Smartphone-Based Gait Cadence to Identify Older Adults with Decreased Functional Capacity.

Background: Functional capacity assessment is a critical step in the preoperative evaluation to identify patients at increased risk of cardiac complications and disability after major noncardiac surgery. Smartphones offer the potential to objectively measure functional capacity but are limited by inaccuracy in patients with poor functional capacity. Open-source methods exist to analyze accelerometer data to estimate gait cadence (steps/min), which is directly associated with activity intensity. Here, we used an updated Step Test smartphone application with an open-source method to analyze accelerometer data to estimate gait cadence and functional capacity in older adults. Methods: We performed a prospective observational cohort study within the Frailty, Activity, Body Composition and Energy Expenditure in Aging study at the University of Chicago. Participants completed the Duke Activity Status Index (DASI) and performed an in-clinic 6-min walk test (6MWT) while using the Step Test application on a study smartphone. Gait cadence was measured from the raw accelerometer data using an adaptive empirical pattern transformation method, which has been previously validated. A 6MWT distance of 370 m was used as an objective threshold to identify patients at high risk. We performed multivariable logistic regression to predict walking distance using a priori explanatory variables. Results: Sixty patients were enrolled in the study. Thirty-seven patients completed the protocol and were included in the final data analysis. The median (IQR) age of the overall cohort was 71 (69-74) years, with a body mass index of 31 (27-32). There were no differences in any clinical characteristics or functional measures between participants that were able to walk 370 m during the 6MWT and those that could not walk that distance. Median (IQR) gait cadence for the entire cohort was 110 (102-114) steps/min during the 6MWT. Median (IQR) gait cadence was higher in participants that walked more than 370 m during the 6MWT 112 (108-118) versus 106 (96-114) steps/min; p = 0.0157). The final multivariable model to identify participants that could not walk 370 m included only median gait cadence. The Youden's index cut-point was 107 steps/min with a sensitivity of 0.81 (95% CI: 0.77, 0.85) and a specificity of 0.57 (95% CI: 0.55, 0.59) and an AUCROC of 0.69 (95% CI: 0.51, 0.87). Conclusions: Our pilot study demonstrates the feasibility of using gait cadence as a measure to estimate functional capacity. Our study was limited by a smaller than expected sample size due to COVID-19, and thus, a prospective study with preoperative patients that measures outcomes is necessary to validate our findings.

Morbidity and Mortality After Acute Myocardial Infarction After Elective Major Noncardiac Surgery.

OBJECTIVES: To develop parsimonious models of in-hospital mortality and morbidity risk after perioperative acute myocardial infarction (AMI). DESIGN: Retrospective data analysis. SETTING: National Inpatient Sample (2008-2013), a 20% sample of all non-federal in-patient hospitalizations in the United States. PARTICIPANTS: Patients 45 years or older who experienced perioperative AMI during elective admission for noncardiac surgery. INTERVENTIONS: The study used a mixed principal components analysis and multivariate logistic regression to identify risk factors for in-hospital mortality after perioperative AMI. A model incorporating only preoperative risk factors, defined by the Revised Cardiac Risk Index (RCRI), was compared with a "full risk factor" model, incorporating a large set of preoperative AMI risk factors. The risk of post-AMI disposition to an intermediate care or skilled nursing facility, a marker of functional impairment, then was evaluated. MEASUREMENTS AND MAIN RESULTS: In the present study, 15,574 cases of AMI after elective noncardiac surgery were identified (0.42%, corresponding with 78,122 cases nationally), with a 12.4% in-hospital mortality rate. The "RCRI-only" model was the best-fit model of post-AMI in-hospital mortality risk, without loss of predictive accuracy compared with the "full risk factor" model (area under the receiver operator characteristic curve 0.80, 95% confidence interval [CI] [0.77-0.82] v area under the receiver operator characteristic curve 0.81, 95% CI [0.77-0.83], respectively). Post-AMI mortality risk was the highest for perioperative complications, including sepsis (odds ratio 4.95, 95% CI [4.32-5.67]). Conversely, functional impairment was best predicted by the "full-risk factor" model and depended strongly on chronic preoperative comorbidities. CONCLUSIONS: The RCRI provides a simple but adequate model of preoperative risk factors for in-hospital mortality after perioperative AMI.

Untangling the dynamics of persistence and colonization in microbial communities.

A central goal of community ecology is to infer biotic interactions from observed distributions of co-occurring species. Evidence for biotic interactions, however, can be obscured by shared environmental requirements, posing a challenge for statistical inference. Here, we introduce a dynamic statistical model, based on probit regression, that quantifies the effects of spatial and temporal covariance in longitudinal co-occurrence data. We separate the fixed pairwise effects of species occurrences on persistence and colonization rates, a potential signal of direct interactions, from latent pairwise correlations in occurrence, a potential signal of shared environmental responses. We first validate our modeling framework with several simulation studies. Then, we apply the approach to a pressing epidemiological question by examining how human papillomavirus (HPV) types coexist. Our results suggest that while HPV types respond similarly to common host traits, direct interactions are sparse and weak, so that HPV type diversity depends largely on shared environmental drivers. Our modeling approach is widely applicable to microbial communities and provides valuable insights that should lead to more directed hypothesis testing and mechanistic modeling.

Economic burden of neonatal sepsis in sub-Saharan Africa.

BACKGROUND AND SIGNIFICANCE: The third Sustainable Development Goal for child health, which aims to end preventable deaths of newborns and children less than 5 years of age by 2030, cannot be met without substantial reduction of infection-specific neonatal mortality in the developing world. Neonatal infections are estimated to account for 26% of annual neonatal deaths, with mortality rates highest in sub-Saharan Africa (SSA). Reliable and comprehensive estimates of the incidence and aetiology surrounding neonatal sepsis in SSA remain incompletely available. We estimate the economic burden of neonatal sepsis in SSA. METHODS: Data available through global health agencies and in the medical literature were used to determine population demographics in SSA, as well as to determine the incidence, disease burden, mortality and resulting disabilities associated with neonatal sepsis. The disability-adjusted life years (DALY) associated with successful treatment or prevention of neonatal sepsis in SSA for 1 year were calculated. The value of a statistical life (VSL) methodology was estimated to evaluate the economic burden of untreated neonatal sepsis in SSA. RESULTS: We conservatively estimate that 5.29-8.73 million DALYs are lost annually in SSA due to neonatal sepsis. Corresponding VSL estimates predict an annual economic burden ranging from $10 billion to $469 billion. CONCLUSIONS: Our results highlight and quantify the scope of the public health and economic burden posed by neonatal sepsis in SSA. We quantify the substantial potential impact of more successful treatment and prevention strategies, and we highlight the need for greater investment in strategies to characterise, diagnose, prevent and manage neonatal sepsis and its long-term sequelae in SSA.

Recurring infection with ecologically distinct HPV types can explain high prevalence and diversity.

The high prevalence of human papillomavirus (HPV), the most common sexually transmitted infection, arises from the coexistence of over 200 genetically distinct types. Accurately predicting the impact of vaccines that target multiple types requires understanding the factors that determine HPV diversity. The diversity of many pathogens is driven by type-specific or "homologous" immunity, which promotes the spread of variants to which hosts have little immunity. To test for homologous immunity and to identify mechanisms determining HPV transmission, we fitted nonlinear mechanistic models to longitudinal data on genital infections in unvaccinated men. Our results provide no evidence for homologous immunity, instead showing that infection with one HPV type strongly increases the risk of infection with that type for years afterward. For HPV16, the type responsible for most HPV-related cancers, an initial infection increases the 1-year probability of reinfection by 20-fold, and the probability of reinfection remains 14-fold higher 2 years later. This increased risk occurs in both sexually active and celibate men, suggesting that it arises from autoinoculation, episodic reactivation of latent virus, or both. Overall, our results suggest that high HPV prevalence and diversity can be explained by a combination of a lack of homologous immunity, frequent reinfections, weak competition between types, and variation in type fitness between host subpopulations. Because of the high risk of reinfection, vaccinating boys who have not yet been exposed may be crucial to reduce prevalence, but our results suggest that there may also be large benefits to vaccinating previously infected individuals.

Rainfall drives hydrocephalus in East Africa.

OBJECT: Hydrocephalus is one of the most common brain disorders in children throughout the world. The majority of infant hydrocephalus cases in East Africa appear to be postinfectious, related to preceding neonatal infections, and are thus preventable if the microbial origins and routes of infection can be characterized. In prior microbiological work, the authors noted evidence of seasonality in postinfectious hydrocephalus (PIH) cases. METHODS: The geographical address of 696 consecutive children with PIH who were treated over 6 years was fused with satellite rainfall data for the same time period. A comprehensive time series and spatiotemporal analysis of cases and rainfall was performed. RESULTS: Four infection-onset peaks were found to straddle the twice-yearly rainy season peaks, demonstrating that the infections occurred at intermediate levels of rainfall. CONCLUSIONS: The findings in this study reveal a previously unknown link between climate and a neurosurgical condition. Satellite-derived rainfall dynamics are an important factor in driving the infections that lead to PIH. Given prior microbial analysis, these findings point to the importance of environmental factors with respect to preventing the newborn infections that lead to PIH.

Association of bacteria with hydrocephalus in Ugandan infants.

OBJECT: Infantile hydrocephalus in East Africa is predominantly postinfectious. The microbial origins remain elusive, since most patients present with postinfectious hydrocephalus after antecedent neonatal sepsis (NS) has resolved. METHODS: To characterize this syndrome in Ugandan infants, the authors used polymerase chain reaction targeting bacterial 16S ribosomal DNA from CSF to determine if bacterial residua from recent infections were detectable. Bacteria were identified based on the relationship of genetic sequences obtained with reference bacteria in public databases. The authors evaluated samples from patients presenting during dry and rainy seasons and performed environmental sampling in the villages of patients. RESULTS: Bacterial DNA was recovered from 94% of patients. Gram-negative bacteria in the phylum Proteobacteria were the most commonly detected. Within this phylum, Gammaproteobacteria dominated in patients presenting after infections during the rainy season, and Betaproteobacteria was most common following infections during the dry season. Acinetobacter species were identified in the majority of patients admitted after rainy season infection. CONCLUSIONS: Postinfectious hydrocephalus in Ugandan infants appears associated with predominantly enteric gram-negative bacteria. These findings highlight the need for linking these cases with antecedent NS to develop more effective treatment and prevention strategies.