This cohort study investigates whether the prone position is associated with improved oxygenation and decreased risk for intubation in spontaneously breathing patients with severe COVID-19 hypoxemic ...respiratory failure.
Little is known about how real-time online rating platforms such as Yelp may complement the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, which is the US standard ...for evaluating patients' experiences after hospitalization. We compared the content of Yelp narrative reviews of hospitals to the topics in the HCAHPS survey, called domains in HCAHPS terminology. While the domains included in Yelp reviews covered the majority of HCAHPS domains, Yelp reviews covered an additional twelve domains not found in HCAHPS. The majority of Yelp topics that most strongly correlate with positive or negative reviews are not measured or reported by HCAHPS. The large collection of patient- and caregiver-centered experiences found on Yelp can be analyzed with natural language processing methods, identifying for policy makers the measures of hospital quality that matter most to patients and caregivers. The Yelp measures and analysis can also provide actionable feedback for hospitals.
Nirmatrelvir/ritonavir (Paxlovid), an oral antiviral medication targeting SARS‐CoV‐2, remains an important treatment for COVID‐19. Initial studies of nirmatrelvir/ritonavir were performed in ...SARS‐CoV‐2 unvaccinated patients without prior confirmed SARS‐CoV‐2 infection; however, most individuals have now either been vaccinated and/or have experienced SARS‐CoV‐2 infection. After nirmatrelvir/ritonavir became widely available, reports surfaced of “Paxlovid rebound,” a phenomenon in which symptoms (and SARS‐CoV‐2 test positivity) would initially resolve, but after finishing treatment, symptoms and test positivity would return. We used a previously described parsimonious mathematical model of immunity to SARS‐CoV‐2 infection to model the effect of nirmatrelvir/ritonavir treatment in unvaccinated and vaccinated patients. Model simulations show that viral rebound after treatment occurs only in vaccinated patients, while unvaccinated (SARS‐COV‐2 naïve) patients treated with nirmatrelvir/ritonavir do not experience any rebound in viral load. This work suggests that an approach combining parsimonious models of the immune system could be used to gain important insights in the context of emerging pathogens.
Objective
Crowdsourcing research allows investigators to engage thousands of people to provide either data or data analysis. However, prior work has not documented the use of crowdsourcing in health ...and medical research. We sought to systematically review the literature to describe the scope of crowdsourcing in health research and to create a taxonomy to characterize past uses of this methodology for health and medical research.
Data sources
PubMed, Embase, and CINAHL through March 2013.
Study eligibility criteria
Primary peer-reviewed literature that used crowdsourcing for health research.
Study appraisal and synthesis methods
Two authors independently screened studies and abstracted data, including demographics of the crowd engaged and approaches to crowdsourcing.
Results
Twenty-one health-related studies utilizing crowdsourcing met eligibility criteria. Four distinct types of crowdsourcing tasks were identified: problem solving, data processing, surveillance/monitoring, and surveying. These studies collectively engaged a crowd of >136,395 people, yet few studies reported demographics of the crowd. Only one (5 %) reported age, sex, and race statistics, and seven (33 %) reported at least one of these descriptors. Most reports included data on crowdsourcing logistics such as the length of crowdsourcing (n = 18, 86 %) and time to complete crowdsourcing task (n = 15, 71 %). All articles (n = 21, 100 %) reported employing some method for validating or improving the quality of data reported from the crowd.
Limitations
Gray literature not searched and only a sample of online survey articles included.
Conclusions and implications of key findings
Utilizing crowdsourcing can improve the quality, cost, and speed of a research project while engaging large segments of the public and creating novel science. Standardized guidelines are needed on crowdsourcing metrics that should be collected and reported to provide clarity and comparability in methods.
To examine the association between a measure of heart rate variability and sudden cardiac death (SCD) in COVID-19 patients.
Patients with SARS-COV-2 infection admitted to Columbia University Irving ...Medical Center who died between 4/25/2020 and 7/14/2020 and had an autopsy were examined for root mean square of successive differences (RMSSD), organ weights, and evidence of SCD.
Thirty COVID-19 patients were included and 12 had SCD. The RMSSD over 7 days without vs with SCD was median 0.0129 (IQR 0.0074–0.026) versus 0.0098 (IQR 0.0056–0.0197), p < 0.0001. The total adjusted adrenal weight of the non-SCD group was 0.40 g/kg (IQR 0.35–0.55) versus 0.25 g/kg (IQR 0.21–0.31) in the SCD group, p = 0.0007.
Hospitalized patients with COVID-19 who experienced SCD had lower parasympathetic activity (RMSSD) and smaller sized adrenal glands. Further research is required to replicate these findings.
COVID-19 presentations range from mild to moderate through severe disease but also manifest with persistent illness or viral recrudescence. We hypothesized that the spectrum of COVID-19 disease ...manifestations was a consequence of SARS-CoV-2-mediated delay in the pathogen-associated molecular pattern (PAMP) response, including dampened type I interferon signaling, thereby shifting the balance of the immune response to be dominated by damage-associated molecular pattern (DAMP) signaling. To test the hypothesis, we constructed a parsimonious mechanistic mathematical model. After calibration of the model for initial viral load and then by varying a few key parameters, we show that the core model generates four distinct viral load, immune response and associated disease trajectories termed "patient archetypes", whose temporal dynamics are reflected in clinical data from hospitalized COVID-19 patients. The model also accounts for responses to corticosteroid therapy and predicts that vaccine-induced neutralizing antibodies and cellular memory will be protective, including from severe COVID-19 disease. This generalizable modeling framework could be used to analyze protective and pathogenic immune responses to diverse viral infections.
•As artificial intelligence (AI) use in critical care increases, identifying and minimizing sources of bias is essential•Bias can be introduced (and be minimized) at all stages of the AI ...lifecycle•Reliance on AI in clinical practice without addressing bias may result in unfair and inequitable treatment of patients•Diverse, multidisciplinary teams that are attuned to sources of bias may have the best chance of minimizing bias in AI
Safety of Health Care in the Inpatient Setting Scanlon, Matthew C.; Catchpole, Kenneth R.; Dietz, Donald E. ...
The New England journal of medicine,
04/2023, Letnik:
388, Številka:
16
Journal Article
Recenzirano
To the Editor:
In their article on the safety of inpatient health care, Bates and colleagues (Jan. 12 issue)
1
describe events that should not surprise anyone for three key reasons. First, many in ...the health care field ignored a warning in 1997 that a focus on “human error” according to data regarding patient safety “would delay any real progress on safety for a decade or more.”
2
Error-related literature supports rejecting “human error as a cause of accidents and adverse events.”
3
However, the patient-safety movement remains fixated on human error instead of complex sociotechnical systems as the cause of preventable harm. . . .
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