Nevin Manimala

BMC Public Health. 2022 Jul 13;22(1):1337. doi: 10.1186/s12889-022-13633-8.

ABSTRACT

BACKGROUND: For assessing the HIV epidemic in Kenya, a series of independent HIV indicator household-based surveys of similar design can be used to investigate the trends in key indicators relevant to HIV prevention and control and to describe geographic and sociodemographic disparities, assess the impact of interventions, and develop strategies. We developed methods and tools to facilitate a robust analysis of trends across three national household-based surveys conducted in Kenya in 2007, 2012, and 2018.

METHODS: We used data from the 2007 and 2012 Kenya AIDS Indicator surveys (KAIS 2007 and KAIS 2012) and the 2018 Kenya Population-based HIV Impact Assessment (KENPHIA 2018). To assess the design and other variables of interest from each study, variables were recoded to ensure that they had equivalent meanings across the three surveys. After assessing weighting procedures for comparability, we used the KAIS 2012 nonresponse weighting procedure to revise normalized KENPHIA weights. Analyses were restricted to geographic areas covered by all three surveys. The revised analysis files were then merged into a single file for pooled analysis. We assessed distributions of age, sex, household wealth, and urban/rural status to identify unexpected changes between surveys. To demonstrate how a trend analysis can be carried out, we used continuous, binary, and time-to-event variables as examples. Specifically, temporal trends in age at first sex and having received an HIV test in the last 12 months were used to demonstrate the proposed analytical approach. These were assessed with respondent-specific variables (age, sex, level of education, and marital status) and household variables (place of residence and wealth index). All analyses were conducted in SAS 9.4, but analysis files were created in Stata and R format to support additional analyses.

RESULTS: This study demonstrates trends in selected indicators to illustrate the approach that can be used in similar settings. The incidence of early sexual debut decreased from 11.63 (95% CI: 10.95-12.34) per 1,000 person-years at risk in 2007 to 10.45 (95% CI: 9.75-11.2) per 1,000 person-years at risk in 2012 and to 9.58 (95% CI: 9.08-10.1) per 1,000 person-years at risk in 2018. HIV-testing rates increased from 12.6% (95% CI: 11.6%-13.6%) in 2007 to 56.1% (95% CI: 54.6%-57.6%) in 2012 but decreased slightly to 55.6% [95% CI: 54.6%-56.6%) in 2018. The decrease in incidence of early sexual debut could be convincingly demonstrated between 2007 and 2012 but not between 2012 and 2018. Similarly, there was virtually no difference between HIV Testing rates in 2012 and 2018.

CONCLUSIONS: Our approach can be used to support trend comparisons for variables in HIV surveys in low-income settings. Independent national household surveys can be assessed for comparability, adjusted as appropriate, and used to estimate trends in key indicators. Analyzing trends over time can not only provide insights into Kenya’s progress toward HIV epidemic control but also identify gaps.

PMID:35831818 | DOI:10.1186/s12889-022-13633-8

BMC Pediatr. 2022 Jul 13;22(1):411. doi: 10.1186/s12887-022-03471-3.

ABSTRACT

BACKGROUND: Neonatal sepsis is one of the leading causes of neonatal morbidity and mortality in developing countries like Ethiopia. The investigation of neonatal sepsis needs the application of inclusive diagnostic tools. Therefore, this study aimed to assess the role of CBC parameters in diagnosing neonatal sepsis.

METHODS: A comparative cross-sectional study was conducted from September 2020 to November 2021 at the University of Gondar Comprehensive Specialized Hospital. A total of 250 neonates were included using a convenient sampling technique. A structured questionnaire and a data collection sheet were used to obtain the socio-demographic and clinical characteristics of the study participants. A venous blood sample was collected for CBC and blood culture tests. Epi-Info Version 7 and SPSS Version 25 were used for data entry and analysis, respectively. The data distribution was checked by the Shapiro-Wilk test. Then, an independent t-test was conducted to compare CBC parameters, and the significant parameters were recruited for the ROC curves analysis. The Younden index test was used to determine the cutoff point for the sensitivity and specificity. A p-value of <0.05 was considered statistically significant.

RESULTS: Out of 250 study participants, 144 (57.6%) were males, with a median age of 6 days (IQR = 4 days). Early-onset and late-onset sepsis were developed in about 29.6% (37/250) and 70.4% (88/250) of the neonates, respectively. The TLC and ANC parameters were significantly lower in cases than in control groups. The TLC, Hgb, lymphocyte count, and ANC parameters have a sensitivity of 64.8, 68, 33.6, and 49.6%, respectively. Their specificity in the diagnosis of neonatal sepsis was 64.8, 53.6, 83.2, and 90.4%, respectively.

CONCLUSION: Total leucocyte count, ANC, and platelet count all showed significant associations with neonatal sepsis. Besides, the TLC, ANC, and platelet counts had good sensitivity and specificity in diagnosing neonatal sepsis. Therefore, these parameters can be used as a diagnostic tool for neonatal sepsis in resource-limited areas.

PMID:35831816 | DOI:10.1186/s12887-022-03471-3

BMC Public Health. 2022 Jul 12;22(1):1333. doi: 10.1186/s12889-022-13727-3.

ABSTRACT

BACKGROUND: State-level racial/ethnic and age differences and the temporal trend of thyroid cancer (TC) incidence in the USA remain unknown. Our research purposes include: Characterizing state-level temporal variation in TC incidence; examining the disparities of TC incidence by state-level race/ethnicity and age; performing an ecological correlation between TC incidence and obesity/physical activity.

METHODS: TC incidence data during 2000-2017 were extracted from the United States cancer statistics. Using joinpoint regression to evaluate TC incidence trends. Annual percent change (APC), average APC (AAPC) and incidence rates were calculated. The obesity prevalence and physical activity level at the state-level were extracted from Behavioral Risk Factor Surveillance System, and the association between state-level AAPC of TC and obesity/physical activity was tested by Pearson correlation coefficient.

RESULTS: We found that the TC incidence had shown an overall downward trend in recent years, but 10 states continued increasing. There were significant differences in state-level race/ethnicity (non-Hispanic Whites as a reference) and age group (45-59 age group as a reference) incidence: Incidence Rate Ratio (IRR) was 0.4-1.2 for non-Hispanic Blacks, 0.7-1.6 for non-Hispanic Asian and Pacific Islanders, 0.4-1.2 for non-Hispanic American Indians/Alaskan Natives, and 0.5-1.3 for Hispanics. High IRR in young people were distributed in northern USA, while in older people were distributed in south. The state-level obesity/physical activity level and AAPC had a weak correlation (r = 0.34, P = 0.016) and inverse weak correlation (r = -0.29, P = 0.037), respectively. The AAPC of states with a consistent increasing trend had an extremely strong correlation with obesity prevalence (r = 0.80, p = 0.006), and an inverse strong correlation with physical activity level (r = -0.65, P = 0.04).

CONCLUSIONS: Thyroid cancer incidence in 10 states continued increasing. State-level variation in race/ethnicity and age group incidence were found. Lifestyle and environmental factors may interfere with the incidence trend of TC in the USA.

PMID:35831811 | DOI:10.1186/s12889-022-13727-3

BMC Genomics. 2022 Jul 12;23(1):504. doi: 10.1186/s12864-022-08715-1.

ABSTRACT

BACKGROUND: Using single-cell RNA sequencing (scRNA-seq) data to diagnose disease is an effective technique in medical research. Several statistical methods have been developed for the classification of RNA sequencing (RNA-seq) data, including, for example, Poisson linear discriminant analysis (PLDA), negative binomial linear discriminant analysis (NBLDA), and zero-inflated Poisson logistic discriminant analysis (ZIPLDA). Nevertheless, few existing methods perform well for large sample scRNA-seq data, in particular when the distribution assumption is also violated.

RESULTS: We propose a deep learning classifier (scDLC) for large sample scRNA-seq data, based on the long short-term memory recurrent neural networks (LSTMs). Our new scDLC does not require a prior knowledge on the data distribution, but instead, it takes into account the dependency of the most outstanding feature genes in the LSTMs model. LSTMs is a special recurrent neural network, which can learn long-term dependencies of a sequence.

CONCLUSIONS: Simulation studies show that our new scDLC performs consistently better than the existing methods in a wide range of settings with large sample sizes. Four real scRNA-seq datasets are also analyzed, and they coincide with the simulation results that our new scDLC always performs the best. The code named “scDLC” is publicly available at https://github.com/scDLC-code/code .

PMID:35831808 | DOI:10.1186/s12864-022-08715-1

BMC Geriatr. 2022 Jul 13;22(1):575. doi: 10.1186/s12877-022-03262-6.

ABSTRACT

BACKGROUND: The use of psychotropics is high among the older population and may have detrimental effects on their physical and mental health. Cardiorespiratory fitness (CRF) is a strong and modifiable measure of health and declines with age. We aimed to study the association of change in CRF with use of psychotropics in community-dwelling older adults.

METHODS: We analyzed longitudinal data from 1531 older adults from the Generation 100 study, aged 70-77 years at inclusion, and with a permanent address in Trondheim, Norway. Data on objectively measured peak oxygen uptake (VO_2peak) were linked with register data from the Norwegian Prescription Database on prescribed psychotropics. The included psychotropics were antidepressants (N06A), antipsychotics (N05A), anxiolytics (N05B), hypnotics and sedatives (N05C), and N03AE (benzodiazepine derivatives). Analyses were done on any psychotropics as one group, and on the following separate groups: antidepressants (N06A), benzodiazepines (N05BA, N05CD, and N03AE), and z-hypnotics (N05CF). Peak oxygen uptake was measured four times over a five-year period and corresponding medication use was measured as defined daily doses (DDD). A random effects estimator was applied to investigate the association of change in VO_2peak with the use of psychotropics.

RESULTS: We found a statistically significant curvilinear association of change in VO_2peak with use of any psychotropics and antidepressants. For VO_2peak up to ~ 40 ml/kg/min, each 1 ml/kg/min increase was associated by a 3.3 DDD and 2.5 DDD decrease in use of any psychotropics and antidepressants, respectively. A bottoming-out effect was found and increases in VO_2peak above ~ 40 ml/kg/min showed increased use of any psychotropics and antidepressants. However, the association of change in VO_2peak with use was stronger for changes in the lower continuum of VO_2peak levels and decreased with increasing VO_2peak. No statistically significant association of change in VO_2peak with use of benzodiazepines and z-hypnotics were found. However, because of a non-randomized design, we cannot rule out the possibility of confounding by indication.

CONCLUSIONS: The results of this study show a curvilinear association of change in VO_2peak with use of any psychotropics and antidepressants in older adults. This relationship adds a new viewpoint on the adverse effects of psychotropic use and should be considered in interventions and policies aimed at reducing psychotropic medication use among the older population.

PMID:35831807 | DOI:10.1186/s12877-022-03262-6

BMC Genomics. 2022 Jul 12;23(1):506. doi: 10.1186/s12864-022-08736-w.

ABSTRACT

BACKGROUND: The genus Sporothrix belongs to the order Ophiostomatales and contains mainly saprobic soil and plant fungi, although pathogenic species capable of causing human infections are also present. The whole-genomes of disease-causing species have already been sequenced and annotated but no comprehensive genomic resources for environmental Sporothrix species are available, thus limiting our understanding of the evolutionary origin of virulence-related genes and pathogenicity.

RESULT: The genome assembly of four environmental Sporothrix species resulted in genome size of ~ 30.9 Mbp in Sporothrix phasma, ~ 35 Mbp in S. curviconia, ~ 38.7 Mbp in S. protearum, and ~ 39 Mbp in S. variecibatus, with a variable gene content, ranging from 8142 (S. phasma) to 9502 (S. variecibatus). The analysis of mobile genetic elements showed significant differences in the content of transposable elements within the sequenced genomes, with the genome of S. phasma lacking several class I and class II transposons, compared to the other Sporothrix genomes investigated. Moreover, the comparative analysis of orthologous genes shared by clinical and environmental Sporothrix genomes revealed the presence of 3622 orthogroups shared by all species, whereas over 4200 genes were species-specific single-copy gene products. Carbohydrate-active enzyme analysis revealed a total of 2608 protein-coding genes containing single and/or multiple CAZy domains, resulting in no statistically significant differences among pathogenic and environmental species. Nevertheless, some families were not found in clinical species. Furthermore, for each sequenced Sporothrix species, the mitochondrial genomes was assembled in a single circular DNA molecule, ranging from 25,765 bp (S. variecibatus) to 58,395 bp (S. phasma).

CONCLUSION: In this study, we present four annotated genome assemblies generated using PacBio SMRT sequencing data from four environmental species: S. curviconia, S. phasma, S. protearum and S. variecibatus with the aim to provide a starting point for future comparative genome evolution studies addressing species diversification, ecological/host adaptation and origin of pathogenic lineages within the genus Sporothrix.

PMID:35831806 | DOI:10.1186/s12864-022-08736-w

BMC Plant Biol. 2022 Jul 13;22(1):337. doi: 10.1186/s12870-022-03712-8.

ABSTRACT

BACKGROUND: Grazing disturbance plays an important role in the desert steppe ecosystem in Inner Mongolia, China. Previous studies found that grazing affected the spatial distribution of species in a community, and showed patchiness characteristics of species under different grazing treatments. Artemisia frigida is the dominant species and semi-shrub in desert steppe, and whether grazing interference will affect the spatial distribution of A. frigida is studied. In this study, geo-statistical methods were mainly used to study the spatial distribution characteristics of A. frigida population in desert steppe of Inner Mongolia at two scales (quadrat size 2.5 m × 2.5 m, 5 m × 5 m) and four stocking rates (control, CK, 0 sheep·ha^-1·month^-1; light grazing, LG, 0.15 sheep·ha^-1·month^-1, moderate grazing, MG, 0.30 sheep·ha^-1·month^-1, heavy grazing, HG, 0.45 sheep·ha^-1·month^-1).

RESULTS: The results showed that the spatial distribution of A. frigida tended to be simplified with the increase of stocking rate, and tended to be banded with increased spatial scale. The density and height of A. frigida increased with increasing scale. With increased stocking rate, the density of A. frigida population decreased linearly, while its height decreased in a step-wise fashion. The spatial distribution of A. frigida was mainly affected by structural factors at different scales and stocking rate. The density of A. frigida was more sensitive to change in stocking rate, and the patchiness distribution of A. frigida was more obvious with increase in scale.

CONCLUSIONS: Stocking rate has a strong regulatory effect on the spatial pattern of A. frigida population in the desert steppe. Heavy grazing reduced the spatial heterogeneity of A. frigida in the desert steppe. The smaller dominant populations are unfavourable for its survival in heavy grazing condition, and affects the stability and productivity of the grassland ecosystem.

PMID:35831803 | DOI:10.1186/s12870-022-03712-8

BMC Psychiatry. 2022 Jul 13;22(1):465. doi: 10.1186/s12888-022-04090-z.

ABSTRACT

BACKGROUND: In low-income nations, suicidal conduct increases within the first year following delivery, ranging from 4 to 17.6%, with a three-fold cause of maternal death. Suicidal behavior was also reported to be 14% among postpartum women in Ethiopia.

OBJECTIVE: To assess the magnitude and associated factors of suicidal behavior among postpartum mothers attending public health centers in Addis Ababa, Ethiopia, 2021.

METHODS: A cross-sectional study was conducted in ten public health facilities of Addis Ababa, Ethiopia with a total sample size of 615 women. The data were entered into Epi data 4.6 and exported to SPSS version 25 for statistical analysis. A logistic regression model with adjusted odds ratio (AOR), 95% confidence interval (CI) and p-value of ≤0.05 was used to identify predictors of the outcome variable.

RESULTS: The magnitude of suicidal behavior among postnatal mothers attending public health centers in Addis Ababa was 41.46% with 95%CI (35.2-44.5%). Being mother’s literate (adjusted odds ratio (AOR) = 0.64, 95% CI: 0.42-0.97), verbal abuses (AOR = 2.18, 95% CI: 1.38-3.44), history of rape (AOR = 3.03, 95% CI 1.14 -8.05), history of depression (AOR = 4.12, 95% CI 1.21-14.03), women’s having sexually unfaithful husband (AOR = 1.42, 95% CI 1.14-6.23) and khat chewing (AOR = 8.48, 95% CI 2.52-28.50) were significantly associated with suicidal behavior.

CONCLUSION: The magnitude of suicidal behavior among postnatal mothers attending public health centers in Addis Ababa was 41.46% and it was found to be associated with being literate, rape, verbal abuse, having a history of depression, having a sexually unfaithful husband and chewing khat. As a result, women should be screened for suicidal behavior during antenatal and postnatal services for early detection and management.

PMID:35831799 | DOI:10.1186/s12888-022-04090-z

Pediatr Crit Care Med. 2022 Jul 14. doi: 10.1097/PCC.0000000000003028. Online ahead of print.

ABSTRACT

OBJECTIVES: Currently, there are no prediction tools available to identify patients at risk of needing high-complexity care following cardiac catheterization for congenital heart disease. We sought to develop a method to predict the likelihood a patient will require intensive care level resources following elective cardiac catheterization.

DESIGN: Prospective single-center study capturing important patient and procedural characteristics for predicting discharge to the ICU. Characteristics significant at the 0.10 level in the derivation dataset (July 1, 2017 to December 31, 2019) were considered for inclusion in the final multivariable logistic regression model. The model was validated in the testing dataset (January 1, 2020 to December 31, 2020). The novel pre-procedure cardiac status (PCS) feature, collection started in January 2019, was assessed separately in the final model using the 2019 through 2020 dataset.

SETTING: Tertiary pediatric heart center.

PATIENTS: All elective cases coming from home or non-ICU who underwent a cardiac catheterization from July 2017 to December 2020.

INTERVENTIONS: None.

MEASUREMENTS AND MAIN RESULTS: A total of 2,192 cases were recorded in the derivation dataset, of which 11% of patients (n = 245) were admitted to the ICU, while 64% (n = 1,413) were admitted to a medical unit and 24% (n = 534) were discharged home. In multivariable analysis, the following predictors were identified: 1) weight less than 5 kg and 5-9.9 kg, 2) presence of systemic illness, 3) recent cardiac intervention less than 90 days, and 4) ICU Admission Tool for Congenital Heart Catheterization case type risk categories (1-5), with C-statistics of 0.79 and 0.76 in the derivation and testing cohorts, respectively. The addition of the PCS feature fit into the final model resulted in a C-statistic of 0.79.

CONCLUSIONS: The creation of a validated pre-procedural risk prediction model for ICU admission following congenital cardiac catheterization using a large volume, single-center, academic institution will improve resource allocation and prediction of capacity needs for this complex patient population.

PMID:35830709 | DOI:10.1097/PCC.0000000000003028

Am J Public Health. 2022 Aug;112(8):1151-1160. doi: 10.2105/AJPH.2022.306805.

ABSTRACT

Life expectancy figures for countries and population segments are increasingly being reported to more decimal places and used as indicators of the strengths or failings of countries’ health and social systems. Reports seldom quantify their intrinsic statistical imprecision or the age-specific numbers of deaths that determine them. The SE formulas available to compute imprecision are all model based. This note adds a more intuitive data-based SE method and extends the jackknife to the analysis of event rates more generally. It also describes the relationships between the magnitude of the SE and the numbers of person-years and deaths on which it is based. These relationships can help quantify the statistical noise present in published year-to-year differences in life expectancies, as well as in same-year differences between or within countries. Agencies and investigators are encouraged to use one of these SEs to report the imprecision of life expectancy numbers and to tailor the number of decimal places accordingly. (Am J Public Health. 2022;112(8):1151-1160. https://doi.org/10.2105/AJPH.2022.306805).

PMID:35830672 | DOI:10.2105/AJPH.2022.306805