Understanding general practitioners’ views and experiences of using clinical prediction rules in the management of respiratory infections: a qualitative study

Background:Respiratory tract infections (RTIs) account for 60% of antibiotic prescribing in primary care. Several clinical prediction rules (CPRs) have been developed to help reduce unnecessary prescribing for RTIs, but there are a lack of studies exploring whether or how these CPRs are being used in UK general practice.Aim:To explore UK GPs’ views and experiences with regards to RTI CPRs and to identify barriers and facilitators to their use in practice.Design & setting:A qualitative analysis of interviews with in-hours GPs working in the South and South West of England.Method:Semi-structured qualitative telephone interviews were conducted, digitally recorded, transcribed verbatim and analysed using an inductive thematic approach. Patient and public involvement representatives contributed to study design and interpretation of findings.Results:Thirty-two GPs were interviewed. Some CPRs were more commonly used than others. Participants used CPRs to facilitate patient-clinician discussion, confirm and support their decision, and document the consultation. GPs also highlighted concerns including lack of time, inability of CPRs to incorporate patient complexity, a shift in focus from the patient during consultations, and limited use in remote consultation (during the COVID-19 pandemic).Conclusion:This study highlights the need for user-friendly CPRs that are readily integrated into computer systems, and easily embedded into routine practice to complement clinical decision making. Existing CPRs need to be validated for other populations where demographics and clinical characteristics may differ as well different settings including remote consultations and self-assessment.

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Bacterial meningitis in Sudanese children; critical evaluation of the clinical decision using clinical prediction rules

BMC Pediatrics ◽

10.1186/s12887-019-1684-3 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Nada Abdelghani Abdelrahim ◽

Imad Mohammed Fadl-Elmula ◽

Hassan Mohammed Ali

Keyword(s):

Bacterial Meningitis ◽

Critical Evaluation ◽

Clinical Decision ◽

Clinical Prediction ◽

Clinical Prediction Rules ◽

Prediction Rules

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The Effect of Amoxicillin in Adult Patients Presenting to Primary Care with Acute Cough Predicted to Have Pneumonia or a Combined Viral-Bacterial Infection

Antibiotics ◽

10.3390/antibiotics10070817 ◽

2021 ◽

Vol 10 (7) ◽

pp. 817

Author(s):

Robin Bruyndonckx ◽

Beth Stuart ◽

Paul Little ◽

Niel Hens ◽

Margareta Ieven ◽

...

Keyword(s):

Primary Care ◽

Bacterial Infection ◽

Controlled Trial ◽

Symptom Duration ◽

Antibiotic Prescribing ◽

Clinical Prediction ◽

Acute Cough ◽

Clinical Prediction Rules ◽

Prediction Rules ◽

Combined Infection

While most cases of acute cough are self-limiting, antibiotics are prescribed to over 50%. This proportion is inappropriately high given that benefit from treatment with amoxicillin could only be demonstrated in adults with pneumonia (based on chest radiograph) or combined viral–bacterial infection (based on modern microbiological methodology). As routine use of chest radiographs and microbiological testing is costly, clinical prediction rules could be used to identify these patient subsets. In this secondary analysis of data from a multicentre randomised controlled trial in adults presenting to primary care with acute cough, we used prediction rules for pneumonia or combined infection and assessed the effect of amoxicillin in patients predicted to have pneumonia or combined infection on symptom duration, symptom severity and illness deterioration. In total, 2056 patients that fulfilled all inclusion criteria were randomised, 1035 to amoxicillin, 1021 to placebo. Neither patients with a predicted pneumonia nor patients with a predicted combined infection were significantly more likely to benefit from amoxicillin. While the studied clinical prediction rules may help primary care clinicians to reduce antibiotic prescribing for low-risk patients, they did not identify adult acute cough patients that would benefit from amoxicillin treatment.

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Clinical prediction rules for childhood UTIs: a cross-sectional study in ambulatory care

BJGP Open ◽

10.3399/bjgpo.2021.0171 ◽

2022 ◽

pp. BJGPO.2021.0171

Author(s):

Hanne Ann Boon ◽

Jan Y Verbakel ◽

Tine De Burghgraeve ◽

Ann Van den Bruel

Keyword(s):

Area Under The Curve ◽

High Specificity ◽

Cross Sectional Study ◽

Clinical Prediction ◽

Sectional Study ◽

Clinical Prediction Rules ◽

Cross Sectional ◽

Prediction Rules ◽

Low Sensitivity ◽

Tract Infections

BackgroundDiagnosing childhood urinary tract infections (UTI) is challenging.AimValidate clinical prediction rules (UTIcalc, DUTY, Gorelick) for paediatric UTIs in primary care.Design & settingPost-hoc analysis of a cross-sectional study in 39 general practices and 2 emergency departments (Belgium, March 2019 to March 2020).MethodPhysicians recruited acutely ill children ≤18 years and sampled urine systematically for culture. Per rule, we performed an apparent validation; calculated sensitivities and specificities with 95%CI per threshold in the target group. For the DUTY coefficient-based algorithm, we performed a logistic calibration and calculated the Area Under the Curve with 95%CI.ResultsOf 834 children ≤18 years recruited, there were 297 children <5 years. The UTIcalc and Gorelick score had high to moderate sensitivity and low specificity (UTIcalc ≥2%) 75%; and 16% respectively; Gorelick (≥2 variables) 91%; and 8%. In contrast, the DUTY score ≥5 points had low sensitivity (8%), but high specificity (99%). Urine samples would be obtained in 72% vs 38% (UTIcalc), 92% vs 38% (Gorelick) or 1% vs 32% (DUTY) of children, compared to routine care. The number of missed infections per score was 1/4 (UTIcalc), 2/23 (Gorelick) and 24/26 (DUTY). The UTIcalc+ dipstick model had high sensitivity and specificity (100%; and 91%); resulting in no missed cases and 59% (95%CI 49%–68%) of antibiotics prescribed inappropriately.ConclusionIn this study, the UTIcalc and Gorelick score were useful for ruling out UTI but resulted in high urine sampling rates. The DUTY score had low sensitivity, meaning that 92% of UTIs would be missed.

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Novel approach to meta-analysis of tests and clinical prediction rules with three or more risk categories

BMJ Open ◽

10.1136/bmjopen-2019-036262 ◽

2021 ◽

Vol 11 (2) ◽

pp. e036262

Author(s):

Mark H Ebell ◽

Mary E Walsh ◽

Fiona Boland ◽

Brian McKay ◽

Tom Fahey

Keyword(s):

Clinical Decision Making ◽

Risk Group ◽

Meta Analysis ◽

Cancer Recurrence ◽

Clinical Prediction ◽

Likelihood Ratios ◽

Clinical Prediction Rules ◽

Prediction Rules ◽

Novel Approach ◽

Risk Categories

ObjectiveMultichotomous tests have three or more outcome or risk categories, and can provide richer information and a better fit with clinical decision-making than dichotomous tests. Our objective is to present a fully developed approach to the meta-analysis of multichotomous clinical prediction rules (CPRs) and tests, including meta-analysis of stratum specific likelihood ratios.Study designWe have developed a novel approach to the meta-analysis of likelihood ratios for multichotomous tests that avoids the need to dichotomise outcome categories, and demonstrate its application to a sample CPR. We also review previously reported approaches to the meta-analysis of the area under the receiver operating characteristic curve (AUROCC) and meta-analysis of a measure of calibration (observed:expected) for multichotomous tests or CPRs.ResultsUsing data from 10 studies of the Cancer of the Prostate Risk Assessment (CAPRA) risk score for prostate cancer recurrence, we calculated summary estimates of the likelihood ratios for low, moderate and high risk groups of 0.40 (95% CI 0.32 to 0.49), 1.24 (95% CI 0.99 to 1.55) and 4.47 (95% CI 3.21 to 6.23), respectively. Applying the summary estimates of the likelihood ratios for each risk group to the overall prevalence of cancer recurrence in a population allows one to estimate the likelihood of recurrence for each risk group in that population.ConclusionAn approach to meta-analysis of multichotomous tests or CPRs is presented. A spreadsheet for data preparation and code for R and Stata are provided for other researchers to download and use. Combined with summary estimates of the AUROCC and calibration, this is a comprehensive strategy for meta-analysis of multichotomous tests and CPRs.

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