Predictors of Clinical Outcomes in Autologous Cranioplasty.

BACKGROUND: Cranioplasty is a common neurosurgical procedure and autologous grafts are preferred due to their aesthetic and biocompatibility benefits. Multiple risk factors are implicated as predictors for neurologic outcome. This study focuses on risk factors that may be associated with complications and analyzes the predictors of neurologic outcomes after autologous cranioplasty. METHODS: This is a retrospective observational study conducted at a tertiary care center between 2015 and 2021. Adults with autologous cranioplasty (n = 132) were recruited from procedure logs and the hospital electronic health record. Clinicodemographic parameters, risk factors, and complications were recorded. Neurologic outcomes were measured using the dichotomized Glasgow Outcome Scale (GOS). Primary outcome measure was pre- and post-cranioplasty GOS at the last follow up. Secondary outcome measures were the predicting factors that contributed to enhanced neurologic outcome post-cranioplasty. RESULTS: Mean age was 41.4 (standard deviation ± 13.5) years with male predominance (12.2:1). Complications developed in 12.9% (n = 17), with infections in 3.8% (n = 5) and hydrocephalus in 2.3% (n = 3). In bivariate analysis, pre-cranioplasty GOS good grades 4 and 5 (P < 0.001), trauma as an indication for decompressive craniectomy (DC) (P < 0.001), and early cranioplasty ≤12 weeks (P = 0.023) were statistically significant predictors for post-cranioplasty neurologic recovery at follow-up. In a multiple logistic regression model, adjusted odds ratio for pre-cranioplasty GOS was 28.77 (95% confidence interval [CI] 7.21-114.74, P < 0.001), for trauma as indication for DC was 5.15 (95% CI 1.65-16.05, P = 0.003), and for early cranioplasty ≤12 weeks was 3.04 (95% CI 1.12-8.27 P = 0.029). CONCLUSIONS: Autologous cranioplasty contributes to a quantifiable neurologic outcome. Pre-cranioplasty neurologic status, cranioplasty done for traumatic DC and early cranioplasty may have potential for enhanced neurologic recovery. Further clinical studies with better evidence may expound upon these findings.

Mental health research in the Arab region in response to the COVID-19 pandemic: a scoping review.

Background: The ongoing pandemic has led to a global surge in coronavirus disease 2019 (COVID-19)-related mental health research. However, most related publications come from Western countries or China, and their findings cannot always be extrapolated to Arab countries. Aims: This study provides a quantitative and qualitative analysis of mental health research pertaining to Arab countries' response to the COVID-19 pandemic. Methods: A scoping review of the World Health Organization (WHO) COVID-19 database for publications on mental health was conducted by authors affiliated with Arab institutions, including articles from inception to 24 October 2020. The included publications were evaluated for their national distribution, international collaboration, publication type, and main research themes. Methodological quality analysis of the included research studies was performed using the original and modified versions of the Newcastle-Ottawa Scale. Results: In total, 102 articles were included in this study, averaging 4.6 articles per Arab country. Most of the articles emerged from the Kingdom of Saudi Arabia, Jordan, and Egypt. A majority of publications demonstrated international collaboration. Most of the publications were original research studies and cross-sectional in design. The predominant research theme was examining the pandemic's mental health effects on the general population and healthcare workers. Only 28.0% of the studies were of high methodological quality, whereas 41.5% were moderate and 30.5% were low in quality. Conclusions: Mental health research in response to the COVID-19 pandemic in the Arab region has quantitative and qualitative shortfalls. Arab institutions need to respond to the pandemic promptly in order to address the delineated research gap and to generate higher-quality research output.

Screening for diabetes and impaired glucose metabolism in Qatar: Models' development and validation.

AIM: To establish two scoring models for identifying individuals at risk of developing Impaired Glucose Metabolism (IGM) or Type two Diabetes Mellitus (T2DM) in Qatari. MATERIALS AND METHODS: A sample of 2000 individuals, from Qatar BioBank, was evaluated to determine features predictive of T2DM and IGM. Another sample of 1000 participants was obtained for external validation of the models. Several scoring models screening for T2DM were evaluated and compared to the model proposed by this study. RESULTS: Age, gender, waist-to-hip-ratio, history of hypertension and hyperlipidemia, and levels of educational were statistically associated with the risk of T2DM and constituted the Qatar diabetes mellitus risk score (QDMRISK). Along with, the 6 aforementioned variables, the IGM model showed that BMI was statistically significant. The QDMRISK performed well with area under the curve (AUC) 0.870 and .815 in the development and external validation cohorts, respectively. The QDMRISK showed overall better accuracy and calibration compared to other evaluated scores. The IGM model showed good accuracy and calibration, with AUCs .796 and .774 in the development and external validation cohorts, respectively. CONCLUSIONS: This study developed Qatari-specific diabetes and IGM risk scores to identify high risk individuals and can guide the development of a nationwide primary prevention program.

SARS-CoV-2 and immune-microbiome interactions: Lessons from respiratory viral infections.

By the beginning of 2020, infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had rapidly evolved into an emergent worldwide pandemic, an outbreak whose unprecedented consequences highlighted many existing flaws within public healthcare systems across the world. While coronavirus disease 2019 (COVID-19) is bestowed with a broad spectrum of clinical manifestations, involving the vital organs, the respiratory system transpires as the main route of entry for SARS-CoV-2, with the lungs being its primary target. Of those infected, up to 20% require hospitalization on account of severity, while the majority of patients are either asymptomatic or exhibit mild symptoms. Exacerbation in the disease severity and complications of COVID-19 infection have been associated with multiple comorbidities, including hypertension, diabetes mellitus, cardiovascular disorders, cancer, and chronic lung disease. Interestingly, a recent body of evidence indicated the pulmonary and gut microbiomes as potential modulators for altering the course of COVID-19, potentially via the microbiome-immune system axis. While the relative concordance between microbes and immunity has yet to be fully elucidated with regards to COVID-19, we present an overview of our current understanding of COVID-19-microbiome-immune cross talk and discuss the potential contributions of microbiome-related immunity to SARS-CoV-2 pathogenesis and COVID-19 disease progression.

External Validation and Recalibration of the CURB-65 and PSI for Predicting 30-Day Mortality and Critical Care Intervention in Multiethnic Patients with COVID-19.

OBJECTIVES: To validate and recalibrate the CURB-65 and pneumonia severity index (PSI) in predicting 30-day mortality and critical care intervention (CCI) in a multiethnic population with COVID-19, along with evaluating both models in predicting CCI. METHODS: Retrospective data was collected for 1181 patients admitted to the largest hospital in Qatar with COVID-19 pneumonia. The area under the curve (AUC), calibration curves, and other metrics were bootstrapped to examine the performance of the models. Variables constituting the CURB-65 and PSI scores underwent further analysis using the Least Absolute Shrinkage and Selection Operator (LASSO) along with logistic regression to develop a model predicting CCI. Complex machine learning models were built for comparative analysis. RESULTS: The PSI performed better than CURB-65 in predicting 30-day mortality (AUC 0.83, 0.78 respectively), while CURB-65 outperformed PSI in predicting CCI (AUC 0.78, 0.70 respectively). The modified PSI/CURB-65 model (respiratory rate, oxygen saturation, hematocrit, age, sodium, and glucose) predicting CCI had excellent accuracy (AUC 0.823) and good calibration. CONCLUSIONS: Our study recalibrated, externally validated the PSI and CURB-65 for predicting 30-day mortality and CCI, and developed a model for predicting CCI. Our tool can potentially guide clinicians in Qatar to stratify patients with COVID-19 pneumonia.

Patient-Reported Outcome for Endovascular Treatment versus Microsurgical Clipping in Aneurysmal Subarachnoid Hemorrhage.

OBJECTIVE: Aneurysmal subarachnoid hemorrhage has a high mortality with significant impact on quality of life despite effective management strategies including endovascular treatment and/or microsurgical clipping. Although the modalities have undergone clinical comparison, they have not been evaluated on patient-reported outcomes (PROs). This study compared endovascular versus microsurgical treatment using a PRO measure. METHODS: We conducted a cross-sectional telephonic survey of adult patients conducted at Hamad General Hospital, Doha, Qatar between 2017 and 2019. Candidate study participants were identified from procedure logs and hospital electronic health records for endovascular treatment (N = 32) versus microsurgical clipping (N = 32) of cerebral aneurysm. The primary outcome measure was the short version of the Stroke-Specific Quality of Life (SS-QoL) measure. The secondary outcome measure was the screened clinician-reported modified Rankin Scale (mRS) for all screened patients (n = 137). Mean scores were compared for the 2 treatment groups. RESULTS: The SS-QoL mean score was 4.23 (standard deviation ± 0.77) in endovascular treatment and 4.19 ± 0.19 in surgical clipping (P = 0.90). In exploratory analysis, mean physical domain score was 3.17 ± 0.60 versus 2.98 ± 0.66 in endovascular treatment and surgical clipping groups, respectively. Mean psychosocial domain scores were 4.43 ± 0.85 versus 4.18 ± 0.0.92, respectively. In multivariable analysis, none of the clinical variables were significantly related to SS-QoL except vasospasm irrespective of intervention received. In secondary outcome analysis, modified Rankin Scale score was higher for endovascular treatment (P = 0.04). CONCLUSIONS: Published evidence has supported clinical benefits of endovascular treatment for cerebral aneurysm treatment, but this study did not find any difference in PROs. Future studies of treatments should include PRO to identify potential differences from the patient's perspective.

SnoRNAs and miRNAs Networks Underlying COVID-19 Disease Severity.

There is a lack of predictive markers for early and rapid identification of disease progression in COVID-19 patients. Our study aims at identifying microRNAs (miRNAs)/small nucleolar RNAs (snoRNAs) as potential biomarkers of COVID-19 severity. Using differential expression analysis of microarray data (n = 29), we identified hsa-miR-1246, ACA40, hsa-miR-4532, hsa-miR-145-5p, and ACA18 as the top five differentially expressed transcripts in severe versus asymptomatic, and ACA40, hsa-miR-3609, ENSG00000212378 (SNORD78), hsa-miR-1231, hsa-miR-885-3p as the most significant five in severe versus mild cases. Moreover, we found that white blood cell (WBC) count, absolute neutrophil count (ANC), neutrophil (%), lymphocyte (%), red blood cell (RBC) count, hemoglobin, hematocrit, D-Dimer, and albumin are significantly correlated with the identified differentially expressed miRNAs and snoRNAs. We report a unique miRNA and snoRNA profile that is associated with a higher risk of severity in a cohort of SARS-CoV-2 infected patients. Altogether, we present a differential expression analysis of COVID-19-associated microRNA (miRNA)/small nucleolar RNA (snoRNA) signature, highlighting their importance in SARS-CoV-2 infection.

Complement C5a and Clinical Markers as Predictors of COVID-19 Disease Severity and Mortality in a Multi-Ethnic Population.

Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n=33), mild (n=33) and asymptomatic (n=23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help in the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.