Dataset Information

Systematic review of the effects of care provided with and without diagnostic clinical prediction rules.

ABSTRACT:

Background

Diagnostic clinical prediction rules (CPRs) are worthwhile if they improve patient outcomes or provide benefits such as reduced resource use, without harming patients. We conducted a systematic review to assess the effects of diagnostic CPRs on patient and process of care outcomes.

Methods

We searched electronic databases and a trial registry and performed citation and reference checks, for randomised trials comparing a diagnostic strategy with and without a CPR. Included studies were assessed for risk of bias and similar studies meta-analysed.

Results

Twenty-seven studies evaluating diagnostic CPRs for 14 conditions were included. A clinical management decision was the primary outcome in the majority of studies. Most studies were judged to be at high or uncertain risk of bias on ?3 of 6 domains. Details of study interventions and implementation were infrequently reported.For suspected Group A Streptococcus throat infection, diagnostic CPRs reduced symptoms (1 study) and antibiotic prescriptions (5 studies, RR 0.86, 95% CI 0.75 to 0.99). For suspected cardiac chest pain, diagnostic strategies incorporating a CPR improved early discharge rates (1 study), decreased objective cardiac testing (1 study) and decreased hospitalisations (1 study). For ankle injuries, Ottawa Ankle Rules reduced radiography when used with clinical examination (1 study) but had no effect on length of stay as a triage test (1 study). For suspected acute appendicitis, CPRs had no effect on rates of perforated appendix (1 study) or the number of non-therapeutic operations (5 studies, RR 0.68, 95% CI 0.43 to 1.08). For suspected pneumonia, CPRs reduced antibiotic prescribing without unfavourable outcomes (3 studies). For children with possible serious bacterial infection, diagnostic CPRs did not improve process of care outcomes (3 studies).

Conclusion

There are few randomised trials of diagnostic CPRs, and patient outcomes are infrequently reported. Diagnostic CPRs had a positive effect on process outcomes in some clinical conditions; however, many studies were at unclear or high risk of bias and the results may be context specific. Future studies should seek to detail how the CPR might alter the diagnostic pathway, report effects on both patient and process outcomes, and improve reporting of the study interventions and implementation.

Trial registration

The protocol for this review was not registered with PROSPERO, the international prospective register of systematic review protocols. The review was conceived and protocol prepared prior to the launch of PROSPERO in February 2011.

SUBMITTER: Sanders SL

PROVIDER: S-EPMC6460683 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Systematic review of the effects of care provided with and without diagnostic clinical prediction rules.

Sanders Sharon L SL Rathbone John J Bell Katy J L KJL Glasziou Paul P PP Doust Jenny A JA

Diagnostic and prognostic research 20170426

<h4>Background</h4>Diagnostic clinical prediction rules (CPRs) are worthwhile if they improve patient outcomes or provide benefits such as reduced resource use, without harming patients. We conducted a systematic review to assess the effects of diagnostic CPRs on patient and process of care outcomes.<h4>Methods</h4>We searched electronic databases and a trial registry and performed citation and reference checks, for randomised trials comparing a diagnostic strategy with and without a CPR. Includ ...[more]

PMID: 31093542

Similar Datasets

Project description:Diagnostic clinical prediction rules (CPRs) are developed to improve diagnosis or decrease diagnostic testing. Whether, and in what situations diagnostic CPRs improve upon clinical judgment is unclear.We searched MEDLINE, Embase and CINAHL, with supplementary citation and reference checking for studies comparing CPRs and clinical judgment against a current objective reference standard. We report 1) the proportion of study participants classified as not having disease who hence may avoid further testing and or treatment and 2) the proportion, among those classified as not having disease, who do (missed diagnoses) by both approaches. 31 studies of 13 medical conditions were included, with 46 comparisons between CPRs and clinical judgment. In 2 comparisons (4%), CPRs reduced the proportion of missed diagnoses, but this was offset by classifying a larger proportion of study participants as having disease (more false positives). In 36 comparisons (78%) the proportion of diagnoses missed by CPRs and clinical judgment was similar, and in 9 of these, the CPRs classified a larger proportion of participants as not having disease (fewer false positives). In 8 comparisons (17%) the proportion of diagnoses missed by the CPRs was greater. This was offset by classifying a smaller proportion of participants as having the disease (fewer false positives) in 2 comparisons. There were no comparisons where the CPR missed a smaller proportion of diagnoses than clinical judgment and classified more participants as not having the disease. The design of the included studies allows evaluation of CPRs when their results are applied independently of clinical judgment. The performance of CPRs, when implemented by clinicians as a support to their judgment may be different.In the limited studies to date, CPRs are rarely superior to clinical judgment and there is generally a trade-off between the proportion classified as not having disease and the proportion of missed diagnoses. Differences between the two methods of judgment are likely the result of different diagnostic thresholds for positivity. Which is the preferred judgment method for a particular clinical condition depends on the relative benefits and harms of true positive and false positive diagnoses.

Project description:OBJECTIVE:To identify and assess the performance of clinical decision rules (CDR) for chest pain in general practice. DESIGN:Systematic review of diagnostic studies. DATA SOURCES:Medline/Pubmed, Embase/Ovid, CINAHL/EBSCO and Google Scholar up to October 2018. STUDY SELECTION:Studies that assessed CDRs for intermittent-type chest pain and for rule out of acute coronary syndrome (ACS) applicable in general practice, thus not relying on advanced laboratory, computer or diagnostic testing. REVIEW METHODS:Reviewers identified studies, extracted data and assessed the quality of the evidence (using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2)), independently and in duplicate. RESULTS:Eight studies comprising five CDRs met the inclusion criteria. Three CDRs are designed for rule out of coronary disease in intermittent-type chest pain (Gencer rule, Marburg Heart Score, INTERCHEST), and two for rule out of ACS (Grijseels rule, Bruins Slot rule). Studies that examined the Marburg Heart Score had the highest methodological quality with consistent sensitivity (86%-91%), specificity (61%-81%) and positive (23%-35%) and negative (97%-98%) predictive values (PPV and NPV). The diagnostic performance of Gencer (PPV: 20%-34%, NPV: 95%-99%) and INTERCHEST (PPV: 35%-43%, NPV: 96%-98%) appear comparable, but requires further validation. The Marburg Heart Score was more sensitive in detecting coronary disease than the clinical judgement of the general practitioner. The performance of CDRs that focused on rule out of ACS were: Grijseels rule (sensitivity: 91%, specificity: 37%, PPV: 57%, NPV: 82%) and Bruins Slot (sensitivity: 97%, specificity: 10%, PPV: 23%, NPV: 92%). Compared with clinical judgement, the Bruins Slot rule appeared to be safer than clinical judgement alone, but the study was limited in sample size. CONCLUSIONS:In general practice, there is currently no clinical decision aid that can safely rule out ACS. For intermittent chest pain, several rules exist, of which the Marburg Heart Score has been most extensively tested and appears to outperform clinical judgement alone.

Project description:Background: Our goal was to identify existing clinical prediction rules for predicting hospitalisation due to lower respiratory tract infection (LRTI) in children in primary care, guiding antibiotic therapy. A validation of these rules was then performed in a novel cohort of children presenting to primary care in Malawi with World Health Organisation clinically defined pneumonia. Methods: MEDLINE & EMBASE databases were searched for studies on the development, validation and clinical impact of clinical prediction models for hospitalisation in children with lower respiratory tract infection between January 1st1946-June 30th 2021. Two reviewers screened all abstracts and titles independently. The study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews & Meta-Analyses guidelines. The BIOTOPE cohort (BIOmarkers TO diagnose PnEumonia) recruited children aged 2-59 months with WHO-defined pneumonia from two primary care facilities in Mzuzu, Malawi. Validation of identified rules was undertaken in this cohort. Findings: 1023 abstracts were identified. Following the removal of duplicates, a review of 989 abstracts was conducted leading to the identification of one eligible model. The CHARMS checklist for prediction modelling studies was utilized for evaluation. The area under the curve (AUC) of the STARWAVe rule for hospitalisation in BIOTOPE was found to be 0.80 (95% C.I of 0.75-0.85). The AUC of STARWAVe for a confirmed diagnosis of bacterial pneumonia was 0.39 (95% C.I 0.25-0.54). Interpretation: This review highlights the lack of clinical prediction rules in this area. The STARWAVe rule identified was useful in predicting hospitalisation from bacterial infection as defined. However, in the absence of a gold standard indicator for bacterial LRTI, this is a reasonable surrogate and could lead to reductions in antibiotic prescription rates, should clinical impact studies prove its utility. Further work to determine the clinical impact of STARWAVe and to identify diagnostic tests for bacterial LRTI in primary care is required.

Project description:ObjectiveTo validate all diagnostic prediction models for ruling out pulmonary embolism that are easily applicable in primary care.DesignSystematic review followed by independent external validation study to assess transportability of retrieved models to primary care medicine.Setting300 general practices in the Netherlands.ParticipantsIndividual patient dataset of 598 patients with suspected acute pulmonary embolism in primary care.Main outcome measuresDiscriminative ability of all models retrieved by systematic literature search, assessed by calculation and comparison of C statistics. After stratification into groups with high and low probability of pulmonary embolism according to pre-specified model cut-offs combined with qualitative D-dimer test, sensitivity, specificity, efficiency (overall proportion of patients with low probability of pulmonary embolism), and failure rate (proportion of pulmonary embolism cases in group of patients with low probability) were calculated for all models.ResultsTen published prediction models for the diagnosis of pulmonary embolism were found. Five of these models could be validated in the primary care dataset: the original Wells, modified Wells, simplified Wells, revised Geneva, and simplified revised Geneva models. Discriminative ability was comparable for all models (range of C statistic 0.75-0.80). Sensitivity ranged from 88% (simplified revised Geneva) to 96% (simplified Wells) and specificity from 48% (revised Geneva) to 53% (simplified revised Geneva). Efficiency of all models was between 43% and 48%. Differences were observed between failure rates, especially between the simplified Wells and the simplified revised Geneva models (failure rates 1.2% (95% confidence interval 0.2% to 3.3%) and 3.1% (1.4% to 5.9%), respectively; absolute difference -1.98% (-3.33% to -0.74%)). Irrespective of the diagnostic prediction model used, three patients were incorrectly classified as having low probability of pulmonary embolism; pulmonary embolism was diagnosed only after referral to secondary care.ConclusionsFive diagnostic pulmonary embolism prediction models that are easily applicable in primary care were validated in this setting. Whereas efficiency was comparable for all rules, the Wells rules gave the best performance in terms of lower failure rates.

Project description:BackgroundClinical examination findings are used in primary care to give an initial diagnosis to patients with low back pain and related leg symptoms. The purpose of this study was to develop best evidence Clinical Diagnostic Rules (CDR] for the identification of the most common patho-anatomical disorders in the lumbar spine; i.e. intervertebral discs, sacroiliac joints, facet joints, bone, muscles, nerve roots, muscles, peripheral nerve tissue, and central nervous system sensitization.MethodsA sensitive electronic search strategy using MEDLINE, EMBASE and CINAHL databases was combined with hand searching and citation tracking to identify eligible studies. Criteria for inclusion were: persons with low back pain with or without related leg symptoms, history or physical examination findings suitable for use in primary care, comparison with acceptable reference standards, and statistical reporting permitting calculation of diagnostic value. Quality assessments were made independently by two reviewers using the Quality Assessment of Diagnostic Accuracy Studies tool. Clinical examination findings that were investigated by at least two studies were included and results that met our predefined threshold of positive likelihood ratio ≥ 2 or negative likelihood ratio ≤ 0.5 were considered for the CDR.ResultsSixty-four studies satisfied our eligible criteria. We were able to construct promising CDRs for symptomatic intervertebral disc, sacroiliac joint, spondylolisthesis, disc herniation with nerve root involvement, and spinal stenosis. Single clinical test appear not to be as useful as clusters of tests that are more closely in line with clinical decision making.ConclusionsThis is the first comprehensive systematic review of diagnostic accuracy studies that evaluate clinical examination findings for their ability to identify the most common patho-anatomical disorders in the lumbar spine. In some diagnostic categories we have sufficient evidence to recommend a CDR. In others, we have only preliminary evidence that needs testing in future studies. Most findings were tested in secondary or tertiary care. Thus, the accuracy of the findings in a primary care setting has yet to be confirmed.

Dataset Information

Systematic review of the effects of care provided with and without diagnostic clinical prediction rules.

Background

Methods

Results

Conclusion

Trial registration

Publications

Systematic review of the effects of care provided with and without diagnostic clinical prediction rules.

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