RESUMEN
Background: Providing efficient care for infectious coronavirus disease 2019 (COVID-19) patients requires an accurate and accessible tool to medically optimize medical resource allocation to high-risk patients. Purpose: To assess the predictive value of on-admission chest CT characteristics to estimate COVID-19 patients' outcome and survival time. Materials and Methods: Using a case-control design, we included all laboratory-confirmed COVID-19 patients who were deceased, from June to September 2020, in a tertiary-referral-collegiate hospital and had on-admission chest CT as the case group. The patients who did not die and were equivalent in terms of demographics and other clinical features to cases were considered as the control (survivors) group. The equivalency evaluation was performed by a fellowship-trained radiologist and an expert radiologist. Pulmonary involvement (PI) was scored (0-25) using a semiquantitative scoring tool. The PI density index was calculated by dividing the total PI score by the number of involved lung lobes. All imaging parameters were compared between case and control group members. Survival time was recorded for the case group. All demographic, clinical, and imaging variables were included in the survival analyses. Results: After evaluating 384 cases, a total of 186 patients (93 in each group) were admitted to the studied setting, consisting of 126 (67.7%) male patients with a mean age of 60.4 ± 13.6 years. The PI score and PI density index in the case vs. the control group were on average 8.9 ± 4.5 vs. 10.7 ± 4.4 (p value: 0.001) and 2.0 ± 0.7 vs. 2.6 ± 0.8 (p value: 0.01), respectively. Axial distribution (p value: 0.01), cardiomegaly (p value: 0.005), pleural effusion (p value: 0.001), and pericardial effusion (p value: 0.04) were mostly observed in deceased patients. Our survival analyses demonstrated that PI score ≥ 10 (p value: 0.02) and PI density index ≥ 2.2 (p value: 0.03) were significantly associated with a lower survival rate. Conclusion: On-admission chest CT features, particularly PI score and PI density index, are potential great tools to predict the patient's clinical outcome.
RESUMEN
The concurrent involvement of the lung and kidneys happens in COVID-19 infection. The patient's respiratory symptoms resolved after hemodialysis. This finding raises the question that if hemodialysis can have a role in the treatment of COVID-19.
RESUMEN
To our knowledge, no previous studies have reported lung abscess as a complication of COVID-19 infection. It is essential to follow-up with the patients after discharge for such complications, especially if they are symptomatic.
RESUMEN
PURPOSE: To investigate the factors contributing to mortality in coronavirus disease 2019 (COVID-19) patients admitted in the intensive care unit (ICU) and design a model to predict the mortality rate. METHOD: We retrospectively evaluated the medical records and CT images of the ICU-admitted COVID-19 patients who had an on-admission chest CT scan. We analyzed the patients' demographic, clinical, laboratory, and radiologic findings and compared them between survivors and nonsurvivors. RESULTS: Among the 121 enrolled patients (mean age, 62.2 ± 14.0 years; male, 82 (67.8%)), 41 (33.9%) survived, and the rest succumbed to death. The most frequent radiologic findings were ground-glass opacity (GGO) (71.9%) with peripheral (38.8%) and bilateral (98.3%) involvement, with lower lobes (94.2%) predominancy. The most common additional findings were cardiomegaly (63.6%), parenchymal band (47.9%), and crazy-paving pattern (44.4%). Univariable analysis of radiologic findings showed that cardiomegaly (p : 0.04), pleural effusion (p : 0.02), and pericardial effusion (p : 0.03) were significantly more prevalent in nonsurvivors. However, the extension of pulmonary involvement was not significantly different between the two subgroups (11.4 ± 4.1 in survivors vs. 11.9 ± 5.1 in nonsurvivors, p : 0.59). Among nonradiologic factors, advanced age (p : 0.002), lower O2 saturation (p : 0.01), diastolic blood pressure (p : 0.02), and hypertension (p : 0.03) were more commonly found in nonsurvivors. There was no significant difference between survivors and nonsurvivors in terms of laboratory findings. Three following factors remained significant in the backward logistic regression model: O2 saturation (OR: 0.91 (95% CI: 0.84-0.97), p : 0.006), pericardial effusion (6.56 (0.17-59.3), p : 0.09), and hypertension (4.11 (1.39-12.2), p : 0.01). This model had 78.7% sensitivity, 61.1% specificity, 90.0% positive predictive value, and 75.5% accuracy in predicting in-ICU mortality. CONCLUSION: A combination of underlying diseases, vital signs, and radiologic factors might have prognostic value for mortality rate prediction in ICU-admitted COVID-19 patients.
RESUMEN
Chloroquine has long been used for the treatment of malaria and rheumatological disorders. Accumulating evidence suggests potential use of chloroquine as a neuroprotective agent. Several studies have reported that endogenous opioids and nitric oxide (NO) system mediate the chloroquine effects. In the present study, the involvements of endogenous opioids and NO in the modulatory effects of chloroquine on pentylenetetrazol-induced seizures were assessed in mice. Chloroquine 5mg/kg significantly increased the seizure threshold, but this effect was reversed with naltrexone 1mg/kg. Acute co-administration of l-NAME (non-selective NO synthase (NOS) inhibitor, 5mg/kg) or 7-NI (selective neuronal NOS inhibitor, 40 mg/kg) with the effective dose of chloroquine completely inhibited its anticonvulsant effects. Acute single injection of a sub-effective dose of l-arginine (NO precursor, 60 mg/kg) with a sub-effective dose of chloroquine 2.5mg/kg increased the seizure threshold but administration of L-arginine 60 mg/kg with chloroquine 10mg/kg decreased the seizure threshold. Moreover, the combination of the lower doses of naltrexone (0.1mg/kg) and 7-NI (15 mg/kg) showed additive effects in blocking the chloroquine-induced anticonvulsant properties. Chloroquine 5mg/kg enhanced the hippocampal nitrite levels. Chloroquine at the dose of 20mg/kg decreased the seizure threshold. This effect was inhibited through L-NAME (5mg/kg), 7-NI (40 mg/kg) and naltrexone (1mg/kg) administration with this dose of chloroquine. In conclusion, NO signaling probably through neuronal NOS, but not inducible NOS could be involved in the opioid-dependent anticonvulsant effects of chloroquine in this model of seizures in mice. It seems that nitric oxide and opioid systems are involved in modulatory effect of chloroquine on seizures induced by pentylenetetrazol.