Improving the predictive accuracy of identifying exudative effusions

Efficacy of Ultrasonography in the Diagnosis of Transudative Pleural Fluids

AIMS

We aimed to evaluate the efficacy of thoracic ultrasonography (USG) in diagnosis of pleural exudates and transudates using pleural thickness (PT) measurement.

PATIENTS AND METHODS

Patients who underwent investigations for pleural fluid between January 2018 and May 2018 were included in this prospective study. The patients were evaluated using radiologic imaging modalities to detect pleural fluid, and PT was measured using thoracic USG. The patients were then divided into 2 groups according to Light's criteria as transudative pleural fluid (TPF) and exudative pleural fluid (EPF), and the results were compared between the groups.

RESULTS

A total of 73 patients were included in the study. The mean age was 62±15.1 years. Forty-eight patients (65.8%) had EPF and 25 (34.2%) had TPF. Thoracic USG revealed a mean PT of 0.3±0.1 cm in the TPF group and 0.6±0.3 cm in the EPF group (P<0.001). The optimal cut-off value for PT was 0.2 cm in the TPF group. The sensitivity and specificity of thoracic USG were calculated as 87.5% and 56%, respectively.

CONCLUSION

The measurement of PT using thoracic USG in this study has a high sensitivity but low specificity for identifying transudates from exudates. This approach may be useful in patients who refuse thoracentesis or have a contraindication for the procedure, and in emergency and intensive care unit settings. We recommend further studies to determine the efficacy of thoracic USG studies in patients with pleural fluids.

A Predictive Model for the Identification of Cardiac Effusions Misclassified by Light's Criteria

OBJECTIVES

The application of Light's criteria misidentifies approximately 30% of transudates as exudates, particularly in patients on diuretics with cardiac effusions. The purpose of this study was to establish a predictive model to effectively identify cardiac effusions misclassified by Light's criteria.

METHODS

We retrospectively studied 675 consecutive patients with pleural effusion diagnosed by Light's criteria as exudates, of which 43 were heart failure patients. A multivariate logistic model was developed to predict cardiac effusions. The performance of the predictive model was assessed by receiver operating characteristic (ROC) curves, as well as by examining the calibration.

RESULTS

It was found that protein gradient of >23 g/L, pleural fluid lactate dehydrogenase (PF-LDH) levels, ratio of pleural fluid LDH to serum LDH level (P/S LDH), pleural fluid adenosine deaminase (PF-ADA) levels, and N-terminal pro-brain natriuretic peptide (NT-pro-BNP) levels had a significant impact on the identification of cardiac effusions, and those were simultaneously analyzed by multivariate regression analysis. The area under the curve (AUC) value of the model was 0.953. The model also had higher discriminatory properties than protein gradients (AUC, 0.760) and NT-pro-BNP (AUC, 0.906), all at a P value of <.01.

CONCLUSION

In cases of suspected cardiac effusion, or where clinicians cannot identify the cause of an exudative effusion, this model may assist in the correct identification of exudative effusions as cardiac effusions.

Selected Disorders of the Respiratory System

Respiration and gas exchange require coordination between the chest wall, lungs, central nervous system, and pulmonary circulation. A disruption within any one of these systems or a change in the relationship between systems can result in impairments of ventilation, perfusion, or gas exchange. These disruptions can result in debilitating acute and chronic respiratory disorders. This chapter discusses the etiology, epidemiology, clinical presentation, diagnostic criteria, management, and notable public health implications of respiratory system disorders not addressed in prior chapters. Topic areas covered include acute respiratory distress syndrome (ARDS), pulmonary hypertension, pneumothorax, pleural effusion, interstitial lung disease, bronchiectasis, atelectasis, and pulmonary sarcoidosis.

Concordant and Discordant Exudates and Their Effect on the Accuracy of Light's Criteria to Diagnose Exudative Pleural Effusions

INTRODUCTION

To describe the incidence of discordant exudate (DE) effusions, their underlying etiologies and their effect on the accuracy of the Light's criteria to diagnose exudate effusions.

METHODS

A retrospective review of pleural fluid analysis (PFA) from a cohort of patients with pleural effusion (PE) who underwent thoracentesis. PEs were defined as exudative based on the Light's criteria. The effusions were further classified in concordant or DE.

RESULTS

From 847 PE samples, 611 (72.1%) were diagnosed as an exudate and 236 (27.9%) as a transudate. In 10.3% of cases (n = 87), there was discordancy between the final pleural fluid diagnosis and the PFA defined by Light's criteria. 281 (33.2%) of the 632 effusions classified as an exudate by Light's criteria were DE (52 transudates and 229 exudates). 182 (65%) of the 281 DE were found to be protein discordant (37 transudates and 145 exudates), and 99 (35.2%) were lactate dehydrogenase discordant (15 transudates and 84 exudates). The positive predictive value and positive likelihood ratio of Light's criteria for the diagnosis of an exudate effusion decreased from 99.4% and 67.4%, respectively, when the exudates were concordant to 81.5% and 1.7, respectively, if they were discordant.

CONCLUSIONS

In a significant percentage of patients, there is discordancy between the results of the PFA and the final clinical diagnosis. DE decreased the accuracy of Light's criteria to identify exudate PE, increasing the risk of misclassifying a transudate as an exudate. Concordant exudates almost universally established the presence of an exudative PE.

Can cholesterol be used to distinguish pleural exudates from transudates? evidence from a bivariate meta-analysis

Background

Many studies have investigated whether pleural cholesterol levels can aid in diagnosis of pleural exudates, and the results have varied considerably. To gain a more reliable answer to this question, we meta-analyzed the literature on using pleural cholesterol or the ratio of cholesterol in pleural fluid to cholesterol in serum (P/S cholesterol ratio) as diagnostic tests to help identify pleural exudates.

Methods

Literature databases were systematically searched for studies examining accuracy of pleural cholesterol or P/S cholesterol ratios for diagnosing pleural exudates. Data on sensitivity, specificity, positive/negative likelihood ratio (PLR/NLR), and diagnostic odds ratio (DOR) were pooled using bivariate-effects models. Summary receiver operating characteristic (SROC) curves and area under the curve (AUC) were used to summarize overall test performance.

Results

Our meta-analysis included up to 20 studies involving 3,496 subjects. Summary estimates for pleural cholesterol in the diagnosis of pleural exudates were as follows: sensitivity, 0.88 (95%CI 0.84 to 0.92); specificity, 0.96 (95% CI 0.92 to 0.98); PLR, 20.31 (95% CI 11.21 to 36.78); NLR, 0.12 (95% CI 0.09 to 0.17); DOR, 167.06 (95% CI 76.79 to 363.95); and AUC 0.97 (95% CI 0.95 to 0.98). The corresponding summary performance estimates for using the P/S cholesterol ratio were as follows: sensitivity, 0.94 (95% CI 0.92 to 0.96); specificity, 0.87 (95% CI 0.83 to 0.91); PLR 7.46 (95% CI, 5.47 to 10.19); NLR, 0.07 (95% CI 0.05 to 0.10); DOR, 107.74 (95% CI 60.91 to 190.60); and AUC 0.97 (95% CI 0.95 to 0.98).

Conclusions

Both pleural cholesterol level and the P/S cholesterol ratio are helpful for the diagnosis of pleural exudates. Nevertheless, the results of pleural cholesterol assays should be interpreted in parallel with the results of traditional tests and clinical information.