Browsing by Author "Rao, Krishna"

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    Baseline Predictors of Longitudinal Changes in Symptom Severity and Quality of Life in Patients with Suspected Gastroparesis
    (Elsevier, 2022) Lee, Allen A.; Rao, Krishna; Parkman, Henry P.; McCallum, Richard W.; Sarosiek, Irene; Nguyen, Linda A.; Wo, John M.; Schulman, Michael I.; Moshiree, Baharak; Rao, Satish; Kuo, Braden; Hasler, William L.; Medicine, School of Medicine
    Background & aims: Whether gastric emptying tests predict longitudinal outcomes in patients with symptoms of gastroparesis is unclear. We aimed to determine whether baseline gastric emptying tests and gut motility parameters could impact longitudinal symptom(s) and quality of life (QOL) in a prospective, observational cohort study of patients with symptoms of gastroparesis. Methods: One hundred fifty patients with gastroparesis symptoms underwent simultaneous scintigraphy (GES) and wireless motility capsule (WMC) measurement of gastric emptying and other motility parameters. Patient Assessment of Upper Gastrointestinal Symptoms and Quality of Life were administered at baseline, and 3 and 6 months after testing. Multivariable generalized linear marginal models were fit to determine which baseline parameters predict longitudinal changes in symptoms and QOL. Results: Overall upper GI symptoms and QOL scores were moderate in severity at baseline and significantly improved over 6 months. Clinical variables, including female gender, harder stools by Bristol stool form score, and presence of functional dyspepsia (FD) by Rome III criteria, were predictive of more severe upper GI symptoms. Even after controlling for these clinical factors, delayed gastric emptying by GES or WMC was associated with worse symptom severity and QOL scores. Low gastric and elevated small bowel contractile parameters by WMC were also independently associated with more severe upper GI symptoms and worse QOL scores. Conclusions: Baseline features, including demographic and clinical variables, delayed gastric emptying and abnormal gastrointestinal contractility, were independent predictors of more severe longitudinal symptoms and worse quality of life outcomes. These factors may help to risk stratify patients and guide treatment decisions.
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    Factors influencing performance by contracted non-state providers implementing a basic package of health services in Afghanistan
    (Biomed Central, 2018-10-05) Salehi, Ahmad Shah; Saljuqi, Abdul Tawab Kawa; Akseer, Nadia; Rao, Krishna; Coe, Kathryn; Social and Behavioral Sciences, School of Public Health
    BACKGROUND: In 2002 Afghanistan's Ministry of Public Health (MoPH) and its development partners initiated a new paradigm for the health sector by electing to Contract-Out (CO) the Basic Package of Health Services (BPHS) to non-state providers (NSPs). This model is generally regarded as successful, but literature is scarce that examines the motivations underlying implementation and factors influencing program success. This paper uses relevant theories and qualitative data to describe how and why contracting out delivery of primary health care services to NSPs has been effective. The main aim of this study was to assess the contextual, institutional, and contractual factors that influenced the performance of NSPs delivering the BPHS in Afghanistan. METHODS: The qualitative study design involved individual in-depth interviews and focus group discussions conducted in six provinces of Afghanistan, as well as a desk review. The framework for assessing key factors of the contracting mechanism proposed by Liu et al. was utilized in the design, data collection and data analysis. RESULTS: While some contextual factors facilitated the CO (e.g. MoPH leadership, NSP innovation and community participation), harsh geography, political interference and insecurity in some provinces had negative effects. Contractual factors, such as effective input and output management, guided health service delivery. Institutional factors were important; management capacity of contracted NSPs affects their ability to deliver outcomes. Effective human resources and pharmaceutical management were notable elements that contributed to the successful delivery of the BPHS. The contextual, contractual and institutional factors interacted with each other. CONCLUSION: Three sets of factors influenced the implementation of the BPHS: contextual, contractual and institutional. The MoPH should consider all of these factors when contracting out the BPHS and other functions to NSPs. Other fragile states and countries emerging from a period of conflict could learn from Afghanistan's example in contracting out primary health care services, keeping in mind that generic or universal contracting policies might not work in all geographical areas within a country or between countries.
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    Gut community structure as a risk factor for infection in Klebsiella pneumoniae-colonized patients
    (American Society for Microbiology, 2024) Vornhagen, Jay; Rao, Krishna; Bachman, Michael A.; Microbiology and Immunology, School of Medicine
    The primary risk factor for infection with members of the Klebsiella pneumoniae species complex is prior gut colonization, and infection is often caused by the colonizing strain. Despite the importance of the gut as a reservoir for infectious K. pneumoniae, little is known about the association between the gut microbiome and infection. To explore this relationship, we undertook a case-control study comparing the gut community structure of K. pneumoniae-colonized intensive care and hematology/oncology patients. Cases were K. pneumoniae-colonized patients infected by their colonizing strain (N = 83). Controls were K. pneumoniae-colonized patients who remained asymptomatic (N = 149). First, we characterized the gut community structure of K. pneumoniae-colonized patients agnostic to case status. Next, we determined that gut community data is useful for classifying cases and controls using machine learning models and that the gut community structure differed between cases and controls. K. pneumoniae relative abundance, a known risk factor for infection, had the greatest feature importance, but other gut microbes were also informative. Finally, we show that integration of gut community structure with bacterial genotype data enhanced the ability of machine learning models to discriminate cases and controls. Interestingly, inclusion of patient clinical variables failed to improve the ability of machine learning models to discriminate cases and controls. This study demonstrates that including gut community data with K. pneumoniae-derived biomarkers improves our ability to classify infection in K. pneumoniae-colonized patients. IMPORTANCE: Colonization is generally the first step in pathogenesis for bacteria with pathogenic potential. This step provides a unique window for intervention since a given potential pathogen has yet to cause damage to its host. Moreover, intervention during the colonization stage may help alleviate the burden of therapy failure as antimicrobial resistance rises. Yet, to understand the therapeutic potential of interventions that target colonization, we must first understand the biology of colonization and if biomarkers at the colonization stage can be used to stratify infection risk. The bacterial genus Klebsiella includes many species with varying degrees of pathogenic potential. Members of the K. pneumoniae species complex have the highest pathogenic potential. Patients colonized in their gut by these bacteria are at higher risk of subsequent infection with their colonizing strain. However, we do not understand if other members of the gut microbiota can be used as a biomarker to predict infection risk. In this study, we show that the gut microbiota differs between colonized patients who develop an infection versus those who do not. Additionally, we show that integrating gut microbiota data with bacterial factors improves the ability to classify infections. Surprisingly, patient clinical factors were not useful for classifying infections alone or when added to microbiota-based models. This indicates that the bacterial genotype and the microbial community in which it exists may determine the progression to infection. As we continue to explore colonization as an intervention point to prevent infections in individuals colonized by potential pathogens, we must develop effective means for predicting and stratifying infection risk.