Beyond the regulatory radar: knowledge and practices of rural medical practitioners in Bangladesh

BACKGROUND

Informal and unregulated rural medical practitioners (RMPs) provide healthcare services to about two-thirds of people in Bangladesh, although their service is assumed to be substandard by qualified providers. As the RMPs are embedded in the local community and provide low-cost services, their practice pattern demands investigation to identify the shortfalls and design effective strategies to ameliorate the service.

METHODS

We conducted a cross-sectional study in 2015-16 using a convenient sample from all 64 districts of Bangladesh. Personnel practising modern medicine, without any recognized training, or with recognized training but practising outside their defined roles, and without any regulatory oversight were invited to take part in the study. Appropriateness of the diagnosis and the rationality of antibiotic and other drug use were measured as per the Integrated Management of Childhood Illness guideline.

RESULTS

We invited 1004 RMPs, of whom 877 consented. Among them, 656 (74.8%) RMPs owned a drugstore, 706 (78.2%) had formal education below higher secondary level, and 844 (96.2%) had informal training outside regulatory oversight during or after induction into the profession. The most common diseases encountered by them were common cold, pneumonia, and diarrhoea. 583 (66.5%) RMPs did not dispense any antibiotic for common cold symptoms. 59 (6.7%) and 64 (7.3%) of them could identify all main symptoms of pneumonia and diarrhoea, respectively. In pneumonia, 28 (3.2%) RMPs dispensed amoxicillin as first-line treatment, 819 (93.4%) dispensed different antibiotics including ceftriaxone, 721 (82.2%) dispensed salbutamol, and 278 (31.7%) dispensed steroid. In diarrhoea, 824 (94.0%) RMPs dispensed antibiotic, 937 (95.4%) dispensed ORS, 709 (80.8%) dispensed antiprotozoal, and 15 (1.7%) refrained from dispensing antibiotic and antiprotozoal together.

CONCLUSIONS

Inappropriate diagnoses, irrational use of antibiotics and other drugs, and polypharmacy were observed in the practising pattern of RMPs. The government and other stakeholders should acknowledge them as crucial partners in the healthcare sector and consider ways to incorporate them into curative and preventive care.

Maternal serum lipidomics identifies lysophosphatidic acid as a predictor of small for gestational age neonates

To discover lipidomic alterations during pregnancy in mothers who subsequently delivered small for gestational age (SGA) neonates and identify predictive lipid markers that can help recognize and manage these mothers, we carried out untargeted lipidomics on maternal serum samples collected between 24-28 weeks of gestation. We used a nested case-control study design and serum from mothers who delivered SGA and appropriate for gestational age babies. We applied untargeted lipidomics using mass spectrometry to characterize lipids and discover changes associated with SGA births during pregnancy. Multivariate pattern recognition software Collaborative Laboratory Integrated Reports (CLIR) was used for the post-analytical recognition of range differences in lipid ratios that could differentiate between SGA and control mothers and their integration for complete separation between the two groups. Here, we report changes in lipids from serum collected during pregnancy in mothers who delivered SGA neonates. In contrast to normal pregnancies where lysophosphatidic acid increased over the course of the pregnancy owing to increased activity of lysophospholipase D, we observed a decrease (32%; P = 0.05) of 20:4-lysophosphatidic acid in SGA mothers, which could potentially compromise fetal growth and development. Integration of lipid ratios in an interpretive tool (CLIR) could completely separate SGA mothers from controls demonstrating the power of untargeted lipidomic analyses for identifying novel predictive biomarkers. Additional studies are required for further assessment of the lipid biomarkers identified in this report.

Antibiotic Prescribing Patterns at COVID-19 Dedicated Wards in Bangladesh: Findings from a Single Center Study

Background

As evidence is mounting regarding irrational and often unnecessary use of antibiotics during the COVID-19 pandemic a cross-sectional Point Prevalence Survey (PPS) (in accordance with WHO guideline) was conducted across COVID-19 dedicated wards in Dhaka Medical College and Hospital (DMCH).

Methodology

Antibiotic usage data were collected from 193 patients at different COVID-19 dedicated wards at DMCH on 11 June 2020. Comparisons in antibiotic usage were made between different groups using Pearson chi-square and Fisher's exact test.

Result

Findings reveal all surveyed patients (100%) were receiving at least one antibiotic with 133 patients (68.91%) receiving multiple antibiotics. Overall, patients presenting with the severe disease received more antibiotics. Third-generation cephalosporins (i.e. ceftriaxone) (53.8%), meropenem (40.9%), moxifloxacin (29.5%), and doxycycline (25.4%) were the four most prescribed antibiotics among surveyed patients. Diabetes mellitus (DM) was independently associated with multiple antibiotic prescribing. Abnormal C-reactive protein (CRP) and serum d-dimer were linked with higher odds of multiple antibiotic prescribing among study patients.

Conclusion

Prevalence of multiple antibiotic prescriptions was high among severely ill patients and those with abnormal CRP and d-dimer levels. Data regarding the quality of antibiotic prescribing were lacking.

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries

IMPORTANCE

Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies.

OBJECTIVE

To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019.

EXPOSURES

Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites.

MAIN OUTCOMES AND MEASURES

The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation.

RESULTS

Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways.

CONCLUSIONS AND RELEVANCE

This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB.

Digital Health and Inequalities in Access to Health Services in Bangladesh: Mixed Methods Study

Background

Globally, the rapid growth of technology and its use as a development solution has generated much interest in digital health. In line with global trends, Bangladesh is also integrating technology into its health system to address disparities. Strong political endorsement and uptake of digital platforms by the government has influenced the rapid proliferation of such initiatives in the country. This paper aims to examine the implications of digital health on access to health care in Bangladesh, considering who uses electronic devices to access health information and services and why.

Objective

This study aims to understand how access to health care and related information through electronic means (digital health) is affected by sociodemographic determinants (ie, age, gender, education, socioeconomic status, and personal and household ownership of mobile phones) in a semiurban community in Bangladesh.

Methods

A cross-sectional survey of 854 households (between October 2013 and February 2014) and 20 focus group discussions (between February 2017 and March 2017) were conducted to understand (1) who owns electronic devices; (2) who, among the owners, uses these to access health information and services and why; (3) the awareness of electronic sources of health information; and (4) the role of intermediaries (family members or peers who helped to look for health information using electronic devices).

Results

A total of 90.3% (771/854) of households (471/854, 55.2% of respondents) owned electronic devices, mostly mobile phones. Among these, 7.2% (34/471) used them to access health information or services. Middle-aged (35-54 years), female, less (or not) educated, and poorer people used these devices the least (α=.05, α is the level of significance). The lack of awareness, discomfort, differences with regular care-seeking habits, lack of understanding and skills, and proximity to a health facility were the main reasons for not using devices to access digital health.

Conclusions

Although influenced by sociodemographic traits, access to digital health is not merely related to device ownership and technical skill. Rather, it is a combination of general health literacy, phone ownership, material resources, and technical skill as well as social recognition of health needs and inequity. This study’s findings should serve as a basis for better integrating technology within the health system and ensuring equitable access to health care.

The influence of travel time on emergency obstetric care seeking behavior in the urban poor of Bangladesh: a GIS study

Background

Availability of Emergency Obstetric Care (EmOC) is crucial to avert maternal death due to life-threatening complications potentially arising during delivery. Research on the determinants of utilization of EmOC has neglected urban settings, where traffic congestion can pose a significant barrier to the access of EmOC facilities, particularly for the urban poor due to costly and limited transportation options. This study investigates the impact of travel time to EmOC facilities on the utilization of facility-based delivery services among mothers living in urban poor settlements in Sylhet, Bangladesh.

Methods

A cross-sectional EmOC health-seeking behavior survey from 39 poor urban clusters was geo-spatially linked to a comprehensive geo-referenced dataset of EmOC facility locations. Geo-spatial techniques and logistic regression were then applied to quantify the impact of travel time on place of delivery (EmOC facility or home), while controlling for confounding socio-cultural and economic factors.

Results

Increasing travel time to the nearest EmOC facility is found to act as a strong deterrent to seeking care for the urban poor in Sylhet. Logistic regression results indicate that a 5-min increase in travel time to the nearest EmOC facility is associated with a 30 % decrease (0.655 odds ratio, 95 % CI: 0.529–0.811) in the likelihood of delivery at an EmOC facility rather than at home. Moreover, the impact of travel time varies substantially between public, NGO and private facilities. A 5-min increase in travel time from a private EmOC facility is associated with a 32.9 % decrease in the likelihood of delivering at a private facility, while for public and Non-Government Organizations (NGO) EmOC facilities, the impact is lower (28.2 and 28.6 % decrease respectively). Other strong determinants of delivery at an EmOC facility are the use of antenatal care and mother’s formal education, while Muslim mothers are found to be more likely to deliver at home.

Conclusions

Geospatial evidence points to the need to strengthen referral and emergency transport systems in order to reduce urban travel time, and establish or relocate EmOC facilities closer to where the poor reside. However, female education and antenatal care coverage remain the most important determinants of facility delivery.