Background: Oral cancer (OC) is usually diagnosed at advanced clinical stages due to its asymptomatic nature and absence of pathognomonic signs in its early development phase. Delayed diagnosis is one of the major causes of OC treatment failure and poor prognosis. Development of alternative diagnostic approaches are imperative for improving early detection and therapeutic success rates. Salivary cytokines (SC) have been studied as potential diagnostic biomarkers for OC and may represent a potential tool for improvement of its early detection.Methods: In this systematic review and meta-analysis we identified SC studied as OC biomarkers by systematically reviewing the PubMed and Cochrane Library databases using the terms: “oral cancer”, “cytokine”, and“saliva”, and also combined with “interleukin”or “interferon”. Only case-control studies that measured SC by ELISA from treatment naïve patients were included in the qualitative review. For the meta-analysis were included all comparable studies that provided enough data (sample size, mean and standard deviation or standard error of the mean) for SC levels in OC patients, non-cancer controls and patients with oral potentially malignant disorders (OPMD), including leukoplakia. Comparisons with patients with oral lichen planus (OLP) and gingivitis were included in the qualitative analysis.Results: A total of 28 articles (from 2004 to 2018) were included in the systematic review, describing 10 different SC, being IL-8 and IL-6 the most studied ones. SC levels were consistently higher among OC patients when compared to healthy controls and to patients with OPMD, OLP and gingivitis. Meta-analysis including 23 eligible studies showed that IL-8, IL-6, TNF-α, IL-1β and IL-10 salivary levels were significantly higher in OC patients compared to controls; and that IL-8, IL-6, TNF-α and IL-1β salivary levels were also higher in OC patients compared to individuals with OPMD. When compared to healthy controls, OPMD patients showed significantly higher IL-6 and TNF-α salivary levels.Conclusions: Our analyses showed that the salivary levels of some cytokines are consistently different among OC, OPMD and healthy patients, indicating that these SC may represent potential diagnostic biomarkers for OC and OPMD. Despite of that, SC levels were highly variable among studies, suggesting that further technical improvement and standardization for SC measurement by ELISA is needed in order to successfully translate these biomarkers to the clinical practice.

Despite the best efforts of intensive care units (ICUs) professionals, the extubation failure rates in mechanically ventilated patients remain in the range of 5%–30%. Extubation failure is associated with increased risk of death and longer ICU stay. This study aimed to identify respiratory and non-respiratory parameters predictive of extubation outcome, and to use these predictors to develop and validate an “Extubation Predictive Score (ExPreS)” that could be used to predict likelihood of extubation success in patients receiving invasive mechanical ventilation (IMV). Derivation cohort was composed by patients aged ≥18 years admitted to the ICU and receiving IMV through an endotracheal tube for >24 hours. The weaning process followed the established ICU protocol. Clinical signs and ventilator parameters of patients were recorded during IMV, in the end phase of weaning in pressure support ventilation (PSV) mode, with inspiratory pressure of 7 cm H₂O over the PEEP (positive end expiratory pressure). Patients who tolerated this ventilation were submitted to spontaneous breathing trial (SBT) with T-tube for 30 minutes. Those who passed the SBT and a subsequent cuff-leak test were extubated. The primary outcome of this study was extubation success at 48 hours. Parameters that showed statistically significant association with extubation outcome were further investigated using the receiver operating characteristics (ROC) analysis to assess their predictive value. The area under the curve (AUC) values were used to select parameters for inclusion in the ExPreS. Univariable logistic regression analysis and ROC analysis were performed to evaluate the performance of ExPreS. Patients’ inclusion and statistical analyses for the prospective validation cohort followed the same criteria used for the derivation cohort and the decision to extubate was based on the ExPreS result. In the derivation cohort, a total of 110 patients were extubated: extubation succeeded in 101 (91.8%) patients and failed in 9 (8.2%) patients. Rapid shallow-breathing index (RSBI) in SBT, dynamic lung compliance, duration of IMV, muscle strength, estimated GCS, hematocrit, and serum creatinine were significantly associated with extubation outcome. These parameters, along with another parameter—presence of neurologic comorbidity—were used to create the ExPreS. The AUC value for the ExPreS was 0.875, which was higher than the AUCs of the individual parameters. The total ExPreS can range from 0 to 100. ExPreS ≥59 points indicated high probability of success (OR = 23.07), while ExPreS ≤44 points indicated low probability of success (OR = 0.82). In the prospective validation cohort, 83 patients were extubated: extubation succeeded in 81 (97.6%) patients and failed in 2 (2.4%) patients. The AUC value for the ExPreS in this cohort was 0.971. The multiparameter score that we propose, ExPreS, shows good accuracy to predict extubation outcome in patients receiving IMV in the ICU. In the prospective validation, the use of ExPreS decreased the extubation failure rate from 8.2% to 2.4%, even in a cohort of more severe patients.

Purpose: We investigated whether COVID-19 patients on mechanical ventilation (MV) had a different extubation outcome compared to non-COVID-19 patients while identifying predictive factors of extubation failure in the former. Methods: A retrospective, single-center, and observational study was done on 216 COVID-19 patients admitted to an intensive care unit (ICU) between March 2020 and March 2021, aged ≥ 18 years, in use of invasive MV for more than 24 h, which progressed to weaning. The primary outcome that was evaluated was extubation failure during ICU stay. A statistical analysis was performed to evaluate the association of patient characteristics with extubation outcome, and a Poisson regression model determined the predictive value. Results: Seventy-seven patients were extubated; the mean age was 57.2 years, 52.5% were male, and their mean APACHE II score at admission was 17.8. On average, MV duration until extubation was 8.7 ± 3.7 days, with 14.9 ± 10.1 days of ICU stay and 24.6 ± 14.0 days with COVID-19 symptoms. The rate of extubation failure (ie, the patient had to be reintubated during their ICU stay) was 22.1% (n = 17), while extubation was successful in 77.9% (n = 60) of cases. Failure was observed in only 7.8% of cases when evaluated 48 hours after extubation. The mean reintubation time was 4.28 days. After adjusting the analysis for age, sex, during of symptoms, days under MV, dialysis, and PaO2/FiO2 ratio, some parameters independently predicted extubation failure: age ≥ 66 years (APR = 5.12 [1.35-19.46]; p = 0.016), ≥ 31 days of symptoms (APR = 5.45 [0.48-62.19]; p = 0.016), and need for dialysis (APR = 5.10 [2.00-13.00]; p = 0.001), while a PaO2/FiO2 ratio >300 decreased the probability of extubation failure (APR = 0.14 [0.04-0.55]; p = 0.005). The presence of three predictors (ie, age ≥ 66 years, time of symptoms ≥ 31 days, need of dialysis, and PaO2/FiO2 ratio < 200) increased the risk of extubation failure by a factor of 23.0 (95% CI, 3.34-158.5). Conclusion: COVID-19 patients had an extubation failure risk that was almost three times higher than non-COVID-19 patients, with the extubation of the former being delayed compared to the latter. Furthermore, an age ≥ 66 years, time of symptoms ≥ 31 days, need of dialysis, and PaO2/FiO2 ratio > 200 were independent predictors for extubation failure, and the presence of three of these characteristics increased the risk of failure by a factor of 23.0.

The western mesoregion of the state of Santa Catarina (SC), Southern Brazil, was heavily affected as a whole by the COVID-19 pandemic in early 2021. This study aimed to evaluate the dynamics of the SARS-CoV-2 virus spreading patterns in the SC state from March 2020 to April 2021 using genomic surveillance. During this period, there were 23 distinct variants, including Beta and Gamma, among which the Gamma and related lineages were predominant in the second pandemic wave within SC. A regionalization of P.1-like-II in the Western SC region was observed, concomitant to the increase in cases, mortality, and the case fatality rate (CFR) index. This is the first evidence of the regionalization of the SARS-CoV-2 transmission in SC and it highlights the importance of tracking the variants, dispersion, and impact of SARS-CoV-2 on the public health systems.