Factors associated with changes in the quality of life and family functioning scores of primary caregivers of children and young people with primary brain tumors in Karachi, Pakistan: a prospective cohort study.

BACKGROUND: There are limited data available, particularly in low- and middle-income countries (LMICs), on the long-term quality of life (QoL) and family functioning of primary caregivers of children and young people (CYPs) affected by primary brain tumors (PBTs). This study aimed to assess the factors associated with the mean change in QoL and family functioning scores of primary caregivers of CYP patients with PBTs 12 months posttreatment. METHODS: This prospective cohort study enrolled CYPs aged 5-21 years with newly diagnosed PBTs and their primary caregivers. The study was carried out between November 2020 and July 2023. The primary caregivers of CYPs were recruited from two major tertiary care centers in Karachi, Pakistan. The primary caregivers QoL were assessed by the Pediatric Quality of Life Inventory (PedsQL) Family Impact Module. The assessment was undertaken by a psychologist at the time of diagnosis and 12 months posttreatment. The data were analyzed with STATA version 12. RESULTS: Forty-eight CYPs with newly diagnosed PBTs and their primary caregivers (46 mothers and 2 fathers) were enrolled. At 12 months posttreatment, 25 (52%) CYPs and their primary caregivers (mothers) were reassessed, and 23 (48%) were lost to follow-up. On multivariable analysis, a significant decrease in mothers' mean 12-month posttreatment QoL and family functioning scores was associated with CYP having posttreatment seizures (beta= -10.2; 95% CI: -18.4 to -2.0) and with the financial burden associated with the CYP's illness (beta= -0.3; 95% CI: -0.4 to -0.1). However, in those cases where CYP had higher posttreatment quality of life scores (beta = 0.4; 95% CI = 0.1, 0.6) and posttreatment higher verbal intelligence scores (beta = 0.1; 95% CI = 0.01, 0.3), the mothers' QoL and family functioning scores were significantly greater. CONCLUSION: We found a significant decrease in QoL of mothers who had a high financial burden and whose CYP had posttreatment seizures. However, those whose CYPs had higher posttreatment verbal intelligence scores and quality of life scores had significantly greater QoL scores. Identification of the factors that influence primary caregivers QoL has the potential to aid in the development of targeted strategies to alleviate stressors and improve the overall quality of life for primary caregivers and their children who are at high risk.

Predictors of neurocognition outcomes in children and young people with primary brain tumor presenting to tertiary care hospitals of Karachi, Pakistan: a prospective cohort study.

INTRODUCTION: Primary brain tumors are a common cause of morbidity and mortality in children and young people (CYP) globally. Impaired neurocognitive function is a potential severe consequence in primary brain tumor (PBT) survivors. There are no in-depth studies from low- and middle-income countries (LMICs) to inform management and follow-up. The research questions of this study were as follows: Are the sociodemographic factors (lower age of CYP, female gender, low socioeconomic status, low parental education), disease-related factors (high grade of tumor, presence of seizures, presence of hydrocephalous), and treatment-related factors (adjuvant therapy, no surgical intervention, post-treatment seizures, placement of shunts) associated with decline in neurcognition outcomes 12 months post-treatment in CYP with PBTs? METHODS: A prospective cohort study was conducted from November 2020 to July 2023 at the Aga Khan University Hospital and Jinnah Postgraduate Medical Centre, tertiary care hospitals in Karachi, Pakistan. All CYP aged 5 to 21 years with a newly diagnosed PBTs were eligible. The neurocognition assessment was undertaken by a psychologist at two points, i.e., pre-treatment and at 12 months post-treatment using validated tools. The verbal intelligence was assessed by Slosson Intelligence tool, revised 3rd edition (SIT-R3), perceptual reasoning by Raven's Progressive Matrices (RPM), and the Processing Speed Index by Wechsler Intelligence Scale (WISC V) and Wechsler Adult Intelligence Scale (WAIS-IV). The data were analyzed by STATA version 12 software. Generalized estimating equation (GEE) was used to determine the factors associated with the mean change in 12 months post-treatment verbal and non-verbal neurocognition scores. Unadjusted and adjusted beta coefficients with their 95% confidence intervals were reported. RESULTS: A total of 48 CYPs with PBTs were enrolled, 23 (48%) of them were lost to follow-up and 10 (21%) died. The remaining 25 (52%) were reassessed 12 months after treatment. On multivariable analysis, a significant decline in verbal intelligence scores at 12 months was predicted by post-treatment seizures beta = - 20.8 (95% CI, - 38.2, - 3.4), mothers having no formal educational status and lower household monthly income. Similarly, a significant decline in perceptual reasoning scores was also predicted by post-treatment seizures beta = - 10.7 (95% CI, - 20.6, - 0.8), mothers having no formal education and having lower household monthly income. Worsening of processing speed scores at 12 months post-treatment were predicted by tumor histology, post-treatment seizures beta = - 33.9 (95% CI, - 47.7, - 20.0), lower educational status of the mother, and having lower household monthly. However, an improvement was seen in processing speed scores after surgical tumor resection. CONCLUSION: In this novel study, the post-treatment mean change in verbal and non-verbal neurocognition scores was associated with sociodemographic, tumor, and treatment factors. These findings may have potential implications for targeted early psychological screening of higher risk CYP with PBTs. Identification of these predictors may serve as a foundation for developing more cost-effective treatment thereby alleviating the burden of neurocognitive morbidity. However to establish generalizability, future research should prioritize larger-scale, multicountry studies. (Trial registration: ClinicalTrials.gov Identifier: NCT05709522).

Automated Annotation of Epileptiform Burden and Its Association with Outcomes.

OBJECTIVE: This study was undertaken to determine the dose-response relation between epileptiform activity burden and outcomes in acutely ill patients. METHODS: A single center retrospective analysis was made of 1,967 neurologic, medical, and surgical patients who underwent >16 hours of continuous electroencephalography (EEG) between 2011 and 2017. We developed an artificial intelligence algorithm to annotate 11.02 terabytes of EEG and quantify epileptiform activity burden within 72 hours of recording. We evaluated burden (1) in the first 24 hours of recording, (2) in the 12-hours epoch with highest burden (peak burden), and (3) cumulatively through the first 72 hours of monitoring. Machine learning was applied to estimate the effect of epileptiform burden on outcome. Outcome measure was discharge modified Rankin Scale, dichotomized as good (0-4) versus poor (5-6). RESULTS: Peak epileptiform burden was independently associated with poor outcomes (p < 0.0001). Other independent associations included age, Acute Physiology and Chronic Health Evaluation II score, seizure on presentation, and diagnosis of hypoxic-ischemic encephalopathy. Model calibration error was calculated across 3 strata based on the time interval between last EEG measurement (up to 72 hours of monitoring) and discharge: (1) <5 days between last measurement and discharge, 0.0941 (95% confidence interval [CI] = 0.0706-0.1191); 5 to 10 days between last measurement and discharge, 0.0946 (95% CI = 0.0631-0.1290); >10 days between last measurement and discharge, 0.0998 (95% CI = 0.0698-0.1335). After adjusting for covariates, increase in peak epileptiform activity burden from 0 to 100% increased the probability of poor outcome by 35%. INTERPRETATION: Automated measurement of peak epileptiform activity burden affords a convenient, consistent, and quantifiable target for future multicenter randomized trials investigating whether suppressing epileptiform activity improves outcomes. ANN NEUROL 2021;90:300-311.

Burst Suppression: Causes and Effects on Mortality in Critical Illness.

BACKGROUND: Burst suppression in mechanically ventilated intensive care unit (ICU) patients is associated with increased mortality. However, the relative contributions of propofol use and critical illness itself to burst suppression; of burst suppression, propofol, and critical illness to mortality; and whether preventing burst suppression might reduce mortality, have not been quantified. METHODS: The dataset contains 471 adults from seven ICUs, after excluding anoxic encephalopathy due to cardiac arrest or intentional burst suppression for therapeutic reasons. We used multiple prediction and causal inference methods to estimate the effects connecting burst suppression, propofol, critical illness, and in-hospital mortality in an observational retrospective study. We also estimated the effects mediated by burst suppression. Sensitivity analysis was used to assess for unmeasured confounding. RESULTS: The expected outcomes in a "counterfactual" randomized controlled trial (cRCT) that assigned patients to mild versus severe illness are expected to show a difference in burst suppression burden of 39%, 95% CI [8-66]%, and in mortality of 35% [29-41]%. Assigning patients to maximal (100%) burst suppression burden is expected to increase mortality by 12% [7-17]% compared to 0% burden. Burst suppression mediates 10% [2-21]% of the effect of critical illness on mortality. A high cumulative propofol dose (1316 mg/kg) is expected to increase burst suppression burden by 6% [0.8-12]% compared to a low dose (284 mg/kg). Propofol exposure has no significant direct effect on mortality; its effect is entirely mediated through burst suppression. CONCLUSIONS: Our analysis clarifies how important factors contribute to mortality in ICU patients. Burst suppression appears to contribute to mortality but is primarily an effect of critical illness rather than iatrogenic use of propofol.

Burden of Epileptiform Activity Predicts Discharge Neurologic Outcomes in Severe Acute Ischemic Stroke.

BACKGROUND/OBJECTIVES: Clinical seizures following acute ischemic stroke (AIS) appear to contribute to worse neurologic outcomes. However, the effect of electrographic epileptiform abnormalities (EAs) more broadly is less clear. Here, we evaluate the impact of EAs, including electrographic seizures and periodic and rhythmic patterns, on outcomes in patients with AIS. METHODS: This is a retrospective study of all patients with AIS aged ≥ 18 years who underwent at least 18 h of continuous electroencephalogram (EEG) monitoring at a single center between 2012 and 2017. EAs were classified according to American Clinical Neurophysiology Society (ACNS) nomenclature and included seizures and periodic and rhythmic patterns. EA burden for each 24-h epoch was defined using the following cutoffs: EA presence, maximum daily burden < 10% versus > 10%, maximum daily burden < 50% versus > 50%, and maximum daily burden using categories from ACNS nomenclature ("rare" < 1%; "occasional" 1-9%; "frequent" 10-49%; "abundant" 50-89%; "continuous" > 90%). Maximum EA frequency for each epoch was dichotomized into ≥ 1.5 Hz versus < 1.5 Hz. Poor neurologic outcome was defined as a modified Rankin Scale score of 4-6 (vs. 0-3 as good outcome) at hospital discharge. RESULTS: One hundred and forty-three patients met study inclusion criteria. Sixty-seven patients (46.9%) had EAs. One hundred and twenty-four patients (86.7%) had poor outcome. On univariate analysis, the presence of EAs (OR 3.87 [1.27-11.71], p = 0.024) and maximum daily burden > 10% (OR 12.34 [2.34-210], p = 0.001) and > 50% (OR 8.26 [1.34-122], p = 0.035) were associated with worse outcomes. On multivariate analysis, after adjusting for clinical covariates (age, gender, NIHSS, APACHE II, stroke location, stroke treatment, hemorrhagic transformation, Charlson comorbidity index, history of epilepsy), EA presence (OR 5.78 [1.36-24.56], p = 0.017), maximum daily burden > 10% (OR 23.69 [2.43-230.7], p = 0.006), and maximum daily burden > 50% (OR 9.34 [1.01-86.72], p = 0.049) were associated with worse outcomes. After adjusting for covariates, we also found a dose-dependent association between increasing EA burden and increasing probability of poor outcomes (OR 1.89 [1.18-3.03] p = 0.009). We did not find an independent association between EA frequency and outcomes (OR: 4.43 [.98-20.03] p = 0.053). However, the combined effect of increasing EA burden and frequency ≥ 1.5 Hz (EA burden * frequency) was significantly associated with worse outcomes (OR 1.64 [1.03-2.63] p = 0.039). CONCLUSIONS: Electrographic seizures and periodic and rhythmic patterns in patients with AIS are associated with worse outcomes in a dose-dependent manner. Future studies are needed to assess whether treatment of this EEG activity can improve outcomes.

Impact of depressed skull fracture surgery on outcome of head injury patients.

OBJECTIVE: To assess outcomes in surgically managed patients with depressed skull fractures and associated moderate to severe head injury. METHODS: The study was conducted in the Department of Neurosurgery Jinnah Postgraduate Medical Centre, Karachi, from January 2016 to December 2017. We analyzed 90 patients with depressed skull fracture managed surgically from January 2015 to December 2016. The patients selected for this study belonged to all age groups with clinically palpable depressed skull fracture confirmed by CT brain with bone window. Outcome was assessed by Glasgow outcome score. RESULTS: Total 90 patients were included in the study. Sixty (66.7%) were male and 30 (33.3%) were female with mean age of years 27.58+11.329. Among 90 patients, 38.8% were aged between 21 and 30 years. Road traffic accident was seen in 72 (80%) patients. The commonest site of fracture was frontal region in 50 patients (55.6%). GCS improved post operatively on comparison to preoperative. Five patients expired. CONCLUSION: Depressed skull fracture is common neuro surgical issue. Timely surgical management gives excellent results by decreasing morbidity and mortality.

Higher order moments of the estimated tangency portfolio weights.

In this paper, we consider the estimated weights of the tangency portfolio. We derive analytical expressions for the higher order non-central and central moments of these weights when the returns are assumed to be independently and multivariate normally distributed. Moreover, the expressions for mean, variance, skewness and kurtosis of the estimated weights are obtained in closed forms. Later, we complement our results with a simulation study where data from the multivariate normal and t-distributions are simulated, and the first four moments of estimated weights are computed by using the Monte Carlo experiment. It is noteworthy to mention that the distributional assumption of returns is found to be important, especially for the first two moments. Finally, through an empirical illustration utilizing returns of four financial indices listed in NASDAQ stock exchange, we observe the presence of time dynamics in higher moments.

Prenatal-onset INPPL1-related skeletal dysplasia in two unrelated families: Diagnosis and prediction of lethality.

This report describes two patients with INPPL1- related skeletal dysplasia diagnosed prenatally. A literature review is conducted to find out if high-lethality is associated with particular pathogenic variants in INPPL1 gene. Prediction of lethality in the prenatal setting has an impact on perinatal management. Some frameshift variants in INPLL1 gene are uniquely observed in lethal cases; however, more patients are needed to confirm the correlation.

Complications After Surgical Repair of Congenital Heart Disease in Infants. An Experience From Tertiary Care Center.

OBJECTIVES: This study aimed to describe the incidence and spectrum of postoperative complications in infants who underwent their first cardiac surgery for the repair of congenital heart diseases. METHODS: This is a single-center retrospective study. Data of infants admitted to King Faisal Specialist Hospital & Research Center; Jeddah; Saudi Arabia, from January 2015 to December 2019 who underwent the first cardiac procedure for congenital heart disease at an age of less than 3 months, were analyzed. The primary outcome is the prevalence and spectrum of postoperative complications during hospitalization. Data were analyzed by using descriptive and analytical statistics using SAS software version 9.4. RESULTS: Data of 130 procedures were analyzed. The most frequent procedure performed was the Norwood procedure (31.5%), aortic coarctation repair (13.8%), arterial switch operation (13%), and Blalock-Taussig and central shunts (10%). The overall postprocedural complications were reported in 96 (73.8%) of the procedures. The most frequent complications were prolonged postoperative mechanical ventilation (27%), pleural effusion (21%), excessive bleeding (19%), cardiac arrest (18%), and systemic infections (18%). CONCLUSION: Cardiac surgery for congenital heart disease in young infants has a substantial risk for postoperative complications. The high incidence of these complications in these cases makes necessary attention to prove the outcomes in the cardiac centers.

A comparison of feature selection methods when using motion sensors data: a case study in Parkinson's disease.

The objective of this study is to investigate the effects of feature selection methods on the performance of machine learning methods for quantifying motor symptoms of Parkinson's disease (PD) patients. Different feature selection methods including step-wise regression, Lasso regression and Principal Component Analysis (PCA) were applied on 88 spatiotemporal features that were extracted from motion sensors during hand rotation tests. The selected features were then used in support vector machines (SVM), decision trees (DT), linear regression, and random forests models to calculate a so-called treatment-response index (TRIS). The validity, testretest reliability and sensitivity to treatment were assessed for each combination (feature selection method plus machine learning method). There were improvements in correlation coefficients and root mean squared error (RMSE) for all the machine learning methods, except DTs, when using the selected features from step-wise regression inputs. Using step-wise regression and SVM was found to have better sensitivity to treatment and higher correlation to clinical ratings on the Unified PD Rating Scale as compared to the combination of PCA and SVM. When assessing the ability of the machine learning methods to discriminate between tests performed by PD patients and healthy controls the results were mixed. These results suggest that the choice of feature selection methods is crucial when working with data-driven modelling. Based on our findings the step-wise regression can be considered as the method with the best performance.