Week 29 – CHADS2

“Validation of Clinical Classification Schemes for Predicting Stroke”

JAMA. 2001 June 13;285(22):2864-70. [free full text]

Atrial fibrillation is the most common cardiac arrhythmia and affects 1-2% of the overall population with increasing prevalence as people age. Atrial fibrillation also carries substantial morbidity and mortality due to the risk of stroke and thromboembolism although the risk of embolic phenomena varies widely across various subpopulations. In 2001, the only oral anticoagulation options available were warfarin and aspirin, which had relative risk reductions of 62% and 22%, respectively, consistent across these subpopulations. Clinicians felt that high risk patients should be anticoagulated, but the two common classification schemes, AFI and SPAF, were flawed. Patients were often classified as low risk in one scheme and high risk in the other. The schemes were derived retrospectively and were clinically ambiguous. Therefore, in 2001, a group of investigators combined the two existing schemes to create the CHADS2 scheme and applied it to a new data set.

Population (NRAF cohort): Hospitalized Medicare patients ages 65-95 with non-valvular AF not prescribed warfarin at hospital discharge.

Intervention: Determination of CHADS2 score (1 point for recent CHF, hypertension, age ≥ 75, and DM; 2 points for a history of stroke or TIA)

Comparison: AFI and SPAF risk schemes

Measured Outcome: Hospitalization rates for ischemic stroke (per ICD-9 codes from Medicare claims), stratified by CHADS2 / AFI / SPAF scores.

Calculated Outcome: performance of the various schemes, based on c statistic (a measure of predictive accuracy in a binary logistic regression model)

Results:
1733 patients were identified in the NRAF cohort. When compared to the AFI and SPAF trials, these patients tended be older (81 in NRAF vs. 69 in AFI vs. 69 in SPAF), have a higher burden of CHF (56% vs. 22% vs. 21%), are more likely to be female (58% vs. 34% vs. 28%), and have a history of DM (23% vs. 15% vs. 15%) or prior stroke/TIA (25% vs. 17% vs. 8%). The stroke rate was lowest in the group with a CHADS2 = 0 (1.9 per 100 patient years, adjusting for the assumption that aspirin was not taken). The stroke rate increased by a factor of approximately 1.5 for each 1-point increase in the CHADS2 score.

CHADS2 score            NRAF Adjusted Stroke Rate per 100 Patient-Years
0                                      1.9
1                                       2.8
2                                      4.0
3                                      5.9
4                                      8.5
5                                      12.5
6                                      18.2

The CHADS2 scheme had a c statistic of 0.82 compared to 0.68 for the AFI scheme and 0.74 for the SPAF scheme.

Implication/Discussion
The CHADS2 scheme provides clinicians with a scoring system to help guide decision making for anticoagulation in patients with non-valvular AF.

The authors note that the application of the CHADS2 score could be useful in several clinical scenarios. First, it easily identifies patients at low risk of stroke (CHADS2 = 0) for whom anticoagulation with warfarin would probably not provide significant benefit. The authors argue that these patients should merely be offered aspirin. Second, the CHADS2 score could facilitate medication selection based on a patient-specific risk of stroke. Third, the CHADS2 score could help clinicians make decisions regarding anticoagulation in the perioperative setting by evaluating the risk of stroke against the hemorrhagic risk of the procedure. Although the CHADS2 is no longer the preferred risk-stratification scheme, the same concepts are still applicable to the more commonly used CHA2DS2-VASc.

This study had several strengths. First, the cohort was from seven states that represented all geographic regions of the United States. Second, CHADS2 was pre-specified based on previous studies and validated using the NRAF data set. Third, the NRAF data set was obtained from actual patient chart review as opposed to purely from an administrative database. Finally, the NRAF patients were older and sicker than those of the AFI and SPAF cohorts, and thus the CHADS2 appears to be generalizable to the very large demographic of frail, elderly Medicare patients.

As CHADS2 became widely used clinically in the early 2000s, its application to other cohorts generated a large intermediate-risk group (CHADS2 = 1), which was sometimes > 60% of the cohort (though in the NRAF cohort, CHADS2 = 1 accounted for 27% of the cohort). In clinical practice, this intermediate-risk group was to be offered either warfarin or aspirin. Clearly, a clinical-risk predictor that does not provide clear guidance in over 50% of patients needs to be improved. As a result, the CHA2DS2-VASc scoring system was developed from the Birmingham 2009 scheme. When compared head-to-head in registry data, CHA2DS2-VASc more effectively discriminated stroke risk among patients with a baseline CHADS2 score of 0 to 1. Because of this, CHA2DS2-VASc is the recommended risk stratification scheme in the most recent AHA/ACC/HRS guidelines. In modern practice, anticoagulation is unnecessary when CHA2DS2-VASc score = 0, should be considered (vs. antiplatelet or no treatment) when score = 1, and is recommended when score ≥ 2.

Further Reading:
1. 2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation
2. CHA2DS2-VASc in Chest (2010)
3. CHADS2 @ 2 Minute Medicine

Summary by Ryan Commins, MD

Image Credit: Alisa Machalek, NIGMS/NIH – National Institute of General Medical Sciences, Public Domain, via Wikimedia Commons

Week 28 – FACT

“Febuxostat Compared with Allopurinol in Patients with Hyperuricemia and Gout”

aka the Febuxostat versus Allopurinol Controlled Trial (FACT)

N Engl J Med. 2005 Dec 8;353(23):2450-61. [free full text]

Gout is thought to affect approximately 3% of the US population, and its prevalence appears to be rising. Gout occurs due to precipitation of monosodium urate crystals from supersaturated body fluids. Generally, the limit of solubility is 6.8 mg/dL, but local factors such as temperature, pH, and other solutes can lower this threshold. A critical element in the treatment of gout is the lowering of the serum urate concentration below the limit of solubility, and generally, the accepted target is 6.0 mg/dL. The xanthine oxidase inhibitor allopurinol is the most commonly used urate-lowering pharmacologic therapy. Allopurinol rarely can have severe or life-threatening side effects, particularly among patients with renal impairment. Thus drug companies have sought to bring to market other xanthine oxidase inhibitors such as febuxostat (trade name Uloric). In this chronic and increasingly burdensome disease, a more efficacious drug with fewer exclusion criteria and fewer side effects would be a blockbuster.

The study enrolled adults with gout and a serum urate concentration of ≥ 8.0 mg/dL. Exclusion criteria included serum Cr ≥ 1.5 mg/dL or eGFR < 50 ml/min (due to this being a relative contraindication for allopurinol use) as well as a the presence of various conditions or use of various drugs that would affect urate metabolism and/or clearance of the trial drugs. (Patients already on urate-lowering therapy were given a two week washout period prior to randomization.) Patients were randomized to treatment for 52 weeks with either febuxostat 80mg PO daily, febuxostat 120mg PO daily, or allopurinol 300mg PO daily. Because the initiation of urate-lowering therapy places patients at increased risk of gout flares, patients were placed on prophylaxis with either naproxen 250mg PO BID or colchicine 0.6mg PO daily for the first 8 weeks of the study. The primary endpoint was a serum urate level of < 6.0 mg/dL at weeks 44, 48, and 52. Selected secondary endpoints included percentage reduction in serum urate from baseline at each visit, percentage reduction in area of a selected tophus, and prevalence of acute gout flares weeks requiring treatment.

762 patients were randomized. Baseline characteristics were statistically similar among all three groups. A majority of the patients were white males age 50+ who drank alcohol. Average serum urate was slightly less than 10 mg/dL. The primary endpoint (urate < 6.0 at the last three monthly measurements) was achieved in 53% of patients taking febuxostat 80mg, 62% of patients taking febuxostat 120mg, and 21% of patients taking allopurinol 300mg (p < 0.001 for each febuxostat groups versus allopurinol). Regarding selected secondary endpoints:

1) The percent reduction in serum urate from baseline at the final visit was 44.73 ± 19.10 in the febuxostat 80mg group, 52.52 ± 19.91 in the febuxostat 120mg group, and 32.99 ± 15.33 in the allopurinol 300mg group (p < 0.001 for each febuxostat group versus allopurinol, and p < 0.001 for febuxostat 80mg versus 120mg). 2) The percentage reduction in area of a single selected tophus was assessed in 156 patients who had tophi at baseline. At week 52, the median percentage reduction in tophus area was 83% in febuxostat 80mg patients, 66% in febuxostat 120mg patients, and 50% in allopurinol patients (no statistical difference per authors, p values not reported). Additionally, there was no significant reduction in tophus count in any of the groups. 3) During weeks 1-8 (in which acute gout flare prophylaxis was scheduled), 36% of patients in the febuxostat 120mg sustained a flare, whereas only 22% of the febuxostat 80mg group and 21% of the allopurinol group sustained a flare (p < 0.001 for both pairwise comparisons versus febuxostat 120mg). During weeks 9-52 (in which acute gout flare prophylaxis was no longer scheduled), a similar proportion of patients in each treatment group sustained an acute flare of gout (64% in the febuxostat 80mg group, 70% in the febuxostat 120mg group, and 64% in the allopurinol group). Finally, the incidence of treatment-related adverse events was similar among all three groups (see Table 3). Treatment was most frequently discontinued in the febuxostat 120mg group (98 patients, versus 88 patients in the febuxostat 80mg group and 66 patients in the allopurinol group; p = 0.003 for comparison between febuxostat 120mg and allopurinol).

In summary, this large RCT of urate-lowering therapy among gout patients found that febuxostat, dosed at either 80mg or 120mg PO daily, was more efficacious than allopurinol 300mg in reducing serum urate to below 6.0 mg/dL. Febuxostat was not superior to allopurinol with respect to the tested clinical outcomes of tophus size reduction, tophus count, and acute gout flares. Safety profiles were similar among the three regimens.

The authors note that the incidence of gout flares during and after the prophylaxis phase of the study “calls attention to a well-described paradox with important implications for successful management of gout: the risk of acute gout flares is increased early in the course of urate-lowering treatment” and the authors suggest that there is “a role for more sustained prophylaxis during the initiation of urate-lowering therapy than was provided here” (2458).

A limitation of this study is that its comparator group, allopurinol 300mg PO daily, may not have represented optimal use of the drug. Allopurinol should be uptitrated q2-4 weeks to the minimum dose required to maintain the goal serum urate of < 6.0 mg/dL (< 5.0 if tophi are present). According to UpToDate, “a majority of gout patients require doses of allopurinol exceeding 300 mg/day in order to maintain serum urate < 6.0 mg/dL.” In the United States allopurinol has been approved for doses of up to 800 mg daily. The authors state that “titration of allopurinol would have compromised the blinding of the study” (2459) but this is not true – blinded protocolized titration of study or comparator drugs has been performed in numerous other RCTs and could have been achieved simply at greater cost to and effort from the study sponsor (which happens to be the drug company TAP Pharmaceuticals). The likelihood that such titration would have shifted the results toward a null effect does not go unnoted. Another limitation is the relatively short duration of the trial – follow-up may have been insufficient to establish superiority in clinical outcomes, given the chronic nature of the disease.

In the UK, the National Institute for Health and Care Excellence (NICE), the agency tasked with assessing cost-effectiveness of various medical therapies, recommended as of 2008 that febuxostat be used for the treatment of hyperuricemia in gout “only for people who are intolerant of allopurinol or for whom allopurinol is contraindicated.”

Of note, a recent study funded by Takeda Pharmaceuticals demonstrated the non-inferiority of febuxostat relative to allopurinol with respect to rates of adverse cardiovascular events in patient with gout and major pre-existing cardiovascular conditions.

Allopurinol started at 100mg PO daily and titrated gradually to goal serum urate is the current general practice in the US. However, patients of Chinese, Thai, Korean, or “another ethnicity with similarly increased frequency of HLA-B*5801” should be tested for HLA-B*5801 prior to initiation of allopurinol therapy, as those patients are at increased risk of a severe cutaneous adverse reaction to allopurinol.

Further Reading/References:
1. FACT @ ClinicalTrials.gov
2. UpToDate “Pharmacologic urate-lowering therapy and treatment of tophi in patients with gout”
3. NICE: “Febuxostat for the management of hyperuricemia in people with gout”
4. “Cardiovascular Safety of Febuxostat or Allopurinol in Patients with Gout.” N Engl J Med. 2018 Mar 29;378(13):1200-1210.

Summary by Duncan F. Moore, MD

Image Credit: James Gilray, US Public Domain, via Wikimedia Commons

Week 27 – ELITE-Symphony

“Reduced Exposure to Calcineurin Inhibitors in Renal Transplantation”

by the Efficacy Limiting Toxicity Elimination (ELITE)-Symphony investigators

N Engl J Med. 2007 Dec 20;357(25):2562-75. [free full text]

A maintenance immunosuppressive regimen following kidney transplantation must balance the benefit of immune tolerance of the transplanted kidney against the adverse effects of the immunosuppressive regimen. Calcineurin inhibitors, such as cyclosporine (CsA) and tacrolimus, are nephrotoxic and can cause long-term renal dysfunction. They can also cause neurologic and infectious complications. At the time of this study, tacrolimus had been only recently introduced but already was appearing to be better than CsA at preventing acute rejection. Sirolimus, an mTOR inhibitor, is notable for causing delayed wound healing, among other adverse effects. The goal of the ELITE-Symphony study was to directly compare two different dosing regimens of CsA (standard- and low-dose) versus low-dose tacrolimus versus low-dose sirolimus, all while on background mycophenolate mofetil (MMF) and prednisone in order to determine which of these immunosuppressive regimens had the lowest nephrotoxicity, most efficacious prevention of rejection, and fewest other adverse effects.

The trial enrolled adults aged 18-75 scheduled to receive kidney transplants. There was a detailed set of exclusion criteria, including the need for treatment with immunosuppressants outside of the aforementioned regimens, specific poor prognostic factors regarding the allograft match or donor status, and specific comorbid or past medical conditions of the recipients. Patients were randomized open-label to one of four immunosuppressive treatment regimens in addition to MMF 2 gm daily and corticosteroids (“according to practice at the center” but with a pre-specified taper of minimum maintenance doses): 1) standard-dose CsA (target trough 150-300 ng/mL x3 months, then target trough 100-200 ng/mL), 2) daclizumab induction accompanied by low-dose cyclosporine (target trough 50-100 ng/mL), 3) daclizumab induction accompanied by low-dose tacrolimus (target trough 3-7 ng/mL), and 4) daclizumab induction accompanied by low-dose sirolimus (target trough 4-8 ng/mL). The primary endpoint was the eGFR at 12 months after transplantation. Secondary endpoints included acute rejection, incidence of delayed allograft function, and frequency of treatment failure (defined as use of additional immunosuppressive medication, discontinuation of any study medication for > 14 consecutive days or > 30 cumulative days, allograft loss, or death) within the first 12 months.

1645 patients were randomized. There were no significant differences in baseline characteristics among the four treatment groups. At 12 months following transplantation, mean eGFR differed among the four groups (p < 0.001). Low-dose tacrolimus patients had an eGFR of 65.4 ± 27.0 ml/min while standard-dose cyclosporine patients had an eGFR of 57.1 ± 25.1 ml/min (p < 0.001 for pairwise comparison with tacrolimus), low-dose cyclosporine patients had an eGFR of 59.4 ± 25.1 ml/min (p = 0.001 for pairwise comparison with tacrolimus), and low-dose sirolimus patients had an eGFR of 56.7 ± 26.9 ml/min (p < 0.001 for pairwise comparison with tacrolimus). The incidence of biopsy-proven acute rejection (excluding borderline values) at 6 months was only 11.3% in the low-dose tacrolimus group; however it was 24.0% in the standard-dose cyclosporine, 21.9% in the low-dose cyclosporine, and 35.3% in the low-dose sirolimus (p < 0.001 for each pairwise comparison with tacrolimus). Values were similar in magnitude and proportionality at 12-month follow-up. Delayed allograft function (among recipients of a deceased donor kidney) was lowest in the sirolimus group at 21.1% while it was 35.7% in the low-dose tacrolimus group (p = 0.001), 33.6% in the standard-dose cyclosporine group, and 32.4% (p = 0.73 for pairwise comparison with tacrolimus) in the low-dose cyclosporine group (p = 0.51 for pairwise comparison with tacrolimus). Treatment failure occurred in 12.2% of the low-dose tacrolimus group, 22.8% of the standard-dose cyclosporine group (p < 0.001 for pairwise comparison with tacrolimus), 20.1% of the low-dose cyclosporine group (p = 0.003 for pairwise comparison with tacrolimus), and in 35.8% of the low-dose sirolimus group (p < 0.001 for pairwise comparison with tacrolimus). Regarding safety events, the incidence of new-onset diabetes after transplantation (NODAT) at 12 months was highest among the low-dose tacrolimus group at 10.6% but only 6.4% among the standard-dose cyclosporine group, 4.7% among the low-dose cyclosporine group, and 7.8% among the low-dose sirolimus group (p = 0.02 for between-group difference per log-rank test). Opportunistic infections were most common in the standard-dose cyclosporine group at 33% (p = 0.03 for between-group difference per log-rank test).

In summary, the post-kidney transplant immunosuppression maintenance regimen with low-dose tacrolimus was superior to the standard- and low-dose cyclosporine regimens and sirolimus regimens with respect to renal function at 12 months, acute rejection at 6 and 12 months, and treatment failure during follow-up. However, this improved performance came at the cost of a higher rate of new-onset diabetes after transplantation. The findings of this study were integral to the 2009 KDIGO Clinical Practice Guideline for the Care of Kidney Transplant Recipients which recommends maintenance with a calcineurin inhibitor (tacrolimus first-line), and antiproliferative agent (MMF first-line), and corticosteroids (can consider discontinuation within 1 week in the relatively few patients at low immunologic risk for acute rejection, though expert opinion at UpToDate disagrees with this recommendation).

Further Reading/References:
1. ELITE-Symphony @ Wiki Journal Club
2. “The ELITE & the Rest in Kidney Transplantation.” Renal Fellow Network.
3. “HARMONY: Is it safe to withdraw steroids early after kidney transplant?” NephJC
4. 2009 KDIGO Clinical Practice Guideline for the Care of Kidney Transplant Recipients
5. “Maintenance immunosuppressive therapy in kidney transplantation in adults.” UpToDate

Summary by Duncan F. Moore, MD

Image Credit: Rmarlin, CC BY-SA 4.0, via Wikimedia Commons

Week 26 – ARISTOTLE

“Apixaban versus Warfarin in Patients with Atrial Fibrillation”

N Engl J Med. 2011 Sep 15;365(11):981-92. [free full text]

Prior to the development of the DOACs, warfarin was the standard of care for the reduction of risk of stroke in atrial fibrillation. Drawbacks of warfarin include a narrow therapeutic range, numerous drug and dietary interactions, the need for frequent monitoring, and elevated bleeding risk. Around 2010, the definitive RCTs for the oral direct thrombin inhibitor dabigatran (RE-LY) and the oral factor Xa inhibitor rivaroxaban (ROCKET AF) showed equivalence or superiority to warfarin. Shortly afterward, the ARISTOTLE trial demonstrated the superiority of the oral factor Xa inhibitor apixaban (Eliquis).

The trial enrolled patients with atrial fibrillation or flutter with at least one additional risk factor for stroke (age 75+, prior CVA/TIA, symptomatic CHF, or reduced LVEF). Notably, patients with Cr > 2.5 were excluded. Patients were randomized to treatment with either apixaban BID + placebo warfarin daily (reduced 2.5mg apixaban dose given in patients with 2 or more of the following: age 80+, weight < 60, Cr > 1.5) or to placebo apixaban BID + warfarin daily. The primary efficacy outcome was the incidence of stroke, and the primary safety outcome was “major bleeding” (clinically overt and accompanied by Hgb drop of ≥ 2, “occurring at a critical site,” or resulting in death). Secondary outcomes included all-cause mortality and a composite of major bleeding and “clinically-relevant non-major bleeding.”

9120 patients were assigned to the apixaban group, and 9081 were assigned to the warfarin group. Mean CHADS2 score was 2.1. Fewer patients in the apixaban group discontinued their assigned study drug. Median duration of follow-up was 1.8 years. The incidence of stroke was 1.27% per year in the apixaban group vs. 1.60% per year in the warfarin group (HR 0.79, 95% CI 0.66-0.95, p < 0.001). This reduction was consistent across all major subgroups (see Figure 2). Notably, the rate of hemorrhagic stroke was 49% lower in the apixaban group, and the rate of ischemic stroke was 8% lower in the apixaban group. All-cause mortality was 3.52% per year in the apixaban group vs. 3.94% per year in the warfarin group (HR 0.89, 95% CI 0.80-0.999, p = 0.047). The incidence of major bleeding was 2.13% per year in the apixaban group vs. 3.09% per year in the warfarin group (HR 0.69, 95% CI 0.60-0.80, p<0.001). The rate of intracranial hemorrhage was 0.33% per year in the apixaban group vs. 0.80% per year in the warfarin group (HR 0.42, 95% CI 0.30-0.58, p < 0.001). The rate of any bleeding was 18.1% per year in the apixaban group vs. 25.8% in the warfarin group (p <  0.001).

In patients with non-valvular atrial fibrillation and at least one other risk factor for stroke, anticoagulation with apixaban significantly reduced the risk of stroke, major bleeding, and all-cause mortality relative to anticoagulation with warfarin. This was a large RCT that was designed and powered to demonstrate non-inferiority but in fact was able to demonstrate the superiority of apixaban. Along with ROCKET AF and RE-LY, the ARISTOTLE trial ushered in the modern era of DOACs in atrial fibrillation. Apixaban was approved by the FDA for the treatment of non-valvular atrial fibrillation in 2012. Patient prescription cost is no longer a major barrier to prescription. These three major DOACs are all preferred in the DC Medicaid formulary (see page 13). To date, no trial has compared the various DOACs directly.

Further Reading/References:
1. ARISTOTLE @ Wiki Journal Club
2. ARISTOTLE @ 2 Minute Medicine
3. “Oral anticoagulants for prevention of stroke in atrial fibrillation: systematic review, network meta-analysis, and cost-effectiveness analysis,” BMJ 2017

Summary by Duncan F. Moore, MD

Week 25 – The Oregon Experiment

“The Oregon Experiment – Effects of Medicaid on Clinical Outcomes”

N Engl J Med. 2013 May 2;368(18):1713-22. [free full text]

Access to health insurance is not synonymous with access to healthcare. However, it has been generally assumed that increased access to insurance should improve healthcare outcomes among the newly insured. In 2008, Oregon expanded its Medicaid program by approximately 30,000 patients. These policies were lotteried among approximately 90,000 applicants. The authors of the Oregon Health Study Group sought to study the impact of this “randomized” intervention, and the results were hotly anticipated given the impending Medicaid expansion of the 2010 PPACA.

Population: Portland, Oregon residents who applied for the 2008 Medicaid expansion

Not all applicants were actually eligible.

Eligibility criteria: age 19-64, US citizen, Oregon resident, ineligible for other public insurance, uninsured for the previous 6 months, income below 100% of the federal poverty level, and assets < $2000.

Intervention: winning the Medicaid-expansion lottery

Comparison: The statistical analyses of clinical outcomes in this study do not actually compare winners to non-winners. Instead, they compare non-winners to winners who ultimately received Medicaid coverage. Winning the lottery increased the chance of being enrolled in Medicaid by about 25 percentage points. Given the assumption that “the lottery affected outcomes only by changing Medicaid enrollment, the effect of being enrolled in Medicaid was simply about 4 times…as high as the effect of being able to apply for Medicaid.” This allowed the authors to conclude causal inferences regarding the benefits of new Medicaid coverage.

Outcomes:
Values or point prevalence of the following at approximately 2 years post-lottery:

      1. blood pressure, diagnosis of hypertension
      2. cholesterol levels, diagnosis of hyperlipidemia
      3. HgbA1c, diagnosis of diabetes
      4. Framingham risk score for cardiovascular events
      5. positive depression screen, depression dx after lottery, antidepressant use
      6. health-related quality of life measures
      7. measures of financial hardship (e.g. catastrophic expenditures)
      8. measures of healthcare utilization (e.g. estimated total annual expenditure)

These outcomes were assessed via in-person interviews, assessment of blood pressure, and a blood draw for biomarkers.

Results:
The study population included 10,405 lottery winners and 10,340 non-winners. Interviews were performed ~25 months after the lottery. While there were no significant differences in baseline characteristics among winners and non-winners, “the subgroup of lottery winners who ultimately enrolled in Medicaid was not comparable to the overall group of persons ho did not win the lottery” (no demographic or other data provided).

At approximately 2 years following the lottery, there were no differences in blood pressure or prevalence of diagnosed hypertension between the lottery non-winners and those who enrolled in Medicaid. There were also no differences between the groups in cholesterol values, prevalence of diagnosis of hypercholesterolemia after the lottery, or use of medications for high cholesterol. While more Medicaid enrollees were diagnosed with diabetes after the lottery (absolute increase of 3.8 percentage points, 95% CI 1.93-5.73, p < 0.001; prevalence 1.1% in non-winners) and were more likely to be using medications for diabetes than the non-winners (absolute increase of 5.43 percentage points, 95% CI 1.39-9.48, p= 0.008), there was no statistically significant difference in HgbA1c values among the two groups. Medicaid coverage did not significantly alter 10-year Framingham cardiovascular event risk. At follow-up, fewer Medicaid-enrolled patients screened positive for depression (decrease of 9.15 percentage points, 95% CI -16.70 to -1.60,  p= 0.02), while more had formally been diagnosed with depression during the interval since the lottery (absolute increase of 3.81 percentage points, 95% CI 0.15-7.46, p= 0.04). There was no significant difference in prevalence of antidepressant use.

Medicaid-enrolled patients were more likely to report that their health was the same or better since 1 year prior (increase of 7.84 percentage points, 95% CI 1.45-14.23, p = 0.02). There were no significant differences in scores for quality of life related to physical health or in self-reported levels of pain or global happiness. As seen in Table 4, Medicaid enrollment was associated with decreased out-of-pocket spending (15% had a decrease, average decrease $215), decreased prevalence of medical debt, and a decreased prevalence of catastrophic expenditures (absolute decrease of 4.48 percentage points, 95% CI -8.26 to 0.69, p = 0.02).

Medicaid-enrolled patients were prescribed more drugs and had more office visits but no change in number of ED visits or hospital admissions. Medicaid coverage was estimated to increase total annual medical spending by $1,172 per person (an approximately 35% increase). Of note, patients enrolled in Medicaid were more likely to have received a pap smear or mammogram during the study period.

Implication/Discussion:
This study was the first major study to “randomize” health insurance coverage and study the health outcome effects of gaining insurance.

Overall, this study demonstrated that obtaining Medicaid coverage “increased overall health care utilization, improved self-reported health, and reduced financial strain.” However, its effects on patient-level health outcomes were much more muted. Medicaid coverage did not impact the prevalence or severity of hypertension or hyperlipidemia. Medicaid coverage appeared to aid in the detection of diabetes mellitus and use of antihyperglycemics but did not affect average A1c. Accordingly, there was no significant difference in Framingham risk score among the two groups.

The glaring limitation of this study was that its statistical analyses compared two groups with unequal baseline characteristics, despite the purported “randomization” of the lottery. Effectively, by comparing Medicaid enrollees (and not all lottery winners) to the lottery non-winners, the authors failed to perform an intention-to-treat analysis. This design engendered significant confounding, and it is remarkable that the authors did not even attempt to report baseline characteristics among the final two groups, let alone control for any such differences in their final analyses. Furthermore, the fact that not all reported analyses were pre-specified raises suspicion of post hoc data dredging for statistically significant results (“p-hacking”). Overall, power was limited in this study due to the low prevalence of the conditions studied.

Contemporary analysis of this study, both within medicine and within the political sphere, was widely divergent. Medicaid-expansion proponents noted that new access to Medicaid provided a critical financial buffer from potentially catastrophic medical expenditures and allowed increased access to care (as measured by clinic visits, medication use, etc.), while detractors noted that, despite this costly program expansion and fine-toothed analysis, little hard-outcome benefit was realized during the (admittedly limited) follow-up at two years.

Access to insurance is only the starting point in improving the health of the poor. The authors note that “the effects of Medicaid coverage may be limited by the multiple sources of slippage…[including] access to care, diagnosis of underlying conditions, prescription of appropriate medications, compliance with recommendations, and effectiveness of treatment in improving health.”

Further Reading/References:
1. Baicker et al. (2013), “The Impact of Medicaid on Labor Force Activity and Program Participation: Evidence from the Oregon Health Insurance Experiment”
2. Taubman et al. (2014), “Medicaid Increases Emergency-Department Use: Evidence from Oregon’s Health Insurance Experiment”
3. The Washington Post, “Here’s what the Oregon Medicaid study really said” (2013)
4. Michael Cannon, “Oregon Study Throws a Stop Sign in Front of ObamaCare’s Medicaid Expansion”
5. HealthAffairs Policy Brief, “The Oregon Health Insurance Experiment”
6. The Oregon Health Insurance Experiment

Summary by Duncan F. Moore, MD

Image Credit: Centers for Medicare and Medicaid Services, Public Domain, via Wikimedia Commons

Week 24 – CHOIR

“Correction of Anemia with Epoetin Alfa in Chronic Kidney Disease”

by the Investigators in the Correction of Hemoglobin and Outcomes in Renal Insufficiency (CHOIR)

N Engl J Med. 2006 Nov 16;355(20):2085-98. [free full text]

Anemia is a prevalent condition in CKD and ESRD. The anemia is largely attributable to the loss of erythropoietin production due to the damage of kidney parenchyma. Thus erythropoiesis-stimulating agents (ESAs) were introduced to improve this condition. Retrospective data and small interventional trials suggested that treatment to higher hemoglobin goals (such as > 12 g/dL) was associated with improved cardiovascular outcomes. However, in 1998, a prospective trial in ESRD patients on HD with a hematocrit treatment target of 42% versus 30% demonstrated a trend toward increased rates of non-fatal MI and death in the higher-target group. In an effort to clarify the hemoglobin goal in CKD patients, the 2006 CHOIR trial was designed. It was hypothesized that treatment of anemia in CKD to a target of 13.5 g/dL would lead to fewer cardiac events and reduced mortality when compared to a target of 11.3 g/dL.

The trial enrolled adults with CKD (eGFR 15-50 ml/min) and Hgb < 11.0 g/dL and notably excluded patients with active cancer. The patients were randomized to erythropoietin support regimens targeting a hemoglobin of either 13.5 g/dL or 11.3 g/dL. The primary outcome was a composite of death, MI, hospitalization for CHF, or stroke. Secondary outcomes included individual components of the primary outcome, need for renal replacement therapy, all-cause hospitalization, and various quality-of-life scores.

The study was terminated early due to an interim analysis revealing a < 5% chance that there would be a demonstrated benefit for the high-hemoglobin group by the scheduled end of the study. Results from 715 high-hemoglobin and 717 low-hemoglobin patients were analyzed. The mean change in hemoglobin was +2.5 g/dL in the high-hemoglobin group versus +1.2g/dL in the low-hemoglobin group (p < 0.001). The primary endpoint occurred in 125 of the high-hemoglobin patients (17.5%) versus 97 of the low-hemoglobin patients (13.5%) [HR 1.34, 95% CI 1.03-1.74, p = 0.03; number needed to harm = 25]. There were no significant group differences among the four components of the primary endpoint when analyzed as individual secondary outcomes, nor was there a difference in rates of renal replacement therapy. Any-cause hospitalization rates were 51.6% in the high-hemoglobin group versus 46.6% in the low-hemoglobin group (p = 0.03). Regarding quality-of-life scores, both groups demonstrated similar, statistically significant improvements from their respective baseline values.

In patients with anemia and CKD, treatment to a higher hemoglobin goal of 13.5 g/dL was associated with an increased incidence of a composite endpoint of death, MI, hospitalization for CHF, or stroke relative to a treatment goal of 11.3 g/dL. There were no differences between the two groups in hospitalization rates or progression to renal replacement therapy, and the improvement in quality of life was similar among the two treatment groups. Thus this study demonstrated no additional benefit and some harm with the higher treatment goal. The authors noted that “this study did not provide a mechanistic explanation for the poorer outcome with the use of a high target hemoglobin level.” Limitations of this trial included its non-blinded nature and relatively high patient withdrawal rates. Following this trial, the KDOQI clinical practice guidelines for the management of anemia in CKD were updated to recommend a Hgb target of 11.0-12.0 g/dL. However, this guideline was superseded by the 2012 KDIGO guidelines which, on the basis of further evidence, ultimately recommend initiating ESA therapy only in iron-replete CKD patients with Hgb < 10 g/dL with the goal of maintaining Hgb between 10 and 11.5 g/dL. Treatment should be individualized in patients with concurrent malignancy.

Further Reading/References:
1. Besarab et al. “The Effects of Normal as Compared with Low Hematocrit Values in Patients with Cardiac Disease Who Are Receiving Hemodialysis and Epoetin.” N Engl J Med. 1998 Aug 27;339(9):584-90.
2. CHOIR @ Wiki Journal Club
3. CHOIR @ 2 Minute Medicine
4. National Kidney Foundation Releases Anemia Guidelines Update (2007)
5. Pfeffer et al. “A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease.” N Engl J Med. 2009;361(21):2019.
6. KDOQI US Commentary on the 2012 KDIGO Clinical Practice Guideline for Anemia in CKD

Summary by Duncan F. Moore, MD

Week 23 – Effect of Early vs. Deferred Therapy for HIV (NA-ACCORD)

“Effect of Early versus Deferred Antiretroviral Therapy for HIV on Survival”

N Engl J Med. 2009 Apr 30;360(18):1815-26. [free full text]

Until recently, the optimal timing of initiation of antiretroviral therapy (ART) in asymptomatic patients with HIV had been a subject of investigation since the advent of antiretrovirals. Guidelines in 1996 recommended starting ART for all HIV-infected patients with CD4 count < 500, but over time provider concerns regarding resistance, medication nonadherence, and adverse effects of medications led to more restrictive prescribing. In the mid-2000s, guidelines recommended ART initiation in asymptomatic HIV patients with CD4 < 350. However, contemporary subgroup analysis of RCT data and other limited observational data suggested that deferring initiation of ART increased rates of progression to AIDS and mortality. Thus the NA-ACCORD authors sought to retrospectively analyze their large dataset to investigate the mortality effect of early vs. deferred ART initiation.

The study examined the cases of treatment-naïve patients with HIV and no hx of AIDS-defining illness evaluated during 1996-2005. Two subpopulations were analyzed retrospectively: CD4 count 351-500 and CD4 count 500+. No intervention was undertaken. The primary outcome was, within each CD4 sub-population, mortality in patients treated with ART within 6 months after the first CD4 count within the range of interest vs. mortality in patients for whom ART was deferred until the CD4 count fell below the range of interest.

8362 eligible patients had a CD4 count of 351-500, and of these, 2084 (25%) initiated ART within 6 months, whereas 6278 (75%) patients deferred therapy until CD4 < 351. 9155 eligible patients had a CD4 count of 500+, and of these, 2220 (24%) initiated ART within 6 months, whereas 6935 (76%) patients deferred therapy until CD4 < 500. In both CD4 subpopulations, patients in the early-ART group were older, more likely to be white, more likely to be male, less likely to have HCV, and less likely to have a history of injection drug use. Cause-of-death information was obtained in only 16% of all deceased patients. The majority of these deaths in both the early- and deferred-therapy groups were from non-AIDS-defining conditions.

In the subpopulation with CD4 351-500, there were 137 deaths in the early-therapy group vs. 238 deaths in the deferred-therapy group. Relative risk of death for deferred therapy was 1.69 (95% CI 1.26-2.26, p < 0.001) per Cox regression stratified by year. After adjustment for history of injection drug use, RR = 1.28 (95% CI 0.85-1.93, p = 0.23). In an unadjusted analysis, HCV infection was a risk factor for mortality (RR 1.85, p= 0.03). After exclusion of patients with HCV infection, RR for deferred therapy = 1.52 (95% CI 1.01-2.28, p = 0.04).

In the subpopulation with CD4 500+, there were 113 deaths in the early-therapy group vs. 198 in the deferred-therapy group. Relative risk of death for deferred therapy was 1.94 (95% CI 1.37-2.79, p < 0.001). After adjustment for history of injection drug use, RR = 1.73 (95% CI 1.08-2.78, p = 0.02). Again, HCV infection was a risk factor for mortality (RR = 2.03, p < 0.001). After exclusion of patients with HCV infection, RR for deferred therapy = 1.90 (95% CI 1.14-3.18, p = 0.01).

Thus, in a large retrospective study, the deferred initiation of antiretrovirals in asymptomatic HIV infection was associated with higher mortality.

This was the first retrospective study of early initiation of ART in HIV that was large enough to power mortality as an endpoint while controlling for covariates. However, it is limited significantly by its observational, non-randomized design that introduced substantial unmeasured confounders. A notable example is the absence of socioeconomic confounders (e.g. insurance status). Perhaps early-initiation patients were more well-off, and their economic advantage was what drove the mortality benefit rather than the early initiation of ART. This study also made no mention of the tolerability of ART or adverse reactions to it.

In the years that followed this trial, NIH and WHO consensus guidelines shifted the trend toward earlier treatment of HIV. In 2015, the INSIGHT START trial (the first large RCT of immediate vs. deferred ART) showed a definitive mortality benefit of immediate initiation of ART in patients with CD4 500+. Since that time, the standard of care has been to treat essentially all HIV-infected patients with ART (with some considerations for specific subpopulations, such as delaying initiation of therapy in patients with cryptococcal meningoencephalitis due to risk of IRIS). See further discussion at UpToDate.

Further Reading/References:
1. NA-ACCORD @ Wiki Journal Club
2. NA-ACCORD @ 2 Minute Medicine
3. INSIGHT START (2015), Pubmed, NEJM PDF
4. UpToDate, “When to initiate antiretroviral therapy in HIV-infected patients”

Summary by Duncan F. Moore, MD

Image Credit: Sigve, CC0 1.0, via WikiMedia Commons

Week 22 – TRICC

“A Multicenter, Randomized, Controlled Clinical Trial of Transfusion Requirements in Critical Care”

N Engl J Med. 1999 Feb 11; 340(6): 409-417. [free full text]

Although intuitively a hemoglobin closer to normal physiologic concentration seems like it would be beneficial, the vast majority of the time in inpatient settings we use a hemoglobin concentration of 7g/dL as our threshold for transfusion in anemia. Historically, higher hemoglobin cutoffs were used with aims to keep Hgb > 10g/dL. In 1999, the landmark TRICC trial demonstrated no mortality benefit in the liberal transfusion strategy and harm in certain subgroup analyses.

Population:

Inclusion: critically ill patients expected to be in ICU > 24h, Hgb ≤ 9g/dL within 72hr of ICU admission, and clinically euvolemic after fluid resuscitation

Exclusion criteria: age < 16, inability to receive blood products, active bleed, chronic anemia, pregnancy, brain death, consideration of withdrawal of care, and admission after routine cardiac procedure.

Patients were randomized to either a liberal transfusion strategy (transfuse to Hgb goal 10-12g/dL, n = 420) or a restrictive strategy (transfuse to Hgb goal 7-9g/dL, n = 418). The primary outcome was 30-day all-cause mortality. Secondary outcomes included 60-day all-cause mortality, mortality during hospital stay (ICU plus step-down), multiple-organ dysfunction score, and change in organ dysfunction from baseline. Subgroup analyses included APACHE II score ≤ 20 (i.e. less-ill patients), patients younger than 55, cardiac disease, severe infection/septic shock, and trauma.

Results:
The primary outcome of 30-day mortality was similar between the two groups (18.7% vs. 23.3%, p = 0.11). The secondary outcome of mortality rate during hospitalization was lower in the restrictive strategy (22.2% vs. 28.1%, p = 0.05). (Of note, the mean length of stay was about 35 days for both groups.) 60-day all-cause mortality trended towards lower in the restrictive strategy although did not reach statistical significance (22.7% vs. 26.5 %, p = 0.23). Between the two groups, there was no significant difference in multiple-organ dysfunction score or change in organ dysfunction from baseline.

Subgroup analyses in patients with APACHE II score ≤ 20 and patients younger than 55 demonstrated lower 30-day mortality and lower multiple-organ dysfunction score among patients treated with the restrictive strategy. In the subgroups of primary disease process (i.e. cardiac disease, severe infection/septic shock, and trauma) there was no significant differences among treatment arms.

Complications in the ICU were monitored, and there was a significant increase in cardiac events (primarily pulmonary edema) in the liberal strategy group when compared to the restrictive strategy group.

Discussion/Implication:
The TRICC trial demonstrated that, among ICU patients with anemia, there was no difference in 30-day mortality between a restrictive and liberal transfusion strategy. Secondary outcomes were notable for a decrease in inpatient mortality with the restrictive strategy. Furthermore, subgroup analyses showed benefit in various metrics for a restrictive transfusion strategy when adjusting for younger and less ill patients. This evidence laid the groundwork for our current standard of transfusing to hemoglobin 7g/dL. A restrictive strategy has also been supported by more recent studies. In 2014 the Transfusion Thresholds in Septic Shock (TRISS) study showed no change in 90-day mortality with a restrictive strategy. Additionally, in 2013 the Transfusion Strategy for Acute Upper Gastrointestinal Bleeding study showed reduced 40-day mortality in the restrictive strategy. However, the study’s exclusion of patients who had massive exsanguination or low rebleeding risk reduced generalizability. Currently, the Surviving Sepsis Campaign endorses transfusing RBCs only when Hgb < 7g/dL unless there are extenuating circumstances such as MI, severe hypoxemia, or active hemorrhage.

Further reading:
1. TRICC @ Wiki Journal Club
2. TRICC @ 2 Minute Medicine
3. TRISS @ Wiki Journal Club, full text, Georgetown Critical Care Top 40 pages 14-15
4. “Transfusion strategies for acute upper gastrointestinal bleeding” (NEJM 2013) @ 52 in 52 (2018-2019) Week 41, @ Wiki Journal Club, full text
5. “Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2016”

Summary by Gordon Pelegrin, MD

Image Credit: U.S. Air Force Master Sgt. Tracy L. DeMarco, public domain, via WikiMedia Commons

Week 21 – PROSEVA

“Prone Positioning in Severe Acute Respiratory Distress Syndrome”
by the PROSEVA Study Group

N Engl J Med. 2013 June 6; 368(23):2159-2168 [free full text]

Prone positioning had been used for many years in ICU patients with ARDS in order to improve oxygenation. Per Dr. Sonti’s Georgetown Critical Care Top 40, the physiologic basis for benefit with proning lies in the idea that atelectatic regions of lung typically occur in the most dependent portion of an ARDS patient, with hyperinflation affecting the remaining lung. Periodic reversal of these regions via moving the patient from supine to prone and vice versa ensures no one region of the lung will have extended exposure to either atelectasis or overdistention. Although the oxygenation benefits have been long noted, the PROSEVA trial established mortality benefit.

Study patients were selected from 26 ICUs in France and 1 in Spain which had daily practice with prone positioning for at least 5 years. Inclusion criteria: ARDS patients intubated and ventilated <36hr with severe ARDS (defined as PaO2:FiO2 ratio < 150, PEEP > 5, and TV of about 6ml/kg of predicted body weight). (NB: by the Berlin definition for ARDS, severe ARDS is defined as PaO2:FiO2 ratio < 100.) Patients were either randomized to the intervention of proning within 36 hours of mechanical ventilation for at least 16 consecutive hours (n = 237) or to the control of being left in a semirecumbent (supine) position (n = 229). The primary outcome was mortality at day 28. Secondary outcomes included mortality at day 90, rate of successful extubation (no reintubation or use of noninvasive ventilation x48hr), time to successful extubation, length of stay in the ICU, complications, use of noninvasive ventilation, tracheotomy rate, number of days free from organ dysfunction, ventilator settings, measurements of ABG, and respiratory system mechanics during the first week after randomization.

At the time of randomization in the study, the majority of characteristics were similar between the two groups, although the authors noted differences in the SOFA score and the use of neuromuscular blockers and vasopressors. The supine group at baseline had a higher SOFA score indicating more severe organ failure, and also had higher rate of vasopressor usage. The prone group had a higher rate of usage of neuromuscular blockade. The primary outcome of 28 day mortality was significantly lower in the prone group than in the supine group, at 16.0% vs 32.8% (p < 0.001, NNT = 6.0). This mortality decrease was still statistically significant when adjusted for the SOFA score. Secondary outcomes were notable for a significantly higher rate of successful extubation in the prone group (hazard ratio 0.45; 95% CI 0.29-0.7, p < 0.001). Additionally, the PaO2:FiO2 ratio was significantly higher in the supine group, whereas the PEEP and FiO2 were significantly lower. The remainder of secondary outcomes were statistically similar.

PROSEVA showed a significant mortality benefit with early use of prone positioning in severe ARDS. This mortality benefit was considerably larger than that seen in past meta-analyses, which was likely due to this study selecting specifically for patients with severe disease as well as specifying longer prone-positioning sessions than employed in prior studies. Critics have noted the unexpected difference in baseline characteristics between the two arms of the study. While these critiques are reasonable, the authors mitigate at least some of these complaints by adjusting the mortality for the statistically significant differences. With such a radical mortality benefit it might be surprising that more patients are not proned at our institution. One reason is that relatively few of our patients have severe ARDS. Additionally, proning places a high demand on resources and requires a coordinated effort of multiple staff. All treatment centers in this study had specially-trained staff that had been performing proning on a daily basis for at least 5 years, and thus were very familiar with the process. With this in mind, we consider the use of proning in patients meeting criteria for severe ARDS.

References and further reading:
1. PROSEVA @ 2 Minute Medicine
2. PROSEVA @ Wiki Journal Club
3. PROSEVA @ Georgetown Critical Care Top 40, pages 8-9
4. Life in the Fastlane, Critical Care Compendium, “Prone Position and Mechanical Ventilation”
5. PulmCCM.org, “ICU Physiology in 1000 Words: The Hemodynamics of Prone”

Summary by Gordon Pelegrin, MD

Image Credit: by James Heilman, MD, CC BY-SA 3.0, via Wikimedia Commons

Week 20 – MELD

“A Model to Predict Survival in Patients With End-Stage Liver Disease”

Hepatology. 2001 Feb;33(2):464-70. [free full text]

Prior to the adoption of the Model for End-Stage Liver Disease (MELD) score for the allocation of liver transplants, the determination of medical urgency was dependent on the Child-Pugh score. The Child-Pugh score was limited by the inclusion of two subjective variables (severity of ascites and severity of encephalopathy), limited discriminatory ability, and a ceiling effect of laboratory abnormalities. Stakeholders sought an objective, continuous, generalizable index that more accurately and reliably represented disease severity. The MELD score had originally been developed in 2000 to estimate the survival of patients undergoing TIPS. The authors of this 2001 study hypothesized that the MELD score would accurately estimate short-term survival in a wide range of severities and etiologies of liver dysfunction and thus serve as a suitable replacement measure for the Child-Pugh score in the determination of medical urgency in transplant allocation.

This study reported a series of four retrospective validation cohorts for the use of MELD in prediction of mortality in advanced liver disease. The index MELD score was calculated for each patient. Death during follow-up was assessed by chart review.

MELD score = 3.8*ln([bilirubin])+11.2*ln(INR)+9.6*ln([Cr])+6.4*(etiology: 0 if cholestatic or alcoholic, 1 otherwise)

The primary study outcome was the concordance c-statistic between MELD score and 3-month survival. The c-statistic is equivalent to the area under receiver operating characteristic (AUROC). Per the authors, “a c-statistic between 0.8 and 0.9 indicates excellent diagnostic accuracy and a c-statistic greater than 0.7 is generally considered as a useful test.” (See page 455 for further explanation.) There was no reliable comparison statistic (e.g. c-statistic of MELD vs. that of Child-Pugh in all groups).

C-statistic for 3-month survival in the four cohorts ranged from 0.78 to 0.87 (no 95% CIs exceeded 1.0). There was minimal improvement in the c-statistics for 3-month survival with the individual addition of spontaneous bacterial peritonitis, variceal bleed, ascites, and encephalopathy to the MELD score (see Table 4, highest increase in c-statistic was 0.03). When the etiology of liver disease was excluded from the MELD score, there was minimal change in the c-statistics (see Table 5, all paired CIs overlap). C-statistics for 1-week mortality ranged from 0.80 to 0.95.

In conclusion, the MELD score is an excellent predictor of short-term mortality in patients with end-stage liver disease of diverse etiology and severity. Despite the retrospective nature of this study, this study represented a significant improvement upon the Child-Pugh score in determining medical urgency in patients who require liver transplant. In 2002, the United Network for Organ Sharing (UNOS) adopted a modified version of the MELD score for the prioritization of deceased-donor liver transplants in cirrhosis. Concurrent with the 2001 publication of this study, Wiesner et al. performed a prospective validation of the use of MELD in the allocation of liver transplantation. When published in 2003, it demonstrated that MELD score accurately predicted 3-month mortality among patients with chronic liver disease on the waitlist. The MELD score has also been validated in other conditions such as alcoholic hepatitis, hepatorenal syndrome, and acute liver failure (see UpToDate). Subsequent additions to the MELD score have come out over the years. In 2006, the MELD Exception Guidelines offered extra points for severe comorbidities (e.g HCC, hepatopulmonary syndrome). In January 2016, the MELDNa score was adopted and is now used for liver transplant prioritization.

References and Further Reading:
1. “A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts” (2000)
2. MDCalc “MELD Score”
3. Wiesner et al. “Model for end-stage liver disease (MELD) and allocation of donor livers” (2003)
4. Freeman Jr. et al. “MELD exception guidelines” (2006)
5. MELD @ 2 Minute Medicine
6. UpToDate “Model for End-stage Liver Disease (MELD)”

Summary by Duncan F. Moore, MD

Image Credit: Ed Uthman, CC-BY-2.0, via WikiMedia Commons