Displasia do desenvolvimento do quadril - uma revisão abrangente sobre a epidemiologia, anatomia, etiologia, aspectos genéticos, diagnóstico, tratamento, prognóstico e prevenção

A displasia do desenvolvimento do quadril (DDQ) é uma condição ortopédica comum em lactentes e crianças, caracterizada por anormalidades na articulação do quadril. Sua incidência varia em diferentes regiões geográficas, mas estima-se que afete cerca de 1 a 3 em cada 100 recém-nascidos, sendo mais frequente em meninas e bebês com histórico familiar de DDQ. Essa articulação complexa é composta pelo osso do quadril (osso ilíaco), a cabeça femoral e o acetábulo. A DDQ ocorre devido a desarmonias na formação dessas estruturas, o que acarreta má posição e estabilidade inadequada do quadril. Quanto à etiologia, múltiplos fatores genéticos, ambientais e mecânicos contribuem para o desenvolvimento da DDQ, incluindo posição intrauterina, primeira gravidez e posição do feto. O diagnóstico precoce é crucial para o tratamento eficaz da condição, sendo o exame físico e métodos de imagem, como ultrassonografia do quadril em recém-nascidos e radiografia em bebês mais velhos, fundamentais para determinar a gravidade da displasia. O tratamento varia conforme a gravidade e a idade do paciente, com opções que vão desde dispositivos ortopédicos, como o coxal de Pavlik, em casos leves a moderados, até a cirurgia corretiva para casos mais graves ou tardios. O prognóstico geralmente é positivo quando o diagnóstico é precoce e o tratamento adequado é instituído, evitando complicações a longo prazo, como osteoartrite e dor crônica. Por fim, a prevenção é essencial por meio do rastreamento adequado em exames de rotina, exames clínicos cuidadosos e conscientização dos pais sobre os fatores de risco, a fim de assegurar o desenvolvimento adequado do quadril e o tratamento bem-sucedido da DDQ

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Neotropical ornithology: Reckoning with historical assumptions, removing systemic barriers, and reimagining the future

A major barrier to advancing ornithology is the systemic exclusion of professionals from the Global South. A recent special feature, Advances in Neotropical Ornithology, and a shortfalls analysis therein, unintentionally followed a long-standing pattern of highlighting individuals, knowledge, and views from the Global North, while largely omitting the perspectives of people based within the Neotropics. Here, we review current strengths and opportunities in the practice of Neotropical ornithology. Further, we discuss problems with assessing the state of Neotropical ornithology through a northern lens, including discovery narratives, incomplete (and biased) understanding of history and advances, and the promotion of agendas that, while currently popular in the north, may not fit the needs and realities of Neotropical research. We argue that future advances in Neotropical ornithology will critically depend on identifying and addressing the systemic barriers that hold back ornithologists who live and work in the Neotropics: unreliable and limited funding, exclusion from international research leadership, restricted dissemination of knowledge (e.g., through language hegemony and citation bias), and logistical barriers. Moving forward, we must examine and acknowledge the colonial roots of our discipline, and explicitly promote anti-colonial agendas for research, training, and conservation. We invite our colleagues within and beyond the Neotropics to join us in creating new models of governance that establish research priorities with vigorous participation of ornithologists and communities within the Neotropical region. To include a diversity of perspectives, we must systemically address discrimination and bias rooted in the socioeconomic class system, anti-Blackness, anti-Brownness, anti-Indigeneity, misogyny, homophobia, tokenism, and ableism. Instead of seeking individual excellence and rewarding top-down leadership, institutions in the North and South can promote collective leadership. In adopting these approaches, we, ornithologists, will join a community of researchers across academia building new paradigms that can reconcile our relationships and transform science. Spanish and Portuguese translations are available in the Supplementary Material.• Research conducted by ornithologists living and working in Latin America and the Caribbean has been historically and systemically excluded from global scientific paradigms, ultimately holding back ornithology as a discipline.• To avoid replicating systems of exclusion in ornithology, authors, editors, reviewers, journals, scientific societies, and research institutions need to interrupt long-held assumptions, improve research practices, and change policies around funding and publication.• To advance Neotropical ornithology and conserve birds across the Americas, institutions should invest directly in basic field biology research, reward collective leadership, and strengthen funding and professional development opportunities for people affected by current research policies.Peer reviewe

Are rare species useful species? Obstacles to the conservation of tree diversity in the dry forest zone agro-ecosystems of Mesoamerica

Aim To test the potential to conserve rare dry forest tree and shrub species circa situm.Location Oaxaca, Mexico and Southern Honduras.Methods Local uses (timber, posts and firewood) of species were determined principally through semistructured interviews with 20 rural householders in each of four communities in Honduras and four in Oaxaca. Tree and shrub diversity inventories were carried out in a total of 227 forest patches and parcels of farmland in those eight communities. Species’ conservation priorities were determined using the star system of Hawthorne (1996) and IUCN listings.Results Despite a large number of useful species, remarkably few were also conservation priorities. Useful species were found to be substitutable as is illustrated by Bombacopsis quinata, Cordia alliodora, Guaiacum sanctum and G. coulteri.Conclusions In these areas, circa situm conservation is inhibited by the lack of species that are both rare and useful. Usefulness must be interpreted as a function of substitutability. Natural regeneration provides an abundance of diversity, farmers are unlikely to invest in the management of a species when suitable substitutes are freely available. The key to conserving rare species may be in maintaining or enhancing the value of the landscape elements in which they are found

BioTIME:a database of biodiversity time series for the Anthropocene

Abstract Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km² (158 cm²) to 100 km² (1,000,000,000,000 cm²). Time period and grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format: .csv and .SQL

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

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 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

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

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: 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. Funding: National Institute for Health and Care Research