Clinical Deterioration In Patients Research Articles

Prognostic Accuracy of Screening Tools for Clinical Deterioration in Adults With Suspected Sepsis in Northeastern Thailand: A Cohort Validation Study.

We sought to assess the performance of commonly used clinical scoring systems to predict imminent clinical deterioration in patients hospitalized with suspected infection in rural Thailand. Patients with suspected infection were prospectively enrolled within 24 hours of admission to a referral hospital in northeastern Thailand between 2013 and 2017. In patients not requiring intensive medical interventions, multiple enrollment scores were calculated including the National Early Warning Score (NEWS), the Modified Early Warning Score, Between the Flags, and the quick Sequential Organ Failure Assessment score. Scores were tested for predictive accuracy of clinical deterioration, defined as a new requirement of mechanical ventilation, vasoactive medications, intensive care unit admission, and/or death approximately 1 day after enrollment. The association of each score with clinical deterioration was evaluated by means of logistic regression, and discrimination was assessed by generating area under the receiver operating characteristic curve. Of 4989 enrolled patients, 2680 met criteria for secondary analysis, and 100 of 2680 (4%) experienced clinical deterioration within 1 day after enrollment. NEWS had the highest discrimination for predicting clinical deterioration (area under the receiver operating characteristic curve, 0.78 [95% confidence interval, .74-.83]) compared with the Modified Early Warning Score (0.67 [.63-.73]; P < .001), quick Sequential Organ Failure Assessment (0.65 [.60-.70]; P < .001), and Between the Flags (0.69 [.64-.75]; P < .001). NEWS ≥5 yielded optimal sensitivity and specificity for clinical deterioration prediction. In patients hospitalized with suspected infection in a resource-limited setting in Southeast Asia, NEWS can identify patients at risk of imminent clinical deterioration with greater accuracy than other clinical scoring systems.

Early treatment with fluvoxamine, bromhexine, cyproheptadine, and niclosamide to prevent clinical deterioration in patients with symptomatic COVID-19: a randomized clinical trial

Repurposed drugs with host-directed antiviral and immunomodulatory properties have shown promise in the treatment of COVID-19, but few trials have studied combinations of these agents. The aim of this trial was to assess the effectiveness of affordable, widely available, repurposed drugs used in combination for treatment of COVID-19, which may be particularly relevant to low-resource countries. We conducted an open-label, randomized, outpatient, controlled trial in Thailand from October 1, 2021, to June 21, 2022, to assess whether early treatment within 48-h of symptoms onset with combinations of fluvoxamine, bromhexine, cyproheptadine, and niclosamide, given to adults with confirmed mild SARS-CoV-2 infection, can prevent 28-day clinical deterioration compared to standard care. Participants were randomly assigned to receive treatment with fluvoxamine alone, fluvoxamine+bromhexine, fluvoxamine+cyproheptadine, niclosamide+bromhexine, or standard care. The primary outcome measured was clinical deterioration within 9, 14, or 28 days using a 6-point ordinal scale. This trial is registered with ClinicalTrials.gov (NCT05087381). Among 1900 recruited, a total of 995 participants completed the trial. No participants had clinical deterioration by day 9, 14, or 28 days among those treated with fluvoxamine plus bromhexine (0%), fluvoxamine plus cyproheptadine (0%), or niclosamide plus bromhexine (0%). Nine participants (5.6%) in the fluvoxamine arm had clinical deterioration by day 28, requiring low-flow oxygen. In contrast, most standard care arm participants had clinical deterioration by 9, 14, and 28 days. By day 9, 32.7% (110) of patients in the standard care arm had been hospitalized without requiring supplemental oxygen but needing ongoing medical care. By day 28, this percentage increased to 37.5% (21). Additionally, 20.8% (70) of patients in the standard care arm required low-flow oxygen by day 9, and 12.5% (16) needed non-invasive or mechanical ventilation by day 28. All treated groups significantly differed from the standard care group by days 9, 14, and 28 (p<0.0001). Also, by day 28, the three 2-drug treatments were significantly better than the fluvoxamine arm (p<0.0001). No deaths occurred in any study group. Compared to standard care, participants treated with the combination agents had significantly decreased viral loads as early as day 3 of treatment (p<0.0001), decreased levels of serum cytokines interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and interleukin-1 beta (IL-1β) as early as day 5 of treatment, and interleukin-8 (IL-8) by day 7 of treatment (p<0.0001) and lower incidence of post-acute sequelae of COVID-19 (PASC) symptoms (p<0.0001). 23 serious adverse events occurred in the standard care arm, while only 1 serious adverse event was reported in the fluvoxamine arm, and zero serious adverse events occurred in the other arms. Early treatment with these combinations among outpatients diagnosed with COVID-19 was associated with lower likelihood of clinical deterioration, and with significant and rapid reduction in the viral load and serum cytokines, and with lower burden of PASC symptoms. When started very soon after symptom onset, these repurposed drugs have high potential to prevent clinical deterioration and death in vaccinated and unvaccinated COVID-19 patients. Ped Thai Su Phai (Thai Ducks Fighting Danger) social giver group.

The medical emergency team pharmacist: describing an overnight service

AbstractBackgroundClinical practice after hours and attendance at medical emergency team (MET) calls are two novel and emerging areas of pharmacy practice. During the COVID‐19 pandemic, our institution's pharmacy services expanded from 8 am–5 pm to 24 h daily, including MET call attendance.AimThis study aimed to describe pharmacist roles, including medications charted by the general medicine and intensive care unit pharmacists during the period of extended‐hours pharmacy practice and the characteristics of MET calls attended.MethodThis descriptive, cross‐sectional study included patients admitted to the Alfred Hospital, Victoria, Australia between 3 April 2020–28 February 2021, when a MET was called between 5 pm–8 am, a pharmacist attended, and medication changes occurred. Data collected included whether the MET call was medication related and a description of medication changes. Ethics approval was granted by the Alfred Hospital Human Research Ethics Committee (Reference no: 297/21).ResultsOne thousand six hundred and forty‐four MET calls (average 5.4 calls per night) were attended by pharmacists during extended hours. Medication changes were made in response to clinical deterioration at 627 (38%) calls. The most frequent change was the initiation of cardiovascular medications (n = 206). Partnered pharmacist medication charting, including commencing, ceasing, or changing medications, occurred at 39% of MET calls with therapy changes.ConclusionPharmacists can play a key role in managing deteriorating patients as part of a MET team. Medications may be implicated in clinical deterioration of patients and are frequently administered at MET calls. The expansion of pharmacy services provided the opportunity for pharmacists to contribute to MET calls across the 24‐h period.

Risk factors and predicting nomogram for the clinical deterioration of non-severe community-acquired pneumonia

BackgroundCurrently, there remains insufficient focus on non-severe community-acquired pneumonia (CAP) patients who are at risk of clinical deterioration, and there is also a dearth of research on the related risk factors. Early recognition of hospitalized patients at risk of clinical deterioration will be beneficial for their clinical management.MethodA retrospective study was conducted in The First Affiliated Hospital of Wenzhou Medical University, China, spanning from January 1, 2018 to April 30, 2022, and involving a total of 1,632 non-severe CAP patients. Based on whether their condition worsened within 72 h of admission, patients were divided into a clinical deterioration group and a non-clinical deterioration group. Additionally, all patients were randomly assigned to a training set containing 75% of patients and a validation set containing 25% of patients. In the training set, risk factors for clinical deterioration in patients with non-severe CAP were identified by using LASSO regression analysis and multivariate logistic regression analysis. A nomogram was developed based on identified risk factors. The effectiveness of the nomogram in both the training and validation sets was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).ResultsAge, body mass index (BMI), body temperature, cardiovascular comorbidity, respiratory rate, LDH level, lymphocyte count and D-dimer level were identified as risk factors associated with the clinical deterioration of non-severe CAP within 72 h of admission. The area under curve (AUC) value of the nomogram was 0.78 (95% CI: 0.74–0.82) in the training set and 0.75 (95% CI: 0.67–0.83) in the validation set. Furthermore, the calibration curves for both the training and validation sets indicated that the predicted probability of clinical deterioration aligned with the actual probability. Additionally, DCA revealed clinical utility for the nomogram at a specific threshold probability.ConclusionThe study successfully identified the risk factors linked to the clinical deterioration of non-severe CAP and constructed a nomogram for predicting the probability of deterioration. The nomogram demonstrated favorable predictive performance and has the potential to aid in the early identification and management of non-severe CAP patients at elevated risk of deterioration.

Validation of oxygen saturations measured in the community by emergency medical services as a marker of clinical deterioration in patients with confirmed COVID-19: a retrospective cohort study

ObjectivesTo evaluate oxygen saturation and vital signs measured in the community by emergency medical services (EMS) as clinical markers of COVID-19-positive patient deterioration.DesignA retrospective data analysis.SettingPatients were conveyed by EMS...

MAJOR REASONS FOR HOSPITALIZATION TO ICU OF CHILDREN WITH ACUTE LYMPHOBLASTIC LEUKEMIA: A LITERATURE REVIEW

Relevance: Acute lymphoblastic leukemia (ALL) is a common malignancy in children. Approximately 85% of ALLs have B-cell origin, and 15% are T-cell ALLs. Many patients diagnosed with hematologic cancer will require hospitalization in the intensive care unit (ICU) at some point in their treatment.&#x0D; The aim was to study the available literature on clinical deterioration in patients with АLL admitted to the ICU, the clinical significance and prognostic value of causes of clinical deterioration, and adverse outcomes in patients with АLL staying in the ICU.&#x0D; Methods: A descriptive cross-sectional study approach was used. We reviewed published sources from 2016 to 2023 to collect data on major reasons for ALL patients’ hospitalization to ICU.&#x0D; Results: First, the patient’s age at the time of initial diagnosis of ALL is crucial. Cure rates for B-cell ALL are higher between 1 and 9 years of age than in other age groups. Second, the initial white blood cell count during diagnosis is a prognostic indicator. Third, the specific subtype of ALL also affects prognosis. The risk factors emphasize the importance of comorbidities and infectious diseases, as well as monitoring and managing pulmonary and cardiovascular function in patients to avoid hospitalization in the ICU. The main causes of hospitalization in the ICU are complications related to chemotherapy, infection, and unplanned hospitalizations. Compared to normal-risk patients, high-risk patients had a higher rate of OIT hospitalization in the ICU. It is important to control chemotherapy and infections to reduce the number of admissions to the ICU in this group.&#x0D; Conclusion: Chemotherapy, concomitant and infectious diseases, hypoxia, and hemodynamic instability are reasons for hospitalization of these patients to ICU. The condition of various organs and systems shall be monitored.

MAJOR REASONS FOR HOSPITALIZATION TO ICU OF CHILDREN&#x0D; WITH ACUTE LYMPHOBLASTIC LEUKEMIA:&#x0D; A LITERATURE REVIEW

Relevance: Acute lymphoblastic leukemia (ALL) is a common malignancy in children. Approximately 85% of ALLs have B-cell origin, and 15% are&#x0D; T-cell ALLs. Many patients diagnosed with hematologic cancer will require hospitalization in the intensive care unit (ICU) at some point in their treatment.&#x0D; The aim was to study the available literature on clinical deterioration in patients with АLL admitted to the ICU, the clinical significance&#x0D; and prognostic value of causes of clinical deterioration, and adverse outcomes in patients with АLL staying in the ICU.&#x0D; Methods: A descriptive cross-sectional study approach was used. We reviewed published sources from 2016 to 2023 to collect data on major&#x0D; reasons for ALL patients’ hospitalization to ICU.&#x0D; Results: First, the patient’s age at the time of initial diagnosis of ALL is crucial. Cure rates for B-cell ALL are higher between 1 and 9 years of&#x0D; age than in other age groups. Second, the initial white blood cell count during diagnosis is a prognostic indicator. Third, the specific subtype of ALL&#x0D; also affects prognosis. The risk factors emphasize the importance of comorbidities and infectious diseases, as well as monitoring and managing&#x0D; pulmonary and cardiovascular function in patients to avoid hospitalization in the ICU. The main causes of hospitalization in the ICU are complications related to chemotherapy, infection, and unplanned hospitalizations. Compared to normal-risk patients, high-risk patients had a higher rate of&#x0D; OIT hospitalization in the ICU. It is important to control chemotherapy and infections to reduce the number of admissions to the ICU in this group.&#x0D; Conclusion: Chemotherapy, concomitant and infectious diseases, hypoxia, and hemodynamic instability are reasons for hospitalization of&#x0D; these patients to ICU. The condition of various organs and systems shall be monitored.

Eleven years of experience in operating a pediatric rapid response system at a children's hospital in South Korea.

Various rapid response systems have been developed to detect clinical deterioration in patients. Few studies have evaluated single-parameter systems in children compared to scoring systems. Therefore, in this study we evaluated a single-parameter system called the acute response system (ARS). This retrospective study was performed at a tertiary children's hospital. Patients under 18 years old admitted from January 2012 to August 2023 were enrolled. ARS parameters such as systolic blood pressure, heart rate, respiratory rate, oxygen saturation, and whether the ARS was activated were collected. We divided patients into two groups according to activation status and then compared the occurrence of critical events (cardiopulmonary resuscitation or unexpected intensive care unit admission). We evaluated the ability of ARS to predict critical events and calculated compliance. We also analyzed the correlation between each parameter that activates ARS and critical events. The critical events prediction performance of ARS has a specificity of 98.5%, a sensitivity of 24.0%, a negative predictive value of 99.6%, and a positive predictive value of 8.1%. The compliance rate was 15.6%. Statistically significant increases in the risk of critical events were observed for all abnormal criteria except low heart rate. There was no significant difference in the incidence of critical events. ARS, a single parameter system, had good specificity and negative predictive value for predicting critical events; however, sensitivity and positive predictive value were not good, and medical staff compliance was poor.

Efficacy of sacubitril / valsartan in the treatment of chronic heart failure: an updated review

Chronic heart failure (CHF) is currently a common disease and the search for new approaches to the treatment of various forms of CHF remains relevant. Sacubitril/valsartan is a member of a new class of angiotensin-neprilysin receptor inhibitors (ARNIs) that act on key neurohormonal mechanisms, including the RAAS and natriuretic peptides. Simultaneous inhibition of RAAS and neprilysin provides more effective neurohormonal modulation, preventing clinical deterioration in patients with CHF. New mechanisms of action of sacubitril/valsartan associated with the inhibition of several targets involved in cardiac hypertrophy, fibrosis, cardiac remodeling and apoptosis have been disclosed. Sacubitril/valsartan is recommended for CHF with low ejection fraction (EF) in addition to traditional therapy with ACE inhibitors, mineralocorticoid receptor antagonists, beta-blockers, and also has an independent effect. A number of studies have shown the effect of sacubitril/valsartan on heart remodeling, a decrease in the level of the NT-proBNP biomarker and an improvement in EF, and according to the PARADIGM-HF study, the drug significantly reduced the risk of cardiovascular mortality by 20% and hospitalizations for CHF by 21%, which found confirmation in three meta-analyses. The use of sacubitril/valsartan in CHF with preserved and intermediate EF showed a beneficial therapeutic effect and a decrease in the level of biomarkers, as well as a significant decrease in the frequency of hospitalizations due to CHF by 15–22%, but without a significant advantage in terms of the effect on mortality, which supported by several meta-analyses of studies. A number of large meta-analyses of studies of sacubitril/valsartan in CHF have shown reverse cardiac remodeling and a reduced risk of atrial fibrillation. Thus, the accumulated data substantiate and expand the possibilities of using sacu-bitril/valsartan in CHF.

Nursing Training for Early Clinical Deterioration Risk Assessment: Protocol for an Implementation Study.

During the hospitalization period, it is possible to observe considerable changes in the vital parameters of patients, which may require emergency interventions or intensive treatment. The alteration of signs and symptoms that lead to physiological instability that can worsen the clinical picture with progression to shock, respiratory failure, or cardiorespiratory arrest is currently defined as clinical deterioration. Identifying signs of clinical deterioration at an early stage can lead to substantial decreases in mortality rates, the need for emergency interventions, and unscheduled treatments in intensive care units. Identifying and appropriately referring patients who show signs of clinical deterioration can be facilitated by applying early warning systems that provide rapid responses. The nursing team is usually the first to identify clinical changes in patients. Although the literature demonstrates that early recognition of clinical deterioration is the key to early intervention and leads to better outcomes, we only sometimes pursue the most appropriate intervention. This study aims to implement and evaluate an evidence-based professional training program designed for nurses and coordinated by a nurse using the "just-in-time" methodology and the National Early Warning Score 2 (NEWS2) to assess the risk of early clinical deterioration and appropriate referral in inpatient units of a public university hospital in southeastern Brazil. This intervention protocol is structured according to the recommendations of the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) Declaration 2013. The type of training to be offered, "Just-in-Time Training," consists of a teaching modality that facilitates the delivery of a time-based and work-based education, with greater emphasis on providing on-the-job learning as needed. A qualitative stage will also be conducted through focus groups and interviews with nurses to verify the factors that influence the professional practice related to the early evaluation of the clinic. A script of previously tested questions will guide and standardize the different groups. The data will define the intervention's elements: the strategy, the type of training, the location, the teaching methodology, and the teaching material. The study has received authorization from the ethics committee, and participants will be recruited in July 2023. Data collection should be completed in October of the same year. The results obtained at the end of this research will be shared with the participating nursing team through the presentation of reports. In addition, the research results will be submitted to scientific journals and presented at international scientific conferences. This study will support nurses and possibly other clinicians to improve their approach to early recognition of clinical deterioration in patients. Brazilian Registry of Clinical Trials RBR-5hq9y3k; https://ensaiosclinicos.gov.br/rg/RBR-5hq9y3k. PRR1-10.2196/47293.

Meta-analysis of quality of life in patients with cancer treated with antibody-drug conjugates in randomized controlled trials.

Purpose: To evaluate the patient-reported outcomes of patients treated with commercially approved antibody-drug conjugates (ADC) reported in randomized controlled trials (RCT) published up toSeptember 2023. Methods: A meta-analysis of 6430 patients from 12randomized controlled trials wasconducted. Results: No significant change was observed between the groups from baseline to end of treatment and end of follow-up, with a standardized mean difference of -0.08 (95% CI: -0.27-0.12) and 0.01 (95% CI: -0.11-0.12), respectively. Treatment with ADCs delayed the deterioration of patients' clinical condition compared with treatment with non-ADCs, with a hazard ratioof 0.78 (95% CI: 0.67-0.92). Conclusion: ADCs have a good correlation with delay of clinical deterioration in patients with cancer.

Noninvasive Assessment of Impaired Gas Exchange with the Alveolar Gas Monitor Predicts Clinical Deterioration in COVID-19 Patients.

The COVID-19 pandemic magnified the importance of gas exchange abnormalities in early respiratory failure. Pulse oximetry (SpO2) has not been universally effective for clinical decision-making, possibly because of limitations. The alveolar gas monitor (AGM100) adds exhaled gas tensions to SpO2 to calculate the oxygen deficit (OD). The OD parallels the alveolar-to-arterial oxygen difference (AaDO2) in outpatients with cardiopulmonary disease. We hypothesized that the OD would discriminate between COVID-19 patients who require hospital admission and those who are discharged home, as well as predict need for supplemental oxygen during the index hospitalization. Patients presenting with dyspnea and COVID-19 were enrolled with informed consent and had OD measured using the AGM100. The OD was then compared between admitted and discharged patients and between patients who required supplemental oxygen and those who did not. The OD was also compared to SpO2 for each of these outcomes using receiver operating characteristic (ROC) curves. Thirty patients were COVID-19 positive and had complete AGM100 data. The mean OD was significantly (p = 0.025) higher among those admitted 50.0 ± 20.6 (mean ± SD) vs. discharged 27.0 ± 14.3 (mean ± SD). The OD was also significantly (p < 0.0001) higher among those requiring supplemental oxygen 60.1 ± 12.9 (mean ± SD) vs. those remaining on room air 25.2 ± 11.9 (mean ± SD). ROC curves for the OD demonstrated very good and excellent sensitivity for predicting hospital admission and supplemental oxygen administration, respectively. The OD performed better than an SpO2 threshold of <94%. The AGM100 is a novel, noninvasive way of measuring impaired gas exchange for clinically important endpoints in COVID-19.

Quick sepsis-related organ failure assessment in identifying clinical deterioration in patients with COVID-19

Quick sepsis-related organ failure assessment in identifying clinical deterioration in patients with COVID-19

Gut Microbiota Dysbiosis in COVID-19: Modulation and Approaches for Prevention and Therapy.

Inflammation and oxidative stress are critical underlying mechanisms associated with COVID-19 that contribute to the complications and clinical deterioration of patients. Additionally, COVID-19 has the potential to alter the composition of patients' gut microbiota, characterized by a decreased abundance of bacteria with probiotic effects. Interestingly, certain strains of these bacteria produce metabolites that can target the S protein of other coronaviruses, thereby preventing their transmission and harmful effects. At the same time, the presence of gut dysbiosis can exacerbate inflammation and oxidative stress, creating a vicious cycle that perpetuates the disease. Furthermore, it is widely recognized that the gut microbiota can metabolize various foods and drugs, producing by-products that may have either beneficial or detrimental effects. In this regard, a decrease in short-chain fatty acid (SCFA), such as acetate, propionate, and butyrate, can influence the overall inflammatory and oxidative state, affecting the prevention, treatment, or worsening of COVID-19. This review aims to explore the current evidence regarding gut dysbiosis in patients with COVID-19, its association with inflammation and oxidative stress, the molecular mechanisms involved, and the potential of gut microbiota modulation in preventing and treating SARS-CoV-2 infection. Given that gut microbiota has demonstrated high adaptability, exploring ways and strategies to maintain good intestinal health, as well as an appropriate diversity and composition of the gut microbiome, becomes crucial in the battle against COVID-19.

Reduced risk of mortality among COVID-19 patients with in-hospital selective serotonin reuptake inhibitor administration

Abstract Objectives The anti-inflammatory properties of selective serotonin reuptake inhibitors (SSRI)s, particularly fluvoxamine, have been hypothesized to reduce clinical deterioration in patients with COVID-19 when administered early in the disease course. The objective of this analysis was to examine the effect of maintenance SSRI administration, including variation among different medications, on the outcomes of hospitalized patients with COVID-19. Methods Retrospective analysis of disease progression and mortality risk of over 230,000 patients hospitalized with COVID-19 at facilities associated with a large healthcare system in the United States. Key findings Receipt of SSRIs during the hospital encounter occurred in approximately 10.6% (n = 24,690) of COVID-19 patients. When matched for patient characteristics, disease severity and other treatments, receipt of any SSRI was associated with a 30% reduction in the relative risk of mortality (RR: 0.70, 95% confidence interval [CI]: 0.67–0.73; adjusted P-value &amp;lt;0.001). Similar reductions in the relative risk of mortality were seen with nearly every individual SSRI; for sertraline-treated patients, the most commonly used SSRI in the data set, there was a 29% reduction in the relative risk of mortality (RR: 0.71, 95% CI: 0.66–0.77; adjusted P-value &amp;lt;0.001). Conclusions In total, this retrospective analysis suggests that there is a significant association between SSRI antidepressants and reduced morality among patients hospitalized with COVID-19.

Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.

We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems. A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death. The final population comprised 743 patients (mean age 65 ± 17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores. Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time. Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.

Development of a machine learning-based clinical decision support system to predict clinical deterioration in patients visiting the emergency department

This study aimed to develop a machine learning-based clinical decision support system for emergency departments based on the decision-making framework of physicians. We extracted 27 fixed and 93 observation features using data on vital signs, mental status, laboratory results, and electrocardiograms during emergency department stay. Outcomes included intubation, admission to the intensive care unit, inotrope or vasopressor administration, and in-hospital cardiac arrest. eXtreme gradient boosting algorithm was used to learn and predict each outcome. Specificity, sensitivity, precision, F1 score, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve were assessed. We analyzed 303,345 patients with 4,787,121 input data, resampled into 24,148,958 1 h-units. The models displayed a discriminative ability to predict outcomes (AUROC > 0.9), and the model with lagging 6 and leading 0 displayed the highest value. The AUROC curve of in-hospital cardiac arrest had the smallest change, with increased lagging for all outcomes. With inotropic use, intubation, and intensive care unit admission, the range of AUROC curve change with the leading 6 was the highest according to different amounts of previous information (lagging). In this study, a human-centered approach to emulate the clinical decision-making process of emergency physicians has been adopted to enhance the use of the system. Machine learning-based clinical decision support systems customized according to clinical situations can help improve the quality of care.

Telemonitoring heart failure in a remote region: data from cardiac implantable electronic devices

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Heart failure (HF) represents an important burden to the medical system attending to its high prevalence and high risk of hospital admissions by decompensations. Remote monitoring (RM) systems using invasive and non-invasive parameters were developed to anticipate clinical deterioration in patients with cardiac implantable electronic devices (CIEDs). Objective To characterize a cohort of patients with HF and CIEDs in an outermost region. We aimed to accessed data from monitoring device algorithms and to analyze the real impact in clinical decompensations, hospital admissions and all-cause mortality. Methods Retrospectively multicenter cohort study included 211 patients with HFrEF and CIEDs, between 2010 and 2020. This study population was divided into two specific groups: Group A including patients with RM data and Group B including patients who receive usual care at regular hospital consultations. RM technology applied used different parameters to access the risk of worsening HF and stablishing an alert threshold. Results Out of 211 patients enrolled, 75% were male and 44.8% were in NYHA functional class II at the time of device implantation. One-hundred and twenty (56.9%) received in-home monitoring system (89% Latitude® and 10.8% Carelink®), corresponding to the Group A. The remaining 91 patients (43.1%) were included in Group B. Forty-nine patients (40.8%) had transvenous implantable cardioverter defibrillator (ICD), 13 (10.8%) had a subcutaneous ICD, 54 (45%) a cardiac resynchronization therapy (CRT) defibrillator and 4 (3.3%) a CRT pacemaker. Group A patients did not have coronary artery disease (p 0.047) and were younger than patients in Group B (median age 66 years, IQR 55 – 73; median age 70 years, IQR 63 – 77). No other statistically differences in main comorbidities were detected between groups. The number of atrial fibrillation (AF) episodes and AF burden was higher in Group A during the follow-up (p 0.006) as well as non-sustained ventricular tachycardia episodes (p 0.016). However, no differences were accessed in emergency department (ED) admissions or heart failure hospitalizations (HFH) by decompensation for patients in group A who received alerts versus patients who not received (p 0.178 and p 0.748, respectively) nor between group A and B (p 0.921 and p 0.213, respectively). Patients in group A had a lower all-cause mortality rate (p &amp;lt; 0.001) and cardiovascular mortality (p 0.002), but no difference in life-threatening ventricular events occurred. Conclusion In our cohort of HF patients, remote monitoring allowed the premature detection and the correct quantification of arrhythmic events but did not reflect any difference in ED nor HFH by decompensation. Instead, RM system demonstrates ability to reduce global mortality when compared to conventional care. More data about the application of this system and the ideal tracking algorithms are necessary.

Acute Liver Failure Guidelines.

Acute liver failure (ALF) is a rare, acute, potentially reversible condition resulting in severe liver impairment and rapid clinical deterioration in patients without preexisting liver disease. Due to the rarity of this condition, published studies are limited by the use of retrospective or prospective cohorts and lack of randomized controlled trials. Current guidelines represent the suggested approach to the identification, treatment, and management of ALF and represent the official practice recommendations of the American College of Gastroenterology. The scientific evidence was reviewed using the Grading of Recommendations, Assessment, Development and Evaluation process to develop recommendations. When no robust evidence was available, expert opinions were summarized using Key Concepts. Considering the variety of clinical presentations of ALF, individualization of care should be applied in specific clinical scenarios.

Acute-on-chronic liver failure: Controversies and consensus.

Acute-on-chronic liver failure (ACLF) is a poorly defined syndrome characterised by rapid clinical deterioration in patients with chronic liver disease. Consequences include high short-term morbidity, mortality, and healthcare resource utilisation. ACLF encompasses a dysregulated, systemic inflammatory response, which can precipitate extra hepatic organ failures. Common precipitants include infection, alcoholic hepatitis, and reactivation of viral hepatitis although frequently no cause is identified. Heterogenous definitions, diagnostic criteria, and treatment guidelines, have been proposed by international hepatology societies. This can result in delayed or missed diagnoses of ACLF, significant variability in clinical management, and under-estimation of disease burden. Liver transplantation may be considered but the mainstay of treatment is organ support, often in the intensive care unit. This review will provide clarity around where are the controversies and consensus in ACLF including: Epidemiology and resource utilisation, key clinical and diagnostic features, strategies for management, and research gaps.