bluuebunny/crossref_metadata_2025_split huggingface dataset:
Megacity-centric mass mobility during Eid holidays: a unique concern for infectious disease transmission in Bangladesh
Authors: Hossain Mohammad Sorowar 
Published: March 2022

AbstractHuman mobility, particularly during certain festivals in rapidly growing megacities in low- and middle-income countries, has critical implications in infectious diseases surveillance and preparedness. In this perspective, we present the interesting case of Dhaka megacity, the capital of Bangladesh with a population of over 20 million. In recent times, three massive infectious disease outbreaks in Dhaka (chikungunya, dengue and COVID-19) coincided with Muslim religious Eid festivals. From a public health standpoint, it is very important to share this information with the international community to fight against emerging infectious diseases around the world.
Multivariable prediction models for health care spending using machine learning: a protocol of a systematic review
Authors: Huang Andrew W. , Haslberger Martin , Coulibaly Neto , Galárraga Omar , Oganisian Arman , Belbasis Lazaros , Panagiotou Orestis A. 
Published: March 2022

Abstract
Background
With rising cost pressures on health care systems, machine-learning (ML)-based algorithms are increasingly used to predict health care costs. Despite their potential advantages, the successful implementation of these methods could be undermined by biases introduced in the design, conduct, or analysis of studies seeking to develop and/or validate ML models. The utility of such models may also be negatively affected by poor reporting of these studies. In this systematic review, we aim to evaluate the reporting quality, methodological characteristics, and risk of bias of ML-based prediction models for individual-level health care spending.

Methods
We will systematically search PubMed and Embase to identify studies developing, updating, or validating ML-based models to predict an individual’s health care spending for any medical condition, over any time period, and in any setting. We will exclude prediction models of aggregate-level health care spending, models used to infer causality, models using radiomics or speech parameters, models of non-clinically validated predictors (e.g., genomics), and cost-effectiveness analyses without predicting individual-level health care spending. We will extract data based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS), previously published research, and relevant recommendations. We will assess the adherence of ML-based studies to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement and examine the inclusion of transparency and reproducibility indicators (e.g. statements on data sharing). To assess the risk of bias, we will apply the Prediction model Risk Of Bias Assessment Tool (PROBAST). Findings will be stratified by study design, ML methods used, population characteristics, and medical field.

Discussion
Our systematic review will appraise the quality, reporting, and risk of bias of ML-based models for individualized health care cost prediction. This review will provide an overview of the available models and give insights into the strengths and limitations of using ML methods for the prediction of health spending.
Real-life quantitative G6PD screening in Plasmodium vivax patients in the Brazilian Amazon: A cost-effectiveness analysis
Authors: Brito-Sousa Jose Diego , Peixoto Henry M. , Devine Angela , Silva-Neto Alexandre V. , Balieiro Patricia C. S. , Sampaio Vanderson S. , Vitor-Silva Sheila , Mendes Maxwell O. , Souza Brenda K. A. , Lacerda Marcus V. G. , Monteiro Wuelton M. 
Published: March 2022

Background
As quantitative glucose 6-phosphate dehydrogenase deficiency (G6PDd) screening tools are evaluated in operational studies, questions remain as to whether they are cost-effective. Here, a cost-effectiveness analysis (CEA) was performed to estimate the Incremental Cost-effectiveness Ratio (ICER) of the introduction of quantitative screening test to detect G6PDd among P. vivax carriers in two municipalities in the Brazilian Amazon.

Methodology/Principal findings
This cost-effectiveness analysis evaluated the use of the Standard G6PD quantitative screening test in vivax malaria treatment units in two municipalities of the Brazilian Amazon. Using the perspective of the Brazilian public health system, the analysis was performed for the outcome ‘PQ-associated hospitalization avoided’, based on a decision tree model. The results indicated that the G6PDd screening strategy compared with the routine strategy was highly cost-effective, with an ICER of US$495 per additional hospitalization avoided, which represented less than 8% of one Brazilian gross domestic product per capita (US$6,822). The uncertainties evaluated in the sensitivity analysis did not significantly affect the ICER identified in the base-case.

Conclusions/Significance
This cost-effectiveness analysis showed the quantitative G6PD testing was effective in avoiding PQ-associated hospitalizations. The incorporation of G6PD screening is of paramount importance towards P. vivax malaria elimination in the Amazon to promote the safe use of primaquine and tafenoquine.
Temporal patterns of inflammation-related proteins measured in the cerebrospinal fluid of patients with aneurysmal subarachnoid hemorrhage using multiplex Proximity Extension Assay technology
Authors: Vlachogiannis Pavlos , Hillered Lars , Enblad Per , Ronne-Engström Elisabeth 
Published: March 2022

BackgroundThe complexity of the inflammatory response post subarachnoid hemorrhage (SAH) may require temporal analysis of multiple protein biomarkers simultaneously to be more accurately described.MethodsVentricular cerebrospinal fluid was collected at days 1, 4 and 10 after SAH in 29 patients. Levels of 92 inflammation-related proteins were simultaneously measured using Target 96 Inflammation®assay (Olink Proteomics, Uppsala, Sweden) based on Proximity Extension Assay (PEA) technology. Twenty-eight proteins were excluded from further analysis due to lack of >50% of measurable values. Temporal patterns of the remaining 64 proteins were analyzed. Repeated measures ANOVA and its nonparametric equivalent Friedman’s ANOVA were used for comparisons of means between time points.ResultsFour different patterns (Groups A-D) were visually observed with an early peak and gradually decreasing trend (11 proteins), a middle peak (10 proteins), a late peak after a gradually increasing trend (30 proteins) and no specific pattern (13 proteins). Statistically significant early peaks defined as Day 1 > Day 4 values were noticed in 4 proteins; no significant decreasing trends defined as Day 1 > Day 4 > Day 10 values were observed. Two proteins showed significant middle peaks (i.e. Day 1 < Day 4 > Day 10 values). Statistically significant late peaks (i.e. Day 4 < Day 10 values) and increasing trends (i.e. Day 1 < Day 4 < Day 10 values) were observed in 14 and 10 proteins, respectively. Four of Group D proteins showed biphasic peaks and the rest showed stable levels during the observation period.ConclusionThe comprehensive data set provided in this explorative study may act as an illustration of an inflammatory profile of the acute phase of SAH showing groups of potential protein biomarkers with similar temporal patterns of activation, thus facilitating further research on their role in the pathophysiology of the disease.
Prevalence and associated factors of anemia among adolescent girls in Ethiopia: A systematic review and meta-analysis
Authors: Habtegiorgis Samuel Derbie , Petrucka Pammla , Telayneh Animut Takele , Getahun Daniel Shitu , Getacher Lemma , Alemu Simegn , Birhanu Molla Yigzaw 
Published: March 2022

Background
Anemia is the reduction of red blood cells in size and numbers and an indicator of both poor nutrition and poor health. It is a major global public health problem. Anemia in adolescents and young adults can have negative effects on their cognitive performance and growth. In Ethiopia, previous studies yielded variable prevalence. This review aimed to determine the pooled prevalence of adolescent girls’ anemia and associated factors in Ethiopia.

Methods
We searched for studies reporting anemia and associated factors among adolescent girls as reported in peer reviews publications in Ethiopia from 1988 to 2021 from PubMed, Google Scholar, Web of Science, Science Direct, Cochrane Library, and Worldwide Science database. The search strategy identified 309 cross-sectional studies. After screening for potentially eligible articles, we identified 37 publications for full text review, following which 10 publications were included in the final review. Using data from the review, we performed meta-analysis to produce pooled estimates and assess the prevalence of anemia and associated risk factors. Data were extracted using a standardized data extraction format prepared in Microsoft Excel™ and transferred to Stata ™ Version 14.0 for management and further analysis. To identify the source of heterogeneity, subgroup analysis using sample size and study setup was computed, and I2 test was used to declare the presence or absence of significant heterogeneity during subgroup analysis. A random-effect meta-analysis model was used to estimate the pooled prevalence of adolescent girls’ anemia. Moreover associated factors for adolescent anemia were assessed too.

Results
The overall pooled prevalence of anemia among adolescent girls’ in Ethiopia was 23.02% (95% CI: 17.21to 28.84). In the subgroup analysis, studies that have a higher sample size than mean have a higher pooled prevalence (27.35%) (95% CI: 21.42 to 33.28) compared to their counterparts. Age being 15–19 (OR: 2.13; 95% CI: 1.52 to 2.96), living in rural areas (OR: 2.05; 95% CI: 1.66 to 2.54), and low dietary diversity (OR: 1.35; 95% CI: 1.00 to 2.34), were the identified factors associated with anemia among adolescent girls’.

Conclusion
The pooled prevalence of anemia among adolescent girls in Ethiopia was moderately high. Being in 15–19 years, rural residence, and low dietary diversity score were found to be the significant factors of anemia among adolescent girls in Ethiopia.
Drug susceptibility profiles and factors associated with non-tuberculous mycobacteria species circulating among patients diagnosed with pulmonary tuberculosis in Tanzania
Authors: Maya Togolani Godfrey , Komba Erick Vitus , Mensah Gloria Ivy , Mbelele Peter Masunga , Mpagama Stella George , Mfinanga Sayoki Godfrey , Addo Kennedy Kwasi , Kazwala Rudovick Reuben 
Published: March 2022

Background
While most Non-tuberculous mycobacteria (NTM) are saprophytic, several species have been associated with human diseases, from localized infection to disseminated diseases. Pulmonary NTM infections lead to TB-like disease called NTM pulmonary disease (NTM-PD). Due to variation in treatment options among NTM species, it is necessary to identify the species and determine drug susceptibility profiles to inform the choice of appropriate regimen for the disease.

Design
A total of 188 culture-positive isolates from patients diagnosed with TB were screened for NTM at the Central Tuberculosis Reference Laboratory. All NTM were further speciated using GenoType® Mycobacterium—Common Mycobacterium and Additional species (GenoType® CM/AS) kit. Mycobacteria avium complex (MAC) and Mycobacteria abscessus complex (MABC) which could not be identified with the test to species were subjected to GenoType® Mycobacteria NTM-DR for further speciation. Using the same test, identified MAC and MABC were genotyped to determine the drug susceptibility profile for each isolate to macrolide and aminoglycosides.

Results
Of all isolates identified as mycobacteria, 24 (13%) were NTM. Fifteen isolates could be identified to species level of which prevalent species was M. avium sub. intracellulare 4 (27%). A total of 10 isolates were MAC (n = 6) and MABC (n = 4) were subjected to GenoType® Mycobacteria NTM-DR for determination of macrolide and aminoglycoside susceptibility. Three of the four MABC had a mutation at the T28 position of the erm (41). All MAC were susceptible to both drugs.

Conclusion
In this study, MAC was the most frequently isolated NTM species followed by MABC. While all MAC and MABC identified, were susceptible to aminoglycosides, three MABC were resistant to the macrolides due to mutation at position 28 of the erm (41) gene. For this, it is important for clinicians need to rule out NTM, understand species and their drug susceptibility for optimal case management.
Engaging citizens in local health policymaking. A realist explorative case-study
Authors: De Weger Esther , Drewes Hanneke W. , Van Vooren Natascha J. E. , Luijkx Katrien G. , Baan Caroline A. 
Published: March 2022

Background
Municipalities have been trying to involve citizens as citizen participation is thought to improve municipalities’ accountability, the quality of services, and to align policies and services to communities’ needs. This study examined citizens’ participation preferences in policymaking by investigating their health policy priorities, expectations of involvement, and required support.

Methods
For this case-study the realist evaluation approach was applied to focus groups with citizens and to a workshop with a local panel consisting of professionals, citizens and citizen representatives.

Results
This study showed that citizens want to be involved in (health) policymaking with the aim of improving their communities’ quality of life and living environment and prioritised local services and amenities (e.g. suitable housing, public transport, health and care services). Instead, professionals’ priorities were focussed on singular public health issues related to prevention and lifestyle factors. The results also show that citizens felt responsible for driving citizen participation and representing community needs to the municipality, but needed the municipality to improve their communication and accessibility in order to do so successfully. Furthermore, the professionals on the panel indicated that they needed training on how to reach out to citizens. Such training should highlight how to better align their language to citizens’ lived experiences. They also wanted their organisations to provide more space, flexibility and resources to build relationships with citizens in order to provide improved communication and accessibility to citizens.

Conclusion
The difference in priorities between citizens and professionals highlights the importance of involving citizens in policymaking. Moreover, citizens’ involvement can act as a lever for change to bring a wider range of services and policy sectors together and has the potential to better align policies to citizens’ lived experiences and hopefully increase the democratic legitimacy of policymaking. However, to fulfil such potential municipalities will need to invest in improving their accessibility and communication with communities.
Analysis of the impact of coronavirus disease 19 on hospitalization rates for chronic non-communicable diseases in Brazil
Authors: Guimarães Rafael Alves , Policena Gabriela Moreira , Paula Hellen da Silva Cintra de , Pedroso Charlise Fortunato , Pinheiro Raquel Silva , Itria Alexander , Braga Neto Olavo de Oliveira , Teixeira Adriana Melo , Silva Irisleia Aires , Oliveira Geraldo Andrade de , Batista Karla de Aleluia 
Published: March 2022

Background
The coronavirus disease (COVID-19) pandemic has impacted health services and healthcare systems worldwide. Studies have shown that hospital admissions for causes related to chronic non-communicable diseases (NCDs) have decreased significantly during peak pandemic periods. An analysis of the impact of the COVID-19 pandemic on hospital admissions for NCDs is essential to implement disability and mortality mitigation strategies for these groups. Therefore, this study aimed to analyze the impact of the COVID-19 pandemic on hospital admissions for NCDs in Brazil according to the type of NCD, sex, age group, and region of Brazil.

Methods
This is an ecological study conducted in Brazil. Data on hospital admissions from January 1, 2017 to May 31, 2021 were extracted from the Unified Health System’s Hospital Admissions Information System. The hospital admission rates per 100,000 thousand inhabitants were calculated monthly according to the type of NCD, sex, age group, and region of Brazil. Poisson regression models were used to analyze the impact of the COVID-19 pandemic on the number of hospital admissions. In this study, the pre-pandemic period was set from January 1, 2017 to February 29, 2020 and the during-pandemic from March 1, 2020 to May 31, 2021.

Results
There was a 27.0% (95.0%CI: -29.0; -25.0%) decrease in hospital admissions for NCDs after the onset of the pandemic compared to that during the pre-pandemic period. Decreases were found for all types of NCDs—cancer (-23.0%; 95.0%CI: -26.0; -21.0%), diabetes mellitus (-24.0%; 95.0%CI: -25.0%; -22.0%), cardiovascular diseases (-30.0%; 95.0%CI: -31.0%; -28.0%), and chronic respiratory diseases (-29.0%; 95.0%CI: -30.0%; -27.0%). In addition, there was a decrease in the number of admissions, regardless of the age group, sex, and region of Brazil. The Northern and Southern regions demonstrated the largest decrease in the percentage of hospital admissions during the pandemic period.

Conclusions
There was a decrease in the hospitalization rate for NCDs in Brazil during the COVID-19 pandemic in a scenario of social distancing measures and overload of health services.
Better survival of patients with hepatitis B virus-related hepatocellular carcinoma in South Korea: Changes in 16-years cohorts
Authors: Choi Sang Il , Cho Yuri , Ki Moran , Kim Bo Hyun , Lee In Joon , Kim Tae Hyun , Kim Seong Hoon , Koh Young Hwan , Kim Hyun Beom , Hong Eun Kyung , Kim Chang-Min , Park Joong-Won 
Published: March 2022

Aims
The incidence and mortality of hepatocellular carcinoma (HCC) have decreased over time in South Korea, where hepatitis B virus (HBV) in endemic. This study investigated the changes in the characteristics and clinical outcomes of HCC patients in Korea.

Methods
Patients initially diagnosed with HCC and treated at the National Cancer Center, Korea between 2000 and 2015 (n = 4,291) were followed up until February 2017. Differences in patient characteristics and outcomes were compared between chronological cohorts: cohort A (2000–2004, n = 1,157) vs. B (2005–2009, n = 1,678) vs. C (2010–2015, n = 1,456).

Results
The median age of the patient cohort was 57 years (range, 13–98 years), and male predominance was noted (81.6%). HBV infection was the most common etiology (74.8%). The proportion of patients diagnosed with good liver function and small tumors (<2 cm) increased significantly over time: 74.6%, 79.9%, and 87.4% for Child–Pugh class A (p<0.001) and 8.0%, 8.5%, and 12.0% for modified UICC stage I (p<0.001) in cohorts A, B, and C, respectively. Median overall survival improved significantly over time: 14.4 months (95% confidence interval [CI], 12.0–16.8 months), 22.9 months (95% CI, 20.3–25.5 months), and 53.6 months (95% CI, 45.7–61.5 months) in cohorts A, B, and C, respectively. HBV-related patients showed significantly improved survival (12.7 vs. 20.4 vs. 64.5 months, p<0.001) associated with the use of antiviral treatments (adjusted hazard ratio, 0.72; 95% CI, 0.64–0.80).

Conclusions
The survival of patients with HCC, especially HBV-related HCC, has improved significantly over time in Korea.
Development and validation of a deep learning model for detection of breast cancers in mammography from multi-institutional datasets
Authors: Ueda Daiju , Yamamoto Akira , Onoda Naoyoshi , Takashima Tsutomu , Noda Satoru , Kashiwagi Shinichiro , Morisaki Tamami , Fukumoto Shinya , Shiba Masatsugu , Morimura Mina , Shimono Taro , Kageyama Ken , Tatekawa Hiroyuki , Murai Kazuki , Honjo Takashi , Shimazaki Akitoshi , Kabata Daijiro , Miki Yukio 
Published: March 2022

Objectives
The objective of this study was to develop and validate a state-of-the-art, deep learning (DL)-based model for detecting breast cancers on mammography.

Methods
Mammograms in a hospital development dataset, a hospital test dataset, and a clinic test dataset were retrospectively collected from January 2006 through December 2017 in Osaka City University Hospital and Medcity21 Clinic. The hospital development dataset and a publicly available digital database for screening mammography (DDSM) dataset were used to train and to validate the RetinaNet, one type of DL-based model, with five-fold cross-validation. The model’s sensitivity and mean false positive indications per image (mFPI) and partial area under the curve (AUC) with 1.0 mFPI for both test datasets were externally assessed with the test datasets.

Results
The hospital development dataset, hospital test dataset, clinic test dataset, and DDSM development dataset included a total of 3179 images (1448 malignant images), 491 images (225 malignant images), 2821 images (37 malignant images), and 1457 malignant images, respectively. The proposed model detected all cancers with a 0.45–0.47 mFPI and had partial AUCs of 0.93 in both test datasets.

Conclusions
The DL-based model developed for this study was able to detect all breast cancers with a very low mFPI. Our DL-based model achieved the highest performance to date, which might lead to improved diagnosis for breast cancer.
An observational study of intensivists’ expectations and effects of fluid boluses in critically ill patients
Authors: Wall Olof , Cutuli Salvatore , Wilson Anthony , Eastwood Glenn , Lipka-Falck Adam , Törnberg Daniel , Bellomo Rinaldo , Cronhjort Maria 
Published: March 2022

Background
Fluid bolus therapy (FBT) is common in ICUs but whether it achieves the effects expected by intensivists remains uncertain. We aimed to describe intensivists’ expectations and compare them to the actual physiological effects.

Methods
We evaluated 77 patients in two ICUs (Sweden and Australia). We included patients prescribed a FBT ≥250 ml over ≤30 minutes. The intensivist completed a questionnaire on triggers for and expected responses to FBT. We compared expected with actual values at FBT completion and after one hour.

Results
Median bolus size (IQR) was 300 ml (250–500) given over a median (IQR) of 21 minutes (15–30 mins). Boluses were 57% Ringer´s Acetate and 43% albumin (40-50g/L). Hypotension was the most common trigger (47%), followed by oliguria (21%). During FBT, 55% of patients received noradrenaline and 38% propofol. Intensivists expected a median MAP increase of 2.6 mmHg (IQR: -3.1 to +6.8) at end of bolus and of 1.3 mmHg (-3.5 to + 4.1) after one hour. Intensivist´s’ expectations were judged to be accurate if they were within 5% above or below measured values. At FBT completion, 33% of MAP expectations were overestimations and 42% were underestimations. One hour later, 19% were overestimations and 43% were underestimations. Only 8% of expectations of measured urine output (UO) were accurate and 44% were overestimations. Correction for sedation or vasopressors did not modify these findings.

Conclusions
The physiological expectations of intensivists after FBT carried a high risk of both over and underestimation. Since the physiological effect FBT was often small and did not meet clinical expectations, a reassessment of its rationale, effect, duration, and role appears justified.