Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis

Early recognition and treatment of sepsis are linked to improved patient outcomes. Machine learning-based early warning systems may reduce the time to recognition, but few systems have undergone clinical evaluation. In this prospective, multi-site cohort study, we examined the association between patient outcomes and provider interaction with a deployed sepsis alert system called the Targeted Real-time Early Warning System (TREWS). During the study, 590,736 patients were monitored by TREWS across five hospitals. We focused our analysis on 6,877 patients with sepsis who were identified by the alert before initiation of antibiotic therapy. Adjusting for patient presentation and severity, patients in this group whose alert was confirmed by a provider within 3 h of the alert had a reduced in-hospital mortality rate (3.3%, confidence interval (CI) 1.7, 5.1%, adjusted absolute reduction, and 18.7%, CI 9.4, 27.0%, adjusted relative reduction), organ failure and length of stay compared with patients whose alert was not confirmed by a provider within 3 h. Improvements in mortality rate (4.5%, CI 0.8, 8.3%, adjusted absolute reduction) and organ failure were larger among those patients who were additionally flagged as high risk. Our findings indicate that early warning systems have the potential to identify sepsis patients early and improve patient outcomes and that sepsis patients who would benefit the most from early treatment can be identified and prioritized at the time of the alert.

Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score

Importance

Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings.

Objectives

To develop an objective measure of PD severity and test construct validity by evaluating the ability of the measure to capture intraday symptom fluctuations, correlate with current standard PD outcome measures, and respond to dopaminergic therapy.

Design, Setting, and Participants

This observational study assessed individuals with PD who remotely completed 5 tasks (voice, finger tapping, gait, balance, and reaction time) on the smartphone application. We used a novel machine-learning-based approach to generate a mobile Parkinson disease score (mPDS) that objectively weighs features derived from each smartphone activity (eg, stride length from the gait activity) and is scaled from 0 to 100 (where higher scores indicate greater severity). Individuals with and without PD additionally completed standard in-person assessments of PD with smartphone assessments during a period of 6 months.

Main Outcomes and Measures

Ability of the mPDS to detect intraday symptom fluctuations, the correlation between the mPDS and standard measures, and the ability of the mPDS to respond to dopaminergic medication.

Results

The mPDS was derived from 6148 smartphone activity assessments from 129 individuals (mean [SD] age, 58.7 [8.6] years; 56 [43.4%] women). Gait features contributed most to the total mPDS (33.4%). In addition, 23 individuals with PD (mean [SD] age, 64.6 [11.5] years; 11 [48%] women) and 17 without PD (mean [SD] age 54.2 [16.5] years; 12 [71%] women) completed in-clinic assessments. The mPDS detected symptom fluctuations with a mean (SD) intraday change of 13.9 (10.3) points on a scale of 0 to 100. The measure correlated well with the Movement Disorder Society Unified Parkinson Disease's Rating Scale total (r = 0.81; P < .001) and part III only (r = 0.88; P < .001), the Timed Up and Go assessment (r = 0.72; P = .002), and the Hoehn and Yahr stage (r = 0.91; P < .001). The mPDS improved by a mean (SD) of 16.3 (5.6) points in response to dopaminergic therapy.

Conclusions and Relevance

Using a novel machine-learning approach, we created and demonstrated construct validity of an objective PD severity score derived from smartphone assessments. This score complements standard PD measures by providing frequent, objective, real-world assessments that could enhance clinical care and evaluation of novel therapeutics.

Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD

Objective

We sought to identify motor features that would allow the delineation of individuals with sleep study-confirmed idiopathic REM sleep behavior disorder (iRBD) from controls and Parkinson disease (PD) using a customized smartphone application.

Methods

A total of 334 PD, 104 iRBD, and 84 control participants performed 7 tasks to evaluate voice, balance, gait, finger tapping, reaction time, rest tremor, and postural tremor. Smartphone recordings were collected both in clinic and at home under noncontrolled conditions over several days. All participants underwent detailed parallel in-clinic assessments. Using only the smartphone sensor recordings, we sought to (1) discriminate whether the participant had iRBD or PD and (2) identify which of the above 7 motor tasks were most salient in distinguishing groups.

Results

Statistically significant differences based on these 7 tasks were observed between the 3 groups. For the 3 pairwise discriminatory comparisons, (1) controls vs iRBD, (2) controls vs PD, and (3) iRBD vs PD, the mean sensitivity and specificity values ranged from 84.6% to 91.9%. Postural tremor, rest tremor, and voice were the most discriminatory tasks overall, whereas the reaction time was least discriminatory.

Conclusions

Prodromal forms of PD include the sleep disorder iRBD, where subtle motor impairment can be detected using clinician-based rating scales (e.g., Unified Parkinson's Disease Rating Scale), which may lack the sensitivity to detect and track granular change. Consumer grade smartphones can be used to accurately separate not only iRBD from controls but also iRBD from PD participants, providing a growing consensus for the utility of digital biomarkers in early and prodromal PD.

Automated Quality Control for Sensor Based Symptom Measurement Performed Outside the Lab

The use of wearable sensing technology for objective, non-invasive and remote clinimetric testing of symptoms has considerable potential. However, the accuracy achievable with such technology is highly reliant on separating the useful from irrelevant sensor data. Monitoring patient symptoms using digital sensors outside of controlled, clinical lab settings creates a variety of practical challenges, such as recording unexpected user behaviors. These behaviors often violate the assumptions of clinimetric testing protocols, where these protocols are designed to probe for specific symptoms. Such violations are frequent outside the lab and affect the accuracy of the subsequent data analysis and scientific conclusions. To address these problems, we report on a unified algorithmic framework for automated sensor data quality control, which can identify those parts of the sensor data that are sufficiently reliable for further analysis. Combining both parametric and nonparametric signal processing and machine learning techniques, we demonstrate that across 100 subjects and 300 clinimetric tests from three different types of behavioral clinimetric protocols, the system shows an average segmentation accuracy of around 90%. By extracting reliable sensor data, it is possible to strip the data of confounding factors in the environment that may threaten reproducibility and replicability.

Development of an Exergame for Urban-dwelling Older Adults With Functional Limitations: Results and Lessons Learned

BACKGROUND

Falls at home are common and potentially fatal for disabled older adults. To address this problem, we created an academic-community partnership involving disabled, urban-dwelling older adults and their families, the housing authority, a Tai Chi master, and a university.

OBJECTIVES

We conducted a pilot to assess safety, acceptability, and feasibility of a Wii-based exergame designed to increase disabled older adults' strength and balance.

METHODS

A working prototype was developed and evaluated. Then, we piloted a refined version with 19 disabled urban-dwelling older adults.

RESULTS

The program was enjoyable, feasible, and acceptable. Participants described multiple functional improvements. Of the 16 who completed at least three gaming sessions, average balance score increased 25% and gait speed increased 19%.

CONCLUSIONS

This pilot showed promising results for improving strength and balance in the home setting, and yielded valuable lessons about health technology development with community partners.

Looking at both sides of the invasion: patterns of colonization in the violet tunicate Botrylloides violaceus

Understanding the ecological and evolutionary forces that shape the genetic structure of invasive populations and facilitate their expansion across a large spectrum of environments is critical for the prediction of spread and management of ongoing invasions. Here, we study the dynamics of postestablishment colonization in the colonial ascidian Botrylloides violaceus, a notorious marine invader. After its initial introduction from the Northwest Pacific, B. violaceus spread rapidly along the Pacific and Atlantic coasts of North America, impacting both aquaculture facilities and natural ecosystems. We compare genetic diversity and patterns of gene flow among 25 populations (N=679) from the West and East coasts, and evaluate the contribution of sexual vs. asexual reproduction to this species' invasion success using data from the mitochondrial cytochrome c oxidase subunit I (COI) gene and 13 nuclear polymorphic microsatellite loci. Our results reveal contrasting patterns of spread in the coastal waters of North America. While the West coast was colonized by noncontiguous (long-distance) dispersal, the East coast invasion appears to have occurred through contiguous (stepping-stone) spread. Molecular data further indicate that although dispersal in colonial ascidians is predominantly achieved through sexually produced propagules, aquaculture practices such as high-pressure washing can facilitate fragmentation and potentially exacerbate infestations and spread via asexual propagules. The results presented here suggest that caution should be used against the general assumption that all invasions, even within a single species, exhibit similar patterns of colonization, as highly contrasting dynamics may transpire in different invaded ranges.

Spontaneous malignant transformation of fibrous dysplasia

OBJECTIVE

To evaluate the clinical and radiological findings in diagnosing spontaneous malignant transformation of fibrous dysplasia.

METHODS

Fifteen cases of sarcomatous transformation proved by operation and pathological examinations were found in a group of 356 patients with fibrous dysplasia, and their radiological manifestations were retrospectively studied. The 15 cases included 8 osteosarcomas, 5 fibrosarcomas and 2 chondrosarcomas. All the 15 patients were known to have long-standing fibrous dysplasia, but no radiation therapy was ever received. Eleven patients had polyostotic fibrous dysplasia and 4 had monostotic type.

RESULTS

Malignant transformation most frequently occurs in the cystic expansive lesion of the long tubular bone. Pains, swelling and late appearance of a bony mass are the main clinical manifestations. The early radiological features of sarcomatous transformation in fibrous dysplasia are moth-eaten or cystic areas of osteolysis located in the involved bone. The cortical destruction and gradual formation of a soft tissue mass that contains tumor-bone are highly suspicious of osteosarcomatous transformation, while ring-like and spotty calcification in the tumor matrix is indicative of chondrosarcoma. Fibrosarcoma usually shows simple osteolytic destruction.

CONCLUSIONS

According to the clinical radiological findings, patients of sarcomatous transformation can be detected in the early stage. These radiological findings may be used as a clue for differentiating various kinds of sarcomatous transformation.