Mortality Associated with Hepatobiliary Disease in Portugal between 2006 and 2012

Palliative care and end stage liver disease: A cohort analysis of palliative care use and factors associated with referral

INTRODUCTION AND OBJECTIVES

Prevalence and mortality of chronic liver disease have risen significantly. In end stage liver disease, the survival of patients is approximately two years. Despite the poor prognosis and high symptom burden of these patients, integration of palliative care is limited. We aim to assess associated factors and trends in palliative care use in recent years.

MATERIALS AND METHODS

A Multicenter retrospective cohort of patients with end stage liver disease who suffered in-hospital mortality between 2017 and 2019. Information regarding patient demographics, hospital characteristics, comorbidities, etiology, decompensations, and interventions was collected. Two-sided tests and logistic regression analysis were used to identify factors associated with palliative care use.

RESULTS

A total of 201 patients were analyzed, with a yearly increase in palliative care consultation: 26.7 % in 2017 to 38.3 % in 2019. Patients in palliative care were older (65.72 ± 11.70 vs. 62.10 ± 11.44; p = 0.003), had a lower Karnofsky functionality scale (χ=18.104; p = 0.000) and had higher rates of hepatic encephalopathy (32.1 % vs. 17.4 %, p = 0.007) and hepatocarcinoma (61.7 % vs. 26.2 %; p = 0.000). No differences were found for Model for End-stage Liver Disease (19.28 ± 6.60 vs. 19,90 ± 5.78; p = 0.507) or Child-Pugh scores (p = 0.739). None of the patients who die in the intensive care unit receive palliative care (0 % vs 31.6 %; p = 0.000). Half of the palliative care consultations occurred 6,5 days before death.

CONCLUSIONS

Palliative care use differs based on demographics, disease complications, and severity. Despite its increasing implementation, palliative care intervention occurs late. Future investigations should identify approaches to achieve an earlier and concurrent care model.

Detection of Systemic Diseases From Ocular Images Using Artificial Intelligence: A Systematic Review

PURPOSE

Despite the huge investment in health care, there is still a lack of precise and easily accessible screening systems. With proven associations to many systemic diseases, the eye could potentially provide a credible perspective as a novel screening tool. This systematic review aims to summarize the current applications of ocular image-based artificial intelligence on the detection of systemic diseases and suggest future trends for systemic disease screening.

METHODS

A systematic search was conducted on September 1, 2021, using 3 databases-PubMed, Google Scholar, and Web of Science library. Date restrictions were not imposed and search terms covering ocular images, systemic diseases, and artificial intelligence aspects were used.

RESULTS

Thirty-three papers were included in this systematic review. A spectrum of target diseases was observed, and this included but was not limited to cardio-cerebrovascular diseases, central nervous system diseases, renal dysfunctions, and hepatological diseases. Additionally, one- third of the papers included risk factor predictions for the respective systemic diseases.

CONCLUSIONS

Ocular image - based artificial intelligence possesses potential diagnostic power to screen various systemic diseases and has also demonstrated the ability to detect Alzheimer and chronic kidney diseases at early stages. Further research is needed to validate these models for real-world implementation.

Machine-Learning Monitoring System for Predicting Mortality Among Patients With Noncancer End-Stage Liver Disease: Retrospective Study

Background

Patients with end-stage liver disease (ESLD) have limited treatment options and have a deteriorated quality of life with an uncertain prognosis. Early identification of ESLD patients with a poor prognosis is valuable, especially for palliative care. However, it is difficult to predict ESLD patients that require either acute care or palliative care.

Objective

We sought to create a machine-learning monitoring system that can predict mortality or classify ESLD patients. Several machine-learning models with visualized graphs, decision trees, ensemble learning, and clustering were assessed.

Methods

A retrospective cohort study was conducted using electronic medical records of patients from Wan Fang Hospital and Taipei Medical University Hospital. A total of 1214 patients from Wan Fang Hospital were used to establish a dataset for training and 689 patients from Taipei Medical University Hospital were used as a validation set.

Results

The overall mortality rate of patients in the training set and validation set was 28.3% (257/907) and 22.6% (145/643), respectively. In traditional clinical scoring models, prothrombin time-international normalized ratio, which was significant in the Cox regression (P<.001, hazard ratio 1.288), had a prominent influence on predicting mortality, and the area under the receiver operating characteristic (ROC) curve reached approximately 0.75. In supervised machine-learning models, the concordance statistic of ROC curves reached 0.852 for the random forest model and reached 0.833 for the adaptive boosting model. Blood urea nitrogen, bilirubin, and sodium were regarded as critical factors for predicting mortality. Creatinine, hemoglobin, and albumin were also significant mortality predictors. In unsupervised learning models, hierarchical clustering analysis could accurately group acute death patients and palliative care patients into different clusters from patients in the survival group.

Conclusions

Medical artificial intelligence has become a cutting-edge tool in clinical medicine, as it has been found to have predictive ability in several diseases. The machine-learning monitoring system developed in this study involves multifaceted analyses, which include various aspects for evaluation and diagnosis. This strength makes the clinical results more objective and reliable. Moreover, the visualized interface in this system offers more intelligible outcomes. Therefore, this machine-learning monitoring system provides a comprehensive approach for assessing patient condition, and may help to classify acute death patients and palliative care patients. Upon further validation and improvement, the system may be used to help physicians in the management of ESLD patients.

Psychological, Cognitive, and Laboratory Characteristics of End-Stage Liver Disease Patients

Background: End-Stage Liver Disease (ESLD) causes several clinical and psychological comorbidities. Some accompanying psychiatric disturbances have significant effects on the patients’ quality of life. Objectives: Thus, we aimed to evaluate some psychological characteristics of ESLD patients. Methods: A cross-sectional study was conducted on 91 ESLD patients aged 18 - 70 years. We assessed the patients using the California Verbal Learning Test (CVLT), Fatigue Severity Scale, Epworth Sleepiness Scale, and Hospital Anxiety and Depression Scale. Also, we measured the demographic and some laboratory data of the participants. The data were analyzed by SPSS version 21 software, and P values of less than 0.05 were considered significant. Results: The study included 68 men and 23 women with a mean age of 41.9 ± 13.72 years (range 19 - 68). The mean scores of fatigue (40.6 ± 14.8) and anxiety (12.98 ± 2.76) were more than the normal range. The most significant association was seen between age and CVLT items (attention (P = 0.01), immediate memory (P < 0.001), short delay free recall (0.01), and short delay cued recall (0.03). Conclusions: End-stage liver disease patients had anxiety, fatigue, and memory disorders in addition to their poor clinical conditions. Although the main treatment of ESLD is liver transplantation but the psychological and cognitive problems before transplantation in these patients are prognostic factors for post-operation compliance and follow up.

Antimicrobial susceptibilities of the ertapenem-non-susceptible non-carbapenemase-producing Enterobacterales isolates causing intra-abdominal infections in the Asia-Pacific region during 2008-2014: Results from the Study for Monitoring the Antimicrobial Resistance Trends (SMART)

OBJECTIVES

To investigate the susceptibility profiles amongst ertapenem-non-susceptible non-carbapenemase-producing Enterobacterales (ETP-NS-non-CPE) isolates.

METHODS

Minimum inhibitory concentrations (MICs) of 404 ETP-NS-non-CPE isolates collected from different intra-abdominal infection (IAI) sites amongst patients in the Asia-Pacific region during 2008-2014 were determined using the broth microdilution method. The susceptibility results were interpreted according to the MIC breakpoints recommended by the Clinical and Laboratory Standards Institute (CLSI) in 2018. The MICs data of several agents were evaluated based on their published pharmacokinetic/pharmacodynamic (PK/PD) profiles.

RESULTS

The majority (>84%) of IAI-ETP-NS-non-CPE isolates - including Escherichia coli (n=83), Klebsiella pneumoniae (n=91) and Enterobacter species (n=210) - were susceptible to imipenem and amikacin. The 193 hepatobiliary ETP-NS-non-CPE isolates exhibited a trend of lower cefepime MIC (≤4mg/L) distribution than those (n=145) cultured from the peritoneal space (P=0.058). Amongst the ETP-NS-non-CP Enterobacter isolates, 65.7% displayed a cefepime MIC≤4mg/L. In addition, compared with Escherichia coli and Klebsiella pneumoniae isolates, 82.9% and 72.9% of the ETP-NS-non-CP Enterobacter isolates were susceptible to levofloxacin and ciprofloxacin, respectively. Of note, 74.5% and 70.3% of the ETP-NS-non-CP Enterobacter isolates cultured from the hepatobiliary tract and peritoneal space exhibited a ciprofloxacin MIC≤2mg/L and ≤0.25mg/L, respectively. Imipenem and amikacin showed good in vitro susceptibility rates against the IAI-ETP-NS-non-CPE isolates. The hepatobiliary ETP-NS-non-CPE displayed lower cefepime MICs than those cultured from the peritoneal space. Additionally, a significant fraction of IAI-ETP-NS-non-CP Enterobacter isolates exhibited ciprofloxacin MIC ≤ 2mg/L.

CONCLUSION

Based upon the PK/PD analyses, ciprofloxacin, imipenem and cefepime are probably effective against IAI-ETP-NS-non-CPE isolates.

Liver Transplantation for Alcoholic Liver Disease: An Update

Alcoholic liver disease is a serious and increasing contributor to the global liver disease burden. Extensive selection criteria, including a minimum abstinence period, has previously been used to secure good outcomes but new research questions the effectiveness of abstinence periods and has recommended changes in integrated alcohol use treatment to effectively prevent relapse. Patients have unique health concerns, including posttransplantation risks of malignancy and metabolic complications, but overall very good long-term outcomes. Severe alcoholic hepatitis has been increasingly treated with early transplantation without a set sobriety period, with overall favorable outcomes, even with respect to recidivism.

Symptom prevalence and quality of life of patients with end-stage liver disease: A systematic review and meta-analysis

BACKGROUND:

End-stage liver disease is a common cause of morbidity and mortality worldwide, yet little is known about its symptomatology and impact on health-related quality of life.

AIM:

To describe symptom prevalence and health-related quality of life of patients with end-stage liver disease to improve care.

DESIGN:

Systematic review.

DATA SOURCES:

We searched eight electronic databases from January 1980 to June 2018 for studies investigating symptom prevalence or health-related quality of life of adult patients with end-stage liver disease. No language restrictions were applied. Meta-analyses were performed where appropriate.

RESULTS:

We included 80 studies: 35 assessing symptom prevalence, 41 assessing health-related quality of life, and 4 both. The instruments assessing symptoms varied across studies. The most frequently reported symptoms were as follows: pain (prevalence range 30%–79%), breathlessness (20%–88%), muscle cramps (56%–68%), sleep disturbance (insomnia 26%–77%, daytime sleepiness 29.5%–71%), and psychological symptoms (depression 4.5%–64%, anxiety 14%–45%). Erectile dysfunction was prevalent (53%–93%) in men. The health-related quality of life of patients with end-stage liver disease was significantly impaired when compared to healthy controls or patients with chronic liver disease. Compared with compensated cirrhosis, decompensation led to significant worsening of both components of the 36-Item Short Form Survey although to a larger degree for the Physical Component Summary score (decrease from average 6.4 (95% confidence interval: 4.0–8.8); p < 0.001) than for the Mental Component Summary score (4.5 (95% confidence interval: 2.4–6.6); p < 0.001).

CONCLUSION:

The symptom prevalence of patients with end-stage liver disease resembled that of patients with other advanced conditions. Given the diversity of symptoms and significantly impaired health-related quality of life, multidisciplinary approach and timely intervention are crucial.