Dyslexia and Comorbid Dyscalculia: rate of comorbidity and underlying cognitive and learning profile

PURPOSE OF THE STUDY. Children diagnosed with a specific learning disorder (SLD) have four to five times higher chances of developing a comorbid condition. In particular, the high prevalence of comorbid dyscalculia (MD) in children with dyslexia (RD) has been documented. Nevertheless, the exact rate of MD comorbidity and the causes underlying the overlap remain unclear since most research has focused on studying them in isolation. Given the relevance of early identification and evidence-based interventions for further compensation of SLD, there is a need for studies on this matter. The study intended to fill this gap. METHOD. The study was a secondary data analysis of the standardised test scores of 215 neuropsychological assessments administered to grade 1 to 3 schoolchildren in Argentina who had a prior diagnosis of RD. For the purposes of the study, they were classified into 2 groups (RD only and comorbid RDMD). Scores were analyzed using SPSS Statistics to (i) explore the rate of MD comorbidity in children with RD; (ii) contrast the cognitive and learning profiles of the RD and the RDMD group; and (iii) assess the predictive value of each cognitive factor to the development of the RDMD comorbidity. RESULTS AND CONCLUSION. The study found that children with RD developed RDMD at a frequency of 33.5%. There was a significant difference in the two groups' learning and cognitive factors scores, with the comorbid group worst affected in all domains. Among these, verbal working memory, spatial skills, semantic long-term memory and phonological awareness were the most sensitive predictors; together they could account for 35% of the MD comorbidity. These findings are evidence of the high incidence of MD comorbidity in the population with RD and highlight the predictive value of specific cognitive markers

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

Background: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Development and validation of a score to predict postoperative respiratory failure in a multicentre European cohort : A prospective, observational study

BACKGROUND Postoperative respiratory failure (PRF) is the most frequent respiratory complication following surgery. OBJECTIVE The objective of this study was to build a clinically useful predictive model for the development of PRF. DESIGN A prospective observational study of a multicentre cohort. SETTING Sixty-three hospitals across Europe. PATIENTS Patients undergoing any surgical procedure under general or regional anaesthesia during 7-day recruitment periods. MAIN OUTCOME MEASURES Development of PRF within 5 days of surgery. PRF was defined by a partial pressure of oxygen in arterial blood (PaO2) less than 8 kPa or new onset oxyhaemoglobin saturation measured by pulse oximetry (SpO(2)) less than 90% whilst breathing room air that required conventional oxygen therapy, noninvasive or invasive mechanical ventilation. RESULTS PRF developed in 224 patients (4.2% of the 5384 patients studied). In-hospital mortality [95% confidence interval (95% CI)] was higher in patients who developed PRF [10.3% (6.3 to 14.3) vs. 0.4% (0.2 to 0.6)]. Regression modelling identified a predictive PRF score that includes seven independent risk factors: low preoperative SpO(2); at least one preoperative respiratory symptom; preoperative chronic liver disease; history of congestive heart failure; open intrathoracic or upper abdominal surgery; surgical procedure lasting at least 2 h; and emergency surgery. The area under the receiver operating characteristic curve (c-statistic) was 0.82 (95% CI 0.79 to 0.85) and the Hosmer-Lemeshow goodness-of-fit statistic was 7.08 (P = 0.253). CONCLUSION A risk score based on seven objective, easily assessed factors was able to predict which patients would develop PRF. The score could potentially facilitate preoperative risk assessment and management and provide a basis for testing interventions to improve outcomes. The study was registered at ClinicalTrials.gov (identifier NCT01346709)