Dataset Information

Validation of a clinical rule to predict complications of acute cough in preschool children: a prospective study in primary care.

ABSTRACT:

Background

Few clinical rules have been derived let alone validated in primary care. A rule was derived to predict complications of acute cough in preschool children presenting to primary care. The clinical rule used the presence/absence of fever and/or chest signs to distinguish children at low, medium, and high risk of complications.

Aim

To validate a clinical rule for predicting complications of acute cough in preschool children in primary care.

Design of study

Prospective cohort study.

Setting

Thirteen general practices in Bristol and Tayside, UK.

Method

Preschool children with cough up to 28 days and without asthma were recruited. The same sociodemographic, clinical history, examination, and complications data as for the derivation study were collected. First, univariable logistic regression was used to explore the associations with complications, and then predictors with stronger relationships (P<0.2) were modelled using multivariable logistic regression. These predictors were compared with derivation predictors with respect to their strength of association with complications. The derivation predictors were used in the validation dataset to allow comparison of the post-test probabilities of complications between derivation and validation studies.

Results

The presence of fever and chest signs in the validation study tended to be protective for complications, with univariable odds ratios (ORs) of 0.37 and 0.81 respectively, compared with ORs of 4.86 and 2.72 in the derivation study. However, 95% confidence limits were wide and evidence for two other possible reasons for these results were found: spectrum bias and confounding by indication.

Conclusion

No evidence was found to validate the clinical rule for predicting complications of acute cough, possibly as a result of spectrum bias, confounding by indication, and/or chance. As paediatric infectious illness is costly and associated with high rates of antibiotic use, further research is needed to derive and validate prediction rules.

SUBMITTER: Hay AD

PROVIDER: S-EPMC2099635 | biostudies-literature | 2007 Jul

REPOSITORIES: biostudies-literature

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Publications

Validation of a clinical rule to predict complications of acute cough in preschool children: a prospective study in primary care.

Hay Alastair D AD Gorst Catharine C Montgomery Alan A Peters Tim J TJ Fahey Tom T

The British journal of general practice : the journal of the Royal College of General Practitioners 20070701 540

<h4>Background</h4>Few clinical rules have been derived let alone validated in primary care. A rule was derived to predict complications of acute cough in preschool children presenting to primary care. The clinical rule used the presence/absence of fever and/or chest signs to distinguish children at low, medium, and high risk of complications.<h4>Aim</h4>To validate a clinical rule for predicting complications of acute cough in preschool children in primary care.<h4>Design of study</h4>Prospecti ...[more]

PMID: 17727745

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Project description:BackgroundAntimicrobial resistance is a serious threat to public health, with most antibiotics prescribed in primary care. General practitioners (GPs) report defensive antibiotic prescribing to mitigate perceived risk of future hospital admission in children with respiratory tract infections. We developed a clinical rule aimed to reduce clinical uncertainty by stratifying risk of future hospital admission.Methods8394 children aged between 3 months and 16 years presenting with acute cough (for ≤28 days) and respiratory tract infection were recruited to a prognostic cohort study from 247 general practitioner practices in England. Exposure variables included demographic characteristics, parent-reported symptoms, and physical examination signs. The outcome was hospital admission for respiratory tract infection within 30 days, collected using a structured, blinded review of medical records.Findings8394 (100%) children were included in the analysis, with 78 (0·9%, 95% CI 0·7%-1·2%) admitted to hospital: 15 (19%) were admitted on the day of recruitment (day 1), 33 (42%) on days 2-7; and 30 (39%) on days 8-30. Seven characteristics were independently associated (p<0·01) with hospital admission: age <2 years, current asthma, illness duration of 3 days or less, parent-reported moderate or severe vomiting in the previous 24 h, parent-reported severe fever in the previous 24 h or a body temperature of 37·8°C or more at presentation, clinician-reported intercostal or subcostal recession, and clinician-reported wheeze on auscultation. The area under the receiver operating characteristic (AUROC) curve for the coefficient-based clinical rule was 0·82 (95% CI 0·77-0·87, bootstrap validated 0·81). Assigning one point per characteristic, a points-based clinical rule consisting of short illness, temperature, age, recession, wheeze, asthma, and vomiting (mnemonic STARWAVe; AUROC 0·81, 0·76-0·85) distinguished three hospital admission risk strata: very low (0·3%, 0·2-0·4%) with 1 point or less, normal (1·5%, 1·0-1·9%) with 2 or 3 points, and high (11·8%, 7·3-16·2%) with 4 points or more.InterpretationClinical characteristics can distinguish children at very low, normal, and high risk of future hospital admission for respiratory tract infection and could be used to reduce antibiotic prescriptions in primary care for children at very low risk.FundingNational Institute for Health Research (NIHR).

Project description:ImportanceBruising caused by physical abuse is the most common antecedent injury to be overlooked or misdiagnosed as nonabusive before an abuse-related fatality or near-fatality in a young child. Bruising occurs from both nonabuse and abuse, but differences identified by a clinical decision rule may allow improved and earlier recognition of the abused child.ObjectiveTo refine and validate a previously derived bruising clinical decision rule (BCDR), the TEN-4 (bruising to torso, ear, or neck or any bruising on an infant <4.99 months of age), for identifying children at risk of having been physically abused.Design, setting, and participantsThis prospective cross-sectional study was conducted from December 1, 2011, to March 31, 2016, at emergency departments of 5 urban children's hospitals. Children younger than 4 years with bruising were identified through deliberate examination. Statistical analysis was completed in June 2020.ExposuresBruising characteristics in 34 discrete body regions, patterned bruising, cumulative bruise counts, and patient's age. The BCDR was refined and validated based on these variables using binary recursive partitioning analysis.Main outcomes and measuresInjury from abusive vs nonabusive trauma was determined by the consensus judgment of a multidisciplinary expert panel.ResultsA total of 21 123 children were consecutively screened for bruising, and 2161 patients (mean [SD] age, 2.1 [1.1] years; 1296 [60%] male; 1785 [83%] White; 1484 [69%] non-Hispanic/Latino) were enrolled. The expert panel achieved consensus on 2123 patients (98%), classifying 410 (19%) as abuse and 1713 (79%) as nonabuse. A classification tree was fit to refine the rule and validated via bootstrap resampling. The resulting BCDR was 95.6% (95% CI, 93.0%-97.3%) sensitive and 87.1% (95% CI, 85.4%-88.6%) specific for distinguishing abuse from nonabusive trauma based on body region bruised (torso, ear, neck, frenulum, angle of jaw, cheeks [fleshy], eyelids, and subconjunctivae), bruising anywhere on an infant 4.99 months and younger, or patterned bruising (TEN-4-FACESp).Conclusions and relevanceIn this study, an affirmative finding for any of the 3 BCDR TEN-4-FACESp components in children younger than 4 years indicated a potential risk for abuse; these results warrant further evaluation. Clinical application of this tool has the potential to improve recognition of abuse in young children with bruising.

Project description:BackgroundWe aimed to prospectively validate a novel 1-hour algorithm using high-sensitivity cardiac troponin T measurement for early rule-out and rule-in of acute myocardial infarction (MI).MethodsIn a multicentre study, we enrolled 1320 patients presenting to the emergency department with suspected acute MI. The high-sensitivity cardiac troponin T 1-hour algorithm, incorporating baseline values as well as absolute changes within the first hour, was validated against the final diagnosis. The final diagnosis was then adjudicated by 2 independent cardiologists using all available information, including coronary angiography, echocardiography, follow-up data and serial measurements of high-sensitivity cardiac troponin T levels.ResultsAcute MI was the final diagnosis in 17.3% of patients. With application of the high-sensitivity cardiac troponin T 1-hour algorithm, 786 (59.5%) patients were classified as "rule-out," 216 (16.4%) were classified as "rule-in" and 318 (24.1%) were classified to the "observational zone." The sensitivity and the negative predictive value for acute MI in the rule-out zone were 99.6% (95% confidence interval [CI] 97.6%-99.9%) and 99.9% (95% CI 99.3%-100%), respectively. The specificity and the positive predictive value for acute MI in the rule-in zone were 95.7% (95% CI 94.3%-96.8%) and 78.2% (95% CI 72.1%-83.6%), respectively. The 1-hour algorithm provided higher negative and positive predictive values than the standard interpretation of highsensitivity cardiac troponin T using a single cut-off level (both p < 0.05). Cumulative 30-day mortality was 0.0%, 1.6% and 1.9% in patients classified in the rule-out, observational and rule-in groups, respectively (p = 0.001).InterpretationThis rapid strategy incorporating high-sensitivity cardiac troponin T baseline values and absolute changes within the first hour substantially accelerated the management of suspected acute MI by allowing safe rule-out as well as accurate rule-in of acute MI in 3 out of 4 patients.Trial registrationClinicalTrials.gov, NCT00470587.

Project description:BackgroundTo date, the Pediatric Emergency Care Applied Research Network (PECARN) rule for identifying children who are at very low risk of clinically-important traumatic brain injuries after minor head trauma has not been validated prospectively in an independent population. Our goal was to evaluate the diagnostic performance of the PECARN clinical decision rule in a French pediatric population in multiple clinical settings.MethodsWe conducted a multicenter, prospective, non-interventional cohort study of patients with minor head trauma who presented to three emergency departments in France. We enrolled patients younger than 16 years of age seeking a consultation within 24 h of head trauma with Glasgow Coma Scale scores of 14-15.ResultsDuring the study period, we included 1499 children of which 421 (28 %) were under 2 years of age, and 955 (64 %) were male. A cranial computed tomography (CT) scan was performed on 76 patients (5.1 %). Of the 1499 included patients, 9 children (0.6 %) had a clinically-important traumatic brain injury, and none were classified as very low risk by the PECARN rule. In our study, the sensitivity of this clinical decision rule was 100 % (95 % CI 66.4 to 100 %), the specificity was 69.9 % (95 % CI 67.5 to 72.2 %) and the negative predictive value was 100 % (95 % CI 99.7 to 100 %).DiscussionOur study confirmed the good predictive performances of the PECARN clinical decision rule for minor head trauma in children. The PECARN rule performed similarly to our study and to its internal validation study.ConclusionsWe conducted an external validation study of the PECARN clinical decision rule for the detection of clinically-important traumatic brain injuries in children with minor head trauma, according to the methodological standards. The PECARN rule successfully identified all patients with clinically-important traumatic brain injuries, with a limited use of CT scans. Conducting a broad validation study with a large cohort is a prerequisite to provide sufficient statistical power before authorizing its implementation and generalization.Trial registrationThis study has been registered in ClinicalTrials.gov with identifier number: NCT02752711 on April 27, 2016.

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Dataset Information

Validation of a clinical rule to predict complications of acute cough in preschool children: a prospective study in primary care.

Background

Aim

Design of study

Setting

Method

Results

Conclusion

Publications

Validation of a clinical rule to predict complications of acute cough in preschool children: a prospective study in primary care.

Similar Datasets

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