| Literature DB >> 33935447 |
Vidyasagar Kanneganti1, Sumit Thakar1, Saritha Aryan1, Prayaag Kini2, Dilip Mohan1, Alangar S Hegde1.
Abstract
Background Cardiogenic brain abscess (CBA) is the commonest noncardiac cause of morbidity and mortality in cyanotic heart disease (CHD). The clinical diagnosis of a CBA is often delayed due to its nonspecific presentations and the scarce availability of computed tomography (CT) imaging in resource-restricted settings. We attempted to identify parameters that reliably point to the diagnosis of a CBA in patients with Tetralogy of Fallot (TOF). Methods From among 150 children with TOF treated at a tertiary care institute over a 15-year period from 2001 to 2016, 30 consecutive patients with CBAs and 85 age- and sex-matched controls without CBAs were included in this retrospective case-control study. Demographic and clinical features, laboratory investigations, and baseline echocardiographic findings were analyzed for possible correlations with the presence of a CBA. Statistical Analysis Variables demonstrating significant bivariate correlations with the presence of a CBA were further analyzed using multivariate logistic regression (LR) analysis. Various LR models were tested for their predictive value, and the best model was then validated on a hold-out dataset of 25 patients. Results Among the 26 variables tested for bivariate associations with the presence of a CBA, some of the clinical, echocardiographic, and laboratory variables demonstrated significant correlations ( p < 0.05). LR analysis revealed elevated neutrophil-lymphocyte ratio and erythrocyte sedimentation rate values and a lower age-adjusted resting heart rate percentile to be the strongest independent biomarkers of a CBA. The LR model was statistically significant, (χ 2 = 23.72, p = <0.001), and it fitted the data well. It explained 53% (Nagelkerke R 2 ) of the variance in occurrence of a CBA, and correctly classified 83.93% of cases. The model demonstrated a good predictive value (area under the curve: 0.80) on validation analysis. Conclusions This study has identified simple clinical and laboratory parameters that can serve as reliable pointers of a CBA in patients with TOF. A scoring model-the 'BA-TOF' score-that predicts the occurrence of a CBA has been proposed. Patients with higher scores on the proposed model should be referred urgently for a CT confirmation of the diagnosis. Usage of such a diagnostic aid in resource-limited settings can optimize the pickup rates of a CBA and potentially improve outcomes. Association for Helping Neurosurgical Sick People. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).Entities:
Keywords: Tetralogy of Fallot; cardiogenic brain abscess; markers
Year: 2021 PMID: 33935447 PMCID: PMC8079174 DOI: 10.1055/s-0041-1722819
Source DB: PubMed Journal: J Neurosci Rural Pract ISSN: 0976-3155
Fig. 1Contrast-enhanced computed tomography images demonstrating some of the cardiogenic brain abscesses (CBAs) in the study: ( A ) a left temporal CBA with mass effect on the temporal horn, ( B ) a left posterior frontal CBA with perilesional edema, ( C ) a large left frontal CBA with evidence of subfalcine herniation, and ( D ) a multiloculated abscess in the right posterior frontal region.
Bivariate correlations between variables and the presence of a CBA
| Clinical variable |
|
|---|---|
| Abbreviations: CBA, cardiogenic brain abscess; CXR, chest X-ray; ESR, erythrocyte sedimentation rate; NLR, neutrophil-lymphocyte ratio; PCV, packed cell volume; SpO2, oxygen saturation; VSD, ventricular septal defect. | |
| Age | 0.74 |
| Body mass index | 0.51 |
| Body surface area | 0.23 |
| Cyanotic spells | 0.03 |
| Persistent cyanosis | <0.001 |
| Dyspnea on exertion | <0.001 |
| Age-adjusted heart rate percentile | 0.001 |
| SpO2 | 0.83 |
|
| |
| Pulmonary artery index | 0.04 |
| Pulmonary stenosis type | 0.04 |
| Branch confluence | 0.001 |
| Pulmonary valve gradient | 0.74 |
| VSD type | 0.03 |
|
| |
| PCV | 0.65 |
| Total count | 0.003 |
| NLR | <0.001 |
| Platelet count | 0.30 |
| ESR | 0.002 |
| Direct bilirubin | 0.29 |
| Indirect bilirubin | 0.77 |
| Total bilirubin | 0.97 |
| Prothrombin time | 0.19 |
| Activated partial thromboplastin time | 0.54 |
| Bleeding time | 0.31 |
| Clotting time | 0.95 |
|
| |
| Pulmonary oligemia on CXR | 0.26 |
Logistic regression analysis for assessing independent correlations with the occurrence of a CBA
| B | SE |
| 95% CI (lower) | 95% CI (upper) | |
|---|---|---|---|---|---|
| Abbreviations: B, unstandardized coefficient; CBA, cardiogenic brain abscess; CI, confidence interval; ESR, erythrocyte sedimentation rate; NLR, neutrophil-lymphocyte ratio; SE, standard error. | |||||
| Constant | –1.60 | 0.85 | |||
| NLR | 0.99 | 0.26 | <0.001 | 1.63 | 4.45 |
| ESR | 0.11 | 0.05 | 0.01 | 1.02 | 1.22 |
| Heart rate percentile | –0.04 | 0.01 | 0.004 | 0.94 | 0.99 |
Predictive ability, threshold, sensitivity, specificity of the individual variables, and the regression model
| Variable | AUC | Threshold | Sensitivity | Specificity |
|---|---|---|---|---|
| Abbreviations: AUC, area under curve; ESR, erythrocyte sedimentation rate; HR, heart rate; NLR, neutrophil-lymphocyte ratio. | ||||
| NLR | 0.80 | 1.6 | 0.83 | 0.70 |
| ESR | 0.57 | 15 | 0.25 | 0.90 |
| HR percentile | 0.31 | 60 | 0.35 | 0.40 |
| Model | 0.86 | –1 | 0.83 | 0.80 |
Fig. 2Receiver operator characteristic curve of the regression model when applied on the validation cohort.