Category: Statistics

PLoS One. 2023 Dec 8;18(12):e0295549. doi: 10.1371/journal.pone.0295549. eCollection 2023.

ABSTRACT

BACKGROUND: Low hemoglobin (Hb) level is a leading cause of many adverse pregnancy outcomes. Patterns of changes in Hb levels during pregnancy are not well understood.

AIM: This study estimated Hb levels, described its changing patterns across gestational trimesters, and identified factors associated with these changes among pregnant women.

MATERIALS AND METHODS: Data from the ongoing maternal and child health cohort study-The Mutaba’ah Study, was used (N = 1,120). KML machine learning algorithm was applied to identify three distinct cluster trajectories of Hb levels between the first and the third trimesters. Descriptive statistics were used to profile the study participants. Multinomial multivariable logistic regression was employed to identify factors associated with change patterns in Hb levels.

RESULTS: The three identified clusters-A, B and C-had, respectively, median Hb levels (g/L) of 123, 118, and 104 in the first trimester and 119, 100, and 108 in the third trimester. Cluster ‘A’ maintained average normal Hb levels in both trimesters. Cluster ‘B’, on average, experienced a decrease in Hb levels below the normal range during the third trimester. Cluster ‘C’ showed increased Hb levels in the third trimester but remained, on average, below the normal range in both trimesters. Pregnant women with higher gravida, diabetes mellitus (type 1 or 2), nulliparity or lower level of education were more likely to be in cluster ‘B’ than the normal cluster ‘A’. Pregnant women who reported using iron supplements before pregnancy or those with low levels of education. were more likely to be in cluster ‘C’ than the normal cluster ‘A’.

CONCLUSION: The majority of pregnant women experienced low Hb levels during pregnancy. Changes in Hb levels during pregnancy were associated with parity, gravida, use of iron before pregnancy, and the presence of diabetes mellitus (type 1 or 2).

PMID:38064469 | DOI:10.1371/journal.pone.0295549

PLoS One. 2023 Dec 8;18(12):e0294326. doi: 10.1371/journal.pone.0294326. eCollection 2023.

ABSTRACT

BACKGROUND: Consideration for patients with visual impairment, from low vision to blindness, is an important part of building a barrier-free society. Some authors have elaborated that visual impairment can indeed lead to delayed development in theory of mind, thereby causing pragmatic knowledge deficiency. Verifying whether those with eye conditions have pragmatic impairment is an essential way for their clinical evaluation, intervention and rehabilitation.

OBJECTIVE: We primarily carry out a meta-analysis of visual impairment from low vision to blindness and pragmatic impairment in people with low vision or blindness to verify visual impairment may cause pragmatic impairment.

DATA SOURCES: Electronic databases Pubmed, Medline, MesH, Psychinfo, Ovid, EBSCO and CNKI and the reference sections of previous reviews.

STUDY ELIGIBILITY CRITERIA: Studies were included when they built on primary data from clinical questionnaire surveys or field trials anywhere in the world, and when they reported impacts of visual impairment on social cognition, communication, skills, behavior and intelligence. In total, 25 original studies were included, in which 25735 people were evaluated.

RESULTS: Statistically, visual impairments and pragmatic impairment exist correlation due to the significant p value(p = 0.0005 < 0.05) in group and the subgroup sorted in the light of 18 years old (p < 0.0001 and p = 0.003 < 0.05). Psychologically, because people with visual impairment can not normally get non-verbal information, they can not get a complete pragmatic knowledge system. Pragmatic knowledge deficiency leads to abnormal in executive functions and development delay from the perspective of theory of mind, inducing pragmatic impairment. Therefore, visual impairment has an impact on pragmatic impairment.

CONCLUSION: The meta-analysis reveals robust evidence on the relationship of vision impairment and pragmatic impairment in children or adults. Such evidence may help to gradually improve the clinical evaluation, intervention and rehabilitation of these people.

PMID:38064440 | DOI:10.1371/journal.pone.0294326

West Afr J Med. 2023 Dec 4;40(12 Suppl 1):S25-S26.

ABSTRACT

BACKGROUND AND AIM: Workplace humanization, when effectively managed can be instrumental in steering an organization towards efficient, and effective work processes. It is on this backdrop that this study aimed at determining the inter-relationship between employee productivity, dignity and empathy.

MATERIALS AND METHODS: This was a cross-sectional study that identified the relationship between the study variables. It was conducted among 233 randomly selected employees of private hospitals in Port Harcourt, Rivers State, Nigeria. A self-administered structured questionnaire was used to assess the study variables. Data analysis was conducted using the Statistical Package for Social Sciences (SPSS) software and the relationship between variables tested using the Spearman correlation test. Statistical significance was set at 0.05.

RESULTS: The indicators of employee dignity, empathy and productivity were found to have high mean values which were above the threshold of 2.0. A strong positive significant correlation was found to exist between dignity and task accomplishment (r2: 0.796, p-value: <0.001) as well as empathy and task accomplishment (r2: 0.843, p-value: <0.001). Also, a moderate positive statistically significant correlation was found to exist between dignity and service quality (r2=0.373, p-value: <0.001) as well as between employee empathy and service quality (r2= 0.402, p-value: <0.001).

CONCLUSION AND RECOMMENDATIONS: The dignity of an employee alongside empathy as measures of work humanization are significant correlates of employee productivity which can be exploited for organizational growth. It is recommended that organizations through institutionalized policies can successfully manage their workplace for optimal productivity via improved employee dignity and empathy as a means of increasing job satisfaction and reduce brain drain.

PMID:38064409

J Infect Dev Ctries. 2023 Nov 30;17(11):1598-1605. doi: 10.3855/jidc.17961.

ABSTRACT

INTRODUCTION: Canine monocytic ehrlichiosis (CME) is a disease caused by the Gram-negative bacteria Ehrlichia canis, a bacterium that affects domestic dogs but can also infect humans. The diagnosis implies a challenge due to its diversity in clinical manifestations.

METHODOLOGY: The frequency of E. canis infection, risk factors, and clinical-pathological parameters associated with seropositivity were calculated with the PROC FREQ TABLES and PROC LOGISTIC procedures of the SAS statistical software.

RESULTS: The study showed a seroprevalence of 26.62% (156/586). Association between seropositivity and risk factors was found. The age and the presence of ticks including clinical signs such as anorexia, seizures, cough, petechiae, epistaxis, and hematochezia, as well as multiple blood and biochemical alterations were analyzed. The logistic regression analysis showed a high predictive power (c = 0.98) for CME for thrombocytopenia, leukopenia, and anemia.

CONCLUSIONS: The high prevalence of E. canis in endemic areas makes its diagnosis difficult. Thus, clinical signs must be considered, along with blood and biochemical alterations, as a possible predictor of the disease.

PMID:38064403 | DOI:10.3855/jidc.17961

IEEE J Biomed Health Inform. 2023 Dec 8;PP. doi: 10.1109/JBHI.2023.3340686. Online ahead of print.

ABSTRACT

The presence of tertiary lymphoid structures (TLSs) on pancreatic pathological images is an important prognostic indicator of pancreatic tumors. Therefore, TLSs detection on pancreatic pathological images plays a crucial role in diagnosis and treatment for patients with pancreatic tumors. However, fully supervised detection algorithms based on deep learning usually require a large number of manual annotations, which is time-consuming and labor-intensive. In this paper, we aim to detect the TLSs in a manner of few-shot learning by proposing a weakly supervised segmentation network. We firstly obtain the lymphocyte density maps by combining a pretrained model for nuclei segmentation and a domain adversarial network for lymphocyte nuclei recognition. Then, we establish a cross-scale attention guidance mechanism by jointly learning the coarse-scale features from the original histopathology images and fine-scale features from our designed lymphocyte density attention. A noise-sensitive constraint is introduced by an embedding signed distance function loss in the training procedure to reduce tiny prediction errors. Experimental results on two collected datasets demonstrate that our proposed method significantly outperforms the state-of-the-art segmentation-based algorithms in terms of TLSs detection accuracy. Additionally, we apply our method to study the congruent relationship between the density of TLSs and peripancreatic vascular invasion and obtain some clinically statistical results.

PMID:38064334 | DOI:10.1109/JBHI.2023.3340686

West Afr J Med. 2023 Dec 4;40(12 Suppl 1):S18-S19.

ABSTRACT

INTRODUCTION: Family planning refers to a couple’s ability to have the number of children they want by spacing out their children appropriately or a person’s ability to avoid unintended pregnancies by using various contraceptive methods and infertility treatment. All hospitals in Rivers State, Nigeria, that provide primary care, offer family planning services.

AIM: To describe the pattern of family planning service uptake in the hospitals in Rivers State.

METHODOLOGY: An 8-year retrospective review of data collection from the District Health Information System 2 (DHIS 2) platform in the Health Management Information System in Rivers State was conducted. Data from 387 health facilities were collated and keyed into the DHIS2 platform. Data was analysed using SPSS version 21 and represented as frequencies, percentages and charts.

RESULTS: During the period under review, the Family Planning clinics counselled a total of 931,774 individuals, of whom 421,785 (45.3%) accepted family planning services. Condoms (65.3%) were the most widely utilized contraceptive, whereas bilateral tubal ligation (0.1%) was the least utilized. Other methods were injectable, implant, oral contraceptive pills and intrauterine contraceptive devices accounting for 16.1%, 9.4%, 7.8%, and 1.3%, respectively. A significant increase was observed in the trend of use of condoms, injectables and oral contraceptive pills between 2016-2021.

CONCLUSION: The findings were that there was an increasing trend in the yearly utilization of family planning services among women of childbearing age in the State from 2014 – 2021. Condom being the most utilized indicates that it is the most accepted and approved by clients in family planning clinics in Rivers State. The knowledge of contraceptive utilization trends can be used to monitor and appraise the acceptance and approval of each method and family planning program over a period.

PMID:38064271

JMIR Form Res. 2023 Dec 8;7:e48402. doi: 10.2196/48402.

ABSTRACT

BACKGROUND: Middle childhood (ages 8-12 years) is a critical period for forming behavioral habits and reducing the risk for the development of skin cancer later in life. During this time, children develop more autonomy and spend more unsupervised time away from their parents. Professional agencies recommend that all children engage in regular sun protection behaviors and avoid the sun during peak daytime hours. Unfortunately, in middle childhood, child sun protection often declines and UV radiation exposure increases. Effective parenting involves balancing ways to encourage the child’s increasing independence while providing practical assistance to ensure sun protection is implemented.

OBJECTIVE: The goal was to evaluate the feasibility, acceptability, and preliminary effects of Sun Safe Families, a Facebook group intervention for parents of children between 8 and 12 years of age.

METHODS: The team developed Facebook messages targeting parent knowledge, normative influences, sun safety barriers, planning and goal setting, confidence in implementing sun safety, communication, forming habits, and managing sun safety in risky situations. A total of 92 parents were enrolled, and the groups ran for 6 weeks. Feasibility was measured by enrollment and retention rates. Acceptability was measured by engagement in the Facebook groups. Satisfaction was assessed by a treatment evaluation. At pre- and post-intervention, parents completed measures of child sun protection, UV radiation exposure, sunburn, sun safety knowledge, child risk, barriers, sun protection self-efficacy, planning, sun safe habits, norms for child sun safety, and communication about sun safety.

RESULTS: Enrollment (64.3%, 92/143) and retention (94.6%, 87/92) were good. On average, participants viewed 67.6% (56.8/84) of posts, “liked” 16.4% (13.77/84) of posts, commented on 14.8% (12.43/84) of posts, and voted on 46% (6.4/14) of polls. Satisfaction was excellent. From pre- to post-intervention, there were significant increases in child sun protection, sun exposure, and sunburn (P<.01; moderate effect sizes), as well as statistically significant increases in planning and self-efficacy (P<.05) and family norms and parent communication (P<.01).

CONCLUSIONS: This study demonstrated high survey retention, acceptability, and satisfaction with the intervention. There were promising preliminary effects on child sun protection behaviors and parent sun protection attitudes and communication with their child. Replication with a larger sample size and a comparison condition is warranted.

PMID:38064250 | DOI:10.2196/48402

Qual Health Res. 2023 Dec 8:10497323231217392. doi: 10.1177/10497323231217392. Online ahead of print.

ABSTRACT

The artificial intelligence (AI) revolution is here and gathering momentum, thanks to new models of natural language processing (NLP) and rapidly increasing adoption by the public. NLP technology uses statistical analysis of language structures to analyse and generate human language, using text or speech as its source material. It can also be applied to visual mediums like images and videos. A few qualitative research early adopters are beginning to adopt this technology into their work, but our understanding of its potential remains in its infancy. This article will define and describe NLP-based AI and discuss its benefits and limitations for reflexive thematic analysis in health research. While there are many platforms available, ChatGPT is the most well-known and accessible. A worked example using ChatGPT to augment reflexive thematic analysis is provided to illustrate potential application in practice. This article is intended to inspire further conversation around the role of AI in qualitative research and offer practical guidance for researchers seeking to adopt this technology.

PMID:38064244 | DOI:10.1177/10497323231217392

J Asthma. 2023 Dec 8:1-9. doi: 10.1080/02770903.2023.2293057. Online ahead of print.

ABSTRACT

OBJECTIVE: The combination of allergen immunotherapy (AIT) and omalizumab is used to treat patients at risk of anaphylaxis. There is currently a very little evidence that this combination increases the effectiveness of AIT in patients with inhalant allergies. The study aimed to evaluate the effectiveness of HDM-SCIT therapy (injection immunotherapy for house dust mites) in combination with omalizumab in treating HDM-induced asthma.

METHODS: This study was a placebo-controlled, randomized, multicenter trial including 82 patients with HDM-driven mild to moderate asthma. Omalizumab alone (A), HDM SCIT + omalizumab (B), SCIT alone (C), or placebo (D) for 24 months were applied. All patients received asthma treatment in accordance with GINA recommendations. The treatment efficacy was defined by a reduction in the daily dose of inhaled steroids (ICS) and a reduction in the number of asthma exacerbations (AX).

RESULTS: After 24 months of therapy, a statistically significant reduction in the daily doses of ICS in groups A and B was observed (p = 0.021 and p = 0.008). Daily ICS reduction was considerably more significant in group B (p = 0.01). During 24 months of observation, the AX was significantly reduced in all study groups, with the greatest significant difference observed between groups A and B and groups C and D (placebo) as follows: 0.42 patient/per year vs. 0.39 vs. 0.84 vs. 0.91 (p = 0.023).

CONCLUSION: The combination of HDM SCIT and omalizumab is significantly and progressively reducing ICS use and AX in a 24-month study. The combination is significantly more effective than the single treatments or placebo.

PMID:38064236 | DOI:10.1080/02770903.2023.2293057

J Vis. 2023 Dec 4;23(14):3. doi: 10.1167/jov.23.14.3.

ABSTRACT

Material depictions in artwork are useful tools for revealing image features that support material categorization. For example, artistic recipes for drawing specific materials make explicit the critical information leading to recognizable material properties (Di Cicco, Wjintjes, & Pont, 2020) and investigating the recognizability of material renderings as a function of their visual features supports conclusions about the vocabulary of material perception. Here, we examined how the recognition of materials from photographs and drawings was affected by the application of the Portilla-Simoncelli texture synthesis model. This manipulation allowed us to examine how categorization may be affected differently across materials and image formats when only summary statistic information about appearance was retained. Further, we compared human performance to the categorization accuracy obtained from a pretrained deep convolutional neural network to determine if observers’ performance was reflected in the network. Although we found some similarities between human and network performance for photographic images, the results obtained from drawings differed substantially. Our results demonstrate that texture statistics play a variable role in material categorization across rendering formats and material categories and that the human perception of material drawings is not effectively captured by deep convolutional neural networks trained for object recognition.

PMID:38064227 | DOI:10.1167/jov.23.14.3