Advantages, barriers, and cues to advance care planning engagement in elderly patients with cancer and family members in Southern Thailand: a qualitative study.

BACKGROUND: Older cancer patients are vulnerable to poorer health outcomes during cancer treatment. Although the Thai elderly had their own preferences towards future medical care and advance care planning (ACP) could help cancer patients make informed decisions, Thai physicians report a low ACP engagement rate. Thus, this study aimed to explore the perceptions of older cancer patients and their families towards ACP engagement. METHOD: We used a qualitative approach to explore the perceptions of non-haematological cancer patients aged ≥ 60 years old and their primary caregivers. The study was conducted at the Oncology Radiotherapy Referral Center, Songklagarind Hospital in Southern Thailand. Semi-structured in-depth interviews were conducted with the patients and their caregivers. Thematic analysis was used to identify and analyze recurring patterns and themes of perceptions regarding ACP engagement within the interview transcripts. RESULTS: Among the 138 families approached, 32 interviews were conducted. Three themes were found: (1) Advantageous opportunity: the patients believed ACP would help them realize their life values, and ensure that their preference would be respected; (2) contemplation and barriers to ACP: ACP is unfamiliar and unnecessary, might have low utility, worry patients and family members, take away optimism, would not be a proper activity for the patient at the current health situation; and (3) Cues for ACP initiation: perceived conformity with one's religion, awareness of the current cancer state, having multiple comorbidity or experience suffering related with medical care, wishing not to burden family, having close family members, and trust in physicians. CONCLUSION: ACP engagement could be hindered or promoted by perceptions of older patients and/ or their family members, as well as the communication skills of the care providers. Care professionals who aim to initiate ACP should minimize the potential barriers, make the ACP benefits salient, and watch for cues indicating a propitious time to start the ACP conversation.

Cancer research provides a model for advancing clinical trials in dementia in the era of disease-modifying Alzheimer's-type dementia therapies.

Dementia and cancer are multifactorial, widely-feared, age-associated clinical syndromes that are increasing in prevalence. There have been major breakthroughs in clinical cancer research leading to some effective treatments, whereas the field of dementia has achieved comparatively limited success in clinical research. The lessons of cancer research may help those in the dementia research field in confronting some of the dilemmas faced when the clinical care regimen is not entirely safe or efficacious. Cancer clinical trials have assumed that untreated individuals with cancer are at high risk for morbidity and mortality after primary diagnoses. Thus, patients deserve a choice of clinical interventions, either standard of care or experimental, even if the benefits are not certain and the therapy's side effects are potentially severe. The prognosis for many individuals at risk for dementia carries a correspondingly high level of risk for both mortality and severe morbidity, particularly if one focuses on "health-span" rather than lifespan. Caregivers and patients can be strongly impacted by dementia and the many troubling associated symptoms that often go well beyond amnesia. Polls, surveys, and a literature on "dementia worry" strongly underscore that the public fears dementia. While there are institutional and industry hurdles that complicate enrollment in randomized trials, the gravity of the future morbidity and mortality inherent in a dementia diagnosis may require reconsideration of the current protective stance that limits the freedom of at-risk individuals (either symptomatic or asymptomatic) to participate and potentially benefit from ongoing clinical research. There is also evidence from both cancer and dementia research that individuals enrolled in the placebo arms of clinical trials have unexpectedly good outcomes, indicating that participation in clinical trial can have medical benefits to enrollees. To highlight aspects of cancer clinical research that may inform present and future dementia clinical research, this review highlights three main themes: the risk of side effects should be weighed against the often dire consequences of non-treatment; the desirability of long-term incremental (rather than "magic bullet") clinical advances; and, the eventual importance of combination therapies, reflecting that the dementia clinical syndrome has many underlying biological pathways.

Intelligent medicine in focus: the 5 stages of evolution in robot-assisted surgery for prostate cancer in the past 20 years and future implications.

Robot-assisted surgery has evolved into a crucial treatment for prostate cancer (PCa). However, from its appearance to today, brain-computer interface, virtual reality, and metaverse have revolutionized the field of robot-assisted surgery for PCa, presenting both opportunities and challenges. Especially in the context of contemporary big data and precision medicine, facing the heterogeneity of PCa and the complexity of clinical problems, it still needs to be continuously upgraded and improved. Keeping this in mind, this article summarized the 5 stages of the historical development of robot-assisted surgery for PCa, encompassing the stages of emergence, promotion, development, maturity, and intelligence. Initially, safety concerns were paramount, but subsequent research and engineering advancements have focused on enhancing device efficacy, surgical technology, and achieving precise multi modal treatment. The dominance of da Vinci robot-assisted surgical system has seen this evolution intimately tied to its successive versions. In the future, robot-assisted surgery for PCa will move towards intelligence, promising improved patient outcomes and personalized therapy, alongside formidable challenges. To guide future development, we propose 10 significant prospects spanning clinical, research, engineering, materials, social, and economic domains, envisioning a future era of artificial intelligence in the surgical treatment of PCa.

The use of individual tracking programs in public health: a bioethics dilemma.

OBJECTIVE: to understand the bioethical perspectives on mobile tracking device use. METHODS: theoretical study based on action research, carried out with eight graduate students from a public university. A focus group was used, with a thematic content analysis methodology with a codebook structure, approved by the Research Ethics Committee. RESULTS: from the analysis, there was a concern about using devices after the pandemic ended. Using or not the device, rights inherent to humans, legislation and effectiveness of methods deepen interpretations, moving participants from a personalistic conception of the topic to a vision focused on professional implications about the methods. FINAL CONSIDERATIONS: the debate on the impact of using technological devices on health, especially those that imply restriction of rights that refer to individuals' private life, involves a discussion of a professional nature, in addition to requirement for clear rules on the topic.

Increased homicide played a key role in driving Black-White disparities in life expectancy among men during the COVID-19 pandemic.

Disparities in life expectancy between Black and White Americans increased substantially during the COVID-19 pandemic. During the same period, the US experienced the largest increase in homicide on record. Yet, little research has examined the contribution of homicide to Black-White disparities in longevity in recent years. Using mortality data and population estimates, we conduct a comprehensive decomposition of the drivers of Black-White inequality in life expectancy and lifespan variability between 2019 and 2021 among men. We find that homicide is one of the principal reasons why lifespans have become shorter for Black men than White men in recent years. In 2020 and 2021, homicide was the leading contributor to inequality in both life expectancy and lifespan variability between Black and White men, accounting for far more of the racial gap in longevity and variability than deaths from COVID-19. Addressing homicides should be at the forefront of any public health discussion aimed at promoting racial health equity.

[Excess deaths in Argentina during the COVID-19 pandemic: analysis of mortality between 2020 and 2022]. / Exceso de muertes en Argentina durante la pandemia por COVID-19: análisis de la mortalidad entre 2020 y 2022.

Reports of excess mortality during the COVID-19 pandemic in Argentina have been partial and fragmented so far. This study aimed to quantify excess deaths and explore their demographic, temporal, and geographic distribution during the period 2020-2022. Using data from 1 192 963 death records from vital statistics and population projections, expected mortality was estimated using regression models. Excess death was calculated as the difference between observed and expected mortality. An excess of 160 676 deaths (95% CI 146 861 to 174 491) was estimated, representing a rate of 116.9 (95% CI 115.5 to 118.3) additional deaths per 100 000 personyears. Significant heterogeneity was found among the different argentine provinces. The results indicate an uneven impact of the pandemic, with higher excess mortality rates in some regions and more vulnerable age groups. These patterns suggest the need for differentiated strategies of healthcare response and support to the most vulnerable populations in scenarios of new epidemics.

Los reportes del exceso de mortalidad durante la pandemia por COVID-19 en Argentina han sido parciales y fragmentados hasta el momento. Este estudio se propuso cuantificar el exceso de muertes y explorar su distribución demográfica, temporal y geográfica durante el periodo 2020-2022. Utilizando datos de 1 192 963 registros de muertes de estadísticas vitales y proyecciones poblacionales, se estimó la mortalidad esperada mediante modelos de regresión. El exceso de muertes se calculó como la diferencia entre la mortalidad observada y la esperada. Se estimó un exceso de 160 676 muertes (IC 95% 146 861 a 174 491), representando una tasa de 116.9 muertes (IC 95% 115.5 a 118.3) adicionales por cada 100 000 personas-año. Se verificó una significativa heterogeneidad entre las distintas provincias argentinas. Los resultados indican un impacto desigual de la pandemia, con mayores tasas de exceso de mortalidad en algunas regiones y grupos de edad más vulnerables. Estos patrones sugieren la necesidad de estrategias diferenciadas de respuesta sanitaria y apoyo a las poblaciones más vulnerables en escenarios de nuevas epidemias.

An explanation of the stagnant under-5 mortality rate in Bangladesh using multilevel, multivariable analysis of three Demographic and Health Surveys.

Despite remarkable success in the Millennium Development Goal era, Bangladesh experienced a sluggish reduction in the under-5 mortality rate (U5MR) between 2014 and 2017-18. Our study aimed to explain this stagnancy by examining the variation in the key predictor-specific mortality risks over time, using the Bangladesh Demographic and Health Survey 2011, 2014 and 2017-18 data. We applied multilevel mixed effects logistic regression to examine the extent to which the under-5 mortality (U5M) risks were associated with the key sociodemographic and health service-specific predictors. We found that the rise in mortality risks attributable to maternal age 18 years or below, low maternal education, mother's overweight or obesity and the absence of a handwashing station within the household were the key contributors to the stagnant U5MR between 2014 and 2017-18. Poverty and low education aggravated the mortality risks. Besides, antenatal care (ANC) and postnatal care (PNC) did not impact U5M risks as significantly as expected. Compulsory use of ANC and PNC cards and strict monitoring of their use may improve the quality of these health services. Leveraging committees like the Upazila Hospital Management Committee can bring harmony to implementing policies and programmes in the sectors related to U5M.

Exploring the determinants of under-five mortality and morbidity from infectious diseases in Cambodia-a traditional and machine learning approach.

Cambodia has made progress in reducing the under-five mortality rate and burden of infectious diseases among children over the last decades. However the determinants of child mortality and morbidity in Cambodia is not well understood, and no recent analysis has been conducted to investigate possible determinants. We applied a multivariable logistical regression model and a conditional random forest to explore possible determinants of under-five mortality and under-five child morbidity from infectious diseases using the most recent Demographic Health Survey in 2021-2022. Our findings show that the majority (58%) of under-five deaths occurred during the neonatal period. Contraceptive use of the mother led to lower odds of under-five mortality (0.51 [95% CI 0.32-0.80], p-value 0.003), while being born fourth or later was associated with increased odds (3.25 [95% CI 1.09-9.66], p-value 0.034). Improved household water source and higher household wealth quintile was associated with lower odds of infectious disease while living in the Great Lake or Coastal region led to increased odds respectively. The odds ratios were consistent with the results from the conditional random forest. The study showcases how closely related child mortality and morbidity due to infectious disease are to broader social development in Cambodia and the importance of accelerating progress in many sectors to end preventable child mortality and morbidity.

Land use land cover change in the African Great Lakes Region: a spatial-temporal analysis and future predictions.

The African Great Lakes Region has experienced substantial land use land cover change (LULCC) over the last decades, driven by a complex interplay of various factors. However, a comprehensive analysis exploring the relationships between LULCC, and its explanatory variables remains unexplored. This study focused on the Lake Kivu catchment in Rwanda, analysing LULCC from 1990 to 2020, identifying major variables, and predicting future LULC scenarios under different development trajectories. Image classification was conducted in Google Earth Engine using random forest classifier, by incorporating seasonal composites Landsat images, spectral indices, and topographic features, to enhance discrimination and capture seasonal variations. The results demonstrated an overall accuracy exceeding 83%. Historical analysis revealed significant changes, including forest loss (26.6 to 18.7%) and agricultural land expansion (27.7 to 43%) in the 1990-2000 decade, attributed to political conflicts and population movements. Forest recovery (24.8% by 2020) was observed in subsequent decades, driven by Rwanda's sustainable development initiatives. A Multi-Layer Perceptron neural network from Land Change Modeler predicted distinct 2030 and 2050 LULC scenarios based on natural, socio-economic variables, and historical transitions. Analysis of explanatory variables highlighted the significant role of proximity to urban centers, population density, and terrain in LULCC. Predictions indicate distinct trajectories influenced by demographic and socio-economic trends. The study recommends adopting the Green Growth Economy scenario aligned with ongoing conservation measures. The findings contribute to identifying opportunities for land restoration and conservation efforts, promoting the preservation of Lake Kivu catchment's ecological integrity, in alignment with national and global goals.

How artificial intelligence is transforming nephrology.

Current research in nephrology is increasingly focused on elucidating the complexity inherent in tightly interwoven molecular systems and their correlation with pathology and related therapeutics, including dialysis and renal transplantation. Rapid advances in the omics sciences, medical device sensorization, and networked digital medical devices have made such research increasingly data centered. Data-centric science requires the support of computationally powerful and sophisticated tools able to handle the overflow of novel biomarkers and therapeutic targets. This is a context in which artificial intelligence (AI) and, more specifically, machine learning (ML) can provide a clear analytical advantage, given the rapid advances in their ability to harness multimodal data, from genomic information to signal, image and even heterogeneous electronic health records (EHR). However, paradoxically, only a small fraction of ML-based medical decision support systems undergo validation and demonstrate clinical usefulness. To effectively translate all this new knowledge into clinical practice, the development of clinically compliant support systems based on interpretable and explainable ML-based methods and clear analytical strategies for personalized medicine are imperative. Intelligent nephrology, that is, the design and development of AI-based strategies for a data-centric approach to nephrology, is just taking its first steps and is by no means yet close to its coming of age. These first steps are not even homogeneously taken, as a digital divide in access to technology has become evident between developed and developing countries, also affecting underrepresented minorities. With all this in mind, this editorial aim to provide a selective overview of the current use of AI technologies in nephrology and heralds the "Artificial Intelligence in Nephrology" special issue launched by BMC Nephrology.

Global burden of thyroid cancer from 1990 to 2021: a systematic analysis from the Global Burden of Disease Study 2021.

Thyroid cancer (TC) is a significant global healthcare burden. However, the lack of comprehensive data has impeded our understanding of its global impact. We aimed to examine the burden of TC and its trends at the global, regional, and national levels using data stratified by sociodemographic index (SDI), sex, and age. Data on TC, including incidence, mortality, and disability-adjusted life-years (DALYs) from 1990 to 2021, were obtained from the Global Burden of Disease Study 2021. Estimated annual percentage changes (EAPCs) were calculated to assess the incidence rate, mortality, and DALYs trends. The incidence, mortality, and DALYs of TC in 2021 were 249,538 (95% uncertainty interval: 223,290-274,638), 44,799 (39,925-48,541), and 646,741 (599,119-717,357), respectively. The age-standardized incidence rate (ASIR) in 2021 was 2.914 (2.607-3.213), with an EAPC of 1.25 (1.14-1.37) compared to 1990. In 2021, the age-standardized death rate (ASDR) was 0.53 (0.47-0.575) and age-standardized DALYs rate was 14.571 (12.783-16.115). Compared with 1990, the EAPCs of ASDR and age-standardized DALYs rate showed decreasing trends, at - 0.24 (- 0.27 to - 0.21) and - 0.14 (- 0.17 to - 0.11), respectively. Low SDI regions showed the highest ASDR and age-standardized DALYs rate, at 0.642 (0.516-0.799) and 17.976 (14.18-23.06), respectively. Low-middle SDI regions had the highest EAPCs for ASDR and age-standardized DALYs rate, at 0.74 (0.71-0.78) and 0.67 (0.63-0.7), respectively. Females exhibited decreasing trend in ASDR and age-standardized DALYs rate, with EAPCs of - 0.58 (- 0.61 to - 0.55) and - 0.45 (- 0.47 to - 0.42), respectively. In contrast, males showed an increasing trend in ASDR and age-standardized DALYs rate, with EAPCs of 0.41 (0.35-0.46) for both. In high-income regions, most countries with decreased annual changes in deaths experience increasing age-related deaths. Over the past few decades, a notable increase in TC incidence and decreased mortality has been observed globally. Regions characterized by lower SDI, male sex, and an aging population exhibited no improvement in TC mortality. Effective resource allocation, meticulous control of risk factors, and tailored interventions are crucial for addressing these issues.

Hybrid nanostructures for neurodegenerative disease theranostics: the art in the combination of biomembrane and non-biomembrane nanostructures.

The diagnosis of neurodegenerative diseases (NDDs) remains challenging, and existing therapeutic approaches demonstrate little efficacy. NDD drug delivery can be achieved through the utilization of nanostructures, hence enabling multimodal NDD theranostics. Nevertheless, both biomembrane and non-biomembrane nanostructures possess intrinsic shortcomings that must be addressed by hybridization to create novel nanostructures with versatile applications in NDD theranostics. Hybrid nanostructures display improved biocompatibility, inherent targeting capabilities, intelligent responsiveness, and controlled drug release. This paper provides a concise overview of the latest developments in hybrid nanostructures for NDD theranostics and emphasizes various engineering methodologies for the integration of diverse nanostructures, including liposomes, exosomes, cell membranes, and non-biomembrane nanostructures such as polymers, metals, and hydrogels. The use of a combination technique can significantly augment the precision, intelligence, and efficacy of hybrid nanostructures, therefore functioning as a more robust theranostic approach for NDDs. This paper also addresses the issues that arise in the therapeutic translation of hybrid nanostructures and explores potential future prospects in this field.

Time series analysis: trend in late maternal mortality in Brazil, 2010-2019.

To analyze the temporal trend of the late maternal mortality ratio (LMMR) in Brazil and its geographic regions in the period from 2010 to 2019, an ecological time series study was conducted. Data related to late maternal mortality from information systems of the Brazilian Ministry of Health were used. Statistical analysis used Prais-Winsten autoregressive models. A total of 1,470 late maternal deaths were reported in Brazil, resulting in an LMMR of 5 deaths per 100,000 live births. The late maternal mortality records revealed regional disparities, with the lowest index in the North (3.5/100,000 live births) and the highest in the South (8.3/100,000 live births). The LMMR showed an increasing trend in the country, with a general increase in the LMMR in the period and a mean annual percentage variation of 9.79% (95%CI: 4.32; 15.54). The Central-West region led this increase, with a mean annual percentage change of 26.06% (95%CI: 16.36; 36.56), followed by the North and Northeast regions, with 23.5% (95%CI: 13.93; 33.88). About 83% of the reported late maternal deaths were investigated, and 65.6% were corrected by the Maternal Mortality Committees. These findings highlight the relevance of late maternal mortality as an important indicator for maternal health, which is often invisible. The increase in the LMMR result from the improvement in the quality of the registration of these deaths in recent years in Brazil, and especially from the work of investigating deaths. The fragility of reporting with regional disparities points to the need for a more comprehensive approach that promotes equity and prevention of avoidable late maternal mortality.