Deep learning algorithms for predicting renal replacement therapy initiation in CKD patients: a retrospective cohort study.

BACKGROUND: Chronic kidney disease (CKD) requires accurate prediction of renal replacement therapy (RRT) initiation risk. This study developed deep learning algorithms (DLAs) to predict RRT risk in CKD patients by incorporating medical history and prescriptions in addition to biochemical investigations. METHODS: A multi-centre retrospective cohort study was conducted in three major hospitals in Hong Kong. CKD patients with an eGFR < 30ml/min/1.73m2 were included. DLAs of various structures were created and trained using patient data. Using a test set, the DLAs' predictive performance was compared to Kidney Failure Risk Equation (KFRE). RESULTS: DLAs outperformed KFRE in predicting RRT initiation risk (CNN + LSTM + ANN layers ROC-AUC = 0.90; CNN ROC-AUC = 0.91; 4-variable KFRE: ROC-AUC = 0.84; 8-variable KFRE: ROC-AUC = 0.84). DLAs accurately predicted uncoded renal transplants and patients requiring dialysis after 5 years, demonstrating their ability to capture non-linear relationships. CONCLUSIONS: DLAs provide accurate predictions of RRT risk in CKD patients, surpassing traditional methods like KFRE. Incorporating medical history and prescriptions improves prediction performance. While our findings suggest that DLAs hold promise for improving patient care and resource allocation in CKD management, further prospective observational studies and randomized controlled trials are necessary to fully understand their impact, particularly regarding DLA interpretability, bias minimization, and overfitting reduction. Overall, our research underscores the emerging role of DLAs as potentially valuable tools in advancing the management of CKD and predicting RRT initiation risk.

An atypical airway cast.

A 60-year-old man intubated for airway protection after smoke inhalation was found to have decompensated hypercapnic respiratory failure. Fiberoptic bronchoscopy revealed obstructive airway slough and pseudomembrane, a manifestation of severe inhalation injury. Veno-venous extracorporeal membrane oxygenation was established for stabilization. The airway casts were removed successfully with periprocedural veno-venous extracorporeal membrane oxygenation support.

Pyroglutamic Acidosis - An Underrecognised Entity Associated with Acetaminophen Use.

Pyroglutamic acidosis (PGA) is an underrecognized entity characterised by raised anion gap metabolic acidosis (RAGMA) and urinary hyper-excretion of pyroglutamic acid. It is frequently associated with chronic acetaminophen (APAP) ingestion. We report the case of a 73-year-old man with invasive pulmonary aspergillosis treated with voriconazole and APAP for analgesia with a cumulative dose of 160 g over 40 days. PGA was suspected as he developed severe RAGMA and common causes were excluded. Diagnosis was confirmed via urinary organic acid analysis which showed significant hyper-excretion of pyroglutamic acid. APAP was discontinued, and N-acetylcysteine (NAC) was administered. His RAGMA rapidly resolved following treatment.

NLR, MLR, PLR and RDW to predict outcome and differentiate between viral and bacterial pneumonia in the intensive care unit.

The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and red cell distribution width (RDW) are emerging biomarkers to predict outcomes in general ward patients. However, their role in the prognostication of critically ill patients with pneumonia is unclear. A total of 216 adult patients were enrolled over 2 years. They were classified into viral and bacterial pneumonia groups, as represented by influenza A virus and Streptococcus pneumoniae, respectively. Demographics, outcomes, and laboratory parameters were analysed. The prognostic power of blood parameters was determined by the respective area under the receiver operating characteristic curve (AUROC). Performance was compared using the APACHE IV score. Discriminant ability in differentiating viral and bacterial aetiologies was examined. Viral and bacterial pneumonia were identified in 111 and 105 patients, respectively. In predicting hospital mortality, the APACHE IV score was the best prognostic score compared with all blood parameters studied (AUC 0.769, 95% CI 0.705-0.833). In classification tree analysis, the most significant predictor of hospital mortality was the APACHE IV score (adjusted P = 0.000, χ2 = 35.591). Mechanical ventilation was associated with higher hospital mortality in patients with low APACHE IV scores ≤ 70 (adjusted P = 0.014, χ2 = 5.999). In patients with high APACHE IV scores > 90, age > 78 (adjusted P = 0.007, χ2 = 11.221) and thrombocytopaenia (platelet count ≤ 128, adjusted P = 0.004, χ2 = 12.316) were predictive of higher hospital mortality. The APACHE IV score is superior to all blood parameters studied in predicting hospital mortality. The single inflammatory marker with comparable prognostic performance to the APACHE IV score is platelet count at 48 h. However, there is no ideal biomarker for differentiating between viral and bacterial pneumonia.

Emerging Infections Due to Shewanella spp.: A Case Series of 128 Cases Over 10 Years.

Background: Shewanella species are emerging pathogens that can cause severe hepatobiliary, skin and soft tissue, gastrointestinal, respiratory infections, and bacteremia. Here we reported the largest case series of infections caused by Shewanella species. Aim: To identify the clinical features and risk factors predisposing to Shewanella infections. To evaluate resistance pattern of Shewanella species and appropriateness of antibiotic use in the study cohort. Methods: Patients admitted to a regional hospital in Hong Kong with Shewanella species infection from April 1, 2010 to December 31, 2020 were included. Demographics, antibiotics, microbiology, and outcomes were retrospectively analyzed. Findings: Over the 10 years, we identified 128 patients with Shewanella species infection. 61.7% were male with a median age of 78 (IQR 65-87). Important underlying diseases included hepatobiliary diseases (63.3%), malignancy (26.6%), chronic kidney disease or end-stage renal failure (25.8%), and diabetes mellitus (22.7%). Hepatobiliary infections (60.4%) were the most common clinical manifestation. Majority (92.2%) were infected with Shewanella algae, while 7.8% were infected with Shewanella putrefaciens. The identified organisms were usually susceptible to ceftazidime (98.7%), gentamicin (97.4%), cefoperazone-sulbactam (93.5%) and ciprofloxacin (90.3%). Imipenem-susceptible strains were only present in 76.6% of isolates. Conclusion: This largest case series suggested that Shewanella infections are commonly associated with underlying comorbidities, especially with hepatobiliary diseases and malignancy. Although Shewanella species remained largely susceptible to third and fourth generation cephalosporins and aminoglycosides, carbapenem resistance has been on a significant rise.