Global anaesthesia-related cardiac arrest rates in children: a systematic review and meta-analysis.

BACKGROUND: Neonates and infants have a higher perioperative risk of cardiac arrest and mortality than adults. The Human Development Index (HDI) ranges from 0 to 1, representing the lowest and highest levels of development, respectively. The relation between anaesthesia safety and country HDI has been described previously. We examined the relationship among the anaesthesia-related cardiac arrest rate (ARCAR), country HDI, and time in a mixed paediatric patient population. METHODS: Electronic databases were searched up to July 2022 for studies reporting 24-h postoperative ARCARs in children. ARCARs (per 10,000 anaesthetic procedures) were analysed in low-HDI (HDI<0.8) vs high-HDI countries (HDI≥0.8) and over time (pre-2001 vs 2001-22). The magnitude of these associations was studied using systematic review methods with meta-regression analysis and meta-analysis. RESULTS: We included 38 studies with 5,493,489 anaesthetic procedures and 1001 anaesthesia-related cardiac arrests. ARCARs were inversely correlated with country HDI (P<0.0001) but were not correlated with time (P=0.82). ARCARs did not change between the periods in either high-HDI or low-HDI countries (P=0.71 and P=0.62, respectively), but were higher in low-HDI countries than in high-HDI countries (9.6 vs 2.0; P<0.0001) in 2001-22. ARCARs were higher in children aged <1 yr than in those ≥1 yr in high-HDI (10.69 vs 1.48; odds ratio [OR] 8.03, 95% confidence interval [CI] 5.96-10.81; P<0.0001) and low-HDI countries (36.02 vs 2.86; OR 7.32, 95% CI 3.48-15.39; P<0.0001) in 2001-22. CONCLUSIONS: The high and alarming anaesthesia-related cardiac arrest rates among children younger than 1 yr of age in high-HDI and low-HDI countries, respectively, reflect an ongoing challenge for anaesthesiologists. SYSTEMATIC REVIEW PROTOCOL: PROSPERO CRD42021229919.

Machine Learning-based Prediction Model for Treatment of Acromegaly With First-generation Somatostatin Receptor Ligands.

CONTEXT: Artificial intelligence (AI), in particular machine learning (ML), may be used to deeply analyze biomarkers of response to first-generation somatostatin receptor ligands (fg-SRLs) in the treatment of acromegaly. OBJECTIVE: To develop a prediction model of therapeutic response of acromegaly to fg-SRL. METHODS: Patients with acromegaly not cured by primary surgical treatment and who had adjuvant therapy with fg-SRL for at least 6 months after surgery were included. Patients were considered controlled if they presented growth hormone (GH) <1.0 ng/mL and normal age-adjusted insulin-like growth factor (IGF)-I levels. Six AI models were evaluated: logistic regression, k-nearest neighbor classifier, support vector machine, gradient-boosted classifier, random forest, and multilayer perceptron. The features included in the analysis were age at diagnosis, sex, GH, and IGF-I levels at diagnosis and at pretreatment, somatostatin receptor subtype 2 and 5 (SST2 and SST5) protein expression and cytokeratin granulation pattern (GP). RESULTS: A total of 153 patients were analyzed. Controlled patients were older (P = .002), had lower GH at diagnosis (P = .01), had lower pretreatment GH and IGF-I (P < .001), and more frequently harbored tumors that were densely granulated (P = .014) or highly expressed SST2 (P < .001). The model that performed best was the support vector machine with the features SST2, SST5, GP, sex, age, and pretreatment GH and IGF-I levels. It had an accuracy of 86.3%, positive predictive value of 83.3% and negative predictive value of 87.5%. CONCLUSION: We developed a ML-based prediction model with high accuracy that has the potential to improve medical management of acromegaly, optimize biochemical control, decrease long-term morbidities and mortality, and reduce health services costs.

Effectiveness of testosterone therapy in obese men with low testosterone levels, for losing weight, controlling obesity complications, and preventing cardiovascular events: Protocol of a systematic review of randomized controlled trials.

BACKGROUND: The use of testosterone replacement therapy in obese men with low testosterone levels has been controversial. This review aims to analyze the effectiveness of testosterone therapy for weight loss and preventing cardiovascular complications in obese men with low testosterone levels. METHODS: We will perform a systematic review according to Cochrane Methodology of randomized studies, including crossover studies, wherein patients are allocated into one of the two groups: testosterone therapy and control (no treatment or placebo). The primary outcomes analyzed will be: weight loss, adverse events, quality of life, improvement of libido, control of obesity complications, frequency of cardiovascular events, and deaths. Four general and adaptive search strategies have been created for the following electronic health databases: Embase, Medline, LILACS, and CENTRAL. Two reviewers will independently select the eligible studies, assess the risk of bias, and extract the data from included studies. Similar outcomes measured in at least two trials will be plotted in the meta-analysis using Review Manager 5.3. The quality of evidence of the effect estimate of the intervention for the outcomes that could be plotted in the meta-analysis will be generated according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group. RESULTS: Although testosterone replacement seems to be an attractive treatment modality for obese men with low testosterone, its potential benefits has been refuted by some studies, whose results have not shown significant differences between treated and untreated patients. CONCLUSION: For obese men with low testosterone concentrations, the proposed systematic review aims to answer the following questions: When compared with no treatment or placebo: Is testosterone therapy safe? Is testosterone therapy effective in promoting weight loss, a sustained reduction in body weight and changes in body composition? Is testosterone effective in improving quality of life, libido, and erectile function? Is testosterone therapy effective in controlling obesity complications and in preventing cardiovascular events?