with potential COVID-19.MethodsA retrospective record linkage cohort study using National Data collected from NHS Scotland over a 5 month period (April-August 2020).ResultsThe SAS responded to 214,082 emergency calls during the study time period. The positive predictive value of the Protocol 36 to identify potentially COVID-19 positive patients was low (17%). Approximately 60% of those identified by Protocol 36 as potentially COVID-19 positive were conveyed. The relationship between conveyance and mortality differed between Protocol 36 Covid-19 positive calls and those that were not. In those identified by Protocol 36 as Covid-19 negative, 30 day mortality was higher in those not conveyed (not conveyed 9.2%; conveyed 6.6%) but in the Protocol 36 Covid-19 positive calls, mortality was higher in those conveyed (not conveyed 4.3% conveyed 8.8%). Thirty-day mortality rates of those with COVID-19 diagnosed through virology was between 28.8 and 30.2%.ConclusionThe low positive predictive value (17%) of Protocol 36 in identifying potential COVID-19 in patients emphasises the importance of ambulance clinicians approaching each call as involving COVID-19, reinforcing the importance of adhering to existing policy and continued use of PPE at all calls. The non-conveyance rate of people that were categorised as COVID-19 negative was higher than in the preceding year in the same service. The reasons for the higher rates of non-conveyance and the relationship between non conveyance rates and death at 3 and 30 days post index call are unknown and would benefit from further study.

Project description:BackgroundLooked after children are defined as children who are in the care of their local authority. Previous studies have reported that looked after children have poorer mental and physical health, increased behavioural problems, and increased self-harm and mortality compared to peers. They also experience poorer educational outcomes, yet population-wide research into the latter is lacking, particularly in the United Kingdom. Education and health share a bidirectional relationship; therefore, it is important to dually investigate both outcomes. Our study aimed to compare educational and health outcomes for looked after children with peers, adjusting for sociodemographic, maternity, and comorbidity confounders.Methods and findingsLinkage of 9 Scotland-wide databases, covering dispensed prescriptions, hospital admissions, maternity records, death certificates, annual pupil census, examinations, school absences/exclusions, unemployment, and looked after children provided retrospective data on 715,111 children attending Scottish schools between 2009 and 2012 (13,898 [1.9%] looked after). Compared to peers, 13,898 (1.9%) looked after children were more likely to be absent (adjusted incidence rate ratio [AIRR] 1.27, 95% confidence interval [CI] 1.24 to 1.30) and excluded (AIRR 4.09, 95% CI 3.86 to 4.33) from school, have special educational need (SEN; adjusted odds ratio [AOR] 3.48, 95% CI 3.35 to 3.62) and neurodevelopmental multimorbidity (AOR 2.45, 95% CI 2.34 to 2.57), achieve the lowest level of academic attainment (AOR 5.92, 95% CI 5.17 to 6.78), and be unemployed after leaving school (AOR 2.12, 95% CI 1.96 to 2.29). They were more likely to require treatment for epilepsy (AOR 1.50, 95% CI 1.27 to 1.78), attention deficit hyperactivity disorder (ADHD; AOR 3.01, 95% CI 2.76 to 3.27), and depression (AOR 1.90, 95% CI 1.62 to 2.22), be hospitalised overall (adjusted hazard ratio [AHR] 1.23, 95% CI 1.19 to 1.28) for injury (AHR 1.80, 95% CI 1.69 to 1.91) and self-harm (AHR 5.19, 95% CI 4.66 to 5.78), and die prematurely (AHR 3.21, 95% CI 2.16 to 4.77). Compared to children looked after at home, children looked after away from home had less absenteeism (AIRR 0.35, 95% CI 0.33 to 0.36), less exclusion (AIRR 0.63, 95% CI 0.56 to 0.71), less unemployment (AOR 0.53, 95% CI 0.46 to 0.62), and better attainment (AIRR 0.31, 95% CI 0.23 to 0.40). Therefore, among those in care, being cared for away from home appeared to be a protective factor resulting in better educational outcomes. The main limitations of this study were lack of data on local authority care preschool or before 2009, total time spent in care, and age of first contact with social care.ConclusionsLooked after children had poorer health and educational outcomes than peers independent of increased neurodevelopmental conditions and SEN. Further work is required to understand whether poorer outcomes relate to reasons for entering care, including maltreatment and adverse childhood events, neurodevelopmental vulnerabilities, or characteristics of the care system.

Project description:BackgroundRecently, studies have examined the underlying patient and practice factors for missed appointments, but less is known about the impact on patient health. People with one or more long-term conditions who fail to attend appointments may be at risk of premature death. This is the first study to examine the effect of missed primary healthcare appointments on all-cause mortality in those with long-term mental and physical health conditions.MethodsWe used a large, nationwide retrospective cohort (n = 824,374) extracted from routinely collected general practice data across Scotland over a 3-year period from September 2013 until September 2016. This data encompasses appointment history for approximately 15% of the Scottish population, and was linked to Scottish deaths records for patients who had died within a 16-month follow-up period. We generated appointment attendance history, number of long-term conditions and prescriptions data for patients. These factors were used in negative binomial and Cox's proportional hazards modelling to examine the risk of missing appointments and all-cause mortality.ResultsPatients with a greater number of long-term conditions had an increased risk of missing general practice appointments despite controlling for number of appointments made, particularly among patients with mental health conditions. These patients were at significantly greater risk of all-cause mortality, and showed a dose-based response with increasing number of missed appointments. Patients with long-term mental health conditions who missed more than two appointments per year had a greater than 8-fold increase in risk of all-cause mortality compared with those who missed no appointments. These patients died prematurely, commonly from non-natural external factors such as suicide.ConclusionsMissed appointments represent a significant risk marker for all-cause mortality, particularly in patients with mental health conditions. For these patients, existing primary healthcare appointment systems are ineffective. Future interventions should be developed with a particular focus on increasing attendance by these patients.

Project description:BackgroundLinkage of electronic healthcare records is becoming increasingly important for research purposes. However, linkage error due to mis-recorded or missing identifiers can lead to biased results. We evaluated the impact of linkage error on estimated infection rates using two different methods for classifying links: highest-weight (HW) classification using probabilistic match weights and prior-informed imputation (PII) using match probabilities.MethodsA gold-standard dataset was created through deterministic linkage of unique identifiers in admission data from two hospitals and infection data recorded at the hospital laboratories (original data). Unique identifiers were then removed and data were re-linked by date of birth, sex and Soundex using two classification methods: i) HW classification - accepting the candidate record with the highest weight exceeding a threshold and ii) PII-imputing values from a match probability distribution. To evaluate methods for linking data with different error rates, non-random error and different match rates, we generated simulation data. Each set of simulated files was linked using both classification methods. Infection rates in the linked data were compared with those in the gold-standard data.ResultsIn the original gold-standard data, 1496/20924 admissions linked to an infection. In the linked original data, PII provided least biased results: 1481 and 1457 infections (upper/lower thresholds) compared with 1316 and 1287 (HW upper/lower thresholds). In the simulated data, substantial bias (up to 112%) was introduced when linkage error varied by hospital. Bias was also greater when the match rate was low or the identifier error rate was high and in these cases, PII performed better than HW classification at reducing bias due to false-matches.ConclusionsThis study highlights the importance of evaluating the potential impact of linkage error on results. PII can help incorporate linkage uncertainty into analysis and reduce bias due to linkage error, without requiring identifiers.

Dataset Information

Survival and new-onset morbidity after critical care admission for acute pancreatitis in Scotland: a national electronic healthcare record linkage cohort study.

Introduction

Objective

Design

Setting

Participants

Methods

Primary and secondary outcome measures

Results

Conclusions

Publications

Survival and new-onset morbidity after critical care admission for acute pancreatitis in Scotland: a national electronic healthcare record linkage cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets