Prehospital system delay in ST-segment elevation myocardial infarction care: a novel linkage of emergency medicine services and in hospital registry data

A prediction model to determine the untapped lung donor pool outside of the DonateLife network in Victoria

Lung transplantation is limited by a lack of suitable lung donors. In Australia, the national donation organisation (DonateLife) has taken a major role in optimising organ donor identification. However, the potential outside the DonateLife network hospitals remains uncertain. We aimed to create a prediction model for lung donation within the DonateLife network and estimate the untapped lung donors outside of the DonateLife network. We reviewed all deaths in the state of Victoria's intensive care units using a prospectively collected population-based intensive care unit database linked to organ donation records. A logistic regression model derived using patient-level data was developed to characterise the lung donors within DonateLife network hospitals. Consequently, we estimated the expected number of lung donors in Victorian hospitals outside the DonateLife network and compared the actual number. Between 2014 and 2018, 291 lung donations occurred from 8043 intensive care unit deaths in DonateLife hospitals, while only three lung donations occurred from 1373 ICU deaths in non-DonateLife hospitals. Age, sex, postoperative admission, sepsis, neurological disease, trauma, chronic respiratory disease, lung oxygenation and serum creatinine were factors independently associated with lung donation. A highly discriminatory prediction model with area under the receiver operator characteristic curve of 0.91 was developed and accurately estimated the number of lung donors. Applying the model to non-DonateLife hospital data predicted only an additional five lung donors. This prediction model revealed few additional lung donor opportunities outside the DonateLife network, and the necessity of alternative and novel strategies for lung donation. A donor prediction model could provide a useful benchmarking tool to explore organ donation potential across different jurisdictions, hospitals and transplanting centres.

The ACIRA Registry: A Regional Tool to Improve the Healthcare Pathway for Patients Undergoing Percutaneous Coronary Interventions and Coronary Angiographies in the French Aquitaine Region: Study Design and First Results

BACKGROUND

In France, there is a lack of information about practices and pathways of coronary angiographies and percutaneous coronary interventions (PCI). We present the design and the first results of the ACIRA registry, the goal of which is to answer questions about quality, security, appropriateness, efficiency of, and access to interventional cardiology (IC) healthcare pathway in the French Aquitaine region.

METHODS

The ACIRA registry is an on-going, multicenter, prospective, exhaustive, scalable, and nominative cohort study of patients who undergo coronary angiographies or percutaneous coronary intervention in any of the catheterization laboratories. The data related to hospitalizations and procedures are directly extracted from hospital information systems. In-hospital mortality, readmissions, and cardiovascular morbidity are collected from the French hospital medical information system database. An identity management system has been implemented to create the patient health care pathway.

RESULTS

From January 1, 2012, to June 30, 2018, 147,136 procedures performed on 106,005 patients have been included in the ACIRA registry.

CONCLUSIONS

ACIRA has shown its ability to study the patient IC healthcare pathway, up to 1 year after the procedure. Nominative data enable the linkage between clinical and medico-administrative databases and possible supplementary data collection. The use of existing databases allowed us to limit patients lost to follow-up, prevent the double entry of data, improve data quality, and reduce the operating costs. The prospect of linkage with the French National Health Data System may offer promising opportunities for future medical research projects and for developing collaboration and benchmarking with other IC registries abroad.

Warning system improve the clinical outcomes in transfer patients with ST-segment elevation myocardial infarction

A warning system included directly faxing electrocardiography information to the mobile phone immediately after an ST-segment elevation myocardial infarction (STEMI) diagnosis was made at a non-percutaneous coronary intervention (PCI) capable hospital. This study aimed to explore the outcomes after using a warning system in transfer STEMI patients.From October 2013 to December 2016, 667 patients experienced a STEMI event and received primary PCI at our institution. 274 patients who were divided into transfer group were transferred from non-PCI capable hospitals and connected to a first-line cardiovascular doctor by the warning system. Other 393 patients were divided into the non-transfer group.The transfer group still had a longer pain-to-reperfusion time and presented higher troponin-I level when compared with non-transfer group. There was no significant difference in the use of drug-eluting stent and procedural devices between non-transfer and transfer groups. The prevalence of different anti-platelet agents loading did not differ between non-transfer and transfer groups. Non-significant trend about higher prevalence of statin use was noted in transfer group (78.9% vs 86.1%, P = .058). The transfer group presented similar clinical short-term results regarding both cardiovascular and all-cause mortality when comparing with non-transfer group. The transfer group provided non-significant trend about lower one-year cardiovascular mortality (10.7% vs 6.2%, P = .052) and lower all-cause mortality (12.2% vs 6.9%, P = .026) when compared with non-transfer group. There was a significant difference in the Kaplan-Meier curve of 1-year cardiovascular mortality between the transfer group and the non-transfer group (P = .049).After using the warning system, the inter-facility transfer group had comparable outcomes even though a longer pain-to-reperfusion time and a higher peak troponin-I level when comparing with non-transfer group.

The FAST-STEMI Network in Biella From 2013 to 2019: Impact of the Delocalization of the Hospital Facilities on Ischemia Time and In-hospital Outcomes

BACKGROUND

The optimization of the strategies for myocardial revascularization has improved the outcomes of patients with ST-segment elevation myocardial infarction. In Piedmont, the FAST-STEMI regional network was created for improving the management and transportation of ST-segment elevation (STEMI) patients to primary percutaneous coronary intervention facilities, reducing the time to reperfusion. Within this network, the Hospital of Biella was delocalized in December 2014 to a new suburban structure designed for an easier access, which might have shortened the duration of patients' transportation and ischemia, with potential positive prognostic effects. The aim of the present study was to define the impact of the decentralization of the hospital structure on the time to reperfusion and in-hospital outcomes among STEMI patients admitted to the Hospital of Biella.

METHODS

We included STEMI patients admitted to our urban hospital between 2013 and 2019 and included in the FAST-STEMI database. The primary endpoint was the duration of ischemia, defined as pain to balloon (PTB). The primary outcome endpoint (PE) was in-hospital mortality.

RESULTS

We included 276 consecutive patients with STEMI undergoing primary percutaneous coronary intervention between 2016 and 2019 in the new hospital facility, which were compared with 170 patients treated between 2013 and June 2014 in the prior structure. Patients' characteristics included a mean age of 67.5 ± 12.5 years, 72.1% males and 18.7% patients with diabetes. In the new facility, the median PTB was 188 minutes [interquartile range: 125-340 min], reduced as compared with the period 2013-2014 [215 (128.5-352 min), P = 0.002]. The median in-hospital stay was also shorter (P = 0.004), whereas a nonsignificant improvement was noted for ejection fraction (EF) at discharge (P = 0.14). A linear relationship was demonstrated between PTB and the EF (r = -0.183, P = 0.003) in patients treated between 2016 and 2019 while not affecting the length of hospitalization or in-hospital outcomes. In fact, in-hospital death occurred in 36 patients, 8% in the new structure versus 7.7% in 2013-2014 [hazard ratio (HR) (95% confidence interval [CI]) = 1.20 (0.59-2.42), P = 0.62]. The independent predictors of mortality were patients' age and EF at discharge (age ≥ 75 y: adjusted HR [95% CI] = 6.75 [1.51-30.1], P = 0.01; EF: adjusted HR [95% CI] = 0.91 [0.88-0.95], P < 0.001).

CONCLUSIONS

The present study shows that, among the STEMI patients treated in our center, the delocalization of the hospital facilities and the optimization of the FAST-STEMI network reduced the duration of ischemia, with positive effects on left ventricular function at discharge. However, this did not translate into a significant benefit in survival, which was instead conditioned by the aging of the population.

Complication during transportation and 30 days mortality of patients with acute coronary syndrome

Background

Patients with acute coronary syndrome (ACS) who present to hospitals without interventional facilities frequently require transfer to another hospital equipped with a cardiac catheterization laboratory. This retrospective cohort study evaluates the association of the type of medical transport with patient outcomes.

Methods

A retrospective analysis of medical records of patients with ACS transported by basic (BT) and specialist transfer (ST) by emergency medical teams (EMTs). We analyzed age, gender, hemodynamic parameters, type of the emergency medical team, and complications during transport as well as patient survival to hospital admission, survival time and the 30-day mortality rate.

Results

Of 500 patients who underwent transfer, ST transported 368 (73.6%) and BT 132 (26.4%) patients (p < 0.001). Complications during transportation occurred in 3 (1%) in the ST group and 2 (1.5%) in and BT group. Cardiac arrest during transfer occurred in no (0%) patients in the ST group, and 2 (1.5%) in the BT group (p = 0.118). Survival to admission was recorded in all patients in the ST group and 131/132 (0.8%) patients in the BT group (p = 0.592). 40 (12%) of patients in the ST group and 13 (11%) patients in the BT group (p = 0.731) died within 30 days of transfer.

Conclusions

Complications during medical transport of ACS patients from hospitals without a cardiac catheter lab to hospitals equipped with such a lab were rare and their incidence was not associated with the type of transporting EMT. The type of EMT was not associated with 30-day patient mortality.

Derivation and validation of a machine learning record linkage algorithm between emergency medical services and the emergency department

OBJECTIVE

Linking emergency medical services (EMS) electronic patient care reports (ePCRs) to emergency department (ED) records can provide clinicians access to vital information that can alter management. It can also create rich databases for research and quality improvement. Unfortunately, previous attempts at ePCR and ED record linkage have had limited success. In this study, we use supervised machine learning to derive and validate an automated record linkage algorithm between EMS ePCRs and ED records.

MATERIALS AND METHODS

All consecutive ePCRs from a single EMS provider between June 2013 and June 2015 were included. A primary reviewer matched ePCRs to a list of ED patients to create a gold standard. Age, gender, last name, first name, social security number, and date of birth were extracted. Data were randomly split into 80% training and 20% test datasets. We derived missing indicators, identical indicators, edit distances, and percent differences. A multivariate logistic regression model was trained using 5-fold cross-validation, using label k-fold, L2 regularization, and class reweighting.

RESULTS

A total of 14 032 ePCRs were included in the study. Interrater reliability between the primary and secondary reviewer had a kappa of 0.9. The algorithm had a sensitivity of 99.4%, a positive predictive value of 99.9%, and an area under the receiver-operating characteristic curve of 0.99 in both the training and test datasets. Date-of-birth match had the highest odds ratio of 16.9, followed by last name match (10.6). Social security number match had an odds ratio of 3.8.

CONCLUSIONS

We were able to successfully derive and validate a record linkage algorithm from a single EMS ePCR provider to our hospital EMR.

A validation of machine learning-based risk scores in the prehospital setting

BACKGROUND

The triage of patients in prehospital care is a difficult task, and improved risk assessment tools are needed both at the dispatch center and on the ambulance to differentiate between low- and high-risk patients. This study validates a machine learning-based approach to generating risk scores based on hospital outcomes using routinely collected prehospital data.

METHODS

Dispatch, ambulance, and hospital data were collected in one Swedish region from 2016-2017. Dispatch center and ambulance records were used to develop gradient boosting models predicting hospital admission, critical care (defined as admission to an intensive care unit or in-hospital mortality), and two-day mortality. Composite risk scores were generated based on the models and compared to National Early Warning Scores (NEWS) and actual dispatched priorities in a prospectively gathered dataset from 2018.

RESULTS

A total of 38203 patients were included from 2016-2018. Concordance indexes (or areas under the receiver operating characteristics curve) for dispatched priorities ranged from 0.51-0.66, while those for NEWS ranged from 0.66-0.85. Concordance ranged from 0.70-0.79 for risk scores based only on dispatch data, and 0.79-0.89 for risk scores including ambulance data. Dispatch data-based risk scores consistently outperformed dispatched priorities in predicting hospital outcomes, while models including ambulance data also consistently outperformed NEWS. Model performance in the prospective test dataset was similar to that found using cross-validation, and calibration was comparable to that of NEWS.

CONCLUSIONS

Machine learning-based risk scores outperformed a widely-used rule-based triage algorithm and human prioritization decisions in predicting hospital outcomes. Performance was robust in a prospectively gathered dataset, and scores demonstrated adequate calibration. Future research should explore the robustness of these methods when applied to other settings, establish appropriate outcome measures for use in determining the need for prehospital care, and investigate the clinical impact of interventions based on these methods.

Do Out-of-Hospital Cardiac Arrest Patients Have Increased Chances of Survival When Transported to a Cardiac Resuscitation Center?

Background

Patients suffering from an out‐of‐hospital cardiac arrest are often transported to the closest hospital. Although it has been suggested that these patients be transported to cardiac resuscitation centers, few jurisdictions have acted on this recommendation. To better evaluate the evidence on this subject, a systematic review and meta‐analysis of the currently available literature evaluating the association between the destination hospital's capability (cardiac resuscitation center or not) and resuscitation outcomes for adult patients suffering from an out‐of‐hospital cardiac arrest was performed.

Methods and Results

PubMed, EMBASE, and the Cochrane Library databases were first searched using a specifically designed search strategy. Both original randomized controlled trials and observational studies were considered for inclusion. Cardiac resuscitation centers were defined as having on‐site percutaneous coronary intervention and targeted temperature management capability at all times. The primary outcome measure was survival. Twelve nonrandomized observational studies were retained in this review. A total of 61 240 patients were included in the 10 studies that could be included in the meta‐analysis regarding the survival outcome. Being transported to a cardiac resuscitation center was associated with an increase in survival (odds ratio=1.95 [95% confidence interval 1.47‐2.59], P<0.001).

Conclusions

Adult patients suffering from an out‐of‐hospital cardiac arrest transported to cardiac resuscitation centers have better outcomes than their counterparts. When possible, it is reasonable to transport these patients directly to cardiac resuscitation centers (class IIa, level of evidence B, nonrandomized).

Clinical Trial Registration

URL: http://www.crd.york.ac.uk/PROSPERO/. Unique identifier: CRD42018086608.

Using deterministic record linkage to link ambulance and emergency department data: is it possible without patient identifiers? A case study from the UK

INTRODUCTION

Routine linkage of emergency ambulance records with those from the emergency department is uncommon in the UK. Our study, known as the Pre-Hospital Emergency Department Data Linking Project (PHED Data), aimed to link records of all patients conveyed by a single emergency ambulance service to thirteen emergency departments in the UK from 2012-2016.

OBJECTIVES

We aimed to examine the feasibility and resource requirements of collecting de-identified emergency department patient record data and, using a deterministic matching algorithm, linking it to ambulance service data.

METHODS

We used a learning log to record contacts and activities undertaken by the research team to achieve data linkage. We also conducted semi-structured interviews with information management/governance staff involved in the process.

RESULTS

We found that five steps were required for successful data linkage for each hospital trust. The total time taken to achieve linkage was a mean of 65 weeks. A total of 958,057 emergency department records were obtained and, of these, 81% were linked to a corresponding ambulance record. The match rate varied between hospital trusts (50%-94%). Staff expressed strong enthusiasm for data linkage. Barriers to successful linkage were mainly due to inconsistencies between and within acute trusts in the recording of two ambulance event identifiers (CAD and call sign). Further data cleaning was required on emergency department fields before full analysis could be conducted. Ensuring the data was not re-identifiable limited validation of the matching method.

CONCLUSION

We conclude that deterministic record linkage based on the combination of two event identifiers (CAD and call sign) is possible. There is an appetite for data linkage in healthcare organisations but it is a slow process. Developments in standardising the recording of emergency department data are likely to improve the quality of the resultant linked dataset. This would further increase its value for providing evidence to support improvements in health care delivery.

HIGHLIGHTS

Ambulance records are rarely linked to other datasets; this study looks at the feasibility and resource requirement to use deterministic matching to link ambulance and emergency department data for patients conveyed by ambulance to the emergency department.It is possible to link these data, with an average match rate of 81% across 13 emergency departments and one large ambulance trust.All trusts approached provided match-able data and there was an appetite for data linkage; however, it was a long process taking an average of 65 weeks.We conclude that deterministic matching using no patient identifiers can be used in this setting.

Emergency medical service delays in ST-elevation myocardial infarction: a meta-analysis

OBJECTIVES

To evaluate emergency medical services (EMS) delays and their impact on time to treatment and mortality in patients with ST-elevation myocardial infarction (STEMI).

METHOD

We collected data on EMS time intervals from published studies across five electronic databases. The primary EMS interval was the time in minutes between first medical contact and arrival at hospital door (FMC-to-door time). Secondary intervals were other components of EMS delay. Weighted means were measured using random-effects models. Meta-regression was used to identify factors associated with EMS delays and to assess the impact of EMS delay on the proportion of patients treated within90 min and mortality.

RESULTS

Two independent reviewers included 100 studies (125 343 patients) conducted in 20 countries. The weighted mean FMC-to-door time was 41 min (n=101 646; 95% CI 39 to 43, range 21-88). However, substantial heterogeneity was observed with each interval, which could be explained by region and urban classification, distance to hospital and method of ECG interpretation. In a meta-regression adjusted for door-to-balloon time, a 10 min increase in FMC-to-door time was associated with a 10.6% (95% CI 7.6% to 13.5%; p<0.001) reduction in the proportion of patients treated within 90 min. Shorter EMS delay was significantly associated with lower short-term mortality in patients receiving prehospital thrombolysis (p=0.018).

CONCLUSION

EMS delays account for half of the total system delay in STEMI. There is a fourfold global variation in EMS delays, which are not completely explained by differences in system characteristics. Reducing unexplained variation could yield improvements in the time to treatment and outcome of STEMI patients.

PROSPERO REGISTRATION NUMBER

CRD42017074118.

Regional "Call 911" Emergency Department Protocol to Reduce Interfacility Transfer Delay for Patients With ST-Segment-Elevation Myocardial Infarction

BACKGROUND

We evaluated the first-medical-contact-to-balloon (FMC2B) time after implementation of a "Call 911" protocol for ST-segment-elevation myocardial infarction (STEMI) interfacility transfers in a regional system.

METHODS AND RESULTS

This is a retrospective cohort study of consecutive patients with STEMI requiring interfacility transfer from a STEMI referring hospital, to one of 35 percutaneous coronary intervention-capable STEMI receiving centers (SRCs). The Call 911 protocol allows the referring physician to activate 911 to transport a patient with STEMI to the nearest SRC for primary percutaneous coronary intervention. Patients with interfacility transfers were identified over a 4-year period (2011-2014) from a registry to which SRCs report treatment and outcomes for all patients with STEMI transported via 911. The primary outcomes were median FMC2B time and the proportion of patients achieving the 120-minute goal. FMC2B for primary 911 transports were calculated to serve as a system reference. There were 2471 patients with STEMI transferred to SRCs by 911 transport during the study period, of whom 1942 (79%) had emergent coronary angiography and 1410 (73%) received percutaneous coronary intervention. The median age was 61 years (interquartile range [IQR] 52-71) and 73% were men. The median FMC2B time was 111 minutes (IQR 88-153) with 56% of patients meeting the 120-minute goal. The median STEMI referring hospital door-in-door-out time was 53 minutes (IQR 37-89), emergency medical services transport time was 9 minutes (IQR 7-12), and SRC door-to-balloon time was 44 minutes (IQR 32-60). For primary 911 patients (N=4827), the median FMC2B time was 81 minutes (IQR 67-97).

CONCLUSIONS

Using a Call 911 protocol in this regional cardiac care system, patients with STEMI requiring interfacility transfers had a median FMC2B time of 111 minutes, with 56% meeting the 120-minute goal.

Association Between Hospital Practices and Door-in-door-out Time in ST-segment Elevation Myocardial Infarction

BACKGROUND

Current guidelines suggest a "door-in-door-out" (DIDO) time of 30 minutes or shorter for patients with ST-segment elevation myocardial infarction (STEMI) who arrive at a STEMI referral hospital and are transferred to a STEMI-receiving center for primary percutaneous coronary intervention. Experts previously identified 18 system practices as critical for reducing DIDO times. The objective of this study was to describe how frequently these critical practices are used and to determine whether their use was associated with shorter DIDO times.

METHODS

We surveyed 18 STEMI referral hospitals for 4 STEMI-receiving centers regarding their use of these 18 practices. The median number used was 14 practices (interquartile range 12-15). We then evaluated their association with DIDO times in all patients (n = 93) transferred from these STEMI referral hospitals to the 4 STEMI-receiving centers for primary percutaneous coronary intervention.

RESULTS

In univariate linear regression analyses, system-wide quality improvement programs with leaders in the emergency medical services agencies and STEMI referral hospitals were associated with shorter DIDO times (P < 0.001 for all). Overall use of system practices was not associated with DIDO times (P = 0.143). The majority (76%, 95% confidence interval: 66%-85%) of DIDO times did not meet the 30-minute goal.

CONCLUSIONS

These findings highlight the difficulty in achieving the 30-minute DIDO goal and the need for continued focus on strategies for reducing DIDO time, including system-wide quality improvement programs.

Call-to-balloon time dashboard in patients with ST-segment elevation myocardial infarction results in significant improvement in the logistic chain

AIMS

Timely reperfusion with primary percutaneous coronary intervention (pPCI) in ST-segment elevation myocardial infarction (STEMI) patients is associated with superior clinical outcomes. Aiming to reduce ischaemic time, an innovative system for home-to-hospital (H2H) time monitoring was implemented, which enabled real-time evaluation of ischaemic time intervals, regular feedback and improvements in the logistic chain. The objective of this study was to assess the results after implementation of the H2H dashboard for monitoring and evaluation of ischaemic time in STEMI patients.

METHODS AND RESULTS

Ischaemic time in STEMI patients transported by emergency medical services (EMS) and treated with pPCI in the Noordwest Ziekenhuis, Alkmaar before (2008-2009; n=495) and after the implementation of the H2H dashboard (2011-2014; n=441) was compared. Median time intervals were significantly shorter in the H2H group (door-to-balloon time 32 [IQR 25-43] vs. 40 [IQR 28-55] minutes, p-value <0.001, FMC-to-balloon time 62 [IQR 52-75] vs. 80 [IQR 67-103] minutes, p-value <0.001, and treatment delay 142 [IQR 103-221] vs. 159 [IQR 123-253] minutes, p-value <0.001). The H2H time dashboard was independently associated with shorter time delays.

CONCLUSIONS

Real-time monitoring and feedback on time delay with the H2H dashboard improves the logistic chain in STEMI patients, resulting in shorter ischaemic time intervals.

Comparing routine administrative data with registry data for assessing quality of hospital care in patients with myocardial infarction using deterministic record linkage

Background

Assessment of quality of care in patients with myocardial infarction (MI) should be based on data that effectively enable determination of quality. With the need to simplify measurement techniques, the question arises whether routine data can be used for this purpose. We therefore compared data from a German sickness fund (AOK) with data from the Berlin Myocardial Infarction Registry (BMIR).

Methods

We included patients hospitalised for treatment of MI in Berlin from 2009-2011. We matched 2305 patients from AOK and BMIR by using deterministic record linkage with indirect identifiers. For matched patients we compared the frequency in documentation between AOK and BMIR for quality assurance variables and calculated the kappa coefficient (KC) as a measure of agreement.

Results

There was almost perfect agreement in documentation between AOK and BMIR data for matched patients for: catheter laboratory (KC: 0.874), ST elevation MI (KC: 0.826), diabetes (KC: 0.818), percutaneous coronary intervention (KC: 0.860) and hospital mortality (KC: 0.952). The remaining variables compared showed moderate or less than moderate agreement (KC < 0.6), and were grouped in Category II with less frequent documentation in AOK for risk factors and aspects of patients’ history; in Category III with more frequent documentation in AOK for comorbidities; and in Category IV for medication at and after hospital discharge.

Conclusions

Routine data are primarily collected and defined for reimbursement purposes. Quality assurance represents merely a secondary use. This explains why only a limited number of variables showed almost perfect agreement in documentation between AOK and BMIR. If routine data are to be used for quality assessment, they must be constantly monitored and further developed for this new application. Furthermore, routine data should be complemented with registry data by well-established methods of record linkage to realistically reflect the situation – also for those quality-associated variables not collected in routine data.

[The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement]

Zunehmend werden routinemäßig gesammelte Gesundheitsdaten, die zu administrativen und klinischen Zwecken und ohne spezifische, a priori festgelegte Forschungsziele erhoben wurden, auch für die Forschung eingesetzt. Die rasche Entwicklung und Verfügbarkeit dieser Daten machten Probleme deutlich, die in den bestehenden Berichts-Leitlinien, wie dem STROBE-Statement (Strengthening the Reporting of Observational Studies in Epidemiology) nicht behandelt werden. Das RECORD-Statement (REporting of studies Conducted using Observational Routinely-collected health Data) wurde entwickelt, um diese Lücken zu schließen. RECORD ist als Erweiterung des STROBE-Statements gedacht, um Punkte abzudecken, die spezifisch sind beim Berichten von Beobachtungsstudien, die routinemäßig gesammelte Gesundheitsdaten verwenden. RECORD besteht aus einer Checkliste von 13 Punkten mit Bezug zu Titel, Abstract, Einleitung, Methoden-, Ergebnis- und Diskussionsteil von Artikeln sowie zu anderen Informationen, die in Forschungsberichten dieser Art enthalten sein sollten. Dieses Dokument enthält die Checkliste sowie Erläuterungen und weitere Erklärungen, um die Verwendung der Checkliste zu verbessern. Beispiele für ein gutes Berichten der einzelnen Punkte der RECORD-Checkliste sind ebenfalls in diesem Dokument enthalten. Dieses Dokument sowie die zugehörige Website und ein Forum (http://www.record-statement.org) werden die Umsetzung und das Verständnis von RECORD verbessern. Autoren, Redakteure von Fachzeitschriften und Peer-Reviewer können die Transparenz beim Berichten von Forschungsergebnissen erhöhen, indem sie RECORD anwenden.

Inter-Facility Transfer vs. Direct Admission of Patients With ST-Segment Elevation Acute Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention

BACKGROUND

Inter-facility transfer for primary percutaneous coronary intervention (PCI) from referring facilities to PCI centers causes a significant delay in treatment of ST-segment elevation acute myocardial infarction (STEMI) patients undergoing primary PCI. However, little is known about the clinical outcomes of STEMI patients undergoing inter-facility transfer in Japan.

METHODS AND RESULTS

In the CREDO-Kyoto acute myocardial infarction (AMI) registry that enrolled 5,429 consecutive AMI patients in 26 centers in Japan, the current study population consisted of 3,820 STEMI patients who underwent primary PCI within 24 h of symptom onset. We compared long-term clinical outcomes between inter-facility transfer patients and those directly admitted to PCI centers. The primary outcome measure was a composite of all-cause death or heart failure (HF) hospitalization. There were 1,725 (45.2%) inter-facility transfer patients, and 2,095 patients (54.8%) with direct admission to PCI centers. The cumulative 5-year incidence of death/HF hospitalization was significantly higher in the inter-facility transfer patients than in those with direct admission (26.9% vs. 22.2%; log-rank P<0.001). After adjusting for potential confounders, the risk for death/HF hospitalization was significantly higher (adjusted hazard ratio: 1.22, 95% confidence interval: 1.07-1.40, P<0.001) in the inter-facility transfer patients than in those directly admitted.

CONCLUSIONS

Inter-facility transfer was associated with significantly worse long-term clinical outcomes for patients with STEMI undergoing primary PCI. (Circ J 2016; 80: 1764-1772).

Influence of heart failure on the prognosis of patients with acute myocardial infarction in southwestern China

The impact of heart failure (HF) on acute myocardial infarction (AMI) in patients from southwestern China remains unclear. The present study aimed to compare in-hospital cardiovascular events, mortality and clinical therapies in AMI patients with or without HF in southwestern China. In total, 591 patients with AMI hospitalized between February 2009 and December 2012 were examined; those with a history of HF were excluded. The patients were divided into four groups according to AMI type (ST-elevated or non-ST-elevated AMI) and the presence of HF during hospitalization. Clinical characteristics, in-hospital cardiovascular events, mortality, coronary angiography and treatment were compared. Clinical therapies, specifically evidence-based drug use were analyzed in patients with HF during hospitalization, including angiotensin converting enzyme inhibitors (ACEIs) and β-blockers (BBs). AMI patients with HF had a higher frequency of co-morbidities, lower left ventricular ejection fraction, longer length of hospital stay and a greater risk of in-hospital mortality compared with AMI patients without HF. AMI patients with HF were less likely to be examined by cardiac angiography or treated with reperfusion therapy or recommended medications. AMI patients with HF co-treated with ACEIs and BBs had a significantly higher survival rate (94.4 vs. 67.5%; P<0.001) compared with untreated patients or patients treated with either ACEIs or BBs alone. Logistic regression analysis revealed that HF and cardiogenic shock in patients with AMI were the strongest predictors of in-hospital mortality. AMI patients with HF were at a higher risk of adverse outcomes. Cardiac angiography and timely standard recommended medications were associated with improved clinical outcomes.

The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement

Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research. The rapid evolution and availability of these data have revealed issues not addressed by existing reporting guidelines, such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement was created to fill these gaps. RECORD was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD consists of a checklist of 13 items related to the title, abstract, introduction, methods, results, and discussion section of articles, and other information required for inclusion in such research reports. This document contains the checklist and explanatory and elaboration information to enhance the use of the checklist. Examples of good reporting for each RECORD checklist item are also included herein. This document, as well as the accompanying website and message board (http://www.record-statement.org), will enhance the implementation and understanding of RECORD. Through implementation of RECORD, authors, journals editors, and peer reviewers can encourage transparency of research reporting.

Probabilistic Linkage of Prehospital and Outcomes Data in Out-of-hospital Cardiac Arrest

OBJECTIVE

Lack of longitudinal patient outcome data is an important barrier in emergency medical services (EMS) research. We aimed to demonstrate the feasibility of linking prehospital data from the California EMS Information Systems (CEMSIS) database to outcomes data from the California Office of Statewide Health Planning and Development (OSHPD) database for patients with out-of-hospital cardiac arrest (OHCA).

METHODS

We included patients age 18 years or older who sustained nontraumatic OHCA and were included in the 2010-2011 CEMSIS databases. The CEMSIS database is a unified EMS data collection system for California. The OSHPD database is a comprehensive data collection system for patient-level inpatient and emergency department encounters in California. OHCA patients were identified in the CEMSIS database using cardiac rhythm, procedures, medications, and provider impression. Probabilistic linkage blocks were created using in-hospital death or one of the following primary or secondary diagnoses (ICD-9-CM) in the OSHPD databases: cardiac arrest (427.5), sudden death (798), ventricular tachycardia (427.1), ventricular fibrillation (427.4), and acute myocardial infarction (410.xx). Blocking variables included incident date, gender, date of birth, age, and/or destination facility. Due to the volume of cases, match thresholds were established based on clerical record review for each block individually. Match variables included incident date, destination facility, date of birth, sex, race, and ethnicity.

RESULTS

Of the 14,603 cases of OHCA we identified in CEMSIS, 91 (0.6%) duplicate records were excluded. Overall, 46% of the data used in the linkage algorithm were missing in CEMSIS. We linked 4,961/14,512 (34.2%) records. Linkage rates varied significantly by local EMS agency, ranging from 1.4 to 61.1% (OR for linkage 0.009-0.76; p < 0.0001). After excluding the local EMS agency with the outlying low linkage rate, we linked 4,934/12,596 (39.2%) records.

CONCLUSION

Probabilistic linkage of CEMSIS prehospital data with OSHPD outcomes data was severely limited by the completeness of the EMS data. States and EMS agencies should aim to overcome data limitations so that more effective linkages are possible.

Minimizing transfer time to an ST segment elevation myocardial infarction-receiving center: a modified Delphi consensus

Of patients with ST segment elevation myocardial infarction (STEMI), approximately two thirds present to a hospital not capable of percutaneous coronary intervention. Transfer to a STEMI-receiving center delays time to reperfusion in patients with STEMI, but factors that affect this delay have not been well studied. We performed a 3-round modified Delphi study to identify system practices that minimize transfer time to a STEMI-receiving center. A comprehensive literature review was used to identify candidate system practices. Emergency medical services, emergency medicine, and cardiology experts were invited to participate. Consensus was defined as 80% agreement that a variable was "very important (5)" or "important (4)" with a mean score ≥ 4.25 or 80% agreement that a variable was "not important (1)" or "somewhat important (2)" with a mean score ≤ 1.75. In round 1, participants rated the candidate items and suggested additional items. Individual feedback was provided, and participants discussed items via conference calls before rating them again in round 2. In round 3, participants ranked the consensus items from rounds 1-2 from most to least important, and the mean score for each item was calculated. Of the 98 experts invited, 29 participated in round 1, 22 in round 2, and 14 in round 3. Participants identified 18 system practices that they agree are critical in minimizing transfer time to STEMI-receiving centers, with the most important being performance of a prehospital electrocardiogram and having established transfer protocols. These factors should be considered in the development of STEMI systems of care.

Impact of pre-procedural cardiopulmonary instability in patients with acute myocardial infarction undergoing primary percutaneous coronary intervention (from the Harmonizing Outcomes With Revascularization and Stents in Acute Myocardial Infarction Trial)

Rapid reperfusion with primary percutaneous coronary intervention improves survival in patients with ST-segment elevation myocardial infarction. Preprocedural cardiopulmonary instability and adverse events (IAE) may delay reperfusion time and worsen prognosis. The aim of this study was to evaluate the relation between preprocedural cardiopulmonary IAE, door-to-balloon time (DBT), and outcomes in the Harmonizing Outcomes With Revascularization and Stents in AMI (HORIZONS-AMI) trial. Preprocedural cardiopulmonary IAE included sustained ventricular or supraventricular tachycardia or fibrillation requiring cardioversion or defibrillation, heart block or bradycardia requiring pacemaker implantation, severe hypotension requiring vasopressors or intra-aortic balloon counterpulsation, respiratory failure requiring mechanical ventilation, and cardiopulmonary resuscitation. Three-year outcomes of patients with and without IAE according to DBT were compared. Among 3,602 patients, 159 (4.4%) had ≥1 IAE. DBT did not differ significantly in patients with and without IAE; however, patients with IAE were less likely to have Thrombolysis In Myocardial Infarction (TIMI) grade 3 flow after percutaneous coronary intervention. Mortality at 3 years was significantly higher in patients with versus those without IAE (17.0% vs 6.3%, p<0.0001), and IAE was an independent predictor of mortality, whereas DBT was not. However, a significant interaction was present such that 3-year mortality was reduced in patients with DBT<99 minutes (the median) versus ≥99 minutes to a greater extent in patients with IAE (9.9% vs 20.7%, hazard ratio 0.43, 95% confidence interval 0.16 to 1.16) compared with those without IAE (5.0% vs 7.2%, hazard ratio 0.69, 95% confidence interval 0.50 to 0.95) (p for interaction=0.004). In conclusion, IAE before PCI is an independent predictor of death and identifies a high-risk group in whom faster reperfusion may be particularly important to improve survival.

Use of prehospital 12-lead electrocardiography and treatment times among ST-elevation myocardial infarction patients with atypical symptoms

OBJECTIVES

Guidelines advise that a prehospital electrocardiogram (ECG) should be obtained in any patients with chest pain, yet up to 20% of patients with ST-elevation myocardial infarction (STEMI) do not present with chest pain. The objective was to determine the association of atypical presentations in the prehospital setting on the likelihood of receiving a prehospital ECG and subsequent time to reperfusion therapy.

METHODS

This study used a data set that linked prehospital medical information from a statewide EMS data system with a clinical registry of treatment and outcomes data for patients with STEMI. Among 2,639 STEMI patients from 2008 to 2010, the association between non-chest pain presentations, prehospital ECG use, and reperfusion times among patients undergoing primary percutaneous coronary intervention (PCI) were examined. Inverse probability weights were used to account for observed baseline confounders.

RESULTS

Overall, 318 of 2,639 patients (12.1%) presented without chest pain. A prehospital ECG was obtained in 2,021 of 2,321 (87.1%) patients with chest pain compared with only 230 of 318 (72.3%) without chest pain (odds ratio [OR] = 2.24, 95% confidence interval [CI] = 1.69 to 2.98). Among patients without chest pain, those who received a prehospital ECG had significantly shorter first medical contact (FMC) to device times (30.9% < 90 minutes vs. 11.4% > 90 minutes, adjusted OR = 2.81, 95% CI = 1.29 to 6.11, p < 0.01).

CONCLUSIONS

Over one-quarter of STEMI patients presenting without chest pain did not receive prehospital ECGs and had significantly longer FMC to device times. Future efforts are needed to promote the use of prehospital ECGs to achieve more rapid identification of STEMI patients with atypical presentations in the prehospital setting.