Response to Letter to the Editor Titled "Risk Modeling for Unplanned Intensive Care Unit (ICU) Admission".
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ABSTRACT:
SUBMITTER: Sukhonthamarn K
PROVIDER: S-EPMC7205677 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
Publications
Response to Letter to the Editor Titled "Risk Modeling for Unplanned Intensive Care Unit (ICU) Admission".
Sukhonthamarn Kamolsak K Grosso Matthew J MJ Parvizi Javad J
The Journal of arthroplasty 20200508 10
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Project description:Background: The Modified Early Warning Score (MEWS) has been proposed to warn healthcare providers of potentially serious adverse events. We evaluated this scoring system during unplanned escalation of care in hospitalized surgical patients during a 1-year period. Methods: Following institutional review board approval, all consecutive, unplanned surgical admissions into the surgical intensive care unit (SICU) during 2016 were entered into this study. MEWS and patient demographics during bedside evaluation for SICU admission were extracted from electronic medical records. Logistic regression was used to analyze the association of MEWS with the incidence of future mortality. P values were set at <0.01 for statistical significance. Results: In this series of 263 consecutive patients, the incidence of mortality following unplanned escalation of care was 29.3% (confidence interval [CI] 24.1% to 35.0%), ranging from 22% to 57%, with all positive MEWS values. The association of MEWS with future mortality was not statistically significant (P=0.0107). A misclassification rate of 0.29 (CI 0.24 to 0.35) was observed with this association. Conclusion: MEWS provided no clinical benefit as an early warning system, as mortality was elevated throughout the MEWS scale in this clinical setting. The high misclassification rate indicates MEWS does not provide discriminatory support for patients at risk for mortality.
| S-EPMC7310184 | biostudies-literature
Project description:In Response To: Walker RH. Reply to: Tardive dyskinesia-like syndrome due to drugs that do not block dopamine receptors: rare or non-existent: literature review. Tremor Other Hyperkinet Mov. 2019; 9. doi: 10.7916/3rez-p096 Original Article: D'Abreu A, Friedman JH. Tardive dyskinesia-like syndrome due to drugs that do not block dopamine receptors: rare or non-existent: literature review. Tremor Other Hyperkinet Mov. 2018; 8. doi: 10.7916/D8FF58Z9.
| S-EPMC6377913 | biostudies-other
Project description:BackgroundA higher chance of survival is a key justification for admission to the intensive care unit (ICU). This implies that physicians should be able to accurately estimate a patient's prognosis, whether cared for on the ward or in the ICU. We aimed to determine whether physicians' survival predictions correlate with the admission decisions and with patients' observed survival. Consecutive ICU consultations for internal medicine patients were included. The ICU physician and the internist were asked to predict patient survival with intensive care and with care on the ward using 5 categories of probabilities (< 10%, 10-40%, 41-60%, 61-90%, > 90%). Patient mortality at 28 days was recorded.ResultsThirty ICU physicians and 97 internists assessed 201 patients for intensive care. Among the patients, 140 (69.7%) were admitted to the ICU. Fifty-eight (28.9%) died within 28 days. Admission to intensive care was associated with predicted survival gain in the ICU, particularly for survival estimates made by ICU physicians. Observed survival was associated with predicted survival, for both groups of physicians. The discrimination of the predictions for survival with intensive care, measured by the area under the ROC curve, was 0.63 for ICU physicians and 0.76 for internists; for survival on the ward the areas under the ROC curves were 0.69 and 0.74, respectively.ConclusionsPhysicians are able to predict survival probabilities when they assess patients for intensive care, albeit imperfectly. Internists are more accurate than ICU physicians. However, ICU physicians' estimates more strongly influence the admission decision. Closer collaboration between ICU physicians and internists is needed.
| S-EPMC6236006 | biostudies-literature
Project description:NHS England recently mandated that the National Early Warning Score of vital signs be used in all acute hospital trusts in the UK despite limited validation in the postoperative setting. We undertook a multicentre UK study of 13,631 patients discharged from intensive care after risk-stratified cardiac surgery in four centres, all of which used VitalPACTM to electronically collect postoperative National Early Warning Score vital signs. We analysed 540,127 sets of vital signs to generate a logistic score, the discrimination of which we compared with the national additive score for the composite outcome of: in-hospital death; cardiac arrest; or unplanned intensive care admission. There were 578 patients (4.2%) with an outcome that followed 4300 sets of observations (0.8%) in the preceding 24 h: 499 out of 578 (86%) patients had unplanned re-admissions to intensive care. Discrimination by the logistic score was significantly better than the additive score. Respective areas (95%CI) under the receiver-operating characteristic curve with 24-h and 6-h vital signs were: 0.779 (0.771-0.786) vs. 0.754 (0.746-0.761), p < 0.001; and 0.841 (0.829-0.853) vs. 0.813 (0.800-0.825), p < 0.001, respectively. Our proposed logistic Early Warning Score was better than the current National Early Warning Score at discriminating patients who had an event after cardiac surgery from those who did not.
| S-EPMC6954099 | biostudies-literature
Project description:Intensive care unit (ICU) care is expensive for patients and providers, and utilization and spending on ICU resources have increased. The No Surprises Act, passed in 2022, specifically prohibits balance billing by ICU specialists (intensivists) for emergency and most non-emergency care. The potential economic impact of this remains unclear, given few data exist on the magnitude of balance billing in the ICU. Using the MarketScan Commercial (IBM) database, we studied hospitalizations in which ICU care was provided ("ICU hospitalizations") between 2010 and 2019. Hospitalizations were characterized as fully in-network, fully out-of-network, or "mixed" (contained both in- and out-of-network services). The share of "mixed" hospitalizations among all ICU hospitalizations rose from 26% to 33% over the study period. Over half of these mixed hospitalizations contained out-of-network services specifically delivered within the ICU. Total hospitalization spending averaged $81 047, with ICU spending averaging $15 799. On average, 11% of ICU spending within these hospitalizations was out-of-network. Patients were plausibly balance-billed in approximately one-third of ICU hospitalizations, for thousands of dollars per hospitalization. Given that the No Surprises Act prevents this type of balance billing, the portended revenue loss may lead to changes in provider negotiations with insurers concerning network status and prices, which could affect the care patients receive.
| S-EPMC10932732 | biostudies-literature
Project description:A hospital readmission is when a patient who was discharged from the hospital is admitted again for the same or related care within a certain period. Hospital readmissions are a significant problem in the healthcare domain, as they lead to increased hospitalization costs, decreased patient satisfaction, and increased risk of adverse outcomes such as infections, medication errors, and even death. The problem of hospital readmissions is particularly acute in intensive care units (ICUs), due to the severity of the patients' conditions, and the substantial risk of complications. Predicting Unplanned Readmissions in ICUs is a challenging task, as it involves analyzing different data modalities, such as static data, unstructured free text, sequences of diagnoses and procedures, and multivariate time-series. Here, we investigate the effectiveness of each data modality separately, then alongside with others, using state-of-the-art machine learning approaches in time-series analysis and natural language processing. Using our evaluation process, we are able to determine the contribution of each data modality, and for the first time in the context of readmission, establish a hierarchy of their predictive value. Additionally, we demonstrate the impact of Temporal Abstractions in enhancing the performance of time-series approaches to readmission prediction. Due to conflicting definitions in the literature, we also provide a clear definition of the term Unplanned Readmission to enhance reproducibility and consistency of future research and to prevent any potential misunderstandings that could result from diverse interpretations of the term. Our experimental results on a large benchmark clinical data set show that Discharge Notes written by physicians, have better capabilities for readmission prediction than all other modalities.
| S-EPMC10507073 | biostudies-literature
Project description: Not available
| S-EPMC6755881 | biostudies-literature
Project description:BackgroundThe Herpesviridae family contains several human-related viruses, which are able to establish colonizing and latency in the human body, posing a significant threat to the prognosis of patients. Pulmonary infections represent one of the predominant infectious diseases globally, characterized by diverse and multifaceted clinical manifestations that have consistently attracted clinician's concern. However, the relationship of herpesviruses on the prognosis of pulmonary infections and the respiratory microbiota remains poorly understood.MethodsHere, we retrospectively analyzed respiratory samples from 100 patients with pulmonary infection detected by metagenomic next-generation sequencing (mNGS).ResultsEmploying mNGS, five herpesvirus species were detected: Human alphaherpesvirus 1 (HSV-1), Human gammaherpesvirus 4 (EBV), Human betaherpesvirus 5 (CMV), Human betaherpesvirus 7 (HHV-7), and Human betaherpesvirus 6B (HHV-6B). Regression analysis showed that the age and positivity of herpesviruses in patients were independently correlated with ICU admission rates. In addition, positivity of herpesvirus was related with increased ICU days and total hospital stay. The herpesvirus-positive group demonstrated markedly higher incidences of co-infections and fungi-positive, predominantly involving Pneumocystis jirovecii and Aspergillus fumigatus. Analysis of respiratory microbiota revealed a substantially altered community composition within the herpesvirus-positive group, and herpesviruses were significantly positively correlated with the diverse respiratory opportunistic pathogens.ConclusionOverall results substantiate that the active herpesviruses in patients with pulmonary infections were significantly associated with high ICU admission rate. Moreover, the herpesviruses promotes the dysbiosis of the respiratory microbiota and an increased proportion of co-infections. These insights could contribute to unraveling the underlying mechanisms connecting active herpesviruses to the progression of severe illnesses.
| S-EPMC11342977 | biostudies-literature
Project description:IntroductionOvarian Hyperstimulation Syndrome (OHSS) is a life-threatening iatrogenic complication of In vitro fertilisation (IVF). This study aimed to quantify rates of Ovarian Hyperstimulation Syndrome (OHSS) requiring intensive care unit (ICU) admission and assess whether trends have changed between 1996-2020 commensurate with the introduction of safer IVF practices.MethodsData regarding Intensive Care Unit (ICU) admission across England, Wales and Northern Ireland was gathered retrospectively from the Intensive Care National Audit and Research Centre (ICNARC) database. 38,957 female patients aged between 18-55 years were admitted to ICU for OHSS or related conditions between 1996-2020. The primary outcome was the rate of OHSS requiring ICU admission expressed as a proportion of the number of fresh IVF cycles conducted in that year according to Human Fertility and Embryology Authority (HFEA) records. Baseline characteristics (for example, age, ethnicity, BMI), biochemical parameters (such as renal function, serum electrolytes), length of ICU stay and duration and need for organ support, were also compared between ICU patients with 'confirmed OHSS' and those 'without OHSS'.ResultsThere were 238 cases of 'confirmed OHSS' requiring ICU admission recorded between 1996-2020. Rates of OHSS requiring ICU admission declined over the study period (P=0.006); the annual rate of severe OHSS requiring intensive care admission halved when comparing those occurring between 1996-2007 and 2008-2020 (OR=0.37, 95% CI 0.37-0.45; P<0.0001). Patients spent a mean of 3.5 days in the ICU, with 86.3% of patients with 'confirmed OHSS' requiring at least 2 days of higher level (i.e., level 2 or 3) care. Patients with 'confirmed OHSS' required a shorter duration of renal, advanced cardiovascular, and advanced respiratory support than patients 'without OHSS' (P<0.0001 for all comparisons). There was no significant difference in BMI or ethnicity between those with 'confirmed OHSS' and those 'without OHSS', however women with 'confirmed OHSS' were younger (34 versus 41 years old, p<0.0001).DiscussionAlthough absolute rates of OHSS requiring ICU admission recorded in this study are likely to represent a significant underestimate of all clinically significant OHSS, rates of OHSS requiring ICU admission have decreased since 1996 in concordance with the introduction of modern IVF practices.
| S-EPMC9797661 | biostudies-literature