Internal and emergency medicine
-
This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection. Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other pneumonia (but with negative COVID-19 RT-PCR), and healthy volunteers (control) from hospitals in four different countries (China, Spain, France, and Italy) were analyzed by GC-MS, LC-MS, and NMR. Machine learning models (PCA and PLS-DA) were developed to predict the diagnosis and prognosis of COVID-19 and identify biomarkers associated with these outcomes. ⋯ The PLS-DA model was able to predict the diagnosis and prognosis of COVID-19 around 95%. Additionally, our investigation pinpointed five novel potential biomarkers linked to the diagnosis and prognosis of COVID-19: N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate. These biomarkers exhibited heightened levels in severe COVID-19 patients compared to those with mild COVID-19 or healthy volunteers.
-
Observational Study
The effects of venovenous bypass use in liver transplantation with piggyback technique: a propensity score-weighted analysis.
Venovenous bypass (VVB) use during liver transplantation (LT) is notably variable among the centres and it is actually restricted to surgically complex cases, severely unstable recipients or grafts from high-risk donors. Historically, VVB was associated with the classical LT with caval cross clamping, while not much is known about the safety of this technique applied to piggyback LT. This retrospective observational study evaluated the effects of VVB applied to piggyback LT on mortality, hospital outcomes, postoperative graft and other organ dysfunction. ⋯ PS-weighted GLMs did not show any differences regarding hospital and graft-related outcomes. However, significantly higher odds ratios for serum creatinine > 2 mg/dL and AKIN stage 2 or 3 during the first 24 h after ICU admission together with a higher renal replacement therapy need during ICU stay were reported for VVB exposure in the weighted analyses. This study suggests similar mortality and length of stay but a higher risk for postoperative acute kidney injury in patients undergoing piggyback LT with VVB.
-
Early resuscitation using blood products is critical for patients with severe hemorrhagic shock. We aimed to develop and validate a new scoring system, hemorrhagic shock transfusion prediction (HSTP) score, to predict the need for massive transfusion (MT) in these patients, compared to the widely used Assessment of Blood Consumption (ABC) score. Trauma patients admitted to Emtiaz Hospital in Iran from 2017 to 2021 were retrospectively included. ⋯ Moreover, the positive and negative predictive values were 77.88% and 49.03% for the HSTP score, versus 74.15% and 33.66% for ABC. The new scoring system demonstrated higher sensitivity and improved positive and negative predictive values compared to the ABC score. This score can assist physicians in making accurate transfusion decisions quickly, but further prospective studies are warranted to validate its clinical utility.
-
Opioid withdrawal is common among hospitalized patients. Those with substance use disorders exhibit higher rates of patient-directed discharge. The literature lacks information regarding the patient perspective on opioid withdrawal in the hospital setting. ⋯ In this population with historically high rates of patient-directed discharge, patients reported having a positive experience with opioid withdrawal management during hospitalization. Amongst our hospitalized patients, we observed several different individualized MOUD induction strategies. All participants were offered MOUD at discharge and most planned to follow-up for further treatment.
-
To develop a more accurate prognostic model that incorporates indicators of multi-organ involvement for immunoglobulin light-chain (AL) Amyloidosis patients. Biopsy-proven AL amyloidosis patients between January 1, 2012, and February 28, 2023, were enrolled and randomly divided into a training set and a test set at a ratio of 7:3. Prognostic indicators that comprehensively cover cardiac, renal, and hepatic involvement were identified in the training set by random survival forest (RSF). ⋯ The RSF model based on the above indicators achieved C-index and IBS values of 0.834 (95% CI 0.725-0.915) and 0.151 (95% CI 0.1402-0.181), respectively. At last, the NRI and IDI of the RSF model were 0.301 (95% CI 0.048-0.546, P = 0.012) and 0.157 (95% CI 0.041-0.269, P < 0.001) at 5-year by comparing the RSF model with the Cox model which is based on the Mayo 2012 staging system. The RSF model that incorporates indicators of multi-organ involvement had a great performance, which may be helpful for physicians' decision-making and more accurate overall survival prediction.