Clinical prediction rules in practice: review of clinical guidelines and survey of GPs

Plüddemann, Annette; Wallace, Emma; Bankhead, C; Keogh, Claire; Windt, D.A.W.M. van der; Lasserson, Daniel; Galvin, Rose; Moschetti, Ivan; Kearley, Karen; O'Brien, Kirsty K; Sanders, Sharon; Mallett, Susan; Malanda, U.L.; Thompson, Matthew; Fahey, Tom; Stevens, R J

doi:10.3399/bjgp14x677860

Cited by 38 publications

(59 citation statements)

References 87 publications

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“…16,17 An exception may be the use of simple stroke risk scores for atrial fibrillation patients which are more widely used 18 despite modest to moderate and highly variable discriminative power demonstrated in different validation studies. 19 Model complexity and skepticism regarding the accuracy of the models in providers’ unique practice settings are believed to limit use of risk scores.…”

Section: Discussionmentioning

confidence: 99%

Inpatient Mortality Risk Scores and Postdischarge Events in Hospitalized Heart Failure Patients

Win

Hussain

Hebl

et al. 2017

Circ: Heart Failure

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Background The Acute Decompensated Heart Failure National Registry (ADHERE) and Get with the Guidelines (GWTG) registries have developed simple heart failure (HF) in-hospital mortality risk scores. We hypothesized that HF scores predictive of in-hospital mortality would perform as well for early post-discharge mortality risk stratification. Methods and Results In this single center, community based, retrospective study of all consecutive primary HF hospitalizations (6203 hospitalizations in 3745 patients) from 2000 to 2013, the ADHERE and GWTG risk scores were calculated from admission data. There were 176 (3.0%) and 399 (6.7%), 869 (14.7%) and 1,272 (21.5%) deaths in-hospital and at 30, 90 and 180 days post-discharge respectively. The GWTG but not ADHERE risk score was well-calibrated for in-hospital mortality. Both the ADHERE (c-statistic 0.66 and 0.67, 0.64, 0.64) and GWTG (c-statistic 0.74 and 0.73, 0.71, 0.70) HF risk scores were similarly predictive of in-hospital and 30, 90 and 180-day post-discharge mortality. The ADHERE risk score identified 10% and the GWTG risk score identified 20% of hospitalizations where 180 day post-discharge mortality was 50%, a prognostic bench mark for hospice referral. In contrast, hospitalizations characterized as lowest risk by the ADHERE (57% of hospitalizations; 180 day mortality 16.2%) or GWTG score (20% of hospitalizations; 180 day mortality 8.0%) had substantially lower mortality (odds ratios high versus low risk of 5–8 (ADHERE) and 11–18 (GWTG) across time points, p<0.0001 for all). Conclusion The simple ADHERE and GWTG scores stratify hospitalized HF patients for both in-patient and early post-discharge mortality risk, allowing comprehensive risk assessment on admission.

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Section: Discussionmentioning

confidence: 99%

Inpatient Mortality Risk Scores and Postdischarge Events in Hospitalized Heart Failure Patients

Win

Hussain

Hebl

et al. 2017

Circ: Heart Failure

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“…10 Types of CPRs used in clinical practice varies, but use has been dictated by perceived clinical utility, familiarity, and local policy requirements. 11 Prioritizing the evaluation of select clinically useful, adequately validated CPRs with proven predictive accuracy could add to this evidence base and facilitate, if appropriate, the inclusion of these select CPRs into clinical practice guidelines and potentially widespread clinical use.…”

Section: N This Issue Of Annals Of Family Medicine An Article Bymentioning

confidence: 99%

Clinical Prediction Rules: Challenges, Barriers, and Promise

Wallace

Johansen

2018

Ann Fam Med

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“…We estimated cardiovascular risk using the Framingham, QRISK2 and SCORE risk equations, (9)(10)(11) which are =commonly used in UK general practice. (27) We compared risk estimates calculated using systolic BP values obtained using different measurement techniques in the clinic, at home or through ABPM (Box 1). The primary comparison was risk calculated using BP measured as in the derivation study of each risk score with risk calculated using daytime ambulatory BP (due to its recommended use in diagnosis of hypertension).…”

Section: Discussionmentioning

confidence: 99%

Using out-of-office blood pressure measurements in established cardiovascular risk scores: a secondary analysis of data from two blood pressure monitoring studies

et al. 2019

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Item Type Article Authors Stevens, S.L.; Stevens, R.J.; de Leeuw, P.; Kroon, A.A.; Greenfield, S.; Mohammed, Mohammed A.; Gill, P.; Verberk, W.J.; McManus, R.J. Citation Stevens SL, Stevens RJ, de Leeuw P et al (2019) Using outof-office blood pressure measurements in established cardiovascular risk scores: implications for practice. British Journal of General Practice. 69(683): e381-e388. Rights AbstractBackground: Blood pressure (BP) measurement is increasingly carried out through home or ambulatory monitoring, yet existing cardiovascular risk scores were developed for use with measurements obtained in clinic.Aim: To describe differences in cardiovascular risk estimates obtained using ambulatory or home BP measurements instead of clinic readings.Design and setting: Secondary analysis of data from adults aged 30-84 without prior history of cardiovascular disease (CVD) in two BP monitoring studies (BP-Eth and HOMERUS). Method:The primary comparison was Framingham risk calculated using BP measured as in the Framingham study or daytime ambulatory BP measurements. The QRISK2 and SCORE risk equations were also studied. Statistical and clinical significance were determined using the Wilcoxon signedrank test and scatter plots respectively. Results:In 442 BP-Eth patients (mean age = 58 years, 50% female) the median absolute difference in 10-year Framingham cardiovascular risk calculated using BP measured as in the Framingham study or daytime ambulatory BP measurements was 1.84% (interquartile range 0.65 to 3.63, p=0.67). Only 31/ 442 (7.0%) of patients were reclassified across the 10% risk treatment threshold. In 165 HOMERUS patients (mean age = 56 years, 46% female) the median difference in 10-year risk was 2.76% (IQR 1.19 to 6.39, p<0.001) and only 8/165 (4.8%) of patient were reclassified.Conclusion: Estimates of cardiovascular risk are similar when calculated using BP measurements obtained as in the risk score derivation study or through ambulatory monitoring. Further research is required to determine if differences in estimated risk would meaningfully influence risk score accuracy. How this fits in:Out-of-office blood pressure (BP) measurement is increasingly common but cardiovascular risk scores were developed using clinic BP measurements. It is unclear how estimates of cardiovascular risk may be affected by the use of out-of-office measurements in risk prediction algorithms. We have shown that differences in risk are generally small and few patients are reclassified across treatment thresholds when using different BP measurements. Extra care on the part of clinicians may be warranted in subgroups with large BP differences or those with risk estimates close to risk thresholds.

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Clinical prediction rules in practice: review of clinical guidelines and survey of GPs

Cited by 38 publications

References 87 publications

Inpatient Mortality Risk Scores and Postdischarge Events in Hospitalized Heart Failure Patients

Inpatient Mortality Risk Scores and Postdischarge Events in Hospitalized Heart Failure Patients

Clinical Prediction Rules: Challenges, Barriers, and Promise

Using out-of-office blood pressure measurements in established cardiovascular risk scores: a secondary analysis of data from two blood pressure monitoring studies

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