ABSTRACT
Despite an increasingly detailed picture of the molecular mechanisms of bacteriophage (phage)-bacterial interactions, we lack an understanding of how these interactions evolve and impact disease within patients. In this work, we report a year-long, nationwide study of diarrheal disease patients in Bangladesh. Among cholera patients, we quantified Vibrio cholerae (prey) and its virulent phages (predators) using metagenomics and quantitative polymerase chain reaction while accounting for antibiotic exposure using quantitative mass spectrometry. Virulent phage (ICP1) and antibiotics suppressed V. cholerae to varying degrees and were inversely associated with severe dehydration depending on resistance mechanisms. In the absence of antiphage defenses, predation was "effective," with a high predator:prey ratio that correlated with increased genetic diversity among the prey. In the presence of antiphage defenses, predation was "ineffective," with a lower predator:prey ratio that correlated with increased genetic diversity among the predators. Phage-bacteria coevolution within patients should therefore be considered in the deployment of phage-based therapies and diagnostics.
Subject(s)
Bacteriophages , Cholera , Genetic Variation , Vibrio cholerae , Cholera/microbiology , Vibrio cholerae/genetics , Vibrio cholerae/virology , Bacteriophages/genetics , Bacteriophages/physiology , Humans , Bangladesh , Anti-Bacterial Agents/therapeutic use , Severity of Illness Index , Adult , MetagenomicsABSTRACT
OBJECTIVE: To develop and evaluate a guideline for a paediatric telemedicine and medication delivery service (TMDS). METHODS: A clinical guideline for paediatric telemedicine was derived from the World Health (WHO) Organization Integrated Management of Childhood Illness (IMCI) Handbook. The guideline was deployed at a TMDS in Haiti and evaluated through a prospective cohort study; children ≤10 years were enrolled. For non-severe cases, paired virtual and in-person examinations were conducted at the call centre and household; severe cases were referred to the hospital. The performance of virtual examination components were evaluated by comparison with the paired in-person examination findings (reference). RESULTS: A total of 391 cases were enrolled. Among the 320 cases with paired examinations, no general WHO danger signs were identified during in-person examinations; 5 cases (2%) required hospital referral due to problem-specific danger signs or other reasons for escalation. Cohen's kappa for the virtual designation of mild cases was 0.78 (95% CI: 0.69 to 0.87). The sensitivity and specificity of a virtually reported fever were 91% (95% CI: 87% to 96%) and 69% (95% CI: 62% to 76%), respectively; the sensitivity and specificity of virtually reported 'fast breathing' were 47% (95% CI: 21% to 72%) and 89% (95% CI: 85% to 94%), respectively. Kappa for 'no' and 'some' dehydration indicated moderate congruence between virtual and in-person examinations (0.69; 95% CI: 0.41 to 0.98). At 10 days, 273 (95%) of the 287 cases reached by phone were better/recovered. CONCLUSION: Critical components of the virtual examination (triage, danger signs and dehydration assessment) performed well despite varied performance among the problem-specific components. The study and associated resources represents formative steps towards an evidence-based paediatric telemedicine guideline built on WHO clinical principles. In-person examinations for select cases were important to address limitations with virtual examinations and identify cases for escalation. TRIAL REGISTRATION NUMBER: NCT03943654.
Subject(s)
Call Centers , Telemedicine , Humans , Child , Dehydration/diagnosis , Dehydration/therapy , Prospective Studies , Resource-Limited SettingsABSTRACT
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.