Abstract Background and Aims The risk of hepatocellular cancer (HCC) after sustained virological response (SVR) with direct acting antivirals (DAA) is unclear. Our aim was to examine the risk and ...determinants of HCC in patients cured with DAA. Methods We conducted a retrospective cohort study of HCV patients who were treated with DAA in any of the 129 Veterans Health Administration hospitals between 1/1/2015 and 12/31/2015. We calculated the annual incidence rates for HCC by SVR. We used Cox regression models to compare the risk of HCC in patients with vs . those without SVR and to identify factors associated with incident HCC among patients with SVR. We reviewed a sample of HCC patients for tumor size and stage at diagnosis. Results Among 22,500 patients treated with DAA (19,518 with SVR; 2,982 without SVR), the mean (SD) age was 61.6 (6.1) year, and 39.0% had cirrhosis. There were 271 new cases of HCC, including 183 in patients with SVR. Compared to patients without SVR, those with SVR had a significantly reduced risk of HCC (0.90 vs. 3.45 HCC/100 PY; adjusted hazard ratio HR, 0.28, 95% CI=0.22–0.36). Patients with cirrhosis had the highest annual incidence of HCC after SVR (1.82 vs. 0.34/100 PY in patients without cirrhosis; adjusted HR, 4.73. 95% CI, 3.34-6.68). Most (>44.8%) HCC were classified as stage I. Maximum size of the largest lesion was ≤5 cm in over 75% of cases. Conclusions Among patients treated with DAA, SVR was associated with a considerable reduction in the risk of HCC. We did not find any evidence to suggest that DAAs promote HCC. However, in patients with SVR, the absolute HCC risk remained high in patients with established cirrhosis. These patients should be considered for ongoing HCC surveillance.
Study objective Emergency department (ED) crowding is a prevalent health delivery problem and may adversely affect the outcomes of patients requiring admission. We assess the association of ED ...crowding with subsequent outcomes in a general population of hospitalized patients. Methods We performed a retrospective cohort analysis of patients admitted in 2007 through the EDs of nonfederal, acute care hospitals in California. The primary outcome was inpatient mortality. Secondary outcomes included hospital length of stay and costs. ED crowding was established by the proxy measure of ambulance diversion hours on the day of admission. To control for hospital-level confounders of ambulance diversion, we defined periods of high ED crowding as those days within the top quartile of diversion hours for a specific facility. Hierarchic regression models controlled for demographics, time variables, patient comorbidities, primary diagnosis, and hospital fixed effects. We used bootstrap sampling to estimate excess outcomes attributable to ED crowding. Results We studied 995,379 ED visits resulting in admission to 187 hospitals. Patients who were admitted on days with high ED crowding experienced 5% greater odds of inpatient death (95% confidence interval CI 2% to 8%), 0.8% longer hospital length of stay (95% CI 0.5% to 1%), and 1% increased costs per admission (95% CI 0.7% to 2%). Excess outcomes attributable to periods of high ED crowding included 300 inpatient deaths (95% CI 200 to 500 inpatient deaths), 6,200 hospital days (95% CI 2,800 to 8,900 hospital days), and $17 million (95% CI $11 to $23 million) in costs. Conclusion Periods of high ED crowding were associated with increased inpatient mortality and modest increases in length of stay and costs for admitted patients.
BACKGROUND AND AIMS
Nonalcoholic fatty liver disease (NAFLD) is now the most common liver condition. Predicting its progression could help clinicians manage and potentially prevent complications. We ...evaluated the independent and joint effects of metabolic traits on the risk of cirrhosis and hepatocellular carcinoma (HCC) among patients with NAFLD.
APPROACH AND RESULTS
We assembled a retrospective cohort of patients with NAFLD diagnosed at 130 facilities in the Veterans Administration between January 1, 2004, and December 31, 2008, with follow‐up through December 31, 2015. We performed competing risk‐adjusted cause‐specific Cox models to evaluate the effects of metabolic traits (diabetes, hypertension, dyslipidemia, obesity) as additive or combined indicators on time to develop cirrhosis or HCC or a composite endpoint of both. Of the 271,906 patients, 22,794 developed cirrhosis, and 253 developed HCC during a mean of 9 years follow‐up. At baseline, the mean body mass index was 31.6 (SD, 5.6), 28.7% had diabetes, 70.3% had hypertension, and 62.3% had dyslipidemia with substantial overlap among these traits. The risk of progression was the lowest in patients with only one or no metabolic trait. There was a stepwise increase in risk with each additional metabolic trait. Compared with patients with no metabolic trait, patients with both hypertension and dyslipidemia had 1.8‐fold higher risk of progression to cirrhosis/HCC (hazard ratio HR = 1.8, 95% confidence interval CI = 1.59‐2.06); the risk was 2.6‐fold higher in patients with diabetes, obesity, dyslipidemia, and hypertension (HR = 2.6, 95% CI = 2.3‐2.9). These associations were stronger for HCC. Diabetes had the strongest association with HCC in this cohort.
CONCLUSIONS
Each additional metabolic trait increased the risk of cirrhosis and HCC in patients with NAFLD. Diabetes conferred the highest risk of progression to HCC. Patients with diabetes and coexisting hypertension and obesity may be important targets for secondary prevention.
Starfield and colleagues have suggested four overarching attributes of good primary care: “first-contact access for each need; long-term person- (not disease) focused care; comprehensive care for ...most health needs; and coordinated care when it must be sought elsewhere.” As this series on reinventing primary care highlights, there is a compelling need for new care delivery models that would advance these objectives. This need is particularly urgent for high-needs, high-cost (HNHC) populations. By definition, HNHC patients require extensive attention and consume a disproportionate share of resources, and as a result they strain traditional office-based primary care practices. In this essay, we offer a clinical vignette highlighting the challenges of caring for HNHC populations. We then describe two categories of primary care-based approaches for managing HNHC populations: complex case management, and specialized clinics focused on HNHC patients. Although complex case management programs can be incorporated into or superimposed on the traditional primary care system, such efforts often fail to engage primary care clinicians and HNHC patients, and proven benefits have been modest to date. In contrast, specialized clinics for HNHC populations are more disruptive, as care for HNHC patients must be transferred to a multidisciplinary team that can offer enhanced care coordination and other support. Such specialized clinics may produce more substantial benefits, though rigorous evaluation of these programs is needed. We conclude by suggesting policy reforms to improve care for HNHC populations.
Widely-prescribed prodrug opioids (e.g., hydrocodone) require conversion by liver enzyme CYP-2D6 to exert their analgesic effects. The most commonly prescribed antidepressant, selective serotonin ...reuptake inhibitors (SSRIs), inhibits CYP-2D6 activity and therefore may reduce the effectiveness of prodrug opioids. We used a machine learning approach to identify patients prescribed a combination of SSRIs and prodrug opioids postoperatively and to examine the effect of this combination on postoperative pain control. Using EHR data from an academic medical center, we identified patients receiving surgery over a 9-year period. We developed and validated natural language processing (NLP) algorithms to extract depression-related information (diagnosis, SSRI use, symptoms) from structured and unstructured data elements. The primary outcome was the difference between preoperative pain score and postoperative pain at discharge, 3-week and 8-week time points. We developed computational models to predict the increase or decrease in the postoperative pain across the 3 time points by using the patient's EHR data (e.g. medications, vitals, demographics) captured before surgery. We evaluate the generalizability of the model using 10-fold cross-validation method where the holdout test method is repeated 10 times and mean area-under-the-curve (AUC) is considered as evaluation metrics for the prediction performance. We identified 4,306 surgical patients with symptoms of depression. A total of 14.1% were prescribed both an SSRI and a prodrug opioid, 29.4% were prescribed an SSRI and a non-prodrug opioid, 18.6% were prescribed a prodrug opioid but were not on SSRIs, and 37.5% were prescribed a non-prodrug opioid but were not on SSRIs. Our NLP algorithm identified depression with a F1 score of 0.95 against manual annotation of 300 randomly sampled clinical notes. On average, patients receiving prodrug opioids had lower average pain scores (p<0.05), with the exception of the SSRI+ group at 3-weeks postoperative follow-up. However, SSRI+/Prodrug+ had significantly worse pain control at discharge, 3 and 8-week follow-up (p < .01) compared to SSRI+/Prodrug- patients, whereas there was no difference in pain control among the SSRI- patients by prodrug opioid (p>0.05). The machine learning algorithm accurately predicted the increase or decrease of the discharge, 3-week and 8-week follow-up pain scores when compared to the pre-operative pain score using 10-fold cross validation (mean area under the receiver operating characteristic curve 0.87, 0.81, and 0.69, respectively). Preoperative pain, surgery type, and opioid tolerance were the strongest predictors of postoperative pain control. We provide the first direct clinical evidence that the known ability of SSRIs to inhibit prodrug opioid effectiveness is associated with worse pain control among depressed patients. Current prescribing patterns indicate that prescribers may not account for this interaction when choosing an opioid. The study results imply that prescribers might instead choose direct acting opioids (e.g. oxycodone or morphine) in depressed patients on SSRIs.
Background
Guidelines widely recommend avoiding antibiotics for many acute upper respiratory infections (aURIs) to avert adverse events in the absence of likely benefit. However, the extent of harm ...from these antibiotics remains a subject of debate and could inform patient‐centered decision‐making. Prior estimates finding a number needed to harm (NNH) between 8 and 10 rely on patient‐reported adverse events of any severity. In this analysis, we sought to estimate adverse events by only measuring comparatively severe events that require subsequent clinical evaluation.
Methods
We constructed a retrospective cohort, including 51 million patient encounters. Using logistic regression models, we determined the adjusted odds ratio (aOR) of clinically detectable adverse events following antibiotic use compared with events among unexposed individuals with aURIs. Our outcomes included candidiasis, diarrhea, Clostridium difficile infection (CDI), and a composite outcome.
Findings
From our analysis, 62.4% of the population received antibiotics in an aURI encounter. Observed adverse events in the antibiotic‐exposed group were 54,279 and 46,936 for diarrhea and candidiasis, respectively, yielding an aOR of 1.24 and 1.61, and an NNH of 3,126 and 1,975. Observed events of CDI in the exposed group were 30,133, and aORs of isolated CDI and combined adverse events were 1.07 and 1.30, resulting in an NNH of 17,695 and 1,150, respectively. Females were more likely to be diagnosed with any adverse event. Overall antibiotics were found to result in 5.7 additional cases of CDI per 100,000 outpatient prescriptions following an upper respiratory tract infection.
Interpretation
Despite higher NNH than previous methods of analysis, we find substantial iatrogenic harm associated with prescribing antibiotics in aURIs.
Sustained virologic response (SVR) after direct acting antiviral agents (DAAs) holds promise for reducing hepatocellular cancer (HCC). DAAs have recently been available long enough to estimate the ...long‐term risk. We conducted a retrospective cohort study of hepatitis C virus (HCV) patients who achieved SVR with DAAs from 129 Veterans Health Administration hospitals between January 1, 2015, and December 31, 2015, with follow‐up through September 30, 2018. We calculated the overall and quarterly HCC incidence rates. We examined the effect of demographic, clinical, and behavioral factors and the decline or increase of FIB‐4 and aspartate aminotransferase to platelet ratio index (APRI) on HCC risk. Among the 18,076 patients with SVR, 544 incident cases of HCC were diagnosed during the mean 2.9 years of follow‐up. The cumulative 1, 2, and 3‐year risks of HCC were 1.1%, 1.9% and 2.8%, respectively. Cirrhosis was strongly associated with HCC risk (adjusted hazard ratio = 4.13, 95% confidence interval = 3.34‐5.11). The quarterly incidence rate of HCC remained stable between 1.00 and 1.23/100 person‐years (PY) and 1.5 to 2.3/100 PY in patients with cirrhosis. The risk of HCC was the highest in patients who had persistently high FIB‐4/APRI and both with and without cirrhosis. HCC risk fell in patients with cirrhosis who experienced a decrease of FIB‐4/APRI scores yet remained higher than the accepted threshold for HCC surveillance. HCC risk was also higher in patients with alcohol use, older age, and infection with HCV genotype 3. Most patients treated at an early stage of liver fibrosis had a stable low risk. Conclusion: Patients successfully treated with DAAs and at risk of HCC did not regress after 3.6 years of follow‐up. HCC risk remained above the accepted thresholds for surveillance in patients with cirrhosis. These data have important implications for HCC surveillance in cured HCV patients.
PDF
