Timing and co-occurrence of symptoms prior to a diagnosis of light chain (AL) amyloidosis.

It is well-established that most patients with systemic light chain (AL) amyloidosis have multi-organ involvement and are often diagnosed after a lag period of increasing symptoms. We leverage electronic health record (EHR) data from the TriNetX research network to describe the incidence, timing, and co-occurrence of precursor conditions of interests in a cohort of AL amyloidosis patients identified between October 2015-December 2020. Nineteen precursor diagnoses of interest representing features of AL amyloidosis were identified using ICD codes up to 36 months prior to AL amyloidosis diagnosis. Among 1,401 patients with at least 36 months of EHR data prior to AL amyloidosis diagnosis, 46% were females, 16% were non-Hispanic Black, and 6% were Hispanic. The median age was 71 (range, 21-91) years. The median number of precursor diagnoses was 5 with dyspnea and fatigue being the most prevalent. The time from the first occurrence of a precursor to AL diagnosis ranged from 3.2 to 21.4 months. Analyses of pairwise co-occurrence of specific diagnoses indicated a high association (Cole's coefficient >0.6) among the examined precursor diagnoses. These findings provide novel information about the timing and co-occurrence of key precursor conditions and could be used to develop algorithms for early identification of AL amyloidosis.

Timing and co-occurrence of symptoms prior to a diagnosis of light chain (AL) amyloidosis.

It is well-established that light chain (AL) amyloidosis patients have multi-organ involvement and are often diagnosed after a lag period of increasing symptoms. We leverage electronic health record (EHR) data from the TriNetX research network to describe the incidence, timing, and co-occurrence of precursor conditions of interests in a cohort of AL amyloidosis patients identified between October 2015-December 2020. Nineteen precursor diagnoses of interest representing features of AL amyloidosis were identified using ICD codes up to 36 months prior to AL amyloidosis diagnosis. Among 1,401 patients with at least 36 months of EHR data prior to AL amyloidosis diagnosis, 46% were females, 16% were non-Hispanic Black, and 6% were Hispanic. The median age was 71 (range, 21-91) years. The median number of precursor diagnoses was 5 with dyspnea and fatigue being the most prevalent. The time from the first occurrence of a precursor to AL diagnosis ranged from 3.2 to 21.4 months. Analyses of pairwise co-occurrence of specific diagnoses indicated a high association (Cole's coefficient > 0.6) among the examined precursor diagnoses. These findings provide novel information about the timing and co-occurrence of key precursor conditions and could be used to develop algorithms for early identification of AL amyloidosis.

Random forest analysis identifies change in serum creatinine and listing status as the most predictive variables of an outcome for young children on liver transplant waitlist.

Young children listed for liver transplant have high waitlist mortality (WL), which is not fully predicted by the PELD score. SRTR database was queried for children < 2 years listed for initial LT during 2002-17 (n = 4973). Subjects were divided into three outcome groups: bad (death or removal for too sick to transplant), good (spontaneous improvement), and transplant. Demographic, clinical, listing history, and laboratory variables at the time of listing (baseline variables), and changes in variables between listing and prior to outcome (trajectory variables) were analyzed using random forest (RF) analysis. 81.5% candidates underwent LT, and 12.3% had bad outcome. RF model including both baseline and trajectory variables improved prediction compared to model using baseline variables alone. RF analyses identified change in serum creatinine and listing status as the most predictive variables. 80% of subjects listed with a PELD score at time of listing and outcome underwent LT, while ~70% of subjects in both bad and good outcome groups were listed with either Status 1 (A or B) prior to an outcome, regardless of initial listing status. Increase in creatinine on LT waitlist was predictive of bad outcome. Longer time spent on WL was predictive of good outcome. Subjects with biliary atresia, liver tumors, and metabolic disease had LT rate >85%, while >20% of subjects with acute liver failure had a bad outcome. Change in creatinine, listing status, need for RRT, time spent on LT waitlist, and diagnoses were the most predictive variables.

Risk factors predicting Candida infective endocarditis in patients with candidemia.

Candida infective endocarditis (CIE) is a rare but serious complication of candidemia. Incidence and risk factors associated with CIE among candidemic patients are poorly defined from small cohorts. Identification of clinical predictors associated with this entity may guide more judicious use of cardiac imaging. We conducted a retrospective analysis of all inpatients aged ≥18 years diagnosed with candidemia at our institution. CIE was diagnosed by fulfilling two of the major Duke criteria: specifically a vegetation(s) on echocardiogram and positive blood cultures for Candida spp. We used univariable and multivariable regression analyses to identify risk factors associated with CIE. Of 1,873 patients with candidemia, 47 (2.5%) were identified to have CIE. In our multivariable logistic model, existing valvular heart disease was associated with a higher risk for CIE (adjusted odds ratio [aOR], 7.66; 95% confidence interval [CI], 2.95-19.84). Predictors that demonstrated a decreased risk of CIE included infection with C. glabrata (aOR, 0.17; 95% CI, 0.04-0.69), hematologic malignancy (aOR, 0.09; 95% CI, 0.01-0.68), and receipt of total parenteral nutrition (aOR, 0.38; 95% CI, 0.16-0.91). The 90-day crude mortality for CIE was 48.9%, similar to the overall non-CIE mortality of 41.9% (P = .338). We identified a set of clinical factors that can predict the presence of CIE among patient with candidemia. These findings may reduce the need for unnecessary expensive and invasive imaging studies in a subset of patients with a lower risk profile for endocarditis and alternative infection source.