Diagnostic Accuracy Of Symptoms Research Articles

Diagnostic accuracy of point-of-care tests for acute respiratory infection: a systematic review of reviews.

Acute respiratory infections are a common reason for consultation with primary and emergency healthcare services. Identifying individuals with a bacterial infection is crucial to ensure appropriate treatment. However, it is also important to avoid overprescription of antibiotics, to prevent unnecessary side effects and antimicrobial resistance. We conducted a systematic review to summarise evidence on the diagnostic accuracy of symptoms, signs and point-of-care tests to diagnose bacterial respiratory tract infection in adults, and to diagnose two common respiratory viruses, influenza and respiratory syncytial virus. The primary approach was an overview of existing systematic reviews. We conducted literature searches (22 May 2023) to identify systematic reviews of the diagnostic accuracy of point-of-care tests. Where multiple reviews were identified, we selected the most recent and comprehensive review, with the greatest overlap in scope with our review question. Methodological quality was assessed using the Risk of Bias in Systematic Reviews tool. Summary estimates of diagnostic accuracy (sensitivity, specificity or area under the curve) were extracted. Where no systematic review was identified, we searched for primary studies. We extracted sufficient data to construct a 2 × 2 table of diagnostic accuracy, to calculate sensitivity and specificity. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies version 2 tool. Where possible, meta-analyses were conducted. We used GRADE to assess the certainty of the evidence from existing reviews and new analyses. We identified 23 reviews which addressed our review question; 6 were selected as the most comprehensive and similar in scope to our review protocol. These systematic reviews considered the following tests for bacterial respiratory infection: individual symptoms and signs; combinations of symptoms and signs (in clinical prediction models); clinical prediction models incorporating C-reactive protein; and biological markers related to infection (including C-reactive protein, procalcitonin and others). We also identified systematic reviews that reported the accuracy of specific tests for influenza and respiratory syncytial virus. No reviews were found that assessed the diagnostic accuracy of white cell count for bacterial respiratory infection, or multiplex tests for influenza and respiratory syncytial virus. We therefore conducted searches for primary studies, and carried out meta-analyses for these index tests. Overall, we found that symptoms and signs have poor diagnostic accuracy for bacterial respiratory infection (sensitivity ranging from 9.6% to 89.1%; specificity ranging from 13.4% to 95%). Accuracy of biomarkers was slightly better, particularly when combinations of biomarkers were used (sensitivity 80-90%, specificity 82-93%). The sensitivity and specificity for influenza or respiratory syncytial virus varied considerably across the different types of tests. Tests involving nucleic acid amplification techniques (either single pathogen or multiplex tests) had the highest diagnostic accuracy for influenza (sensitivity 91-99.8%, specificity 96.8-99.4%). Most of the evidence was considered low or very low certainty when assessed with GRADE, due to imprecision in effect estimates, the potential for bias and the inclusion of participants outside the scope of this review (children, or people in hospital). Currently evidence is insufficient to support routine use of point-of-care tests in primary and emergency care. Further work must establish whether the introduction of point-of-care tests adds value, or simply increases healthcare costs. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number NIHR159948.

Diagnostic accuracy of symptoms as a diagnostic tool for SARS-CoV 2 infection: a cross-sectional study in a cohort of 2,173 patients

BackgroundThe SARS-CoV-2 pandemic continues to be a priority health problem; According to the World Health Organization data from October 13, 2020, 37,704,153 confirmed COVID-19 cases have been reported, including 1,079,029 deaths, since the outbreak. The identification of potential symptoms has been reported to be a useful tool for clinical decision-making in emergency departments to avoid overload and improve the quality of care. The aim of this study was to evaluate the performances of symptoms as a diagnostic tool for SARS -CoV-2 infection.MethodsAn observational, cross-sectional, prospective and analytical study was carried out, during the period of time from April 14 to July 21, 2020. Data (demographic variables, medical history, respiratory and non-respiratory symptoms) were collected by emergency physicians. The diagnosis of COVID-19 was made using SARS-CoV-2 RT-PCR. The diagnostic accuracy of these characteristics for COVID-19 was evaluated by calculating the positive and negative likelihood ratios. A Mantel-Haenszel and multivariate logistic regression analysis was performed to assess the association of symptoms with COVID-19.ResultsA prevalence of 53.72% of SARS-CoV-2 infection was observed. The symptom with the highest sensitivity was cough 71%, and a specificity of 52.68%. The symptomatological scale, constructed from 6 symptoms, obtained a sensitivity of 83.45% and a specificity of 32.86%, taking ≥2 symptoms as a cut-off point. The symptoms with the greatest association with SARS-CoV-2 were: anosmia odds ratio (OR) 3.2 (95% CI; 2.52–4.17), fever OR 2.98 (95% CI; 2.47–3.58), dyspnea OR 2.9 (95% CI; 2.39–3.51]) and cough OR 2.73 (95% CI: 2.27–3.28).ConclusionThe combination of ≥2 symptoms / signs (fever, cough, anosmia, dyspnea and oxygen saturation < 93%, and headache) results in a highly sensitivity model for a quick and accurate diagnosis of COVID-19, and should be used in the absence of ancillary diagnostic studies. Symptomatology, alone and in combination, may be an appropriate strategy to use in the emergency department to guide the behaviors to respond to the disease.Trial registrationInstitutional registration R-2020-3601-145, Federal Commission for the Protection against Sanitary Risks 17 CI-09-015-034, National Bioethics Commission: 09 CEI-023-2017082.

Diagnostic Accuracy of Symptoms, Physical Signs, and Laboratory Tests for Giant Cell Arteritis: A Systematic Review and Meta-analysis

Diagnostic Accuracy of Symptoms, Physical Signs, and Laboratory Tests for Giant Cell Arteritis: A Systematic Review and Meta-analysis

Diagnostic Accuracy of Symptoms, Signs, and Lab Tests for Giant Cell Arteritis

Prompt diagnosis and treatment of patients with giant cell arteritis (GCA) can avert morbidity, such as vision loss. In patients with suspected GCA,

AB0537 DIAGNOSTIC ACCURACY OF SYMPTOMS AND SIGNS FOR GIANT CELL ARTERITIS: SYSTEMATIC REVIEW AND META-ANALYSIS

Background:Making a correct diagnosis of giant cell arteritis (GCA) is critical given the potential complications of the disease and its therapy. Estimation of the clinical probability of GCA is challenging. Prediction models might be helpful, but have methodological and practical draw backs. One earlier meta-analysis described the diagnostic accuracy of symptoms and signs for a positive temporal artery biopsy [1]. In the latter study, the diagnostic accuracy of symptoms and signs might have been overestimated due to inclusion of case-control studies.Objectives:To evaluate the diagnostic accuracy of symptoms and signs for GCA.Methods:PubMed, EMBASE and the Cochrane Database were searched for relevant studies. Studies were eligible if: all patients were suspected of having GCA; either a temporal artery biopsy (TAB), imaging test, or clinical diagnosis was used as reference standard for GCA; a 2x2 table was available for at least one symptom, physical sign or routine laboratory test (i.e. the index tests). Case reports and case-control studies were excluded. The screening, full text review, quality assessment with QUADAS-2 tool and data extraction were performed by two investigators. Hierarchical logistic regression modelling provided the pooled estimates of likelihood ratios with their 95% confidence intervals. Likelihood ratios &lt;0.5 (i.e. making GCA less likely) or &gt;2.0 (i.e. making GCA more likely) were considered diagnostically relevant.Results:Out of 1359 reports screened, 59 studies were included in the study. These reports contained 13406 patients, including 3940 GCA patients. Most studies were retrospective, performed at tertiary centres and published after the prior meta-analysis [1]. TAB was the reference standard in 36 studies and a clinical diagnosis in 23 studies. Quality assessment revealed substantial risk of selection bias in the majority of studies. Studies using a clinical diagnosis were at risk of bias, as the reference standard might be influenced by the index tests (e.g. symptoms). Jaw claudication, limb claudication, temporal tenderness, temporal artery abnormalities, especially arterial thickening or loss of pulse, and anterior ischemic optic neuropathy provided a positive likelihood ratio &gt;2.0. None of the 19 symptoms and 7 physical signs evaluated, provided a negative likelihood ratio &lt;0.5. An ESR &gt;60mm/hr and platelet count &gt;400*109/L provided a positive likelihood ratio of &gt;2.0. Absence of an elevated CRP level or ESR &gt;60mm/hr yielded a negative likelihood ratio of &lt;0.5. Studies using a clinical diagnosis as reference standard reported higher positive likelihood ratios for jaw claudication, weight loss and PMR when compared to TAB studies. Absence of an elevated CRP provided a lower negative likelihood ratio in studies using the clinical diagnosis.Conclusion:Few clinical findings may help to estimate the clinical probability of GCA. The presence or absence of any particular symptom or sign does not sufficiently rule out or rule in GCA. These findings highlight the need of additional tests (i.e. imaging, biopsy) in patients suspected of having GCA.

Limited evidence for diagnosing bacterial skin infections in older adults in primary care: systematic review

BackgroundOlder adults with bacterial skin infections may present with atypical symptoms, making diagnosis difficult. There is limited authoritative guidance on how older adults in the community present with bacterial skin infections. To date there have been no systematic reviews assessing the diagnostic value of symptoms and signs in identifying bacterial skin infections in older adults in the community.MethodsWe searched Medline and Medline in process, Embase and Web of Science, from inception to September 2017. We included cohort and cross-sectional studies assessing the diagnostic accuracy of symptoms and signs in predicting bacterial skin infections in adults in primary care aged over 65 years. The QUADAS-2 tool was used to assess study quality.ResultsWe identified two observational studies of low-moderate quality, with a total of 7991 participants, providing data to calculate the diagnostic accuracy of 5 unique symptoms in predicting bacterial skin infections. The presence of wounds [LR+: 7.93 (CI 4.81–13.1)], pressure sores [LR+: 4.85 (CI 2.18–10.8)] and skin ulcers [LR+: 6.26 (CI 5.49–7.13)] help to diagnose bacterial skin infections. The presence of urinary incontinence does not help to predict bacterial skin infections (LR + ‘s of 0.99 and 1.04; LR-‘s of 0.96 and 1.04).ConclusionsCurrently, there is insufficient evidence to inform the diagnosis of bacterial skin infections in older adults in the community; clinicians should therefore rely upon their clinical judgement and experience. Evidence from high quality primary care studies in older adults, including studies assessing symptoms traditionally associated with bacterial skin infections (e.g. erythema and warmth), is urgently needed to guide practice.

Diagnostic accuracy of symptoms characterising chronic fatigue syndrome

Purpose. To determine the diagnostic accuracy for single symptoms and clusters of symptoms to distinguish between individuals with and without chronic fatigue syndrome (CFS).Methods. A cohort study was conducted in an exercise physiology laboratory in an academic setting. Thirty subjects participated in this study (n == 16 individuals with CFS; n == 14 non-disabled sedentary matched control subjects). An open-ended symptom questionnaire was administered 1 week following the second of two maximal cardiopulmonary exercise tests administered 24 h apart.Results. Receiver operating characteristics (ROC) curve analysis was significant for failure to recover within 1 day (area under the curve == 0.864, 95%% confidence interval [[CI]]: 0.706–1.00, p == 0.001) but not within 7 days. Clinimetric properties of failure to recover within 1 day to predict membership in the CFS cohort were sensitivity 0.80, specificity 0.93, positive predictive value 0.92, negative predictive value 0.81, positive likelihood ratio 11.4, and negative likelihood ratio 0.22. Fatigue demonstrated high sensitivity and modest specificity to distinguish between cohorts, while neuroendocrine dysfunction, immune dysfunction, pain, and sleep disturbance demonstrated high specificity and modest sensitivity. ROC analysis suggested cut-point of three associated symptoms (0.871, 95%% CI: 0.717–1.00, p < 0.001). A significant binary logistic regression model (p < 0.001) revealed immune abnormalities, sleep disturbance and pain accurately classified 92%% of individuals with CFS and 88%% of control subjects.Conclusions. A cluster of associated symptoms distinguishes between individuals with and without CFS. Fewer associated symptoms may be necessary to establish a diagnosis of CFS than currently described.

Abdominal Symptoms: Do They Predict Gallstones?: A Systematic Review

Our objective was to evaluate the diagnostic accuracy of abdominal symptoms in gallstones in studies using ultrasonography or oral cholecystography as the reference standard and to assess the extent to which variability in diagnostic accuracy is explained by patient selection and other characteristics of study design. A Medline search (1966-1998) was conducted in combination with reference checking for further relevant publications. Two independent assessors selected controlled studies that included patients > or =18 years of age. Articles were excluded if sensitivity and specificity could not be extracted or the included patients were at extraordinary risk for gallstones. Seven abdominal symptoms were evaluated. Modification of the diagnostic accuracy by clinical setting, extent of the disease, blinding, age, and sex was analysed by using logistic regression. A total of 24 publications were included. The symptoms 'biliary colic', 'radiating pain', and 'analgesics used' were consistently related to gallstones. The setting of the study had a significant effect on the diagnostic accuracy of these symptoms. The unadjusted, pooled diagnostic odds ratios, however, were low (2.6 (95% confidence interval, 2.4-2.9), 2.8 (2.2-3.7), and 2 (1.6-2.5), respectively). The diagnostic odds ratio of biliary colic increased with the extent of gallstone disease (13.3 (4.2-42). Although biliary colic was specific for gallstones, 80% of the referred patients with gallstones presented with other abdominal symptoms. There is no current evidence that justifies the use of single abdominal symptoms, other than biliary colic, in the diagnosis of symptomatic gallstones. Further research should focus on the prognosis of patients with non-specific abdominal symptoms and gallstones.