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Brain and Behavior Dec 2023Dysregulated appetite control is characteristic of anorexia nervosa (AN), bulimia nervosa (BN), and obesity (OB). Studies using a broad range of methods suggest the... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
Dysregulated appetite control is characteristic of anorexia nervosa (AN), bulimia nervosa (BN), and obesity (OB). Studies using a broad range of methods suggest the cerebellum plays an important role in aspects of weight and appetite control, and is implicated in both AN and OB by reports of aberrant gray matter volume (GMV) compared to nonclinical populations. As functions of the cerebellum are anatomically segregated, specific localization of aberrant anatomy may indicate the mechanisms of its relationship with weight and appetite in different states. We sought to determine if there were consistencies in regions of cerebellar GMV changes in AN/BN and OB, as well as across normative (NOR) variation.
METHOD
Systematic review and meta-analysis using GingerALE.
RESULTS
Twenty-six publications were identified as either case-control studies (n = 277; n = 510) or regressed weight from NOR data against brain volume (total n = 3830). AN/BN and OB analyses both showed consistently decreased GMV within Crus I and Lobule VI, but volume reduction was bilateral for AN/BN and unilateral for OB. Analysis of the NOR data set identified a cluster in right posterior lobe that overlapped with AN/BN cerebellar reduction. Sensitivity analyses indicated robust repeatability for NOR and AN/BN cohorts, but found OB-specific heterogeneity.
DISCUSSION
Findings suggest that more than one area of the cerebellum is involved in control of eating behavior and may be differentially affected in normal variation and pathological conditions. Specifically, we hypothesize an association with sensorimotor and emotional learning via Lobule VI in AN/BN, and executive function via Crus I in OB.
Topics: Humans; Appetite; Anorexia Nervosa; Bulimia Nervosa; Gray Matter; Cerebellum; Obesity
PubMed: 37830247
DOI: 10.1002/brb3.3286 -
BMJ Open Oct 2023To identify, synthesise and appraise evidence relating to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and pregnancy.
Identifying, synthesising and appraising existing evidence relating to myalgic encephalomyelitis/chronic fatigue syndrome and pregnancy: a mixed-methods systematic review.
OBJECTIVES
To identify, synthesise and appraise evidence relating to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and pregnancy.
DESIGN
Mixed-methods systematic review, using convergent segregated design.
DATA SOURCES
MEDLINE, EMBASE, Scopus, PsycINFO, CINAHL, MedRxiv, PROSPERO and grey literature sources through 6 August 2023.
ELIGIBILITY CRITERIA
We included original research studies, expert opinion and grey literature reporting on ME/CFS and pregnancy/post partum (up to 2 years), risk of pregnancy outcomes with ME/CFS or experiences during pregnancy for mother, partner or health and social care professionals following ME/CFS during pregnancy, all where the evidence was relevant to a confirmed ME/CFS diagnosis prior to pregnancy.
DATA EXTRACTION AND SYNTHESIS
Three independent reviewers completed all screening, data extraction and quality assessment. Risk of bias was assessed using the mixed-methods appraisal tool V.2018. Qualitative and quantitative literature was analysed separately using thematic and descriptive syntheses. Findings were integrated through configuration.
RESULTS
Searches identified 3675 articles, 16 met the inclusion criteria: 4 quantitative (1 grey), 11 qualitative (9 grey) and 1 grey mixed-methods study. Of the four quantitative studies that reported on ME/CFS severity during pregnancy, two suggested pregnancy negatively impacted on ME/CFS, one found most women had no change in ME/CFS symptoms and one found ME/CFS improved; this difference in symptom severity across studies was supported by the qualitative evidence. The qualitative literature also highlighted the importance of individualised care throughout pregnancy and birth, and the need for additional support during family planning, pregnancy and with childcare. Only one quantitative study reported on pregnancy outcomes, finding decreased vaginal births and higher rates of spontaneous abortions and developmental and learning delays associated with pregnancies in those with ME/CFS.
CONCLUSIONS
Current evidence on ME/CFS in pregnancy is limited and findings inconclusive. More high-quality research is urgently needed to support the development of evidence-based guidelines on ME/CFS and pregnancy.
Topics: Humans; Female; Pregnancy; Fatigue Syndrome, Chronic; Mothers
PubMed: 37798026
DOI: 10.1136/bmjopen-2022-070366 -
Frontiers in Public Health 2023Given the increased availability of data sources such as hospital information systems, electronic health records, and health-related registries, a novel approach is...
BACKGROUND
Given the increased availability of data sources such as hospital information systems, electronic health records, and health-related registries, a novel approach is required to develop artificial intelligence-based decision support that can assist clinicians in their diagnostic decision-making and shorten rare disease patients' diagnostic odyssey. The aim is to identify key challenges in the process of mapping European rare disease databases, relevant to ML-based screening technologies in terms of organizational, FAIR and legal principles.
METHODS
A scoping review was conducted based on the PRISMA-ScR checklist. The primary article search was conducted in three electronic databases (MEDLINE/Pubmed, Scopus, and Web of Science) and a secondary search was performed in Google scholar and on the organizations' websites. Each step of this review was carried out independently by two researchers. A charting form for relevant study analysis was developed and used to categorize data and identify data items in three domains - organizational, FAIR and legal.
RESULTS
At the end of the screening process, 73 studies were eligible for review based on inclusion and exclusion criteria with more than 60% ( = 46) of the research published in the last 5 years and originated only from EU/EEA countries. Over the ten-year period (2013-2022), there is a clear cycling trend in the publications, with a peak of challenges reporting every four years. Within this trend, the following dynamic was identified: except for 2016, organizational challenges dominated the articles published up to 2018; legal challenges were the most frequently discussed topic from 2018 to 2022. The following distribution of the data items by domains was observed - (1) organizational ( = 36): data accessibility and sharing (20.2%); long-term sustainability (18.2%); governance, planning and design (17.2%); lack of harmonization and standardization (17.2%); quality of data collection (16.2%); and privacy risks and small sample size (11.1%); (2) FAIR ( = 15): findable (17.9%); accessible sustainability (25.0%); interoperable (39.3%); and reusable (17.9%); and (3) legal ( = 33): data protection by all means (34.4%); data management and ownership (22.9%); research under GDPR and member state law (20.8%); trust and transparency (13.5%); and digitalization of health (8.3%). We observed a specific pattern repeated in all domains during the process of data charting and data item identification - in addition to the outlined challenges, good practices, guidelines, and recommendations were also discussed. The proportion of publications addressing only good practices, guidelines, and recommendations for overcoming challenges when mapping RD databases in at least one domain was calculated to be 47.9% ( = 35).
CONCLUSION
Despite the opportunities provided by innovation - automation, electronic health records, hospital-based information systems, biobanks, rare disease registries and European Reference Networks - the results of the current scoping review demonstrate a diversity of the challenges that must still be addressed, with immediate actions on ensuring better governance of rare disease registries, implementing FAIR principles, and enhancing the EU legal framework.
Topics: Humans; Data Management; Rare Diseases; Artificial Intelligence; Registries; Privacy
PubMed: 37780450
DOI: 10.3389/fpubh.2023.1214766 -
NPJ Digital Medicine Sep 2023Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images... (Review)
Review
Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images via neural networks to make predictions. A focus of deep learning research is skin lesion triage to detect cancer, but this may not translate to the wider scope of >2000 other skin diseases. We searched for studies applying deep learning to skin images, excluding benign/malignant lesions (1/1/2000-23/6/2022, PROSPERO CRD42022309935). The primary outcome was accuracy of deep learning algorithms in disease diagnosis or severity assessment. We modified QUADAS-2 for quality assessment. Of 13,857 references identified, 64 were included. The most studied diseases were acne, psoriasis, eczema, rosacea, vitiligo, urticaria. Deep learning algorithms had high specificity and variable sensitivity in diagnosing these conditions. Accuracy of algorithms in diagnosing acne (median 94%, IQR 86-98; n = 11), rosacea (94%, 90-97; n = 4), eczema (93%, 90-99; n = 9) and psoriasis (89%, 78-92; n = 8) was high. Accuracy for grading severity was highest for psoriasis (range 93-100%, n = 2), eczema (88%, n = 1), and acne (67-86%, n = 4). However, 59 (92%) studies had high risk-of-bias judgements and 62 (97%) had high-level applicability concerns. Only 12 (19%) reported participant ethnicity/skin type. Twenty-four (37.5%) evaluated the algorithm in an independent dataset, clinical setting or prospectively. These data indicate potential of deep learning image analysis in diagnosing and monitoring common skin diseases. Current research has important methodological/reporting limitations. Real-world, prospectively-acquired image datasets with external validation/testing will advance deep learning beyond the current experimental phase towards clinically-useful tools to mitigate rising health and cost impacts of skin disease.
PubMed: 37758829
DOI: 10.1038/s41746-023-00914-8 -
Environment International Oct 2023The World Health Organization is coordinating an international project aimed at systematically reviewing the evidence regarding the association between radiofrequency... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The World Health Organization is coordinating an international project aimed at systematically reviewing the evidence regarding the association between radiofrequency electromagnetic field (RF-EMF) exposure and adverse health effects. Within the project, 6 topics have been prioritized by an expert group, which include reproductive health outcomes.
OBJECTIVES
According to the protocol published in 2021, a systematic review and meta-analyses on the adverse effects of RF-EMF exposure during pregnancy in offspring of experimental animals were conducted.
METHODS
Three electronic databases (PubMed, Scopus and EMF Portal) were last searched on September 8 or 17, 2022. Based on predefined selection criteria, the obtained references were screened by two independent reviewers. Studies were included if they met the following criteria: 1) original, sham controlled experimental study on non-human mammals exposed in utero, published in peer-reviewed journals, 2) the experimental RF-EMF exposure was within the frequency range 100 kHz-300 GHz, 3) the effects of RF-EMF exposure on fecundity (litter size, embryonic/fetal losses), on the offspring health at birth (decrease of weight or length, congenital malformations, changes of sex ratio) or on delayed effects (neurocognitive alterations, female infertility or early-onset cancer) were studied. Study characteristics and outcome data were extracted by two reviewers. Risk of bias (RoB) was assessed using the Office of Health Assessment and Translation (OHAT) guidelines. Study results were pooled in a random effects meta-analysis comparing average exposure to no-exposure and in a dose-response meta-analysis using all exposure doses, after exclusion of studies that were rated at "high concern" for RoB. Subgroup analyses were conducted for species, Specific Absorption Rate (SAR) and temperature increase. The certainty of the evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.
RESULTS
Eighty-eight papers could be included in this review. Effects on fecundity. The meta-analysis of studies on litter size, conducted at a whole-body average SAR of 4.92 W/kg, did not show an effect of RF-EMF exposure (MD 0.05; 95% CI -0.21 to 0.30). The meta-analysis of studies on resorbed and dead fetuses, conducted at a whole-body average SAR of 20.26 W/kg, showed a significant increase of the incidence in RF-EMF exposed animals (OR 1.84; 95% CI 1.27 to 2.66). The results were similar in the dose-response analysis. Effects on the offspring health at birth. The meta-analysis of studies on fetal weight, conducted at a whole-body average SAR of 9.83 W/kg, showed a small decrease in RF-EMF exposed animals (SMD 0.31; 95% CI 0.15 to 0.48). The meta-analysis of studies on fetal length, conducted at a whole-body average SAR of 4.55 W/kg, showed a moderate decrease in length at birth (SMD 0.45; 95% CI 0.07 to 0.83). The meta-analysis of studies on the percentage of fetuses with malformations, conducted at a whole-body average SAR of 6.75 W/kg, showed a moderate increase in RF-EMF exposed animals (SMD -0.45; 95% CI -0.68 to -0.23). The meta-analysis of studies on the incidence of litters with malformed fetuses, conducted at a whole-body average SAR of 16.63 W/kg, showed a statistically significant detrimental RF-EMF effect (OR 3.22; 95% CI 1.9 to 5.46). The results were similar in the dose-response analyses. Delayed effects on the offspring health. RF-EMF exposure was not associated with detrimental effects on brain weight (SMD 0.10; 95% CI -0.09 to 0.29) and on learning and memory functions (SMD -0.54; 95% CI -1.24 to 0.17). RF-EMF exposure was associated with a large detrimental effect on motor activity functions (SMD 0.79; 95% CI 0.21 to 1.38) and a moderate detrimental effect on motor and sensory functions (SMD -0.66; 95% CI -1.18 to -0.14). RF-EMF exposure was not associated with a decrease of the size of litters conceived by F2 female offspring (SMD 0.08; 95% CI -0.39 to 0.55). Notably, meta-analyses of neurobehavioural effects were based on few studies, which suffered of lack of independent replication deriving from only few laboratories.
DISCUSSION
There was high certainty in the evidence for a lack of association of RF-EMF exposure with litter size. We attributed a moderate certainty to the evidence of a small detrimental effect on fetal weight. We also attributed a moderate certainty to the evidence of a lack of delayed effects on the offspring brain weight. For most of the other endpoints assessed by the meta-analyses, detrimental RF-EMF effects were shown, however the evidence was attributed a low or very low certainty. The body of evidence had limitations that did not allow an assessment of whether RF-EMF may affect pregnancy outcomes at exposure levels below those eliciting a well-known adverse heating impact. In conclusion, in utero RF-EMF exposure does not have a detrimental effect on fecundity and likely affects offspring health at birth, based on the meta-analysis of studies in experimental mammals on litter size and fetal weight, respectively. Regarding possible delayed effects of in utero exposure, RF-EMF probably does not affect offspring brain weight and may not decrease female offspring fertility; on the other hand, RF-EMF may have a detrimental impact on neurobehavioural functions, varying in magnitude for different endpoints, but these last findings are very uncertain. Further research is needed on the effects at birth and delayed effects with sample sizes adequate for detecting a small effect. Future studies should use standardized endpoints for testing prenatal developmental toxicity and developmental neurotoxicity (OECD TG 414 and 426), improve the description of the exposure system design and exposure conditions, conduct appropriate dosimetry characterization, blind endpoint analysis and include several exposure levels to better enable the assessment of a dose-response relationship.
PROTOCOL REGISTRATION AND PUBLICATION
The protocol was published in Pacchierotti et al., 2021 and registered in PROSPERO CRD42021227746 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=227746).
Topics: Pregnancy; Animals; Female; Electromagnetic Fields; Fetal Weight; Reproduction; Fertility; Mammals
PubMed: 37729852
DOI: 10.1016/j.envint.2023.108178 -
PloS One 2023With the advances in technology and data science, machine learning (ML) is being rapidly adopted by the health care sector. However, there is a lack of literature...
A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data.
With the advances in technology and data science, machine learning (ML) is being rapidly adopted by the health care sector. However, there is a lack of literature addressing the health conditions targeted by the ML prediction models within primary health care (PHC) to date. To fill this gap in knowledge, we conducted a systematic review following the PRISMA guidelines to identify health conditions targeted by ML in PHC. We searched the Cochrane Library, Web of Science, PubMed, Elsevier, BioRxiv, Association of Computing Machinery (ACM), and IEEE Xplore databases for studies published from January 1990 to January 2022. We included primary studies addressing ML diagnostic or prognostic predictive models that were supplied completely or partially by real-world PHC data. Studies selection, data extraction, and risk of bias assessment using the prediction model study risk of bias assessment tool were performed by two investigators. Health conditions were categorized according to international classification of diseases (ICD-10). Extracted data were analyzed quantitatively. We identified 106 studies investigating 42 health conditions. These studies included 207 ML prediction models supplied by the PHC data of 24.2 million participants from 19 countries. We found that 92.4% of the studies were retrospective and 77.3% of the studies reported diagnostic predictive ML models. A majority (76.4%) of all the studies were for models' development without conducting external validation. Risk of bias assessment revealed that 90.8% of the studies were of high or unclear risk of bias. The most frequently reported health conditions were diabetes mellitus (19.8%) and Alzheimer's disease (11.3%). Our study provides a summary on the presently available ML prediction models within PHC. We draw the attention of digital health policy makers, ML models developer, and health care professionals for more future interdisciplinary research collaboration in this regard.
Topics: Humans; Prognosis; Retrospective Studies; Administrative Personnel; Machine Learning; Primary Health Care
PubMed: 37682909
DOI: 10.1371/journal.pone.0274276 -
BMC Public Health Aug 2023Despite being easily corrected with eyeglasses, over two-thirds of the world's child population presents with vision impairment (VI) due to uncorrected refractive...
BACKGROUND
Despite being easily corrected with eyeglasses, over two-thirds of the world's child population presents with vision impairment (VI) due to uncorrected refractive errors. While systematic reviews have shown that VI can significantly impact children's depression and anxiety, none have reviewed the existing literature on the association between spectacle correction and well-being. This review aims to address this knowledge gap.
MAIN OUTCOME MEASURES
The main outcome measures were i) cognitive and education well-being which included mathematics and english literacy, reading fluency, school function, academic performance and grades; ii) psychological and mental health well-being which included physical anxiety, learning anxiety and mental health test scores and iii) quality of life.
METHODS
We searched eight databases for articles published between 1999 to 2021 that assessed the associations between spectacle correction and children's (0 to 18 years) well-being. There were no restrictions on language or geographic location. Two reviewers independently screened all publications using validated quality checklists. The findings of the review were analysed using narrative synthesis. [PROSPERO CRD42020196847].
RESULTS
Of 692 records found in the databases, six randomised control trials, one cohort, one cross-sectional and one qualitative study (N = 9, 1.3%) were eligible for analysis. Data were collected from 25 522 children, 20 parents and 25 teachers across the nine studies. Seven were rated as good quality (67 to 100% of quality criteria fulfilled), and two were satisfactory (33 to 66% of quality criteria fulfilled). Spectacle correction was found to improve children's educational well-being (n = 4 very strong evidence; n = 2 strong evidence), quality of life (n = 1, very strong evidence) and decrease anxiety and increase mental health scores (n = 1, strong evidence).
CONCLUSION
Evidence suggests that spectacle correction improves children's cognitive and educational well-being, psychological well-being, mental health, and quality of life. More research is needed, given the paucity of published literature and the focus on only three aspects of well-being.
Topics: Humans; Child; Quality of Life; Cross-Sectional Studies; Eyeglasses; Educational Status; Anxiety
PubMed: 37596579
DOI: 10.1186/s12889-023-16484-z -
Research in Social & Administrative... Nov 2023The field of pharmacogenomics is rapidly advancing, but its adoption and implementation remain slow and lacking. Lack of pharmacogenomics knowledge among healthcare... (Review)
Review
BACKGROUND
The field of pharmacogenomics is rapidly advancing, but its adoption and implementation remain slow and lacking. Lack of pharmacogenomics knowledge among healthcare professionals is the most frequently cited barrier to adopting and implementing pharmacogenomics in clinical settings.
OBJECTIVES
This study aimed to critically evaluate and determine the effectiveness of educational interventions in improving pharmacogenomics knowledge and practice.
METHODS
Four electronic databases were searched: MEDLINE, EMBASE, CENTRAL, and PsycINFO. Studies on pharmacogenomics educational interventions for health care professionals and students with pre- and post-intervention assessments and results were included. No restrictions were placed on time, language, or educational contexts. The educational outcomes measured include both objective and subjective outcomes. The pharmacogenomics competency domains used to judge educational interventions are based on the competency domains listed by the American Association of Colleges of Pharmacies (AACP). The National Heart, Lung, and Blood Institute of the National Institutes of Health was used for the quality assessment of pre-post studies with no control group and the controlled intervention studies. No meta-analysis was conducted; the data were synthesized qualitatively. The systematic review was reported in accordance with the PRISMA statement.
RESULTS
Fifty studies were included in this review. All included studies integrated the AACP pharmacogenomics competency domains into their educational interventions. Most of the studies had educational interventions that integrated clinical cases (n = 44; 88%). Knowledge was the most frequently evaluated outcome (n = 34; 68%) and demonstrated significant improvement after the educational intervention that integrated AACP pharmacogenomics competency domains and employed active learning with clinical case inclusion.
CONCLUSION
This review provided evidence of the effectiveness of educational interventions in improving pharmacogenomics knowledge and practice. Incorporating pharmacogenomics competency domains into education and training, with patient cases for healthcare professionals and students, dramatically improved their pharmacogenomics knowledge, attitudes, and confidence in practice.
Topics: Humans; Pharmacogenetics; Students; Health Personnel; Educational Status; Delivery of Health Care
PubMed: 37586945
DOI: 10.1016/j.sapharm.2023.07.012 -
PloS One 2023Whether food source or energy mediates the effect of fructose-containing sugars on blood pressure (BP) is unclear. We conducted a systematic review and meta-analysis of... (Meta-Analysis)
Meta-Analysis
Whether food source or energy mediates the effect of fructose-containing sugars on blood pressure (BP) is unclear. We conducted a systematic review and meta-analysis of the effect of different food sources of fructose-containing sugars at different levels of energy control on BP. We searched MEDLINE, Embase and the Cochrane Library through June 2021 for controlled trials ≥7-days. We prespecified 4 trial designs: substitution (energy matched substitution of sugars); addition (excess energy from sugars added); subtraction (excess energy from sugars subtracted); and ad libitum (energy from sugars freely replaced). Outcomes were systolic and diastolic BP. Independent reviewers extracted data. GRADE assessed the certainty of evidence. We included 93 reports (147 trial comparisons, N = 5,213) assessing 12 different food sources across 4 energy control levels in adults with and without hypertension or at risk for hypertension. Total fructose-containing sugars had no effect in substitution, subtraction, or ad libitum trials but decreased systolic and diastolic BP in addition trials (P<0.05). There was evidence of interaction/influence by food source: fruit and 100% fruit juice decreased and mixed sources (with sugar-sweetened beverages [SSBs]) increased BP in addition trials and the removal of SSBs (linear dose response gradient) and mixed sources (with SSBs) decreased BP in subtraction trials. The certainty of evidence was generally moderate. Food source and energy control appear to mediate the effect of fructose-containing sugars on BP. The evidence provides a good indication that fruit and 100% fruit juice at low doses (up to or less than the public health threshold of ~10% E) lead to small, but important reductions in BP, while the addition of excess energy of mixed sources (with SSBs) at high doses (up to 23%) leads to moderate increases and their removal or the removal of SSBs alone (up to ~20% E) leads to small, but important decreases in BP in adults with and without hypertension or at risk for hypertension. Trial registration: Clinicaltrials.gov: NCT02716870.
Topics: Adult; Humans; Fructose; Blood Pressure; Fruit; Sugars; Hypertension
PubMed: 37582096
DOI: 10.1371/journal.pone.0264802 -
Malaria Journal Aug 2023Malaria affects 24 million children globally, resulting in nearly 500,000 child deaths annually in low- and middle-income countries (LMICs). Recent studies have provided... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Malaria affects 24 million children globally, resulting in nearly 500,000 child deaths annually in low- and middle-income countries (LMICs). Recent studies have provided evidence that severe malaria infection results in sustained impairment in cognition and behaviour among young children; however, a formal meta-analysis has not been published. The objective was to assess the association between severe malaria infection with cognitive and behavioural outcomes among children living in LMICs.
METHODS
Six online bibliographic databases were searched and reviewed in November 2022. Studies included involved children < 18 years of age living in LMICs with active or past severe malaria infection and measured cognitive and/or behaviour outcomes. The quality of studies was assessed. Definitions of severe malaria included cerebral malaria, severe malarial anaemia, and author-defined severe malaria. Results from all studies were qualitatively summarized. For studies with relevant data on attention, learning, memory, language, internalizing behaviour and externalizing behaviour, results were pooled and a meta-analysis was performed. A random-effects model was used across included cohorts, yielding a standardized mean difference between the severe malaria group and control group.
RESULTS
Out of 3,803 initial records meeting the search criteria, 24 studies were included in the review, with data from 14 studies eligible for meta-analysis inclusion. Studies across sub-Saharan Africa assessed 11 cohorts of children from pre-school to school age. Of all the studies, composite measures of cognition were the most affected areas of development. Overall, attention, memory, and behavioural problems were domains most commonly found to have lower scores in children with severe malaria. Meta-analysis revealed that children with severe malaria had worse scores compared to children without malaria in attention (standardized mean difference (SMD) -0.68, 95% CI -1.26 to -0.10), memory (SMD -0.52, 95% CI -0.99 to -0.06), and externalizing behavioural problems (SMD 0.45, 95% CI 0.13-0.78).
CONCLUSION
Severe malaria is associated with worse neuropsychological outcomes for children living in LMICs, specifically in attention, memory, and externalizing behaviours. More research is needed to identify the long-term implications of these findings. Further interventions are needed to prevent cognitive and behavioural problems after severe malaria infection.
TRIAL REGISTRATION
This systematic review was registered under PROSPERO: CRD42020154777.
Topics: Child; Child, Preschool; Humans; Developing Countries; Cognition; Malaria, Cerebral; Africa South of the Sahara
PubMed: 37537555
DOI: 10.1186/s12936-023-04653-9