Likelihood Of Survival Research Articles

Surviving the pandemic: COVID-19 and restaurant closures in Suzhou

ABSTRACT The outbreak of COVID-19 disrupts the economy and presents challenges to small and medium enterprises in various sectors. Focused on the restaurant industry in Suzhou, China, this study draws upon secondary data from Meituan Dianping and Baidu Map API and considers how variables related to restaurants themselves and variables pertaining to restaurants’ built environment conditions contribute to their survival during the pandemic with the use of regression analysis. For restaurants, it is important to have certain core competencies, such as price or quality advantage, if they were to survive external shocks. In addition, high population density of a restaurant’s surrounding area, one of the most crucial factors in determining business success under normal circumstances, significantly reduces its survival likelihood during the pandemic. We conclude by outlining opportunities for future research. Highlights This study examines what determines restaurant survival in the pandemic. The survival is influenced by both restaurant and built environment factors. Restaurants need to have specific core competencies to survive market shocks. Density and accessibility have adverse impacts on restaurant survival. The analysis provides policy suggestions for similar circumstances in the future.

Epidemiology of major trauma in older adults within Scotland: A national perspective from the Scottish Trauma Audit Group (STAG)

BackgroundMajor trauma in older adults (MTOA) poses distinctive health and social care challenges, further underlined by the unique socioeconomic and geographical environment of Scotland. This study provides epidemiological trends of MTOA, to provide insight into areas where further evaluation and research are required. Materials and MethodsPseudonymised aggregated demographic, injury and outcome data from 2011 to 2020 were obtained from the Scottish Trauma Audit Group (STAG) Database, covering 28 hospitals across Scotland. Only individuals age ≥ 70 with an Injury Severity Score (ISS) > 15 were included. ResultsThere was an average of 216 annual cases of MTOA, with a 259 % rise in incidence from 2011 to 2020. This was predominantly driven by a rise in low velocity trauma (fall <2 m height; 287 % increase).The proportion of all major trauma attributable to those aged ≥70 rose from 18.5 % in 2011 to 34.6 % in 2020. Death censored median (IQR) acute hospital length of stay was 18 days (9–30).Overall, 30-day survival was 65.3 %, with no improvement seen between 2011 and 2020 (p = 0.50). Independent predictors of improved 30-day survival included Ages 70–79 & 80–89 [compared to reference ≥ 90] (OR 3.12; 95 %CI 2.24,4.31; p < 0.001 and OR 1.66; 95 %CI 1.21,2.29; p = 0.002 respectively), and Extremity injury (OR 1.89; 95 %CI 1.48,2.41; p < 0.001). Head injury (OR 0.72; 95 %CI 0.54,0.96; p = 0.027) and increasing ISS score (OR 0.88, 95 %CI 0.86,0.89; p < 0.001) were associated with lower likelihood of 30-day survival. A further model also including the admission ward (from eSTAG data November 2017 onwards) demonstrated an association with reduced 30-day survival with admission to General Surgery (OR 0.42; 95 %CI 0.19,0.93; p = 0.033), Intensive Care (OR 0.25; 95 %CI 0.10,0.60; p = 0.002) and Medical Specialities (OR 0.33; 95 %CI 0.15,0.73; p = 0.007) compared to the reference (Major Trauma).Exponential Smoothing predictions revealed a further potential 184 % rise in incidence of MTOA from 2021 to 2030 (3657 per 100,000 population at risk to 10,392 per 100,000 population at risk). ConclusionMTOA is likely to be a rising health care burden, requiring larger quantities of health and social care resource. Urgent preventative strategies are required to reduce low velocity trauma (standing height falls), as well as the high mortality and morbidity of MTOA.

Investigation of Stem Cell-Like Characteristics and Immune Cell Interaction of Tumor Cells Survived from Continuous Shear Flow Environment.

When tumor cells are released from a primary tumor into the bloodstream or lymphatic circulation system, they are exposed to a continuous shear flow environment. This environment exerts physical stresses on the tumor cells, which can activate apoptotic pathways. However, certain tumor cells have the ability to adapt to these mechanical stresses, enhancing their likelihood of survival and promoting metastasis. In this study, these tumor cells survived from shear flow environment are examined and revealed to closely link to stem cell-like characteristics. Higher gene expression levels of self-renewal and differentiation markers and enhanced abilities of migration, spheroid formation, and colony formation are shown. Moreover, the interaction between immune cells and the surviving cells is investigated. The results show that the surviving cells possess immune escape capabilities, implying their ability to evade immune surveillance. Additionally, these surviving cells display characteristics reminiscent of stem cells. This study holds great importance in advancing the understanding of tumor biology. By comprehending the behavior and properties of these surviving cells, new therapeutic strategies can be developed to specifically target circulating tumor cells (CTCs) and enhance cancer treatment outcomes.

Development of a prognostic signature for immune-associated genes in bladder cancer and exploring potential drug findings.

Bladder cancer, predominantly affecting men, is a prevalent malignancy of the urinary system. Although platinum-based chemotherapy has demonstrated certain enhancements in overall survival when compared to surgery alone, the efficacy of treatments is impeded by the unfavorable side effects of conventional chemotherapy medications. Nonetheless, immunotherapy exhibits potential in the treatment of bladder cancer. To create an immune-associated prognostic signature for bladder cancer, bioinformatics analyses were performed utilizing The Cancer Genome Atlas (TCGA) database in this study. By identifying differential gene expressions between the high-risk and low-risk groups, a potential therapeutic drug was predicted using the Connectivity Map database. Subsequently, the impact of this drug on the growth of T24 cells was validated through MTT assay and 3D cell culture techniques. The signature included 1 immune-associated LncRNA (NR2F1-AS1) and 16 immune-associated mRNAs (DEFB133, RBP7, PDGFRA, CGB3, PDGFD, SCG2, ADCYAP1R1, OPRL1, PGR, PSMD1, TANK, PRDX1, ADIPOR2, S100A8, AHNAK, EGFR). Based on the assessment of risk scores, the patients were classified into cohorts of low-risk and high-risk individuals. The cohort with low risk demonstrated a considerably higher likelihood of survival in comparison to the group with high risk. Furthermore, variations in immune infiltration were noted among the two categories. Cephaeline, a possible medication, was discovered by analyzing variations in gene expression. It exhibited promise in suppressing the viability and growth of T24 bladder cancer cells. The novel predictive pattern allows for efficient categorization of patients with bladder cancer, enabling focused and rigorous treatment for those expected to have a worse prognosis. The discovery of a possible curative medication establishes a basis for forthcoming immunotherapy trials in bladder cancer.

An Evolutionary Model for the Ancient Origins of Polycystic Ovary Syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrinopathy of reproductive-aged women, characterized by hyperandrogenism, oligo-anovulation and insulin resistance and closely linked with preferential abdominal fat accumulation. As an ancestral primate trait, PCOS was likely further selected in humans when scarcity of food in hunter-gatherers of the late Pleistocene additionally programmed for enhanced fat storage to meet the metabolic demands of reproduction in later life. As an evolutionary model for PCOS, healthy normal-weight women with hyperandrogenic PCOS have subcutaneous (SC) abdominal adipose stem cells that favor fat storage through exaggerated lipid accumulation during development to adipocytes in vitro. In turn, fat storage is counterbalanced by reduced insulin sensitivity and preferential accumulation of highly lipolytic intra-abdominal fat in vivo. This metabolic adaptation in PCOS balances energy storage with glucose availability and fatty acid oxidation for optimal energy use during reproduction; its accompanying oligo-anovulation allowed PCOS women from antiquity sufficient time and strength for childrearing of fewer offspring with a greater likelihood of childhood survival. Heritable PCOS characteristics are affected by today's contemporary environment through epigenetic events that predispose women to lipotoxicity, with excess weight gain and pregnancy complications, calling for an emphasis on preventive healthcare to optimize the long-term, endocrine-metabolic health of PCOS women in today's obesogenic environment.

Functional architecture of dopamine neurons driving fear extinction learning

The ability to extinguish fear responses to stimuli that no longer predict danger is critical for adaptive behavior and increases the likelihood of survival. During fear extinction, dopamine (DA) neurons signal the absence of the expected aversive outcome, and this extinction prediction error (EPE) signal is crucial for initiating and driving extinction learning. However, the neural circuits underlying the EPE signal have remained elusive. Here, we investigate the input-output circuitry of EPE-encoding DA neurons in male mice. By employing projection-specific fiber photometry and optogenetics, we demonstrate that these neurons project to a restricted subregion of the nucleus accumbens. Comprehensive anatomical analyses, as well as projection-specific chemogenetic manipulations combined with recordings of DA biosensors, further uncover the dorsal raphe as one key input structure critical for generating the EPE signal. Together, our results reveal for the first time the functional architecture of EPE-encoding DA neurons crucial for driving fear extinction learning.

Outcomes of Transcatheter Aortic Valve Replacement in Asymptomatic or Minimally Symptomatic Aortic Stenosis

BackgroundLittle is known about the outcomes of transcatheter aortic valve replacement (TAVR) in minimally symptomatic patients. ObjectivesThe authors aimed to evaluate the outcomes of patients with minimally symptomatic severe aortic stenosis treated with TAVR in the STS/ACC TVT registry. MethodsMinimally symptomatic status was defined as a baseline Kansas City Cardiomyopathy Questionnaire overall summary score (KCCQ-OS) ≥75. Clinical and health status outcomes of TAVR in patients with severe aortic stenosis and normal left ventricular ejection fraction were compared between minimally symptomatic patients and those with moderate or severe symptoms. ResultsAmong 231,285 patients who underwent TAVR between 2015 and 2021 (median age 80.0 years [IQR: 74.0-86.0 years], 47.5% female), 20.0% were minimally symptomatic before TAVR. Survival at 1 year was higher in minimally symptomatic patients vs those with moderate or severe symptoms (adjusted HR for death: 0.70 [95% CI: 0.66-0.75]). Mean KCCQ-OS increased by 2.7 points (95% CI: 2.6-2.9 points) at 30 days and 3.8 points (95% CI: 3.6-4.0 points) at 1 year in minimally symptomatic patients compared with increases of 32.2 points (95% CI: 32.0-32.3 points) at 30 days and 34.9 points (95% CI: 34.7-35.0 points) at 1 year in more symptomatic patients. Minimally symptomatic patients had higher odds of being alive and well at 1 year (OR: 1.19 [95% CI: 1.16-1.23]). ConclusionsAlthough minimally symptomatic patients treated with TAVR experience only small improvements in health status, their overall outcomes are favorable with a higher likelihood of survival with good health status at 1 year compared with more symptomatic patients.

Outcomes and Complications Associated With Caudal Thoracic and Abdominal Air Sac Cannulation in 68 Birds.

Air sac cannulation is used both as an emergency procedure in avian patients with severe upper respiratory compromise, as well as a means of routine ventilation for surgery of the head and neck. The objective of this retrospective study was to describe and quantify the complications associated with air sac cannulation in birds. Medical records were retrieved for all patients that underwent caudal thoracic or abdominal air sac cannulation at a single center between August 2004 and October 2020. Patient signalment, indication for air sac cannulation, location of air sac cannula (ASC) placement, occurrence and category of complications encountered, and survival data were recorded. Eighty-four ASCs were placed in 68 birds across 6 orders; 95.2% (80/84) of cases survived general anesthesia for initial ASC placement. The side and position of ASC placement were known in 33.3% (28/84) and 21.4% (18/84) of cases, respectively. Survival to ASC removal was known in 91.3% (73/80) of cases; 43 (58.9%) of these 73 cases survived to ASC removal. Complications were observed in 32.5% (26/80) of cases, and 11.5% (3/26) of cases died as a direct result of the complication. The most common reported ASC complication was loss of patency in 23.8% (19/80) of cases. Increased likelihoods for complications were seen in cases where exercise intolerance (P = 0.04) or abnormal respiratory sounds (P = 0.04) were reported at presentation. Increased likelihoods for survival to ASC removal were seen with intercostal placements (P = 0.049) and peri-interventional antibiotic therapy (P = 0.005). Decreased likelihood for survival to ASC removal was seen in cases where voice change was reported at presentation (P = 0.02). This study demonstrates a moderate risk of ASC complication, with a guarded overall prognosis for survival to ASC removal.

Primary care practitioners' priorities for improving the timeliness of cancer diagnosis in primary care: a European cluster-based analysis

BackgroundDiagnosing cancer at an early stage increases the likelihood of survival, and more advanced cancers are more difficult to treat successfully.Primary care practitioners (PCPs) play a key role in timely diagnosis of cancer. PCPs’ knowledge of their own patient populations and health systems could help improve the planning of more effective approaches to earlier cancer recognition and referral.How PCPs act when faced with patients who may have cancer is likely to depend on how their health systems are organised, and this may be one explanation for the wide variation on cancer survival rates across Europe.ObjectivesTo identify and characterise clusters of countries whose PCPs perceive the same factors as being important in improving the timeliness of cancer diagnosis.MethodsA cluster analysis of qualitative data from an online survey was carried out. PCPs answered an open-ended survey question on how the speed of diagnosis of cancer in primary care could be improved. Following coding and thematic analysis, we identified the number of times per country that an item in a theme was mentioned. k-means clustering identified clusters of countries whose PCPs perceived the same themes as most important. Post-hoc testing explored differences between these clusters.SettingTwenty-five primary care centres in 20 European countries. Each centre was asked to recruit at least 50 participants.ParticipantsPrimary care practitioners of each country.ResultsIn all, 1,351 PCPs gave free-text answers. We identified eighteen themes organising the content of the responses. Based on the frequency of the themes, k-means clustering identified three groups of countries. There were significant differences between clusters regarding the importance of: access to tests (p = 0.010); access to specialists (p = 0.014), screening (p < 0.001); and finances, quotas & limits (p < 0.001).ConclusionsOur study identified three distinct clusters of European countries within which PCPs had similar views on the factors that would improve the timeliness of cancer diagnosis. Further work is needed to understand what it is about the clusters that have produced these patterns, allowing healthcare systems to share best practice and to reduce disparities.

Awareness, knowledge and attitude towards CPR, BLS training among general population in Chennai – A cross sectional survey

Out-of-hospital cardiac arrest is a leading cause of death globally. The likelihood of survival is doubled when basic life support procedures are performed immediately. As a result, the purpose of this study was to assess public awareness, understanding, and attitude towards basic life support and CPR in Chennai population.The study was done among general population in Chennai, India, utilising a printed questionnaire with 15 questions each. A pilot study was conducted among 40 individuals in Chennai city. Power analysis was performed to calculate the sample size by using Open Epi, Version 3, open – source calculator – SSPropor The data was analysed using descriptive statistics. 1200 individuals participated in the survey. Of the final population (n =1200) majority of people are unaware about the significance of basic life support and CPR. From this survey we could able to find the positive attitude of public towards learning the CPR. The most important concern about performing CPR was making a mistake and legal issues. Noteworthy is the positive attitude towards learning CPR &amp; BLS courses among common public, which provides a solid foundation for improving CPR training implementation. However, the majority of youngsters reported a lack of training opportunities, emphasising the need for more aggressive implementation.

Temporal trends in out-of-hospital cardiac arrest with an initial non-shockable rhythm in Singapore

AimOut-of-hospital cardiac arrest (OHCA) with an initial non-shockable rhythm is the predominant form of OHCA in adults. We evaluated its 10-year trends in epidemiology and management in Singapore. MethodsUsing the national OHCA registry we studied the trends of 20,844 Emergency Medical Services-attended adult OHCA from April 2010 to December 2019. Survival to hospital discharge was the primary outcome. Trends and outcomes were analyzed using linear and logistic regression, respectively. ResultsIncidence rates of adult OHCAs increased during the study period, driven by non-shockable OHCA. Compared to shockable OHCA, non-shockable OHCAs were significantly older, had more co-morbidities, unwitnessed and residential arrests, longer no-flow time, and received less bystander cardiopulmonary resuscitation (CPR) and in-hospital interventions (p < 0.001). Amongst non-shockable OHCA, age, co-morbidities, residential arrests, no-flow time, time to patient, bystander CPR and epinephrine administration increased during the study period, while presumed cardiac etiology decreased (p < 0.05). Unlike shockable OHCA, survival for non-shockable OHCA did not improve (p < 0.001 for trend difference). The likelihood of survival for non-shockable OHCA significantly increased with witnessed arrest (adjusted odds ratio (aOR) 2.02) and bystander CPR (aOR 3.25), but decreased with presumed cardiac etiology (aOR 0.65), epinephrine administration (aOR 0.66), time to patient (aOR 0.93) and age (aOR 0.98). Significant two-way interactions were observed for no-flow time and residential arrest with bystander CPR (aOR 0.96 and 0.40 respectively). ConclusionThe incidence of non-shockable OHCA increased between 2010 and 2019. Despite increased interventions, survival did not improve for non-shockable OHCA, in contrast to the improved survival for shockable OHCA.

Green Roof Plant Traits: Influence of Functional Diversity on Ecosystem Services and Coexistence

Green roofs are a novel ecosystem incorporated into the urban landscape to increase green space and provide ecosystem services. Different plant traits excel at providing different green roof ecosystem services, leading to a growing demand for biodiverse green roofs. Research is needed to understand how plant biodiversity can be maintained over time on green roofs, and to determine which species combinations might maximize a given ecosystem service. In this three-year green roof experiment, we use 11 species incorporated into 7 species combinations to create treatments that vary in functional diversity, with treatments including species that are functionally similar, dissimilar, or of intermediate similarity. The selected species combinations were used to determine how trait diversity influences the key ecosystem services of stormwater retention, reduced substrate temperature, pollinator appeal (flower quantity), and the production of aboveground biomass. Additionally, we examine the likelihood of species survival and facilitation within each combination. Here, high functional diversity in leaf thickness and low functional diversity in height and leaf dry matter content was associated with increased biomass, while higher functional diversity in leaf thickness and root length density was associated with decreased substrate temperatures.

Pancreatic cancer near the splenic hilum has a higher likelihood of splenic vessel invasion and unfavorable survival.

This study aimed to investigate whether clinical outcomes varied based on the tumor location within the pancreatic body and tail in patients with pancreatic cancer (PC). Ninety-five patients who had undergone a distal pancreatectomy for resectable (R) or borderline resectable (BR) PC within the pancreatic body or tail region were retrospectively investigated and divided into four groups (three subgroups of R-PC according to tumor location, and BR-PC): R-PC in the pancreatic body region (group A, n = 24), R-PC on the right side of the pancreatic tail region (group B, n = 17), R-PC on the left side of the pancreatic tail region (group C, n = 29), and BR-PC located in any region within the pancreatic body and tail (group BR, n = 25). Group C patients showed a higher incidence of pretreatment splenic artery and vein involvement than group A and B patients (splenic artery: 8.3/11.8/41.4%, p < 0.010; splenic vein: 25.0/23.5/79.3%, p < 0.010, in groups A/B/C, respectively). The overall survival of group C patients was significantly unfavorable compared to that of group A and B patients (median: 3.9/4.2/2.3years in groups A/B/C, p = 0.029, respectively). Pretreatment clinical factors were comparable between group C and group BR. Median survival rates were comparable between group C and BR patients (2.3 and 2.0years, respectively) (p = 0.93). Differences in anatomical location within the pancreatic body and tail characterize the unfavorable outcomes of PC near the splenic hilum.

The interaction between cortisol and testosterone predicts leadership within rock hyrax social groups

Group movement leadership is associated with higher risks for those in the front. Leaders are the first to explore new areas and may be exposed to predation. Individual differences in risk-taking behavior may be related to hormonal differences. In challenging circumstances, such as risk-taking leadership that may pose a cost to the leader, cortisol is secreted both to increase the likelihood of survival by restoring homeostasis, and to mediate cooperative behavior. Testosterone too has a well-established role in risk-taking behavior, and the dual-hormone hypothesis posits that the interaction of testosterone and cortisol can predict social behavior. Based on the dual-hormone hypothesis, we investigated here whether the interaction between testosterone and cortisol can predict risk-taking leadership behavior in wild rock hyraxes (Procavia capensis). We used proximity loggers, observations, and playback trials to characterize hyrax leaders in three different leadership contexts that varied in their risk levels. In support of the dual-hormone hypothesis, we found that cortisol and testosterone interactions predict leadership that involves risk. Across different circumstances that involved low or high levels of risk, testosterone was positively related to leadership, but only in individuals (both males and females) with low levels of cortisol. We also found an interaction between these hormone levels and age at the low-risk scenarios. We suggest that the close social interactions and affiliative behavior among hyrax females within small egalitarian groups may make female leadership less risky, and therefore less stressful, and allow female leaders to influence group activities.

Precision in Dermatology: Developing an Optimal Feature Selection Framework for Skin Lesion Classification.

Melanoma is widely recognized as one of the most lethal forms of skin cancer, with its incidence showing an upward trend in recent years. Nonetheless, the timely detection of this malignancy substantially enhances the likelihood of patients' long-term survival. Several computer-based methods have recently been proposed, in the pursuit of diagnosing skin lesions at their early stages. Despite achieving some level of success, there still remains a margin of error that the machine learning community considers to be an unresolved research challenge. The primary objective of this study was to maximize the input feature information by combining multiple deep models in the first phase, and then to avoid noisy and redundant information by downsampling the feature set, using a novel evolutionary feature selection technique, in the second phase. By maintaining the integrity of the original feature space, the proposed idea generated highly discriminant feature information. Recent deep models, including Darknet53, DenseNet201, InceptionV3, and InceptionResNetV2, were employed in our study, for the purpose of feature extraction. Additionally, transfer learning was leveraged, to enhance the performance of our approach. In the subsequent phase, the extracted feature information from the chosen pre-existing models was combined, with the aim of preserving maximum information, prior to undergoing the process of feature selection, using a novel entropy-controlled gray wolf optimization (ECGWO) algorithm. The integration of fusion and selection techniques was employed, initially to incorporate the feature vector with a high level of information and, subsequently, to eliminate redundant and irrelevant feature information. The effectiveness of our concept is supported by an assessment conducted on three benchmark dermoscopic datasets: PH2, ISIC-MSK, and ISIC-UDA. In order to validate the proposed methodology, a comprehensive evaluation was conducted, including a rigorous comparison to established techniques in the field.

COVID-19 in the intensive care unit: unmasking the critical factors impacting patient survival.

In the midst of the coronavirus disease 2019 (COVID-19) pandemic, intensive care units (ICUs) around the world have been pushed to their limits as they grapple with the effects of the severe acute respiratory syndrome coronavirus 2 virus. Identifying prognostic factors that influence mortality in COVID-19 patients admitted to the ICU could offer valuable insights for clinicians seeking to prevent disease progression. A retrospective analysis was conducted on COVID-19 patients admitted to the ICU between January and September 2020. The analysis considered patient demographics, comorbidities, neurological and non-neurological symptoms, as well as laboratory markers. The multivariate logistic regression analysis aims to uncover associations between these factors and patient outcomes. Of the 387 patients included in this study, nearly half (48.5%) of the ICU patients succumbed to COVID-19. Factors that contributed to increased mortality included being 60 years of age or older, impaired consciousness, lung disease, elevated international normalized ratio (INR), and elevated blood urea nitrogen (BUN) levels. Surprisingly, symptoms such as dizziness/lightheadedness, myalgia, and headache were associated with a higher likelihood of survival. In addition, elevated D-dimer and aspartate aminotransferase (AST) levels, as well as lymphopenia, were more commonly observed in deceased patients. The study concluded that those who died in the ICU tended to be older, white, and burdened with more comorbidities and impaired consciousness. With the intriguing link between specific symptoms and survival, further research is essential to uncover the underlying pathophysiological mechanisms that influence ICU patient outcomes in the context of COVID-19.

Preoperative imaging findings to predict 2-year native liver survival after the Kasai procedure in patients with biliary atresia.

To investigate the feasibility of using preoperative imaging indices to predict 2-year native liver survival after the Kasai procedure in patients with biliary atresia (BA). The retrospective review included 190 BA patients who underwent the Kasai procedure between 2000 and 2020, with preoperative US and/or MRI, excluding cases with less than 2-year follow-up period. Multivariable logistic regression analysis was performed to identify imaging indices to predict 2-year native liver survival. Kasai failure was defined as the need for liver transplantation or death within 2 years of the Kasai procedure. Of the 90 patients included, all had preoperative US, and 61 also had MRI. Kasai failure occurred in 52% (47/90). Preoperative US identified gallbladder length (OR 0.40, 95% CI 0.17-0.95, p= 0.039; cutoff 1.6 cm, AUC 67.66) and biliary cysts (OR 24.64, 95% CI 1.97-308.08, p= 0.013) as significant Kasai failure predictors, with a combined accuracy of 73% (60/82). For patients having both preoperative US and MRI, significant predictors were hepatic artery diameter (OR 6.75, 95% CI 1.31-34.88, p= 0.023; cutoff 2 mm, AUC 73.83) and biliary cysts (OR 23.89, 95% CI 1.43-398.82, p= 0.027) on US, and gallbladder length (OR 0.25, 95% CI 0.08-0.76, p= 0.014; cutoff 1.2 cm, AUC 74.72) and spleen size (OR 2.53, 95% CI 1.02-6.29, p= 0.045; cutoff 6.9 cm, AUC 73.72) on MRI, with a combined accuracy of 85% (52/61). Preoperative US and/or MRI enhance the 2-year native liver survival prediction in BA patients after the Kasai procedure. BA patients with hepatic artery diameter > 2 mm (US), gallbladder length < 1.6 cm (US) or < 1.2 cm (MRI), spleen size > 6.9 cm (MRI), and absence of biliary cysts (US/MRI) have a decreased likelihood of 2-year native liver survival. • Preoperative US and/or MRI can predict the probability of achieving 2-year native liver survival following the Kasai procedure. • Combining US and MRI improved the accuracy to 85% for predicting 2-year native liver survival in BA patients. • The hepatic artery diameter > 2 mm (US), gallbladder length < 1.6 cm (US) or < 1.2 cm (MRI), spleen size > 6.9 cm (MRI), and no biliary cysts (US/MRI) are significant predictors of Kasai failure in patients with biliary atresia.

Modelling Child Survival at Birth Data Using Logistic Regression Model: A Case Study of Yobe State Specialist Hospital Damaturu, Nigeria

This research examines factors influencing the survival of child at birth in Yobe State Specialist Hospital using a well-known logistics regression model. A total of 150 data points were collected through transcription from the maternity record of the Hospital to test significant factors that affect survival of child at birth. Analysis of logistic regression model was applied to the data using the Generalized Linear Model (GLM) package in R programming software. The results indicate that Type of delivery and weight at birth have the most significant influence on the probability of child survival at birth at 0.001 level of significance. Correlation analysis results show that all the five variables (age, parity, apgar, birth weight, and type of delivery) have a weak relationship, which implies that there is no multicollinearity in the data. Therefore, these results may help policy makers and health personnel to educate pregnant women on the effect of overweight baby at birth to reduce the incidence of deaths at birth. This study recommend that pregnant women should be educated about the effect of baby weight in a worm as that may increases the chance of caesarean section which in turn may affect the likelihood of child survival at birth. Further studies are suggested to consider factors like educational level, income of level of the family, antennal status, and blood pressure. A more advance community-based survey is recommended since not pregnant women attain formal health care facilities for antennal and postnatal services, which may expose more factors that influence child survival at birth.

Lung Ultrasound in Predicting Outcomes in Patients with COVID-19 Treated with Extracorporeal Membrane Oxygenation.

Pulmonary involvement due to SARS-CoV-2 infection can lead to acute respiratory distress syndrome in patients with COVID-19. Consequently, pulmonary imaging is crucial for management of COVID-19. This study aimed to evaluate the prognostic value of lung ultrasound (LUS) with a handheld ultrasound device (HHUD) in patients with COVID-19 treated with extracorporeal membrane oxygenation (ECMO). Therefore, patients underwent LUS with a HHUD every two days until they were either discharged from the intensive care unit or died. The study was conducted at the University Hospital of Bonn's anesthesiological intensive care ward from December 2020 to August 2021. A total of 33 patients (median [IQR]: 56.0 [53-60.5] years) were included. A high LUS score was associated with a decreased P/F ratio (repeated measures correlation [rmcorr]: -0.26; 95% CI: -0.34, -0.15; p < 0.001), increased extravascular lung water, defined as fluid accumulation in the pulmonary interstitium and alveoli (rmcorr: 0.11; 95% CI: 0.01, 0.20; p = 0.030), deteriorated electrolyte status (base excess: rmcorr: 0.14; 95% CI: 0.05, 0.24; p = 0.004; pH: rmcorr: 0.12; 95% CI: 0.03, 0.21; p = 0.001), and decreased pulmonary compliance (rmcorr: -0.10; 95% CI: -0.20, -0.01; p = 0.034). The maximum LUS score was lower in survivors (median difference [md]: -0.35; 95% CI: -0.55, -0.06; p = 0.006). A cutoff value for non-survival was calculated at a LUS score of 2.63. At the time of maximum LUS score, P/F ratio (md: 1.97; 95% CI: 1.12, 2.76; p < 0.001) and pulmonary compliance (md: 18.67; 95% CI: 3.33, 37.15; p = 0.018) were higher in surviving patients. In conclusion, LUS with a HHUD enables continuous evaluation of cardiopulmonary function in COVID-19 patients receiving ECMO support therapy and provides prognostic value in determining the patients' likelihood of survival.

Enhancing Skin Cancer Detection and Classification in Dermoscopic Images through Concatenated MobileNetV2 and Xception Models.

One of the most promising research initiatives in the healthcare field is focused on the rising incidence of skin cancer worldwide and improving early discovery methods for the disease. The most significant factor in the fatalities caused by skin cancer is the late identification of the disease. The likelihood of human survival may be significantly improved by performing an early diagnosis followed by appropriate therapy. It is not a simple process to extract the elements from the photographs of the tumors that may be used for the prospective identification of skin cancer. Several deep learning models are widely used to extract efficient features for a skin cancer diagnosis; nevertheless, the literature demonstrates that there is still room for additional improvements in various performance metrics. This study proposes a hybrid deep convolutional neural network architecture for identifying skin cancer by adding two main heuristics. These include Xception and MobileNetV2 models. Data augmentation was introduced to balance the dataset, and the transfer learning technique was utilized to resolve the challenges of the absence of labeled datasets. It has been detected that the suggested method of employing Xception in conjunction with MobileNetV2 attains the most excellent performance, particularly concerning the dataset that was evaluated: specifically, it produced 97.56% accuracy, 97.00% area under the curve, 100% sensitivity, 93.33% precision, 96.55% F1 score, and 0.0370 false favorable rates. This research has implications for clinical practice and public health, offering a valuable tool for dermatologists and healthcare professionals in their fight against skin cancer.