Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

BACKGROUND

Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications.

METHODS

We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC).

FINDINGS

In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]).

INTERPRETATION

In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required.

FUNDING

British Journal of Surgery Society.

Impact of cardiac rehabilitation on 3 year outcomes amongst patients after acute coronary syndrome: (ACS) SNAPSHOT ACS follow-up study

Background

Cardiovascular disease is the leading cause of disease burden globally. With advancements in medical and surgical care more people are surviving initial acute coronary syndrome (ACS) and are in need of secondary prevention and cardiac rehabilitation (CR). Increasing availability of high quality individual-level data linkage provides robust estimates of outcomes long-term.

Purpose

To compare 3 year outcomes amongst ACS survivors who did and did not participate in Australian CR programs.

Methods

SNAPSHOT ACS follow-up study included 1806 patients admitted to 232 hospitals who were followed-up by data linkage (cross-jurisdictional morbidity, national death index, Pharmaceutical Benefit Schedule) at 6 and 36 months to compare those who did/not attend CR.

Results

In total, the cohort had a mean age of 65.8 (13.4) years, 60% were male, only 25% (461/1806) attended CR. During index admission, attendees were more likely to have had PCI (39% v 14%, p<0.001), CABG (11% v 2%, p<0.001) and a diagnosis of STEMI (21% v 5%, p<0.001) than those who did not attend. However, there was no significant difference between CR attendees/non-attendees for risk factors (LDL-cholesterol, smoking, obesity). Only 19% of eligible women attended CR compared to 30% of men (p<0.001). At 36 months, there were fewer deaths amongst CR attendees (19/461, 4.1%) than non-attendees (116/1345, 8.6%) (p=0.001). CR attendees were more likely to have repeat ACS, PCI, CABG at both 6 and 36 months (Table). At 36 months, CR attendees were more likely to have been prescribed antiplatelets (78% v 53%, p<0.001), statins (91% 73%, p<0.001), beta-blockers (11% v 13%, p=0.002) and ACEI/ARBs (72% v 61%, p<0.001) than non-attendees.

Conclusions

Amongst Australian ACS survivors, participation in CR was associated with less likelihood of death and increased prescription of pharmacotherapy. However, attendance at CR was associated with higher rates of repeat ACS and revascularisation.

Funding Acknowledgement

Type of funding source: Foundation. Main funding source(s): New South Wales Cardiovascular Research Network, National Heart Foundation

The impact of socioeconomic status on secondary prevention of the acute coronary syndrome

Background

Although socioeconomic status (SES) has been reported to be associated with health inequities, there are limited studies exploring the association between SES and secondary prevention of acute coronary syndrome (ACS) in countries with universal health cover.

Purpose

The aim is to examine whether SES has an impact on the secondary prevention of ACS in Australia.

Methods

Australian SNAPSHOT ACS data (2012) and its 18-month follow-up data were linked to admissions data from 6 jurisdictions covering all states and territories, national death index and Medicare Pharmaceutical Benefits Scheme data covering up to 3 years post-discharge. The five SES groups (lowest in Group 1 and highest in Group 5) were derived from the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) using the residential postcode at baseline. Outcomes were cardiac rehabilitation (CR) participation and smoking rate at 18 months post discharge as well as the use of ≥3 of the 4 indicated medications, all-cause death and cardiovascular disease (CVD) rates by 36 months of discharge. Outcomes were compared between the groups using the multilevel logistic regression with covariates of SES (5 groups), sex, GRACE risk score (4 groups), ACS diagnosis (STEMI/NSTEMI/UA) and the jurisdictions where the admissions data were linked.

Results

Of 1655 patients with ACS (mean age 68±13.5 yrs, 65% were male), who were discharged from hospital alive and had linked data available, 353 (21%) were in SES Group 1 (lowest SES), 369 (22%) in Group 2, 382 (23%) in Group 3, 296 (18%) in Group 4 and 255 (15%) in Group 5 (highest SES). Baseline clinical characteristics were comparable across the five SES groups. At 18-month after discharge, 1014 (61%) patients were followed-up with comparable loss to follow-up in each group. After adjustment, fewer patients in the lower SES groups (Groups 1 and 2) had participated in CR than those in the highest SES group (Group 5) (OR (95% CI): 0.60 (0.36, 0.99) and 0.56 (0.35, 0.91), respectively). Moreover, the odds of smoking was greater in Group 3 than Group 5 (2.60 (1.15, 5.89)) but no trend was found across the groups. By 36 months of discharge after adjustment, there was no difference in the odds of using ≥3 out of 4 medications between the SES groups. Despite this, patients in Groups 1 and 2 were significantly more likely to die than those in the highest SES group (1.96 (1.19, 3.21) and 1.91 (1.19, 3.07), respectively). The odds of CVD readmission did not differ across SES groups.

Conclusion

This study suggests that patients with low SES were less likely to participate in CR programs and more likely to die than those with high SES. Smoking rates varied between patients with intermediate and high SES but no trend was found across the groups. Despite the universal health cover available, inequity between the SES groups still exist. Future research is needed to further explore strategies to help close the evidence-practice gaps.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Australian National Heart Foundation Postdoctoral Fellowship

Differences in outcomes for hospitalizations of systemic and non-systemic infections associated with vascular and cardiac grafts and devices: a population-based study

BACKGROUND

Use of vascular and cardiac devices has expanded and is associated with a relative, though disproportionate, increase in device-associated infections.

AIM

To describe the association between cardiac/vascular device infections and outcomes in those with, and without systemic infections.

METHODS

We used the 2016 National Inpatient Sample and the International Classification of Diseases - 10^th revision codes to identify hospitalized individuals with vascular and cardiac device infections. Linear and logistic regression models were utilized to compare outcomes of death, length of stay (LOS) and hospitalization costs between individuals with and without systemic infection.

FINDINGS

There were a total of 65,110 hospitalizations associated with device infections with a mean age of 61.3 ± 15.9 years (standard deviation); 28,650 (44%) had systemic infections. Elixhauser comorbidity scores of three or greater were observed in 91.2% of individuals with systemic infections along with a higher prevalence of diabetes, renal disease and heart failure. The primary outcome of mortality was observed in 3965 individuals with an odds ratio of 3.97 (95% confidence interval (CI), 2.92-3.95) in those with systemic infections compared with those without. Mean LOS was 3.44 days longer (95% CI, 2.92-3.95) and mean cost was US$11,776 greater (95% CI, US$9826-12,727) in the systemic infection cohort.

CONCLUSION

Systemic cardiac and vascular device infections were associated with increased mortality, LOS and costs. Considering the increasing use of these life-saving devices, further work is needed to identify those at risk for infectious complications, particularly systemic infection, in order to enhance preventative strategies and improve health outcomes.

P2717Type-II MI and chronic myocardial injury rates, invasive management and 4 year mortality among consecutive patients undergoing high sensitivity troponin T testing in the emergency department

Background

In emergency departments (EDs), assessment of patients with suspected acute coronary syndromes (ACS) represents a major workload and high sensitivity troponin (HsTn) T and I levels are frequently measured. A minority of patients have final diagnosis of myocardial infarction (MI).

Methods and results

Among 2738 consecutive patients with suspected ACS presenting to ED at Liverpool Hospital, Australia, between March and June 2014, we determined the relative frequencies of 3 patient groups: type-I MI, type-II MI including chronic myocardial injury (CMI), and assessed the use of invasive and pharmacological therapies and 4-year outcomes. Adjudication of MI was according to the 4th universal definition of MI as follows: 1) type-I MI; 2) type-II MI (including acute myocardial injury), and 3) CMI. Of 995 patients (36%) median age 76 years [IQR 65–83]), with at least 2 HsTnT measurements and one >14ng/l, 727 (73%) had chronic myocardial injury, 171 (17%) had type-II MI; and 97 (9.7%) had type-I MI. Patients with type-I MI (mean age 63 years) were younger than those with type-II MI or chronic myocardial injury by 12 and 14 years respectively. The main triggering factors for type-II MI/acute injury included: sepsis (21.1%), acute heart failure (18.3%), tachyarrhythmia (16.9%), anaemia (8.6%) and a combination of factors (16%). In-hospital angiography (62% had PCI) rates were 95% for patients with type-I MI, 24% (7% PCI) for those with type-II MI and 3.4% for CMI. Mortality at 4 years was 55% for type-II MI, 44% for CMI and 18% for type-1 MI (P<0.001; Figure), though after Cox modelling adjusting for age, gender, renal function and COPD, compared to type 1 MI, type-II MI (hazard ratio 1.61 [95% CIs 0.90–2.86]; p=0.106) and CMI (hazard ratio 1.01 [95% CIs 0.59–1.74]; p=0.963) were not independently associated with increased late mortality, largely because patients with type 1 MI were a decade younger.

Conclusion

Among unselected patients undergoing HsTnT testing in EDs, type-II MI including acute myocardial injury was more common than type-I MI. Chronic myocardial injury, which occurred in 3 of 4 patients. While patients with type-II MI acute myocardial injury had higher late mortality rates than type-I MI, though after multivariable analyses mortality rates were not different.

P4343Reconciling acute coronary syndrome diagnoses between linked administrative data and hospital medical records in medical research

Background/Introduction

Administrative data incorporating the International Classification of Diseases 10th Revision (ICD-10) is commonly used in cardiac research. Using patient records, diagnoses are systematically coded by trained coders who have limited/no clinical experience. Therefore, it is important to understand how systematically coded cardiac diagnoses compare with clinically assessed diagnoses to better analyse and interpret studies that have used linked administrative data to adjudicate patient's diagnosis.

Purpose

To assess the agreement between the acute coronary syndrome (ACS) diagnoses according to linked data compared to those extracted from hospital medical records by clinicians participating in a national registry and determine the factors associated with diagnoses disagreement.

Methods

The rate of ST-elevation myocardial infarction (STEMI), non-STEMI (NSTEMI) and unstable angina (UA) obtained from the medical records, from admission to discharge, for the nationwide SNAPSHOT ACS audit in 2012 were compared to the corresponding ICD-10 Australian Modification (ICD-10-AM) codes using linked data from 6 jurisdictions covering all Australian states (6) and territories (2). The proportions of the overall agreement (OA), the positive agreement (PA) and the Cohen's weighted kappa and the 95% confidence interval (CI) were derived using both data sources for STEMI, NSTEMI and UA individually, where kappa≥0.8 confers strong agreement and 0.6≤kappa<0.8 moderate agreement. The factors associated with the diagnostic disagreement were explored using multilevel multivariable logistic regression model (backward selection method), accounting for the hospital clustering effect.

Results

Overall, 3130 patients had both medical records and linked data available for comparison. The degree of agreement was greatest for STEMI and lowest for UA (STEMI: OA=97%, PA=85%, kappa (95% CI)=0.84 (0.81, 0.87); NSTEMI: OA=91%, PA=81%, kappa (95% CI)=0.76 (0.73,0.79); UA: OA = 81%, PA=53%, kappa (95% CI)=0.41 (0.38, 0.45)). Further, the independent factors associated with the disagreement between the medical records and the linked data were the diagnosis of UA (UA vs. STEMI (odds ratio (95% CI)): 6.85 (4.12, 11.40)), not receiving revascularisation (2.27 (1.69, 3.03)), and the state where the ICD-10-AM was coded (p=0.007) (see Figure).

Figure 1

Conclusion

This study suggests that the agreement between the systematically coded diagnoses from linked administrative data and the diagnosis from the clinical assessment is greater in patients who received revascularisation and worse in those with UA. Also, the degree of agreement varies between states. As the linked data and the ICD codes are being used more often in research to support the evidence-based policies and practice, more attention is needed in testing and improving the accuracy of the ICD-10 codes as well as the ICD-11 codes that are soon to be introduced.

Acknowledgement/Funding

KH is funded by Heart Foundation Postdoctoral Fellowship. SNAPSHOT data linkage project was funded by the NSW Heart Foundation CVRN Project Grant