Incidence and predictors of hepatocellular carcinoma in patients with autoimmune hepatitis

Background and Aims: Autoimmune hepatitis (AIH) is a rare chronic liver disease of unknown aetiology; the risk of hepatocellular carcinoma (HCC) remains unclear and risk factors are not well-defined. We aimed to investigate the risk of HCC across a multicentre AIH cohort and to identify predictive factors. Methods: We performed a retrospective, observational, multicentric study of patients included in the International Autoimmune Hepatitis Group Retrospective Registry. The assessed clinical outcomes were HCC development, liver transplantation, and death. Fine and Gray regression analysis stratified by centre was applied to determine the effects of individual covariates; the cumulative incidence of HCC was estimated using the competing risk method with death as a competing risk. Results: A total of 1,428 patients diagnosed with AIH from 1980 to 2020 from 22 eligible centres across Europe and Canada were included, with a median follow-up of 11.1 years (interquartile range 5.2-15.9). Two hundred and ninety-three (20.5%) patients had cirrhosis at diagnosis. During follow-up, 24 patients developed HCC (1.7%), an incidence rate of 1.44 cases/1,000 patient-years; the cumulative incidence of HCC increased over time (0.6% at 5 years, 0.9% at 10 years, 2.7% at 20 years, and 6.6% at 30 years of follow-up). Patients who developed cirrhosis during follow-up had a significantly higher incidence of HCC. The cumulative incidence of HCC was 2.6%, 4.6%, 5.6% and 6.6% at 5, 10, 15, and 20 years after the development of cirrhosis, respectively. Obesity (hazard ratio [HR] 2.94, p = 0.04), cirrhosis (HR 3.17, p = 0.01), and AIH/PSC variant syndrome (HR 5.18, p = 0.007) at baseline were independent risk factors for HCC development. Conclusions: HCC incidence in AIH is low even after cirrhosis development and is associated with risk factors including obesity, cirrhosis, and AIH/PSC variant syndromeCellular mechanisms in basic and clinical gastroenterology and hepatolog

Prophylactic Haloperidol for Critically Ill Adults-Reply

Item does not contain fulltex

Association between delirium prediction scores and days spent with delirium

Contains fulltext : 220796.pdf (Publisher’s version ) (Closed access)PURPOSE: To determine the correlation and discriminative value of the E-PRE-DELIRIC and PRE-DELIRIC scores with delirium exposure to evaluate the prognostic value of both models. METHODS: A secondary analysis of a randomized clinical trial enrolling 1506 delirium-free, critically ill adults with an anticipated ICU stay of ≥2 days. Days spent with delirium (≥1 positive CAM-ICU) or coma (≥1 RASS ≤-4) in the 28-days after ICU admission were calculated. Patients were categorized into four groups: no delirium, short-exposure (1 delirium day), moderate-exposure (2-5 delirium days), and long- exposure (≥6 delirium days) to determine the correlation and discriminative value of the E-PRE-DELIRIC and the PRE-DELIRIC with days spent with delirium. RESULTS: The correlation between the overall E-PRE-DELIRIC and PRE-DELIRIC scores and days spent with delirium were: R = 0.08 (P = .005) and R = 0.26 (P < .001), respectively. The correlation between both prediction scores and days spent with coma or delirium were R = 0.21 (P < .0001) and R = 0.46 (P < .0001), respectively. The highest Area Under the Receiver Operating Characteristic for both E-PRE-DELIRIC [0.57 (95% CI:0.51-0.62)] and PRE-DELIRIC [0.58 (95% CI:0.53-0.62)] was found in the long delirium exposure group. CONCLUSION: The E-PRE-DELIRIC and PRE-DELIRIC model each poorly correlate and discriminate with days spent with delirium in the 28 days after ICU admission

[Recognising postoperative delirium in the elderly]

Item does not contain fulltextOBJECTIVE: To determine the degree of agreement between delirium experts on the diagnosis of delirium based on exactly the same information, and to assess the sensitivity of delirium screening methods used by clinical nurses. DESIGN: Prospective observational longitudinal study. METHOD: Older patients (>/= 60 years) who underwent major surgery were included. During the first three days after surgery they had a standardised cognitive screening test which was recorded on video. Two delirium experts independently evaluated these videos and the information from the patient records. They classified the patients as having 'no delirium', 'possible delirium' or 'delirium'. If there was disagreement, a third expert was consulted. The final classification, based on consensus of two or three delirium experts, was compared with the result of the delirium screening carried out by the clinical nurses. RESULTS: A total of 167 patients were included and 424 postoperative classifications were obtained. The agreement between the experts was 0.61 (95% confidence interval (CI): 0.53-0.68), based on Cohen's kappa. In 89 (21.0%) of the postoperative classifications there was no agreement between the experts and a third expert was consulted. The nurses using the delirium screening tools recognised 32% of the cases that had been classified as delirium by the experts. CONCLUSION: There was considerable disagreement between the classifications of individual delirium experts, based on exactly the same information, indicating the difficulty of the diagnosis. Furthermore, the sensitivity of the delirium screening tools used by the clinical nurses was poor. Further research should focus on the development of objective methods for recognising delirium

Delirium prediction in the intensive care unit: comparison of two delirium prediction models

Contains fulltext : 191587.pdf (publisher's version ) (Open Access

Factors associated with a persistent delirium in the intensive care unit: A retrospective cohort study

Item does not contain fulltex

The teaching of reading in New South Wales schools : an historical analysis.

PURPOSE: It is assumed that there is a relation between light exposure and delirium incidence. The aim of our study was to determine the effect of prehospital light exposure on the incidence of intensive care unit (ICU)-acquired delirium. MATERIALS AND METHODS: Data from 3 ICUs in the Netherlands were analyzed retrospectively. Delirium was assessed with the Confusion Assessment Method for the ICU. Daily light intensity data were obtained from meteorological stations in the vicinity of the 3 hospitals. The association between light intensity and delirium incidence was analyzed using logistic regression analysis adjusting for known covariates for delirium. RESULTS: Data of 3198 patients, aged (mean +/- SD) 61.9 +/- 15.3 years with Acute Physiology and Chronic Health Evaluation II score 16.4 +/- 6.6 were analyzed. Delirium incidence was 31.2% and did not vary significantly throughout the year. Twenty-eight-day preadmission photoperiod was highest in spring and lowest in winter; however, no association between light exposure and delirium incidence was found (odds ratio, 1.00; 95% confidence interval, 0.99-1.00; P = 0.72). Furthermore, delirium was significantly associated with age, infection, use of sedatives, Acute Physiology and Chronic Health Evaluation II score, and diagnosis of neurological disease or trauma. CONCLUSIONS: The incidence of delirium does not differ per season and prior sunlight exposure does not play a role of importance in the development of ICU-acquired delirium

Intensive insulin therapy increases the risk of hypoglycemia in neurocritical care patients

Item does not contain fulltextBACKGROUND: Intensive insulin therapy protocols are widely used in intensive care medicine. A disadvantage of these protocols may be the occurrence of hypoglycemic episodes. Neurocritical care patients are particularly vulnerable to the effects of hypoglycemia. We aimed to study the risk of hypoglycemia in neurocritical care patients in relation to intensive insulin therapy. METHODS: To determine the effects of 2 different intensive insulin therapy protocols on glucose levels and hypoglycemia incidence, we collected data before and after implementation of the protocols in 2 university hospitals. The risk of hypoglycemia (blood glucose level below 3.0 mmol/L) was studied retrospectively with logistic regression analyses. RESULTS: In hospital A, data were obtained on 152 patients before implementation of the protocol and on 649 patients after implementation of the protocol. In hospital B, data were obtained on 111 patients before implementation of the protocol and on 118 patients thereafter. Implementation of intensive insulin therapy protocols increased the time spent in the desired blood glucose range of 4.6 to 6.0 mmol/L in both hospitals, but increased the risk of hypoglycemia: the absolute risk of hypoglycemia during intensive care unit admission increased in hospital A from 14.5% to 20.3% (adjusted odds ratio=1.3; 95% confidence interval: 0.8-2.3) and in hospital B from 3.6% to 29.7% (adjusted odds ratio=28.6; 95% confidence interval: 5.9-138.9). CONCLUSIONS: Implementation of intensive insulin therapy protocols in neurocritical care patients not only seems to increase the time spent in the desired blood glucose range, but also seems to increase the risk of hypoglycemia. The risk of hypoglycemia strongly depends on characteristics of the intensive insulin therapy protocol