Evaluation of elderly specific pre-hospital trauma triage criteria: a systematic review

Abstract Background Pre-hospital identification of major trauma in elderly patients is key for delivery of optimal care, however triage of this group is challenging. Elderly-specific triage criteria may be valuable. This systematic review aimed to summarise the published pre-hospital elderly-specific trauma triage tools and evaluate their sensitivity and specificity and associated clinical outcomes. Methods MEDLINE and EMBASE databases were searched using predetermined criteria (PROSPERO: CRD42019140879). Two authors independently assessed search results, performed data extraction, risk of bias and quality assessments following the Grading of Recommendations, Assessment, Development and Evaluation system. Results 801 articles were screened and 11 studies met eligibility criteria, including 1,332,300 patients from exclusively USA populations. There were eight unique elderly-specific triage criteria reported. Most studies retrospectively applied criteria to trauma databases, with few reporting real-world application. The Ohio Geriatric Triage Criteria was reported in three studies. Age cut-off ranged from 55 to 70 years with ≥ 65 most frequently reported. All reported existing adult criteria with modified physiological parameters using higher thresholds for systolic blood pressure and Glasgow coma scale, although the values used varied. Three criteria added co-morbidity or anti-coagulant/anti-platelet use considerations. Modifications to anatomical or mechanism of injury factors were used by only one triage criteria. Criteria sensitivity ranged from 44 to 93%, with a median of 86.3%, whilst specificity was generally poor (median 54%). Scant real-world data showed an increase in patients meeting triage criteria, but minimal changes to patient transport destination and mortality. All studies were at risk of bias and assessed of “very low” or “low” quality. Conclusions There are several published elderly-specific pre-hospital trauma triage tools in clinical practice, all developed and employed in the USA. Consensus exists for higher thresholds for physiological parameters, however there was variability in age-cut offs, triage criteria content, and tool sensitivity and specificity. Although sensitivity was improved over corresponding ‘adult’ criteria, specificity remained poor. There is a paucity of published real-world data examining the effect on patient care and clinical outcomes of elderly-specific triage criteria. There is uncertainty over the optimal elderly triage tool and further study is required to better inform practice and improve patient outcomes.

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Real-World Data on Clinical Outcomes of Patients with Liver Cancer: A Prospective Validation of the National Cancer Centre Singapore Consensus Guidelines for the Management of Hepatocellular Carcinoma

Liver Cancer ◽

10.1159/000514400 ◽

2021 ◽

pp. 1-16

Author(s):

Xin Hui Chew ◽

Rehena Sultana ◽

Eshani N. Mathew ◽

David Chee Eng Ng ◽

Richard H.G. Lo ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Cancer ◽

Clinical Outcomes ◽

Real World ◽

Compliance Rate ◽

Locally Advanced ◽

Consensus Guidelines ◽

Real World Data ◽

World Data ◽

Cancer Centre

Introduction: Real-world management of patients with hepatocellular carcinoma (HCC) is crucially challenging in the current rapidly evolving clinical environment which includes the need for respecting patient preferences and autonomy. In this context, regional/national treatment guidelines nuanced to local demographics have increasing importance in guiding disease management. We report here real-world data on clinical outcomes in HCC from a validation of the Consensus Guidelines for HCC at the National Cancer Centre Singapore (NCCS). Method: We evaluated the NCCS guidelines using prospectively collected real-world data, comparing the efficacy of treatment received using overall survival (OS) and progression-free survival (PFS). Treatment outcomes were also independently evaluated against 2 external sets of guidelines, the Barcelona Clinic Liver Cancer (BCLC) and Hong Kong Liver Cancer (HKLC). Results: Overall treatment compliance to the NCCS guidelines was 79.2%. Superior median OS was observed in patients receiving treatment compliant with NCCS guidelines for early (nonestimable vs. 23.5 months p < 0.0001), locally advanced (28.1 vs. 22.2 months p = 0.0216) and locally advanced with macrovascular invasion (10.3 vs. 3.3 months p = 0.0013) but not for metastatic HCC (8.1 vs. 6.8 months p = 0.6300), but PFS was similar. Better clinical outcomes were seen in BCLC C patients who received treatment compliant with NCCS guidelines than in patients with treatment only allowed by BCLC guidelines (median OS 14.2 vs. 7.4 months p = 0.0002; median PFS 6.1 vs. 4.0 months p = 0.0286). Clinical outcomes were, however, similar for patients across all HKLC stages receiving NCCS-recommended treatment regardless of whether their treatment was allowed by HKLC. Conclusion: The high overall compliance rate and satisfactory clinical outcomes of patients managed according to the NCCS guidelines confirm its validity. This validation using real-world data considers patient and treating clinician preferences, thus providing a realistic analysis of the usefulness of the NCCS guidelines when applied in the clinics.

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Utilisation of real-world data from heart failure registries in OECD countries - A systematic review

IJC Heart & Vasculature ◽

10.1016/j.ijcha.2018.02.006 ◽

2018 ◽

Vol 19 ◽

pp. 90-97 ◽

Cited By ~ 2

Author(s):

Xiaoyang Du ◽

Adina Khamitova ◽

Mattias Kyhlstedt ◽

Sun Sun ◽

Mathilde Sengoelge

Keyword(s):

Heart Failure ◽

Systematic Review ◽

Real World ◽

Oecd Countries ◽

Real World Data ◽

World Data

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P0816CLINICAL CHARACTERISTICS AND EGFR AND UACR DISTRIBUTION ACCORDING TO THE 2012 KDIGO CKD CLASSIFICATION: A REPORT FROM THE US DISCOVER CKD COHORT

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfaa142.p0816 ◽

2020 ◽

Vol 35 (Supplement_3) ◽

Author(s):

Juan Jose Garcia Sanchez ◽

Juan Jesus Carrero ◽

Supriya Kumar ◽

Roberto Pecoits-Filho ◽

Glen James ◽

...

Keyword(s):

Kidney Disease ◽

Real World ◽

Patient Characteristics ◽

Study Cohort ◽

Diagnostic Code ◽

Inclusion Criteria ◽

Real World Data ◽

Electronic Health Record Data ◽

World Data ◽

Co Morbidity

Abstract Background and Aims In 2012, the Kidney Disease Improving Global Outcomes (KDIGO) guidelines recommended categorising and prognosticating chronic kidney disease (CKD) based on estimated glomerular filtration rate (eGFR) and urine albumin to creatinine ratio (UACR). Contemporary studies describing the prevalence and characteristics of patients with CKD categorised according KDIGO 2012 and how studies of new pharmacotherapies relate to these categories are scarce. One such new therapy class of key interest are the sodium glucose co-transporter 2 inhibitors (SGLT-2i), shown to delay the progression to renal failure and prevent cardiovascular/renal death in patients with CKD. We aimed to describe patient characteristics and the prevalence of CKD according to the 2012 KDIGO categories in a large real-world US cohort of patients with CKD (part A). We also describe a subset of the population according to the DAPA-CKD trial inclusion criteria (eGFR [25-75ml/min/1.73m2] and UACR [200-5000mg/g]) (part B). Method DISCOVER-CKD is an international observational study in patients with CKD. The DISCOVER-CKD retrospective US cohort of patients was extracted using real-world data from the integrated Limited Claims and Electronic Health Record data (IBM Health, Armonk, NY) and HealthVerity. Patients were aged ≥18 years, with ≥1 UACR measure. For part A, required first diagnostic code of CKD (Stages 3A, 3B, 4, 5, or ESRD) or two eGFR of <75 mL/min/1.73 m2 recorded at least 90 days apart and for part B, two measures of eGFR 25-75 mL/min/1.73 m2 recorded at least 90 days apart between 1st January 2008 and September 2018. Index date was diagnostic code or 2nd eGFR. The first UACR, recorded +/-12 months of index, was used to categorise patients. Descriptive analyses were used to summarise prevalence and patient characteristics. Results Of the overall study cohort (N=4330, 49.1% women, mean age 65.3±10.64 years), by KDIGO categories (part A): 85.7% (n=3601) had normal to mildly increased albuminuria, 11.0% (n=463) had moderately increased albuminuria and 3.3% (n=137) had severely increased albuminuria (Figure 1). 4.6% (n=193) fulfilled DAPA-CKD trial inclusion criteria (part B). In both populations, the most common comorbidities were hypertension (HTN, 73.0% for both) and type 2 diabetes (T2D, 57.6% and 56.2%, respectively). Anti-hypertensive drugs were frequently used (76.4% and 76.9%, respectively). Conclusion This study, utilising real-world data, adds to the scarcity of knowledge reporting the characteristics of patients with CKD in different eGFR and UACR strata according to the KDIGO 2012 definitions. We observed a trend in higher UACR in the group of patients with lower eGFR and report a high prevalence of T2D and HTN in the study population, demonstrating the high co-morbidity burden in patients, for whom new therapies may be beneficial.

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S0899 Meta-Analysis and Systematic Review: Real World Data Rates of Deep Remission in IBD With Anti-TNFα

The American Journal of Gastroenterology ◽

10.14309/01.ajg.0000705644.98291.13 ◽

2020 ◽

Vol 115 (1) ◽

pp. S462-S463

Author(s):

Omeed Alipour ◽

Alakh Gulati ◽

Ling Shao ◽

Bing Zhang

Keyword(s):

Systematic Review ◽

Real World ◽

Meta Analysis ◽

Real World Data ◽

World Data ◽

Data Rates

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Abatacept retention and clinical outcomes in rheumatoid arthritis: real-world data from the German cohort of the ACTION study and a comparison with other participating countries

Clinical Rheumatology ◽

10.1007/s10067-019-04648-5 ◽

2019 ◽

Vol 38 (11) ◽

pp. 3049-3059 ◽

Cited By ~ 1

Author(s):

Rieke Alten ◽

Eugen Feist ◽

Hanns-Martin Lorenz ◽

Hubert Nüßlein ◽

Reinhard E. Voll ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Clinical Outcomes ◽

Real World ◽

Real World Data ◽

World Data

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Leveraging real world data and AIML to inform smart patient care in oncology.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e20002 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e20002-e20002

Author(s):

Li Zhou ◽

Rob Steen ◽

Lynn Lu

Keyword(s):

Patient Care ◽

Predictive Model ◽

Real World ◽

Model Performance ◽

Treatment Decision ◽

Treatment Patterns ◽

Real World Data ◽

World Data ◽

Co Morbidity ◽

Low Probability

e20002 Background: Identifying optimal therapy options can help maximize treatment outcomes. Finding ways to help improve treatment decision is of great value to achieve better patient care. With the availability of robust patient real world data and the application of state of the art Artificial Intelligence and Machine Learning (AIML) technology, new opportunities have emerged for a broad spectrum of research needs from oncology R&D to commercialization. To illustrate the above advancements, this study identified patients diagnosed with CLL who may progress to next line of treatment in the near future (e.g. future 3 months). More importantly, we can identify treatment patterns which are more effective in treating different types of CLL patients. Methods: This study includes multiple steps which have already been analyzed for feasibility: 1. Collect CLL patients. IQVIA's real world data contains ~60,000 active CLL treated patients. ~2,000 patients have progressed line of treatment in 3 month. 2. Define patients into positive and negative cohorts based on those who have/have not advanced to line L2+. 3. Determine patient profiles based on treatment regimens, symptoms, lab tests, doctor visits, hospital visits, and co-morbidity, etc. 4. Select patient and treatment features to fit an AIML predictive model. 5. Test different algorithms to achieve best model results and validate model performance. 6. Score and classify CLL patients into high and low probability based on the predictive model. 7. Match patients based on feature importance and compare regimens between positive and negative cohort. Results: Model accuracy is above 90%. Top clinical features are calculated for each patient. Optimum treatment patterns between high and low probability patients are identified, with controlling patient key features. Conclusions: Conclusions from this study is expected to yield deeper insight into more tailored treatments by patient type. CLL patients started with oral therapy(targeting) have better response than other treatments.

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