Category: Nevin Manimala

PLoS One. 2023 Dec 6;18(12):e0287702. doi: 10.1371/journal.pone.0287702. eCollection 2023.

ABSTRACT

BACKGROUND: Plasmodium falciparum cases are rising in China due to the imported malaria cases from African countries. The main goal of this study is to examine the impact of imported malaria cases in African countries on the rise of P. falciparum cases in China before and during the COVID-19 pandemic.

METHODS: A generalized regression model was used to investigate the association of time trends between imported malaria cases from 45 African countries and P. falciparum cases in 31 provinces of China from 2012 to 2018 before the COVID-19 pandemic and during the COVID-19 pandemic from October 2020 to May 2021. Based on the analysis, we proposed a statistical and deep learning hybrid approach to model the resurgence of malaria in China using monthly data of P. falciparum from 2004 to 2016. This study builds a hybrid model known as the ARIMA-GRU approach for modeling the P. falciparum cases in all provinces of China and the number of malaria deaths in China before and during the COVID-19 pandemic.

RESULTS: The analysis showed an emerging link between the rise of imported malaria cases from Africa and P. falciparum cases in many provinces of China. Many imported malaria cases from Africa were P. falciparum cases. The proposed deep learning model achieved a high prediction accuracy score on the testing dataset of 96%.

CONCLUSION: The study provided an analysis of the reduction of P. falciparum cases and deaths caused by imported P. falciparum cases during the COVID-19 pandemic due to the control measures regarding the limitation of international travel in China. The Chinese government has to prepare the imported malaria control measures after the normalization of international travel, to prevent the resurgence of malaria disease in China.

PMID:38055693 | DOI:10.1371/journal.pone.0287702

PLoS One. 2023 Dec 6;18(12):e0295284. doi: 10.1371/journal.pone.0295284. eCollection 2023.

ABSTRACT

Canagliflozin (CANA) is a sodium-glucose cotransporter 2 (SGLT2) inhibitor with blood glucose lowering effects. CANA also promotes kidney protection in patients with cardiovascular diseases and type 2 diabetes (T2D), as well as in normoglycemic patients with hypertension or heart failure. Clinical studies, although conduct in both sexes, do not report sex-dependent differences in T2DM treated with CANA. However, the impact of CANA in type 1 diabetes, as well in sex-dependent outcomes in such cohort needs further understanding. To analyze the effects of CANA in mice with combined hypertension and type 1 diabetes, diabetes was induced by STZ injection (5 days, 50mg/kg/day) in both male and female 8 weeks old genetic hypertensive mice (Lin), whereas the control (Lin) received 0.1M sodium citrate injections. 8 weeks after STZ. Mice were fed either regular or CANA-infused diet for 4 weeks. 8 weeks after STZ, hyperglycemia was present in both male and female mice. CANA reversed BG increase mice fed regular diet. Male LinSTZ mice had elevated water intake, urine output, urinary albumin to creatinine ratio (ACR), kidney lesion score, and creatinine clearance compared to the Lin control group. Kidney injury was improved in male LinSTZ + CANA group in male mice. Water intake and urine output were not statistically significantly different in female LinSTZ compared to female LinSTZ+ CANA. Moreover, CANA did not improve kidney injury in female mice, showing no effect in creatinine clearance, lesion score and fibrosis when compared to LinSTZ fed regular diet. Here we show that Canagliflozin might exert different kidney protection effects in male compared to female mice with hypertension and type 1 diabetes. Sex-dimorphisms were previously found in the pathophysiology of diabetes induced by STZ. Therefore, we highlight the importance of in-depth investigation on sex-dependent effects of CANA, taking in consideration the unique characteristics of disease progression for each sex.

PMID:38055691 | DOI:10.1371/journal.pone.0295284

PLoS One. 2023 Dec 6;18(12):e0295359. doi: 10.1371/journal.pone.0295359. eCollection 2023.

ABSTRACT

BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of mortality worldwide. Atherosclerosis occurs due to accumulation of low-density lipoprotein cholesterol (LDL-c) in the arterial system. Thus, lipid lowering therapy is essential for both primary and secondary prevention. Proprotein convertase subtilisn/kexin type 9 (PCSK9) inhibitors (Evolocumab, Alirocumab) and small interfering RNA (siRNA) therapy (Inclisiran) have been demonstrated to lower LDL-c and ASCVD events in conjunction with maximally tolerated statin therapy. However, the degree of LDL-c reduction and the impact on reducing major adverse cardiac events, including their impact on mortality, remains unclear.

OBJECTIVE: The purpose of this study is to examine the effects of PCSK9 inhibitors and small interfering RNA (siRNA) therapy on LDL-c reduction and major adverse cardiac events (MACE) and mortality by conducting a meta-analysis of randomized controlled trials.

METHODS: Using Pubmed, Embase, Cochrane Library and clinicaltrials.gov until April 2023, we extracted randomized controlled trials (RCTs) of PCSK9 inhibitors (Evolocumab, Alirocumab) and siRNA therapy (Inclisiran) for lipid lowering and risk of MACE. Using random-effects models, we pooled the relative risks and 95% CIs and weighted least-squares mean difference in LDL-c levels. We estimated odds ratios with 95% CIs among MACE subtypes and all-cause mortality. Fixed-effect model was used, and heterogeneity was assessed using the I2 statistic.

RESULTS: In all, 54 studies with 87,669 participants (142,262 person-years) met criteria for inclusion. LDL-c percent change was reported in 47 studies (n = 62,634) evaluating two PCSK9 inhibitors and siRNA therapy. Of those, 21 studies (n = 41,361) included treatment with Evolocumab (140mg), 22 (n = 11,751) included Alirocumab (75mg), and 4 studies (n = 9,522) included Inclisiran (284mg and 300mg). Compared with placebo, after a median of 24 weeks (IQR 12-52), Evolocumab reduced LDL-c by -61.09% (95% CI: -64.81, -57.38, p<0.01) and Alirocumab reduced LDL-c by -46.35% (95% CI: -51.75, -41.13, p<0.01). Inclisiran 284mg reduced LDL-c by -54.83% (95% CI: -59.04, -50.62, p = 0.05) and Inclisiran 300mg reduced LDL-c by -43.11% (95% CI: -52.42, -33.80, p = 0.01). After a median of 8 months (IQR 6-15), Evolocumab reduced the risk of myocardial infarction (MI), OR 0.72 (95% CI: 0.64, 0.81, p<0.01), coronary revascularization, 0.77 (95% CI: 0.70, 0.84, p<0.01), stroke, 0.79 (95% CI: 0.66, 0.94, p = 0.01) and overall MACE 0.85 (95% CI: 0.80, 0.89, p<0.01). Alirocumab reduced MI, 0.57 (0.38, 0.86, p = 0.01), cardiovascular mortality 0.35 (95% CI: 0.16, 0.77, p = 0.01), all-cause mortality 0.60 (95% CI: 0.43, 0.84, p<0.01), and overall MACE 0.35 (0.16, 0.77, p = 0.01).

CONCLUSION: PCSK9 inhibitors (Evolocumab, Alirocumab) and siRNA therapy (Inclisiran) significantly reduced LDL-c by >40% in high-risk individuals. Additionally, both Alirocumab and Evolocumab reduced the risk of MACE, and Alirocumab reduced cardiovascular and all-cause mortality.

PMID:38055686 | DOI:10.1371/journal.pone.0295359

PLoS One. 2023 Dec 6;18(12):e0295433. doi: 10.1371/journal.pone.0295433. eCollection 2023.

ABSTRACT

The aim of this study was to use linear body measurements to develop and validate a regression-based model for prediction of live weights (LW) of pigs reared under smallholder settings in rural areas in the southern highlands of Tanzania. LW of 400 pigs (range 7 to 91 kg) was measured, along with their heart girths (HG) and body lengths (BL). BL was measured from the midpoint between the ears to the tail base. HG was measured as chest circumference just behind the front legs. LW was determined using a portable hanging scale. An analysis of covariance was performed to test for differences in LW between male and female pigs, including age, HG and BL as covariates. LW was regressed on HG and BL using simple and multiple linear regressions. Models were developed for all pig ages, and separately for market/breeding-age pigs and those below market/breeding age. Model validation was done using a split-samples approach, followed by PRESS-related statistics. Model efficiency and accuracy were assessed using the coefficient of determination, R2, and standard deviation of the random error, respectively. Model stability was determined by assessing ‘shrinkage’ of R2 value. Results showed that HG was the best predictor of LW in market/breeding-age pigs (model equation: LW = 1.22HG-52.384; R2 = 0.94, error = 3.7). BL, age and sex of pigs did not influence LW estimates. It is expected that LW estimation tools will be developed to enable more accurate estimation of LW in the pig value chain in the area.

PMID:38055667 | DOI:10.1371/journal.pone.0295433

PLoS One. 2023 Dec 6;18(12):e0295219. doi: 10.1371/journal.pone.0295219. eCollection 2023.

ABSTRACT

BACKGROUND: Home delivery is defined as is an even of pregnant women getting giving birth in a woman her home or other homes without an unskilled health professional assistance. It is continuing as public health problem since its responsible for death of women and newborn. In Gambia there is a high maternal mortality rate, which may be related to home delivery. Therefore, this study aimed to assess the trend of home delivery and identify predictors using Gambia Demographic and Health Survey (GDHS) 2013 and 2019-2020 data sets.

METHODS: A Cross-Section survey was conducted based on GDHS 2013 and 2019-2020 among reproductive age group women. A total of 8607 women participated in this study. A bivariate decomposition model was fitted, and variables that had a p-value > 0.25 were dropped. Finally, variables that got a p-value of < 0.05 with 95% confidence interval (CI) in the multivariate decomposition analysis were considered as statistical significance variables in the overall decomposition.

RESULTS: There has been a dramatic decrement in maternal home delivery in Gambia. It was 36.18% (95% CI:34.78, 37.58) in 2013 GDHS and 14.39% (95% CI:13.31,15.47) in 2019-2020 GDHS. This reduction is real because there was a change in the characteristics effect of the population and the coefficient effect some variables in the home delivery. Changes in characteristics effect of husband education, women education, rural residents, more than three antenatal cares follow up, and no problem reaching health facilities played a significant role in the reduction of home delivery. Being urban resident and women who had occupation were variables that had a positive effect on coefficient effect change.

CONCLUSION: In this study, the home delivery rate had steeply declined in the Gambia during the study period of the two surveys. Just above nine-tenths decrement in home delivery rate resulted because there was a change in the characteristics effect of the study participants. Enhancing more citizens to attend high school and above, narrowing the gap between rural and urban in terms of accessing health facilities, and improving the availability of infrastructure should be done.

PMID:38055662 | DOI:10.1371/journal.pone.0295219

Hepatol Commun. 2023 Dec 7;7(12):e0329. doi: 10.1097/HC9.0000000000000329. eCollection 2023 Dec 1.

ABSTRACT

BACKGROUND: Sensors within smartphones, such as accelerometer and location, can describe longitudinal markers of behavior as represented through devices in a method called digital phenotyping. This study aimed to assess the feasibility of digital phenotyping for patients with alcohol-associated liver disease and alcohol use disorder, determine correlations between smartphone data and alcohol craving, and establish power assessment for future studies to prognosticate clinical outcomes.

METHODS: A total of 24 individuals with alcohol-associated liver disease and alcohol use disorder were instructed to download the AWARE application to collect continuous sensor data and complete daily ecological momentary assessments on alcohol craving and mood for up to 30 days. Data from sensor streams were processed into features like accelerometer magnitude, number of calls, and location entropy, which were used for statistical analysis. We used repeated measures correlation for longitudinal data to evaluate associations between sensors and ecological momentary assessments and standard Pearson correlation to evaluate within-individual relationships between sensors and craving.

RESULTS: Alcohol craving significantly correlated with mood obtained from ecological momentary assessments. Across all sensors, features associated with craving were also significantly correlated with all moods (eg, loneliness and stress) except boredom. Individual-level analysis revealed significant relationships between craving and features of location entropy and average accelerometer magnitude.

CONCLUSIONS: Smartphone sensors may serve as markers for alcohol craving and mood in alcohol-associated liver disease and alcohol use disorder. Findings suggest that location-based and accelerometer-based features may be associated with alcohol craving. However, data missingness and low participant retention remain challenges. Future studies are needed for further digital phenotyping of relapse risk and progression of liver disease.

PMID:38055637 | DOI:10.1097/HC9.0000000000000329

Am J Epidemiol. 2023 Dec 5:kwad237. doi: 10.1093/aje/kwad237. Online ahead of print.

ABSTRACT

Studies have highlighted the potential importance of modeling interactions for suicide attempt prediction. This case-cohort study identified risk factors for suicide attempts among persons with depression in Denmark using statistical approaches that do (random forests) or do not model interactions (least absolute shrinkage and selection operator regression [LASSO]). Cases made a non-fatal suicide attempt (n = 6,032) between 1995 and 2015. The comparison subcohort was a 5% random sample of all persons in Denmark on January 1, 1995 (n = 11,963). We used random forests and LASSO for sex-stratified prediction of suicide attempts from demographic variables, psychiatric and somatic diagnoses, and treatments. Poisonings, psychiatric disorders, and medications were important predictors for both sexes. Area under the receiver operating characteristic curve (AUC) values were higher in LASSO models (0.85 [95% CI = 0.84, 0.86] in men; 0.89 [95% CI = 0.88, 0.90] in women) than random forests (0.76 [95% CI = 0.74, 0.78] in men; 0.79 [95% CI = 0.78, 0.81] in women). Automatic detection of interactions via random forests did not result in better model performance than LASSO models that did not model interactions. Due to the complex nature of psychiatric comorbidity and suicide, modeling interactions may not always be the optimal statistical approach to enhancing suicide attempt prediction in high-risk samples.

PMID:38055633 | DOI:10.1093/aje/kwad237

JMIR Med Educ. 2023 Dec 6;9:e52202. doi: 10.2196/52202.

ABSTRACT

BACKGROUND: The reliability of GPT-4, a state-of-the-art expansive language model specializing in clinical reasoning and medical knowledge, remains largely unverified across non-English languages.

OBJECTIVE: This study aims to compare fundamental clinical competencies between Japanese residents and GPT-4 by using the General Medicine In-Training Examination (GM-ITE).

METHODS: We used the GPT-4 model provided by OpenAI and the GM-ITE examination questions for the years 2020, 2021, and 2022 to conduct a comparative analysis. This analysis focused on evaluating the performance of individuals who were concluding their second year of residency in comparison to that of GPT-4. Given the current abilities of GPT-4, our study included only single-choice exam questions, excluding those involving audio, video, or image data. The assessment included 4 categories: general theory (professionalism and medical interviewing), symptomatology and clinical reasoning, physical examinations and clinical procedures, and specific diseases. Additionally, we categorized the questions into 7 specialty fields and 3 levels of difficulty, which were determined based on residents’ correct response rates.

RESULTS: Upon examination of 137 GM-ITE questions in Japanese, GPT-4 scores were significantly higher than the mean scores of residents (residents: 55.8%, GPT-4: 70.1%; P<.001). In terms of specific disciplines, GPT-4 scored 23.5 points higher in the “specific diseases,” 30.9 points higher in “obstetrics and gynecology,” and 26.1 points higher in “internal medicine.” In contrast, GPT-4 scores in “medical interviewing and professionalism,” “general practice,” and “psychiatry” were lower than those of the residents, although this discrepancy was not statistically significant. Upon analyzing scores based on question difficulty, GPT-4 scores were 17.2 points lower for easy problems (P=.007) but were 25.4 and 24.4 points higher for normal and difficult problems, respectively (P<.001). In year-on-year comparisons, GPT-4 scores were 21.7 and 21.5 points higher in the 2020 (P=.01) and 2022 (P=.003) examinations, respectively, but only 3.5 points higher in the 2021 examinations (no significant difference).

CONCLUSIONS: In the Japanese language, GPT-4 also outperformed the average medical residents in the GM-ITE test, originally designed for them. Specifically, GPT-4 demonstrated a tendency to score higher on difficult questions with low resident correct response rates and those demanding a more comprehensive understanding of diseases. However, GPT-4 scored comparatively lower on questions that residents could readily answer, such as those testing attitudes toward patients and professionalism, as well as those necessitating an understanding of context and communication. These findings highlight the strengths and limitations of artificial intelligence applications in medical education and practice.

PMID:38055323 | DOI:10.2196/52202

Sci Prog. 2023 Oct-Dec;106(4):368504231215591. doi: 10.1177/00368504231215591.

ABSTRACT

Introduction: Post-adenotonsillectomy (PAT) bleeding, a life-threatening surgical complication, remains unpredictable despite preoperative blood tests. Every surgeon would like predictive markers for this complication of one of the most common procedures performed in pediatric ear, nose, and throat (ENT). Objective: The purpose of the study is to see whether the results of the blood tests we perform routinely preoperatively in children undergoing adenotonsillectomy (AT) (lymphocyte count and percentage, C reactive protein, fibrinogen, or coagulation variables International Normalized Ratio and activated partial thromboplastin time) can potentially predict early post-AT bleeding. Focus has been placed on the presence of relative lymphocytosis (a value of lymphocyte percentage above 55%) in the blood cell count of the patients and its possible connection to postoperative hemorrhage. Method: We conducted an observational retrospective study on 801 children undergoing adenoidectomy, tonsillectomy, or AT over a period of 6 months in our ENT department. Statistical analysis was performed to compare the data. Results: we did not find a statistically significant correlation between preoperative blood markers (coagulation or inflammatory) and early post-AT bleeding. An important blood marker in relation to PAT bleeding appears to be relative lymphocytosis. Relative lymphocytosis has a weak predictive value of early postoperative bleeding in children with AT (sensitivity of only 31.58%, but acceptable specificity of above 80%). In other words, 80% of patients without relative lymphocytosis will not bleed in the first 24 h postoperatively. Children with relative lymphocytosis may need tighter surveillance in the first 24 h after AT. Conclusions: Relative lymphocytosis has a weak predictive value of early postoperative bleeding in children with AT children.

PMID:38055322 | DOI:10.1177/00368504231215591

JMIR Mhealth Uhealth. 2023 Dec 6;11:e46558. doi: 10.2196/46558.

ABSTRACT

BACKGROUND: There is growing interest in enhancing stroke self-management support using mobile health (mHealth) technology (eg, smartphones and apps). Despite this growing interest, “self-management support” is inconsistently defined and applied in the poststroke mHealth intervention literature, which limits efforts to synthesize and compare evidence. To address this gap in conceptual clarity, a scoping review was conducted.

OBJECTIVE: The objectives were to (1) identify and describe the types of poststroke mHealth interventions evaluated using a randomized controlled trial design, (2) determine whether (and how) such interventions align with well-accepted conceptualizations of self-management support (the theory by Lorig and Holman and the Practical Reviews in Self-Management Support [PRISMS] taxonomy by Pearce and colleagues), and (3) identify the mHealth functions that facilitate self-management.

METHODS: A scoping review was conducted according to the methodology by Arksey and O’Malley and Levac et al. In total, 7 databases were searched. Article screening and data extraction were performed by 2 reviewers. The data were analyzed using descriptive statistics and content analysis.

RESULTS: A total of 29 studies (26 interventions) were included. The interventions addressed 7 focal areas (physical exercise, risk factor management, linguistic exercise, activities of daily living training, medication adherence, stroke education, and weight management), 5 types of mobile devices (mobile phones or smartphones, tablets, wearable sensors, wireless monitoring devices, and laptops), and 7 mHealth functions (educating, communicating, goal setting, monitoring, providing feedback, reminding, and motivating). Collectively, the interventions aligned well with the concept of self-management support. However, on an individual basis (per intervention), the alignment was less strong.

CONCLUSIONS: On the basis of the results, it is recommended that future research on poststroke mHealth interventions be more theoretically driven, more multidisciplinary, and larger in scale.

PMID:38055318 | DOI:10.2196/46558