Chesdachai, Supavit

Background: Lactic acidosis is a heterogeneous condition with multiple underlying causes and associated outcomes. The use of multi-dimensional patient data to subtype lactic acidosis can personalize patient care. Machine learning consensus clustering may identify lactic acidosis subgroups with unique clinical profiles and outcomes. Methods: We used the Medical Information Mart for Intensive Care III database to abstract electronic medical record data from patients admitted to intensive care units (ICU) in a tertiary care hospital in the United States. We included patients who developed lactic acidosis (defined as serum lactate ≥ 4 mmol/L) within 48 h of ICU admission. We performed consensus clustering analysis based on patient characteristics, comorbidities, vital signs, organ supports, and laboratory data to identify clinically distinct lactic acidosis subgroups. We calculated standardized mean differences to show key subgroup features. We compared outcomes among subgroups. Results: We identified 1919 patients with lactic acidosis. The algorithm revealed three best unique lactic acidosis subgroups based on patient variables. Cluster 1 (n = 554) was characterized by old age, elective admission to cardiac surgery ICU, vasopressor use, mechanical ventilation use, and higher pH and serum bicarbonate. Cluster 2 (n = 815) was characterized by young age, admission to trauma/surgical ICU with higher blood pressure, lower comorbidity burden, lower severity index, and less vasopressor use. Cluster 3 (n = 550) was characterized by admission to medical ICU, history of liver disease and coagulopathy, acute kidney injury, lower blood pressure, higher comorbidity burden, higher severity index, higher serum lactate, and lower pH and serum bicarbonate. Cluster 3 had the worst outcomes, while cluster 1 had the most favorable outcomes in terms of persistent lactic acidosis and mortality. Conclusions: Consensus clustering analysis synthesized the pattern of clinical and laboratory data to reveal clinically distinct lactic acidosis subgroups with different outcomes.

Background: Lactic acidosis is the most common cause of anion gap metabolic acidosis in the intensive care unit (ICU), associated with poor outcomes including mortality. We sought to compare machine learning (ML) approaches versus logistic regression analysis for prediction of mortality in lactic acidosis patients admitted to the ICU. Methods: We used the Medical Information Mart for Intensive Care (MIMIC-III) database to identify ICU adult patients with lactic acidosis (serum lactate ≥4 mmol/L). The outcome of interest was hospital mortality. We developed prediction models using four ML approaches consisting of random forest (RF), decision tree (DT), extreme gradient boosting (XGBoost), artificial neural network (ANN), and statistical modeling with forward stepwise logistic regression using the testing dataset. We then assessed model performance using area under the receiver operating characteristic curve (AUROC), accuracy, precision, error rate, Matthews correlation coefficient (MCC), F1 score, and assessed model calibration using the Brier score, in the independent testing dataset. Results: Of 1919 lactic acidosis ICU patients, 1535 and 384 were included in the training and testing dataset, respectively. Hospital mortality was 30%. RF had the highest AUROC at 0.83, followed by logistic regression 0.81, XGBoost 0.81, ANN 0.79, and DT 0.71. In addition, RF also had the highest accuracy (0.79), MCC (0.45), F1 score (0.56), and lowest error rate (21.4%). The RF model was the most well-calibrated. The Brier score for RF, DT, XGBoost, ANN, and multivariable logistic regression was 0.15, 0.19, 0.18, 0.19, and 0.16, respectively. The RF model outperformed multivariable logistic regression model, SOFA score (AUROC 0.74), SAP II score (AUROC 0.77), and Charlson score (AUROC 0.69). Conclusion: The ML prediction model using RF algorithm provided the highest predictive performance for hospital mortality among ICU patient with lactic acidosis.

Endogenous endophthalmitis caused by Enterococcus gallinarum, an organism with intrinsic resistance to vancomycin, has rarely been reported. We present a case of persistent E. gallinarum bacteremia in a female recipient of hematopoietic stem cell transplant (HSCT) complicated by endophthalmitis and meningoventriculitis, resulting in a fatal outcome despite treatment with intravenous ampicillin and daptomycin. Treatment of endophthalmitis often presents a challenge due to the lack of options for antimicrobials with reliable ocular penetration. Therapeutic decisions can become particularly complex with the involvement of drug-resistant pathogens and host characteristics that limit the choice of antimicrobials due to drug toxicity. This case illustrates a rare manifestation of an opportunistic pathogen.

Abstract Background Statins up-regulate angiotensin-converting enzyme 2, the receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), while also exhibiting pleiotropic antiviral, antithrombotic, and anti-inflammatory properties. Uncertainties exist about their effect on the course of SARS-CoV-2 infection. We sought to systematically review the literature and perform a meta-analysis to examine the association between prior statin use and outcomes of patients with coronavirus disease 2019 (COVID-19). Methods We searched Ovid Medline, Web of Science, Scopus, and the preprint server medRxiv from inception to December 2020. We assessed the quality of eligible studies with the Newcastle-Ottawa quality scale. We pooled adjusted relative risk (aRRs) of the association between prior statin use and outcomes of patients with COVID-19 using the DerSimonian-Laird random-effects model and assessed heterogeneity using the I2 index. Results Overall, 19 (16 cohorts and 3 case-control) studies were eligible, with a total of 395 513 patients. Sixteen of 19 studies had low or moderate risk of bias. Among 109 080 patients enrolled in 13 separate studies, prior statin use was associated with a lower risk of mortality (pooled aRR, 0.65 [95% confidence interval {CI}, .56–.77], I2 = 84.1%) and a reduced risk of severe COVID-19 was also observed in 48 110 patients enrolled in 9 studies (pooled aRR, 0.73 [95% CI, .57–.94], I2 = 82.8%), with no evidence of publication bias. Conclusions Cumulative evidence suggests that prior statin use is associated with lower risks of mortality or severe disease in patients with COVID-19. These data support the continued use of statins medications in patients with an indication for lipid-lowering therapy during the COVID-19 pandemic.

AbstractDisseminated blastomycosis in solid organ transplant is uncommon. The diagnosis is usually challenging due to vague clinical presentations, which could lead to a devastating outcome. We reported a unique case of disseminated blastomycosis with laryngeal involvement in a kidney transplant recipient who presented with hoarseness. The diagnosis was made by histopathology and culture of laryngeal mass.

Abstract Background Capnocytopha ga is a gram-negative, facultative anaerobe. Human infection is rare but can lead to devastating outcomes. Capnocytophaga canimorsus can cause sepsis following an animal bite, whereas human-oral–associated Capnocytophaga infections were reported in immunocompromised patients. Current data on these infections are not robust. Our goal is to provide a contemporary description of a unique characteristic of Capnocytophaga infections. Methods We performed a retrospective review of all patients with Capnocytophaga infection from January 2010 to August 2020 at 3 main hospitals of Mayo Clinic in Rochester, Minnesota; Scottsdale, Arizona; and Jacksonville, Florida. We collected baseline demographic data, clinical characteristics, microbiological data, and outcomes of C. canimorsus and human-oral–associated Capnocytophaga infection. Results Among 82 patients with Capnocytophaga infection, 46 patients (56.0%) had bacteremia. The most common species identified in this group was C. sputigena (57.9%), followed by C. canimorsus (34.8%). Patients with human-oral–associated Capnocytophaga bacteremia were often immunocompromised, presented with neutropenic fever, and had worse 6-month all-cause mortality compared to C. canimorsus bacteremia (36.4% vs 6.2%, P = .03). They also had a higher β-lactamase production rate (36.4% vs 0.0%, P = .02). Among patients without bacteremia, the main clinical syndrome was polymicrobial head and neck infections (47.2%). Conclusions Human-oral–associated Capnocytophaga bacteremia occurs primarily in immunocompromised patients, particularly those with hematologic malignancy. In contrast, C. canimorsus bacteremia is more likely to present with community-onset infection related to zoonotic exposure. Human-oral–associated Capnocytophaga infection without bacteremia is frequently isolated in polymicrobial infection; this phenomenon’s significance is yet to be fully understood.

AbstractBackgroundIn the United States, increasing ethnic diversity has been apparent. However, the epidemiology and trends of BKV genotypes remain unclear. This meta‐analysis was conducted with the aim to assess the prevalence of BKV genotypes among kidney transplant (KTx) recipients in the United States.MethodsA comprehensive literature review was conducted through October 2018 utilizing MEDLINE, Embase, and Cochrane Database to identify studies that reported the prevalence of BKV subtypes and/or subgroups in KTx recipients in the United States. Pooled prevalence rates were combined using random effects, generic inverse variance method. The protocol for this study is registered with PROSPERO (no. CRD42019134582).ResultsA total of eight observational studies with a total of 193 samples (urine, blood, and kidney tissues) from 188 BKV‐infected KTX recipients were enrolled. Overall, the pooled estimated prevalence rates of BKV subtypes were 72.2% (95% confidence of interval [CI]: 62.7‐80.0%) for subtype I, 6.8% (95% CI: 2.5‐16.9%) for subtype II, 8.3% (95% CI: 4.4‐15.1%) for subtype III, and 16.1% (95% CI: 10.4‐24.2%) for subtype IV, respectively. While metaregression analysis demonstrated a significant positive correlation between year of study and the prevalence of BKV subtype I (slopes = +0.1023, P = .01), there were no significant correlations between year of study and percentages of BKV subtype II‐IV (P > .05). Among KTx recipients with BKV subtype I, the pooled estimated percentages of BKV subgroups were 22.4% (95% CI: 13.7‐34.5%) for subgroup Ia, 30.6% (95% CI: 17.7‐47.5%) for subgroup Ib1, 47.7% (95% CI: 35.8‐59.9%) for subgroup Ib2, and 4.1% (95% CI:1.2‐13.3%) for subgroup Ic, respectively.ConclusionBKV subtype I is the most prevalent subtype among KTx recipients in the United States and its prevalence seems to increasing overtime. Subgroup Ib2 is the most common subgroup among BKV subtype I.

BACKGROUND: The possible relationship between obesity and the risk of colonic diverticulosis has been suggested by recent epidemiologic studies, although the results were inconsistent. OBJECTIVE: This systematic review and meta-analysis was conducted to summarize all of the available data. DATA SOURCES: A comprehensive literature review was conducted using the MEDLINE and EMBASE databases through January 2017. STUDY SELECTION: Studies that compared the risk of colonic diverticulosis among subjects with obesity versus those without obesity were included. MAIN OUTCOME MEASURES: Effect estimates from each study were extracted and combined together using a random-effect, generic inverse variance method. RESULTS: Of 2989 potentially eligible articles, 10 studies (9 cross-sectional studies and 1 prospective cohort study) with 53,520 participants met the eligibility criteria and were included in the meta-analysis. The risk of colonic diverticulosis in obese subjects was significantly higher than in those without obesity, with a pooled OR of 1.41 (95% CI, 1.20–1.65). The statistical heterogeneity was high, with an I2 of 75%. LIMITATIONS: High statistical heterogeneity and publication bias in favor of positive studies may have been present in this meta-analysis. CONCLUSIONS: A significant association between colonic diverticulosis and obesity was shown in this study. However, additional studies are still required to determine the causality. See Video Abstract at http://links.lww.com/DCR/A500.

Background/objective Hepatitis C virus (HCV) infection is one of the most common infections worldwide. Recent epidemiologic studies have suggested that patients with HCV infection might be at an increased risk of Parkinson’s disease. However, the data on this relationship remain inconclusive. This meta-analysis was conducted with the aim to summarize all available evidence. Patients and methods A literature search was performed using MEDLINE and EMBASE database from inception to May 2017. Studies that reported relative risks, odd ratios (ORs), or hazard ratios comparing the risk of Parkinson’s disease among HCV-infected patients versus participants without HCV infection were included. Pooled OR and 95% confidence interval were calculated using a random-effect, generic inverse variance method. Results Of 468 studies, five studies with 323 974 participants met our eligibility criteria and were included in the analysis. We found a higher risk of Parkinson’s disease among patients with chronic HCV infection compared with participants without HCV infection with the pooled OR of 1.35 (95% confidence interval: 1.19–1.52). The statistical heterogeneity of this study was insignificant (I 2=3%). The main limitation of this meta-analysis was the limited accuracy of diagnosis in the primary studies as they were coding-based studies. Conclusion This study demonstrated a higher risk of Parkinson’s disease among HCV-infected patients. Further studies are required to clarify how this risk should be addressed in the clinical picture.