Mucorales PCR in blood as an early marker of invasive gastrointestinal mucormycosis might decrease the delay in treatment: A case report.

We describe the fatal case of a patient with gastric perforation due to ischemia and necrosis of the stomach secondary to generalized vascular thrombosis following allogeneic hematopoietic cell transplantation. Histopathological examination of the resected stomach, spleen and omentum unexpectedly showed fungal hyphae suggestive of invasive mucormycosis. We retrospectively performed Mucorales PCR (MucorGenius®, PathoNostics, Maastricht, The Netherlands) in blood and tissue samples of this patient. The PCR was positive 16 days before time of death and 9 days before abdominal pain.

Development and validation of clinical prediction models for acute kidney injury recovery at hospital discharge in critically ill adults.

PURPOSE: Acute kidney injury (AKI) recovery prediction remains challenging. The purpose of the present study is to develop and validate prediction models for AKI recovery at hospital discharge in critically ill patients with ICU-acquired AKI stage 3 (AKI-3). METHODS: Models were developed and validated in a development cohort (n = 229) and a matched validation cohort (n = 244) from the multicenter EPaNIC database to create prediction models with the least absolute shrinkage and selection operator (Lasso) machine-learning algorithm. We evaluated the discrimination and calibration of the models and compared their performance with plasma neutrophil gelatinase-associated lipocalin (NGAL) measured on first AKI-3 day (NGAL_AKI3) and reference model that only based on age. RESULTS: Complete recovery and complete or partial recovery occurred in 33.20% and 51.23% of the validation cohort patients respectively. The prediction model for complete recovery based on age, need for renal replacement therapy (RRT), diagnostic group (cardiac/surgical/trauma/others), and sepsis on admission had an area under the receiver operating characteristics curve (AUROC) of 0.53. The prediction model for complete or partial recovery based on age, need for RRT, platelet count, urea, and white blood cell count had an AUROC of 0.61. NGAL_AKI3 showed AUROCs of 0.55 and 0.53 respectively. In cardiac patients, the models had higher AUROCs of 0.60 and 0.71 than NGAL_AKI3's AUROCs of 0.52 and 0.54. The developed models demonstrated a better performance over the reference models (only based on age) for cardiac surgery patients, but not for patients with sepsis and for a general ICU population. CONCLUSION: Models to predict AKI recovery upon hospital discharge in critically ill patients with AKI-3 showed poor performance in the general ICU population, similar to the biomarker NGAL. In cardiac surgery patients, discrimination was acceptable, and better than NGAL. These findings demonstrate the difficulty of predicting non-reversible AKI early.

Overall performance of a drug-drug interaction clinical decision support system: quantitative evaluation and end-user survey.

BACKGROUND: Clinical decision support systems are implemented in many hospitals to prevent medication errors and associated harm. They are however associated with a high burden of false positive alerts and alert fatigue. The aim of this study was to evaluate a drug-drug interaction (DDI) clinical decision support system in terms of its performance, uptake and user satisfaction and to identify barriers and opportunities for improvement. METHODS: A quantitative evaluation and end-user survey were performed in a large teaching hospital. First, very severe DDI alerts generated between 2019 and 2021 were evaluated retrospectively. Data collection comprised alert burden, override rates, the number of alert overrides reviewed by pharmacists and the resulting pharmacist recommendations as well as their acceptance rate. Second, an e-survey was carried out among prescribers to assess satisfaction, usefulness and relevance of DDI alerts as well as reasons for overriding. RESULTS: A total of 38,409 very severe DDI alerts were generated, of which 88.2% were overridden by the prescriber. In 3.2% of reviewed overrides, a recommendation by the pharmacist was provided, of which 79.2% was accepted. False positive alerts were caused by a too broad screening interval and lack of incorporation of patient-specific characteristics, such as QTc values. Co-prescribing of a non-vitamin K oral anticoagulant and a low molecular weight heparin accounted for 49.8% of alerts, of which 92.2% were overridden. In 88 (1.1%) of these overridden alerts, concurrent therapy was still present. Despite the high override rate, the e-survey revealed that the DDI clinical decision support system was found useful by prescribers. CONCLUSIONS: Identified barriers were the lack of DDI-specific screening intervals and inclusion of patient-specific characteristics, both leading to a high number of false positive alerts and risk for alert fatigue. Despite these barriers, the added value of the DDI clinical decision support system was recognized by prescribers. Hence, integration of DDI-specific screening intervals and patient-specific characteristics is warranted to improve the performance of the DDI software.

An update on congenital melanocytic nevus syndrome: A case report and literature review.

Congenital melanocytic nevus syndrome (CMNS) is a rare condition characterized by pigmented skin lesions that are usually present at birth and are associated with an increased risk of neurological abnormalities and malignant melanoma. It mostly results from a post-zygotic NRAS mutation of neural-derived crest cells, leading to uncontrolled cell growth. Because of the increased knowledge of the genetics underlying CMNS, targeted therapy becomes a promising treatment option. We present a case of CMNS in a newborn. Physical examination at birth showed a giant congenital melanocytic nevus, extending from the occipital to the lower lumbar region. A magnetic resonance imaging scan revealed multiple cerebral and cerebellar parenchymal lesions. Genetic analysis of the cutaneous lesions showed the presence of an NRAS Q61R mutation. The patient was treated with dermabrasion to reduce the color intensity of the nevus. However, this was complicated by recurrent wound infections and laborious wound healing. At the age of 1 year, the patient had an age-appropriate psychomotor development, without neurological deficits.

Artificial intelligence to guide management of acute kidney injury in the ICU: a narrative review.

PURPOSE OF REVIEW: Acute kidney injury (AKI) frequently complicates hospital admission, especially in the ICU or after major surgery, and is associated with high morbidity and mortality. The risk of developing AKI depends on the presence of preexisting comorbidities and the cause of the current disease. Besides, many other parameters affect the kidney function, such as the state of other vital organs, the host response, and the initiated treatment. Advancements in the field of informatics have led to the opportunity to store and utilize the patient-related data to train and validate models to detect specific patterns and, as such, predict disease states or outcomes. RECENT FINDINGS: Machine-learning techniques have also been applied to predict AKI, as well as the patients' outcomes related to their AKI, such as mortality or the need for kidney replacement therapy. Several models have recently been developed, but only a few of them have been validated in external cohorts. SUMMARY: In this article, we provide an overview of the machine-learning prediction models for AKI and its outcomes in critically ill patients and individuals undergoing major surgery. We also discuss the pitfalls and the opportunities related to the implementation of these models in clinical practices.

Cytomegalovirus serostatus and outcome in nonimmunocompromised critically ill patients.

OBJECTIVE: The impact of cytomegalovirus reactivation during critical illness remains unclear and studies investigating prophylaxis in cytomegalovirus seropositive patients are being considered. This study investigates the association between cytomegalovirus seropositivity and outcome in a large population of nonimmunocompromised critically ill patients. DESIGN: Cytomegalovirus serostatus was determined on prospectively collected serum samples. The primary end point was intensive care unit mortality. The secondary end points were in-hospital mortality, time to alive discharge from intensive care unit and hospital, time to alive weaning from mechanical ventilation, and need for renal replacement therapy. SETTING: This retrospective study was performed in a 17-bed medical and 56-bed surgical intensive care unit in a 1,900-bed referral hospital. PATIENTS: We analyzed serum of 1,504 nonimmunocompromised critically ill patients with an intensive care unit length of stay of 3 days or more. Patients with hematologic malignancy, transplantation, immunosuppressive therapy (calcineurin inhibitors, antitumor necrosis factor-α drugs, antilymphocyte antibodies, or chemotherapeutic agents), or a do-not-resuscitate order were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Sixty-four percent of the studied patients were cytomegalovirus seropositive. Multivariable analysis revealed no associated risk for intensive care unit or hospital mortality, or for time to alive discharge from intensive care unit or hospital. The risk for alive weaning from mechanical ventilation and the need for renal replacement therapy were also comparable in seropositive and seronegative groups. CONCLUSION: : No association was found between the cytomegalovirus serostatus and the studied major clinical outcomes. Based on these results, the design of an intervention study assessing the impact of cytomegalovirus prophylaxis in all cytomegalovirus seropositive critically ill patients appears premature.