Derivation of the first clinical diagnostic models for dehydration severity in patients over five years with acute diarrhea

Are young and older children with diarrhea presenting in the same way?

BACKGROUND

Diarrhoea is a global health problem. More than a quarter of diarrhoeal deaths occur among children less than five years. Different literatures analyzed presentation and outcomes of less than five diarrhoeal children. The world has made remarkable progress in reducing child mortality. So, older children are growing in number. Our aim was to identify clinical differentials and variations of pathogens among younger (less than five) and older (five to nine years) diarrhoeal children.

METHOD

Data were extracted from the diarrhoeal disease surveillance system (DDSS) of Dhaka Hospital (urban site) and Matlab Hospital (rural site) of the International Centre for Diarrhoeal Disease Research, Bangladesh for the period of January 2012 to December 2021. Out of 28,781 and 12,499 surveillance patients in Dhaka and Matlab Hospital, 614 (2.13%) and 278 (2.22%) children were five to nine-years of age, respectively. Among under five children, 2456 from Dhaka hospital and 1112 from Matlab hospital were selected randomly for analysis (four times of five to nine years age children, 1:4).

RESULTS

Vomiting, abdominal pain, and dehydrating diarrhoea were significantly higher in older children in comparison to children of less than five years age (p-value <0.05) after adjusting study site, gender, antibiotic use before hospitalization, diarrhoeal duration < 24 hours, intake of oral rehydration fluid at home, parental education, WASH practice and history of cough. Vibrio. cholerae, Salmonella, and Shigella were the common fecal pathogen observed among older children compared to under five after adjusting for age, gender and study site.

CONCLUSION

Although percentage of admitted diarrhoeal children with five to nine years is less than under five years children but they presented with critical illness with different diarrhoeal pathogens. These observations may help clinicians to formulate better case management strategies for children of five to nine years that may reduce morbidity.

Anti-diarrheal effect of piperine possibly through the interaction with inflammation inducing enzymes: In vivo and in silico studies

Piperine is a natural alkaloid that possesses a variety of therapeutic properties, including anti-inflammatory, antioxidant, antibacterial, and anticarcinogenic activities. The present study aims to assess the medicinal benefits of piperine as an anti-diarrheal agent in a chick model by utilizing in vivo and in silico techniques. For this, castor oil was administered orally to 2-day-old chicks to cause diarrhea. Bismuth subsalicylate (10 mg/kg), loperamide (3 mg/kg), and nifedipine (2.5 mg/kg) were used as positive controls, while the vehicle was utilized as a negative control. Two different doses (25 and 50 mg/kg b.w.) of the test sample (piperine) were administered orally, and the highest dose was tested with standards to investigate the synergistic activity of the test sample. In our findings, piperine prolonged the latent period while reducing the number of diarrheal feces in the experimental chicks during the monitoring period (4 h). At higher doses, piperine appears to reduce diarrheal secretion while increasing latency in chicks. Throughout the combined pharmacotherapy, piperine outperformed bismuth subsalicylate and nifedipine in terms of anti-diarrheal effects with loperamide. In molecular docking, piperine exhibited higher binding affinities towards different inflammatory enzymes such as cyclooxygenase 1 (-7.9 kcal/mol), cyclooxygenase 2 (-8.4 kcal/mol), nitric oxide synthases (-8.9 kcal/mol), and L-type calcium channel (-8.8 kcal/mol), indicating better interaction of PP with these proteins. In conclusion, piperine showed a potent anti-diarrheal effect in castor oil-induced diarrheal chicks by suppressing the inflammation and calcium ion influx induced by castor oil.

A comparison of the NIRUDAK models and WHO algorithm for dehydration assessment in older children and adults with acute diarrhoea: a prospective, observational study

BACKGROUND

Despite the importance of accurate and rapid assessment of hydration status in patients with acute diarrhoea, no validated tools exist to help clinicians assess dehydration severity in older children and adults. The aim of this study is to validate a clinical decision support tool (CDST) and a simplified score for dehydration severity in older children and adults with acute diarrhoea (both developed during the NIRUDAK study) and compare their accuracy and reliability with current WHO guidelines.

METHODS

A random sample of patients aged 5 years or older presenting with diarrhoea to the icddr,b Dhaka Hospital in Bangladesh between Jan 30 and Dec 13, 2022 were included in this prospective cohort study. Patients with fewer than three loose stools per day, more than 7 days of symptoms, previous enrolment in the study, or a diagnosis other than acute gastroenteritis were excluded. Patients were weighed on arrival and assessed separately by two nurses using both our novel clinical tools and WHO guidelines. Patients were weighed every 4 h to determine their percent weight change with rehydration, our criterion standard for dehydration. Accuracy for the diagnosis of dehydration category (none, some, or severe) was assessed using the ordinal c-index (ORC). Reliability was assessed by comparing the prediction of severe dehydration from each nurse's independent assessment using the intraclass correlation coefficient (ICC).

FINDINGS

1580 patients were included in our primary analysis, of whom 921 (58·3%) were female and 659 (41·7%) male. The ORC was 0·74 (95% CI 0·71-0·77) for the CDST, 0·75 (0·71-0·78) for the simplified score, and 0·64 (0·61-0·67) for the WHO guidelines. The ICC was 0·98 (95% CI 0·97-0·98) for the CDST, 0·94 (0·93-0·95) for the simplified score, and 0·56 (0·52-0·60) for the WHO guidelines.

INTERPRETATION

Use of our CDST or simplified score by clinicians could reduce undertreatment and overtreatment of older children and adults with acute diarrhoea, potentially reducing morbidity and mortality for this common disease.

FUNDING

US National Institutes of Health.

TRANSLATION

For the Bangla translation of the abstract see Supplementary Materials section.

Use of Framework Matrix and Thematic Coding Methods in Qualitative Analysis for mHealth: NIRUDAK Study Data

Objective

Framework Matrix Analysis (FMA) and Applied Thematic Analysis (ATA) are qualitative methods that have not been as widely used/cited compared to content analysis or grounded theory. This paper compares methods of FMA with ATA for mobile health (mHealth) research. The same qualitative data were analyzed separately, using each methodology. The methods, utility, and results of each are compared, and recommendations made for their effective use.

Methods

Formative qualitative data were collected in eight focus group discussions with physicians and nurses from three hospitals in Bangladesh. Focus groups were conducted via video conference in the local language, Bangla, and audio recorded. Audio recordings were used to complete a FMA of participants' opinions about key features of a novel mHealth application (app) designed to support clinical management in patients with acute diarrhea. The resulting framework matrix was shared with the app design team and used to guide iterative development of the product for a validation study of the app. Subsequently, focus group audio recordings were transcribed in Bangla then translated into English for ATA; transcripts and codes were entered into NVivo qualitative analysis software. Code summaries and thematic memos explored the clinical utility of the mHealth app including clinicians' attitudes about using this decision support tool.

Results

Each of the two methods contributes differently to the research goal and have different implications for an mHealth research timeline. Recommendations for the effective use of each method in app development include: using FMA for data reduction where specific outcomes are needed to make programming and design decisions and using ATA to capture the more nuanced issues that guide use, product implementation, training, and workflow.

Conclusions

By describing how both analytical methods were used in this context, this paper provides guidance and an illustration for use of these two methods, specifically in mHealth design.

Correction: Derivation of the first clinical diagnostic models for dehydration severity in patients over five years with acute diarrhea

[This corrects the article DOI: 10.1371/journal.pntd.0009266.].

Risk Prediction Score for Pediatric Patients with Suspected Ebola Virus Disease

Rapid diagnostic tools for children with Ebola virus disease (EVD) are needed to expedite isolation and treatment. To evaluate a predictive diagnostic tool, we examined retrospective data (2014-2015) from the International Medical Corps Ebola Treatment Centers in West Africa. We incorporated statistically derived candidate predictors into a 7-point Pediatric Ebola Risk Score. Evidence of bleeding or having known or no known Ebola contacts was positively associated with an EVD diagnosis, whereas abdominal pain was negatively associated. Model discrimination using area under the curve (AUC) was 0.87, which outperforms the World Health Organization criteria (AUC 0.56). External validation, performed by using data from International Medical Corps Ebola Treatment Centers in the Democratic Republic of the Congo during 2018-2019, showed an AUC of 0.70. External validation showed that discrimination achieved by using World Health Organization criteria was similar; however, the Pediatric Ebola Risk Score is simpler to use.

Clinical, Sociodemographic and Environmental Risk Factors for Acute Bacterial Diarrhea among Adults and Children over Five Years in Bangladesh

In 2016, diarrheal disease was the eighth leading cause of mortality globally accounting for over 1.6 million deaths with the majority of deaths in adults and children over 5 years. This study aims to investigate the clinical, sociodemographic, and environmental risk factors associated with common bacterial acute diarrhea among adults and children over 5. Data were collected from March 2019 to March 2020 in patients over 5 years presenting with acute gastroenteritis at icddr,b. Stool samples were collected from each patient for culture and polymerase chain reaction (PCR) testing. Bivariate associations between independent variables and stool-testing indicating bacterial etiology were calculated. This analysis included 2,133 diarrheal patients of whom a bacterial enteropathogen was identified in 1,537 (72%). Detection of bacteria was associated with: younger age (OR 0.92; 95% CI: 0.88-0.96), lower mean arterial pressure (OR 0.84; 95% CI: 0.79-0.89), heart rate (OR 1.06; 95% CI: 1.01-1.10), percentage dehydration (OR 1.33; 95% CI: 1.13-1.55), respiration rate (OR 1.23; 95% CI: 1.04-1.46), lower mid-upper arm circumference (OR 0.97; 95% CI: 0.94-0.99), confused/lethargic mental status (OR 1.85; 95% CI: 1.11-3.25), rice watery stool (OR 1.92; 95% CI: 1.54-2.41), and vomiting more than three times in the past 24 hours (OR 1.30; 95% CI: 1.06-1.58). Higher monthly income (OR 0.92; 95% CI: 0.86-0.98), > 8 years of education (OR 0.79; 95% CI: 0.63-1.00), and having more than five people living at home (OR 0.80; 95% CI: 0.66-0.98) were associated with lower odds of bacterial diarrhea. These findings may help guide the development of predictive tools to aid in identifying patients with bacterial diarrhea for timely and appropriate use of antibiotics.

Assessing the performance of clinical diagnostic models for dehydration among patients with cholera and undernutrition in Bangladesh

OBJECTIVE

Accurately assessing dehydration severity is a critical step in reducing mortality from diarrhoea, but is complicated by cholera and undernutrition. This study seeks to assess the accuracy of two clinical diagnostic models for dehydration among patients over five years with cholera and undernutrition and compare their respective performance to the World Health Organization (WHO) algorithm.

METHODS

In this secondary analysis of data collected from the NIRUDAK study, accuracy of the full and simplified NIRUDAK models for predicting severe and any dehydration was measured using the area under the Receiver Operator Characteristic curve (AUC) among patients over five with/without cholera and with/without wasting. Bootstrap with 1000 iterations was used to compare the m-index for each NIRUDAK model to that of the WHO algorithm.

RESULTS

A total of 2,139 and 2,108 patients were included in the nutrition and cholera subgroups respectively with an overall median age of 35 years (IQR = 42) and 49.6% female. All subgroups had acceptable discrimination in diagnosing severe or any dehydration (AUC > 0.60); though the full NIRUDAK model performed best among patients without cholera, with an AUC of 0.82 (95%CI:0.79, 0.85) and among patients without wasting, with an AUC of 0.79 (95%CI:0.76, 0.81). Compared with the WHO's algorithm, both the full and simplified NIRUDAK models performed significantly better in terms of their m-index (p < 0.001) for all comparisons, except for the simplified NIRUDAK model in the wasting group.

CONCLUSIONS

Both the full and simplified NIRUDAK models performed less well in patients over five years with cholera and/or wasting; however, both performed better than the WHO algorithm.

Designing a Novel Clinician Decision Support Tool for the Management of Acute Diarrhea in Bangladesh: Formative Qualitative Research (Preprint)

Background

The availability of mobile clinical decision support (CDS) tools has grown substantially with the increased prevalence of smartphone devices and apps. Although health care providers express interest in integrating mobile health (mHealth) technologies into their clinical settings, concerns have been raised, including perceived disagreements between information provided by mobile CDS tools and standard guidelines. Despite their potential to transform health care delivery, there remains limited literature on the provider’s perspective on the clinical utility of mobile CDS tools for improving patient outcomes, especially in low- and middle-income countries.

Objective

This study aims to describe providers’ perceptions about the utility of a mobile CDS tool accessed via a smartphone app for diarrhea management in Bangladesh. In addition, feedback was collected on the preliminary components of the mobile CDS tool to address clinicians’ concerns and incorporate their preferences.

Methods

From November to December 2020, qualitative data were gathered through 8 web-based focus group discussions with physicians and nurses from 3 Bangladeshi hospitals. Each discussion was conducted in the local language—Bangla—and audio recorded for transcription and translation by the local research team. Transcripts and codes were entered into NVivo (version 12; QSR International), and applied thematic analysis was used to identify themes that explore the clinical utility of an mHealth app for assessing dehydration severity in patients with acute diarrhea. Summaries of concepts and themes were generated from reviews of the aggregated coded data; thematic memos were written and used for the final analysis.

Results

Of the 27 focus group participants, 14 (52%) were nurses and 13 (48%) were physicians; 15 (56%) worked at a diarrhea specialty hospital and 12 (44%) worked in government district or subdistrict hospitals. Participants’ experience in their current position ranged from 2 to 14 years, with an average of 10.3 (SD 9.0) years. Key themes from the qualitative data analysis included current experience with CDS, overall perception of the app’s utility and its potential role in clinical care, barriers to and facilitators of app use, considerations of overtreatment and undertreatment, and guidelines for the app’s clinical recommendations. Participants felt that the tool would initially take time to use, but once learned, it could be useful during epidemic cholera. Some felt that clinical experience remains an important part of treatment that can be supplemented, but not replaced, by a CDS tool. In addition, diagnostic information, including mid-upper arm circumference and blood pressure, might not be available to directly inform programming decisions.

Conclusions

Participants were positive about the mHealth app and its potential to inform diarrhea management. They provided detailed feedback, which developers used to revise the mobile CDS tool. These formative qualitative data provided timely and relevant feedback to improve the utility of a CDS tool for diarrhea treatment in Bangladesh.

Continuous diagnostic models for volume deficit in patients with acute diarrhea

Background

Episodes of acute diarrhea lead to dehydration, and existing care algorithms base treatment around categorical estimates for fluid resuscitation. This study aims to develop models for the percentage dehydration (fluid deficit) in individuals with acute diarrhea, to better target treatment and avoid the potential sequelae of over or under resuscitation.

Methods

This study utilizes data from two prospective cohort studies of patients with acute diarrhea in Dhaka, Bangladesh. Data were collected on patient arrival, including weight, clinical signs and symptoms, and demographic information. Consecutive weights were obtained to determine the true volume deficit of each patient. Data were entered into two distinct forward stepwise regression logistic models (DHAKA for under 5 years and NIRUDAK for 5 years and over).

Results

A total of 782 patients were included in the final analysis of the DHAKA data set, and 2139 were included in the final analysis of the NIRUDAK data set. The best model for the DHAKA data achieved an R² of 0.27 and a root mean square error (RMSE) of 3.7 (compared to R² of 0.06 and RMSE of 5.5 with the World Health Organization child care algorithm) and selected 6 predictors. The best performance model for the NIRUDAK data achieved an R² of 0.28 and a RMSE of 2.6 (compared to R² of 0.08 and RMSE of 4.3 with the World Health Organization adolescent/adult care algorithm) and selected 7 predictors with 2 interactions.

Conclusions

These are the first mathematical models for patients with acute diarrhea that allow for the calculation of a patient’s percentage dehydration (fluid deficit) and subsequent targeted treatment with fluid resuscitation. These findings are an improvement on existing World Health Organization care algorithms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41182-021-00361-9.

Derivation and Internal Validation of a Score to Predict Dehydration Severity in Patients over 5 Years with Acute Diarrhea

Diarrheal disease accounts for more than one million deaths annually in patients over 5 years of age. Although most patients can be managed with oral rehydration solution, patients with severe dehydration require resuscitation with intravenous fluids. Scoring systems to assess dehydration have been empirically derived and validated in children under 5 years, but none have been validated for patients over 5 years. In this study, a prospective cohort of 2,172 patients over 5 years presenting with acute diarrhea to International Centre for Diarrhoeal Disease Research, Dhaka Hospital, Bangladesh, were assessed for clinical signs of dehydration. The percent difference between presentation and posthydration stable weight determined severe (≥ 9%), some (3-9%), or no (< 3%) dehydration. An ordinal regression model was derived using clinical signs and demographics and was then converted to a 13-point score to predict none (score of 0-3), some (4-6), or severe (7-13) dehydration. The Novel, Innovative Research for Understanding Dehydration in Adults and Kids (NIRUDAK) Score developed by our team included age, sex, sunken eyes, radial pulse, respiration depth, skin turgor, and vomiting episodes in 24 hours. Accuracy of the NIRUDAK Score for predicting severe dehydration, as measured by the area under the receiver operating characteristic curve, was 0.76 (95% confidence interval = 0.73-0.78), with a sensitivity of 0.78 and a specificity of 0.61. Reliability was also robust, with an Inter-Class Correlation Coefficient of 0.88 (95% confidence interval = 0.84-0.91). This study represents the first empirically derived and internally validated scoring system for assessing dehydration in children ≥ 5 years and adults with acute diarrhea in a resource-limited setting.

Multidrug-resistant enteric pathogens in older children and adults with diarrhea in Bangladesh: epidemiology and risk factors

BACKGROUND

Antimicrobial resistance (AMR) is a global public health threat and is increasingly prevalent among enteric pathogens in low- and middle-income countries (LMICs). However, the burden of multidrug-resistant organisms (MDROs) in older children, adults, and elderly patients with acute diarrhea in LMICs is poorly understood. This study's aim was to characterize the prevalence of MDR enteric pathogens isolated from patients with acute diarrhea in Dhaka, Bangladesh, and assess a wide range of risk factors associated with MDR.

METHODS

This study was a secondary analysis of data collected from children over 5 years, adults, and elderly patients with acute diarrhea at the International Centre for Diarrhoeal Disease Research, Bangladesh Dhaka Hospital between March 2019 and March 2020. Clinical, historical, socio-environmental information, and a stool sample for culture and antimicrobial susceptibility testing were collected from each patient. Univariate statistics and multiple logistic regression were used to assess the prevalence of MDR among enteric pathogens and the association between independent variables and presence of MRDOs among culture-positive patients.

RESULTS

A total of 1198 patients had pathogens isolated by stool culture with antimicrobial susceptibility results. Among culture-positive patients, the prevalence of MDR was 54.3%. The prevalence of MDR was highest in Aeromonas spp. (81.5%), followed by Campylobacter spp. (72.1%), Vibrio cholerae (28.1%), Shigella spp. (26.2%), and Salmonella spp. (5.2%). Factors associated with having MDRO in multiple logistic regression included longer transport time to hospital (>90 min), greater stool frequency, prior antibiotic use prior to hospital presentation, and non-flush toilet use. However, pseudo-R2 was low 0.086, indicating that other unmeasured variables need to be considered to build a more robust predictive model of MDR.

CONCLUSIONS

MDR enteric pathogens were common in this study population with clinical, historical, and socio-environmental risk factors associated with MDROs. These findings may help guide clinical decision-making regarding antibiotic use and selection in patients at greatest risk of complications due to MDROs. Further prospective research is urgently needed to determine what additional factors place patients at greatest risk of MDRO, and the best strategies to mitigate the spread of MDR in enteric pathogens.