Contribuições da natureza para a qualidade de vida.

O capítulo avalia a contribuição da natureza para a qualidade de vida das pessoas, incluindo a inter-relação entre a biodiversidade, o funcionamento de ecossistemas e os serviços ecossistêmicos. Além da situação atual, trabalha com a dinâmica e as tendências futuras dos serviços ecossistêmicos essenciais para o bem-estar humano (como saúde, segurança alimentar, segurança hídrica, segurança energética). O texto aborda também a contribuição do conhecimento e das práticas de populações indígenas e tradicionais para a conservação da biodiversidade, para a diversificação de espécies (gerando novas espécies), bem como para a distribuição de espécies e formação de paisagens nos diversos biomas

Apresentando o diagnóstico brasileiro de biodiversidade e serviços ecossistêmicos.

Apresentando o Diagnóstico Brasileiro de Biodiversidade e Serviços Ecossistêmicos: aborda conceitos-chave sobre os quais a Plataforma Brasileira de Biodiversidade e Serviços Ecossistêmicos (BPBES, da sigla em inglês) se baseia para elaborar o Diagnóstico, além daqueles que estarão presentes ao longo de todo o documento (Figura 1.1). O capítulo apresenta um resumo de dados relevantes por bioma, questões de política ambiental e temas como degradação e restauração, espécies invasoras e uso sustentável da biodiversidade

Air quality and urban sustainable development: the application of machine learning tools

[EN] Air quality has an efect on a population¿s quality of life. As a dimension of sustainable urban development, governments have been concerned about this indicator. This is refected in the references consulted that have demonstrated progress in forecasting pollution events to issue early warnings using conventional tools which, as a result of the new era of big data, are becoming obsolete. There are a limited number of studies with applications of machine learning tools to characterize and forecast behavior of the environmental, social and economic dimensions of sustainable development as they pertain to air quality. This article presents an analysis of studies that developed machine learning models to forecast sustainable development and air quality. Additionally, this paper sets out to present research that studied the relationship between air quality and urban sustainable development to identify the reliability and possible applications in diferent urban contexts of these machine learning tools. To that end, a systematic review was carried out, revealing that machine learning tools have been primarily used for clustering and classifying variables and indicators according to the problem analyzed, while tools such as artifcial neural networks and support vector machines are the most widely used to predict diferent types of events. The nonlinear nature and synergy of the dimensions of sustainable development are of great interest for the application of machine learning tools.Molina-Gómez, NI.; Díaz-Arévalo, JL.; López Jiménez, PA. (2021). Air quality and urban sustainable development: the application of machine learning tools. 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Physicians’ misperceived cardiovascular risk and therapeutic inertia as determinants of low LDL-cholesterol targets achievement in diabetes

Background: Greater efforts are needed to overcome the worldwide reported low achievement of LDL-c targets. This survey aimed to dissect whether and how the physician-based evaluation of patients with diabetes is associated with the achievement of LDL-c targets. Methods: This cross-sectional self-reported survey interviewed physicians working in 67 outpatient services in Italy, collecting records on 2844 patients with diabetes. Each physician reported a median of 47 records (IQR 42–49) and, for each of them, the physician specified its perceived cardiovascular risk, LDL-c targets, and the suggested refinement in lipid-lowering-treatment (LLT). These physician-based evaluations were then compared to recommendations from EAS/EASD guidelines. Results: Collected records were mostly from patients with type 2 diabetes (94%), at very-high (72%) or high-cardiovascular risk (27%). Physician-based assessments of cardiovascular risk and of LDL-c targets, as compared to guidelines recommendation, were misclassified in 34.7% of the records. The misperceived assessment was significantly higher among females and those on primary prevention and was associated with 67% lower odds of achieving guidelines-recommended LDL-c targets (OR 0.33, p < 0.0001). Peripheral artery disease, target organ damage and LLT-initiated by primary-care-physicians were all factors associated with therapeutic-inertia (i.e., lower than expected probability of receiving high-intensity LLT). Physician-suggested LLT refinement was inadequate in 24% of overall records and increased to 38% among subjects on primary prevention and with misclassified cardiovascular risk. Conclusions: This survey highlights the need to improve the physicians’ misperceived cardiovascular risk and therapeutic inertia in patients with diabetes to successfully implement guidelines recommendations into everyday clinical practice

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

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening