Abstract Several disorders are associated with a monoclonal immunoglobulin detected by serum or urine electrophoresis, the most common being a monoclonal gammopathy of undetermined significance, multiple myeloma, Waldenström’s macroglobulinemia, and amyloidosis. The clinical features of these conditions, as well as other similar entities, are described in this review. The objective is to demonstrate the importance of electrophoretic studies in the differential diagnosis of plasma cell dyscrasias and in guiding the decision for rational therapies.
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The Merit-based Incentive Payment System (MIPS) is a mandatory pay-for-performance program through the Centers for Medicare & Medicaid Services (CMS) that aims to incentivize high-quality care, promote continuous improvement, facilitate electronic exchange of information, and lower health care costs. Previous research has highlighted several limitations of the MIPS program in assessing nephrology care delivery, including administrative complexity, limited relevance to nephrology care, and inability to compare performance across nephrology practices, emphasizing the need for a more valid and meaningful quality assessment program. This article details the iterative consensus-building process used by the American Society of Nephrology Quality Committee from May 2020 to July 2022 to develop the Optimal Care for Kidney Health MIPS Value Pathway (MVP). Two rounds of ranked-choice voting among Quality Committee members were used to select among nine quality metrics, 43 improvement activities, and three cost measures considered for inclusion in the MVP. Measure selection was iteratively refined in collaboration with the CMS MVP Development Team, and new MIPS measures were submitted through CMS's Measures Under Consideration process. The Optimal Care for Kidney Health MVP was published in the 2023 Medicare Physician Fee Schedule Final Rule and includes measures related to angiotensin-converting enzyme inhibitor and angiotensin receptor blocker use, hypertension control, readmissions, acute kidney injury requiring dialysis, and advance care planning. The nephrology MVP aims to streamline measure selection in MIPS and serves as a case study of collaborative policymaking between a subspecialty professional organization and national regulatory agencies.
Providing high-quality patient-centered care is the central mission of dialysis facilities. Assessing quality and patient-centeredness of dialysis care is necessary for continuous dialysis facility improvement. Based predominantly on readily measured items, current quality measures in dialysis care emphasize biochemical and utilization outcomes, with very few patient-reported items. Additionally, current metrics often do not account for patient preferences and may compromise patient-centered care by limiting the ability of providers to individualize care targets, such as dialysis adequacy, based on patient priorities rather than a fixed numerical target. Developing, implementing, and maintaining a quality program using readily quantifiable data while also allowing for individualization of care targets that emphasize the goals of patients and their care partners provided the motivation for a September 2022 Kidney Disease Outcomes Quality Initiative (KDOQI) Workshop on Patient-Centered Quality Measures for Dialysis Care. Workshop participants focused on 4 questions: (1) What are the outcomes that are most important to patients and their care partners? (2) How can social determinants of health be accounted for in quality measures? (3) How can individualized care be effectively addressed in population-level quality programs? (4) What are the optimal means for collecting valid and robust patient-reported outcome data? Workshop participants identified numerous gaps within the current quality system and favored a conceptually broader, but not larger, quality system that stresses highly meaningful and adaptive measures that incorporate patient-centered principles, individual life goals, and social risk factors. Workshop participants also identified a need for new, low-burden tools to assess patient goals and priorities. Providing high-quality patient-centered care is the central mission of dialysis facilities. Assessing quality and patient-centeredness of dialysis care is necessary for continuous dialysis facility improvement. Based predominantly on readily measured items, current quality measures in dialysis care emphasize biochemical and utilization outcomes, with very few patient-reported items. Additionally, current metrics often do not account for patient preferences and may compromise patient-centered care by limiting the ability of providers to individualize care targets, such as dialysis adequacy, based on patient priorities rather than a fixed numerical target. Developing, implementing, and maintaining a quality program using readily quantifiable data while also allowing for individualization of care targets that emphasize the goals of patients and their care partners provided the motivation for a September 2022 Kidney Disease Outcomes Quality Initiative (KDOQI) Workshop on Patient-Centered Quality Measures for Dialysis Care. Workshop participants focused on 4 questions: (1) What are the outcomes that are most important to patients and their care partners? (2) How can social determinants of health be accounted for in quality measures? (3) How can individualized care be effectively addressed in population-level quality programs? (4) What are the optimal means for collecting valid and robust patient-reported outcome data? Workshop participants identified numerous gaps within the current quality system and favored a conceptually broader, but not larger, quality system that stresses highly meaningful and adaptive measures that incorporate patient-centered principles, individual life goals, and social risk factors. Workshop participants also identified a need for new, low-burden tools to assess patient goals and priorities.
Abstract We present intense radiotracer activity in a soft tissue density abutting the aortic arch of the left lung on 18 F–prostate-specific membrane antigen PET/CT scan in a patient with prostate cancer, mimicking metastatic disease from prostate cancer versus primary lung malignancy. 18 F-FDG PET/CT scan, however, shows no elevated FDG activity. The results of pathology examination from resected specimen are consistent with pulmonary hemangioma.
Because of the unprecedented increase in critically ill patients with coronavirus disease 2019 (COVID-19), capacity to provide continuous RRT (CRRT) for AKI may quickly be overwhelmed (1). Exacerbating this resource crunch is the hypercoagulability observed in COVID-19 (2,3). Frequent CRRT circuit clotting leads to blood loss and wastage of already overextended resources, and need for troubleshooting increases health care provider exposure to infected patients. At our quaternary care academic institution, we perform CRRT using a uniform protocol in five intensive care units (ICUs). We do not use anticoagulation routinely but add it (mostly heparin) as needed. Additionally, for more than a decade, we have used regional citrate anticoagulation (RCA) as the default protocol in our surgical ICU. During the COVID-19 pandemic, our hospital added ten more ICUs. Systemic anticoagulation was available in all 16 ICUs, whereas RCA remained restricted to the surgical ICU, albeit with less frequent postfilter ionized calcium monitoring to reduce nurse exposure to infected patients. Herein, we describe our experience with the life of 502 CRRT circuits on different anticoagulation regimens in 80 patients with RT-PCR–confirmed COVID-19 who received continuous venovenous hemodialysis (NxStage System One) between March 5 and May 8, 2020 (Figure 1A). These circuits were categorized by their anticoagulation regimen at the time of filter stoppage: heparin (systemic unfractionated or low–mol wt heparin [LMWH]), prefilter heparin, argatroban, RCA (citrate), citrate plus heparin (when patients received systemic heparin for medical indications), or no anticoagulation (none).Figure 1.: Baseline characteristics of the study population and CRRT circuit survival. (A) Baseline characteristics at the start of continuous RRT (CRRT) and in-hospital mortality rate. (B) Kaplan–Meier estimated probability of continuous venovenous hemodialysis (CVVHD) circuit clotting-free survival on the basis of different anticoagulation regimens. IQR, interquartile range; SOFA, sequential organ failure assessment score.Circuit clotting was our analysis end point. Circuit life was the time (hours) from initiation of CRRT to clotting or censoring. Circuits that functioned beyond 72 hours were censored at 72 hours. Circuits terminated for reasons other than clotting were censored at the time of termination. We determined the association between circuit clotting and anticoagulation groups by Cox regression in Stata 16 software. Initial anticoagulation regimens for the 80 patients were systemic heparin (n=32), prefilter heparin (n=8), citrate (n=3), argatroban (n=2), citrate plus heparin (n=1), and none (n=34). While 39 of the 80 patients received the same anticoagulation (17 systemic heparin, four prefilter, two argatroban, and 16 none) for all of their circuits, 41 patients were switched to different anticoagulation regimens for subsequent circuits on the basis of the treating nephrologist's discretion. Of the 502 circuits, 350 (70%) received anticoagulation, and 152 (30%) did not. Among the circuits that received anticoagulation, heparin was used in 265 (76%; 191 systemic, 64 prefilter, and ten LWMH), citrate was used in 46 (13%; target postfilter ionized calcium <0.35 mmol/L), and argatroban was used in 39 (11%). Of the 46 citrate circuits, 25 (54%) received additional systemic heparin. For the purposes of this analysis, systemic heparin and LWMH were analyzed as one group. Clotting occurred in 203 (40%) circuits. Among 350 circuits with anticoagulation, 124 (35%) clotted, and among 152 with no anticoagulation, 79 (52%) clotted. Among circuits with anticoagulation, 13 (62%) with citrate, 33 (52%) with prefilter heparin, 63 (31%) with systemic heparin, ten (26%) with argatroban, and five (19%) with citrate plus heparin clotted. Median clotting-free survival was 21 hours (interquartile range, 48–7 hours) for no anticoagulation. For anticoagulated circuits, clotting-free survival was 25 hours (interquartile range, 57–10 hours) for prefilter heparin, 40 hours (interquartile range, 63–10 hours) for citrate, 49 hours (interquartile range, >72–14 hours) for systemic heparin, >72 hours (interquartile range, >72–40 hours) for argatroban, and >72 (interquartile range, >72–43 hours) for citrate plus heparin (Figure 1B). The hazard ratios for circuit clotting, independent of patient age and sex, were 0.92 (95% confidence interval, 0.50 to 1.68) for citrate, 0.85 (95% confidence interval, 0.56 to 1.29) for prefilter heparin, 0.59 (95% confidence interval, 0.44 to 0.80) for systemic heparin, 0.29 (95% confidence interval, 0.15 to 0.56) for argatroban, and 0.21 (95% confidence interval, 0.08 to 0.54) for citrate plus heparin compared with no anticoagulation. Frailty analysis revealed significant patient heterogeneity, suggesting that other patient-level characteristics were associated with filter clotting. Our findings are notable for several reasons. First, circuits with no anticoagulation performed below expectation. Data on filter patency using the NxStage system without anticoagulation are sparse; one study found 96.7% filter patency at 9 hours (4), and another documented an average filter life of 54.2 hours in a cohort in which nearly 90% of the circuits were run without anticoagulation (5). In contrast, >30% of filters in our study had clotted by 9 hours, and median filter life was only 21 hours. As such, treating teams may wish to empirically anticoagulate circuits to mitigate potential filter clotting. Second, citrate anticoagulation was not overtly effective. This contrasts with published data and our own experience over the last decade of citrate use. However, of the seven patients who were ever on citrate, four had circuit clotting on initial anticoagulation modality prior to being switched to citrate, and two had known episodes of thromboembolism during their hospital course. We speculate that aside from this possible selection bias, slightly reduced frequency of postfilter ionized calcium monitoring and other patient-level confounders may have affected citrate efficacy. Third, although argatroban and citrate plus heparin cannot be unequivocally recommended for routine use without further studies on safety and efficacy in this population, it is notable that these regimens performed extremely well, even though they were mostly used as escalation therapy in high-risk patients who had already developed thromboembolism necessitating systemic anticoagulation. Our report is limited by the study design, sample size, and patient-level heterogeneity. Further studies to elucidate these patient-level characteristics in circuit clotting are ongoing. Nevertheless, we believe that this first report of CRRT circuit life in the highly thrombophilic cohort of patients with COVID-19 will help physicians plan resources during this public health emergency. Disclosures F. Liu reports receiving consulting fees from CVS/Accordant, serving on the speakers' bureau for Janssen Pharmaceutical, and receiving personal fees from Fresenius as a guest lecturer for sales staff. He also served on the clinical events committee for Outset Medical and received consulting fees from Medtronic. All remaining authors have nothing to disclose. Funding None.
AKI is a recognized complication of coronavirus disease 2019 (COVID-19) (1). In this study, we characterized the AKI incidence and outcomes in patients with COVID-19 and AKI. We conducted a retrospective cohort study of 1002 patients admitted from March 1 to April 19, 2020 through the Emergency Department at NewYork-Presbyterian/Weill Cornell Medical Center. Patient follow-up was until at least June 20, 2020, at which time 22 patients were still hospitalized and nine were transferred to another hospital facility. Baseline creatinine was defined as the closest creatinine prior to March 1, 2020 or, if none was available, the creatinine at time of hospital presentation. The Weill Cornell Institutional Review Board approved this study. AKI, defined by the Kidney Disease Improving Global Outcomes criteria (2), occurred in 294 (29%) of the 1002 patients: stage 1 AKI (n=182, 18%); stage 2 AKI (n=29, 3%); and stage 3 AKI (n=83, 8%). KRT was performed in 59 patients (6%); 53 received hemodialysis and/or continuous venovenous hemodialysis, five received a combination of acute peritoneal dialysis and hemodialysis/continuous venovenous hemodialysis, and one received acute peritoneal dialysis. The time from hospitalization to AKI was a median of 2.2 days in stage 1 AKI, 2.4 days in stage 2 AKI, and 1.6 days in stage 3 AKI. We evaluated the urine electrolytes and microscopy associated with the AKI event within 3 days. Among those available, the fractional excretion of sodium (FENa) was <1% in 76%, and urine microscopy had granular casts in 21%. The presumed etiology of stage 3 AKI on the basis of manual chart review was acute tubular necrosis (ATN) in 28%, prerenal in 13%, prerenal/ATN in 11%, other causes in 4%, and unknown in 45% of patients. Granular casts were observed more frequently in stage 3 AKI than stage 1 AKI and stage 2 AKI (33% versus 16%, P=0.006). We compared clinical characteristics of the patients with AKI with those without AKI (Table 1). Patients who developed AKI were older and more frequently had a history of hypertension, diabetes mellitus, congestive heart failure, CKD, and kidney transplantation than patients without AKI (P<0.001). Proteinuria and hematuria were more frequent in patients with AKI than in patients without AKI (P<0.001). Baseline creatinine, admission creatinine, peak creatinine, white blood cells, procalcitonin, troponin I, C-reactive protein, d-dimer, ferritin, lactate dehydrogenase, lactate, and creatine kinase were significantly higher in patients with AKI than in patients without AKI (P<0.001), whereas hemoglobin and albumin levels were significantly lower in patients with AKI than in those without AKI (P<0.001). Patients with AKI were also more likely to have usage of nonsteroidal anti-inflammatory drugs, diuretics, and hydroxychloroquine during hospitalization; intensive care unit admission; mechanical ventilation; use of vasopressors; and longer hospital length of stay than patients without AKI (P<0.001). Table 1. - For continuous variable, the numbers of measurements are listed (n = number in total cohort/number in AKI group/number in the no AKI group) Characteristics Total Cohort, n=1002, No. (%) or Median (Interquartile Range) AKI Group, n=294, No. (%) or Median (Interquartile Range) No AKI Group, n=708, No. (%) or Median (Interquartile Range) Demographics and comorbidities Age, median, yr 66 (53–76) 69 (59–79) 63 (51–74) Men 619 (62%) 208 (71%) 411 (58%) Race White 354 (35%) 112 (38%) 242 (34%) Black 119 (12%) 41 (14%) 78 (11%) Other 272 (27%) 86 (29%) 186 (26%) Unknown/declined 257 (26%) 55 (19%) 202 (29%) Hypertensiona 597 (60%) 211 (72%) 386 (55%) Diabetes mellitusa 378 (38%) 138 (47%) 240 (34%) Congestive heart failurea 131 (13%) 67 (23%) 64 (9%) COPDa 81 (8%) 36 (12%) 45 (6%) Obesitya 184 (18%) 71 (24%) 113 (16%) CKDb 138 (14%) 66 (22%) 72 (10%) Kidney transplant recipient 33 (3%) 20 (7%) 13 (2%) Laboratory parametersc Baseline creatinine, mg/dl, n=1002/294/708 0.9 (0.8–1.2) 1.1 (0.9–1.4) 0.9 (0.8–1.1) Admission creatinine, mg/dl, n=1002/294/708 1.0 (0.8–1.3) 1.2 (0.9–1.9) 0.9 (0.8–1.1) Peak creatinine, mg/dl, n=1002/294/708 1.1 (0.8–1.8) 2.8 (1.8–5.0) 0.9 (0.8–1.2) WBC×103/μl, n=1002/294/708 6.9 (5.1–9.6) 7.6 (5.5–10.7) 6.7 (4.9–9.3) Hemoglobin, g/dl, n=1002/294/708 13.4 (12.2–14.8) 13.1 (11.5–14.5) 13.6 (12.4–14.8) Platelets ×103/μl, n=1000/294/706 207 (156–270) 200 (146–258) 213 (160–273) ALT, U/L, n=995/294/701 34 (22–57) 34 (21–54) 35 (23–59) AST, U/L, n=986/291/695 42 (28–65) 46 (30–70) 41 (27–63) Alkaline phosphatase, U/L, n=995/294/701 74 (59–100) 78 (59–105) 73 (58–99) Total bilirubin, mg/dl, n=995/294/701 0.6 (0.4–0.8) 0.6 (0.4–0.9) 0.6 (0.4–0.8) Albumin, g/dl, n=995/294/701 3.2 (2.8–3.5) 3.1 (2.7–3.4) 3.2 (2.9–3.6) Prothrombin time, s, n=878/284/594 13.3 (12.3–14.6) 13.4 (12.6–15) 13.2 (12.3–14.4) Procalcitonin, ng/ml, n=930/278/652 0.17 (0.09–0.42) 0.32 (0.16–0.69) 0.14 (0.08–0.30) Troponin I, ng/ml, n=845/262/583 0.03 (0.03–0.05) 0.04 (0.03–0.12) 0.03 (0.03–0.03) ESR, mm/h, n=716/216/500 73 (49–99) 76 (49–101) 72 (48–97) CRP, mg/dl, n=748/228/520 11 (6–19) 14 (7–22) 10 (5–17) d-dimer, ng/ml, n=686/211/475 442 (273–900) 636 (339–1845) 391 (248–772) Ferritin, ng/ml, n=784/240/544 732 (339–1392) 965 (500–1566) 611 (292–1278) IL-6, pg/ml, n=181/91/90 26 (10–58) 33 (14–63) 18 (9–50) LDH, U/L, n=866/263/603 417 (319–545) 478 (353–608) 399 (311–515) Lactate, mmol/L, n=619/197/422 1.6 (1.1–2.2) 1.9 (1.3–3) 1.5 (1.1–2.0) Creatine kinase, U/L, n=582/199/383 144 (76–308) 186 (86–409) 130 (71–255) Urine protein, 1+, 2+, 3+, n=748/269/479 505 (68%) 207 (77%) 298 (62%) Hematuria, 1+, 2+, 3+, n=748/269/479 362 (48%) 174 (65%) 188 (39%) Fractional excretion of sodium <1%, n=148 112 (76%) Urine granular casts >0/hpf, n=220 46 (21%) Hospital characteristics/outcomes NSAID usage in hospital 278 (28%) 104 (35%) 174 (25%) Diuretic usage in hospital 277 (28%) 178 (61%) 99 (14%) Anticoagulation usage in hospital 675 (67%) 201 (68%) 474 (67%) Hydroxychloroquine usage in hospital 695 (69%) 231 (79%) 464 (66%) ICU admission 274 (27%) 183 (62%) 91 (13%) Mechanical ventilation 261 (26%) 179 (61%) 82 (12%) Vasopressor usage 261 (26%) 183 (62%) 78 (11%) Length of stay, d, n=971/281/690 7 (3–17) 17 (7–39) 6 (3–12) Mortality 172 (17%) 118 (40%) 54 (8%) Among the laboratory parameters, WBCs, hemoglobin, platelets, ALT, AST, alkaline phosphatase, total bilirubin, albumin, procalcitonin, ESR, CRP, d-dimer, ferritin, and LDH were measured similarly in the AKI group and in the no AKI group (P>0.05), whereas prothrombin time, troponin I, IL-6, lactate, urine protein, and hematuria were measured more frequently in the AKI group than the no AKI group (P<0.05). P values were calculated using the Wilcoxon rank sum test for analysis of continuous variables and using the Fisher's exact test for analysis of dichotomous variables. All statistical analyses were performed using R 3.3.3. CKD indicates baseline creatinine of ≥1.5 mg/dl. COPD, chronic obstructive pulmonary disease; WBC, white blood cell; ALT, alanine aminotransferase; AST, aspartate aminotransferase; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; LDH, lactate dehydrogenase; hpf, high-power field; NSAID, nonsteroidal anti-inflammatory drug; ICU, intensive care unit.aObtained using International Classification of Diseases-9 and International Classification of Diseases-10 codes.bA baseline creatinine prior to Emergency Department presentation was used in 320 patients (32%).cAll laboratory values were the first values obtained after Emergency Department presentation except for the fractional excretion of sodium <1% and urine granular casts >0/hpf, which were obtained within 3 days of the AKI event. Urine granular casts were detected using an automated system (iRiCELL; Beckman Coulter, Brea, CA), and they were manually verified by laboratory technicians. Patients with AKI had higher mortality than patients without AKI (40% versus 8%, P<0.001). Among the patients with AKI, 140 (48%) recovered to their baseline kidney function. Among the 154 (52%) who did not recover to their baseline kidney function, 43 received dialysis, among which 34 were dialysis dependent and 26 died (60%), and 111 did not receive dialysis, among which 80 (72%) died (P=0.18). Patients with AKI who did not recover to their baseline kidney function were older; had more congestive heart failure; had less anticoagulation use; and had higher d-dimer, troponin I, and peak creatinine levels than patients with AKI who recovered to their baseline kidney function (P<0.001). Within the AKI group, we found that the FENa was <1% in a majority of patients, and granular casts were present in 21% of patients. However, another study found that FENa was <1% in 38% of cases of patients with AKI and COVID-19 (3), and therefore, FENa evaluation needs to be interpreted with due caution and may not reflect the AKI etiology. As for potential etiology for the AKI, limited data from patient series of kidney biopsies support ATN as the most common cause of AKI (4). Further studies are needed to better understand the basis for kidney dysfunction. In this study, we found several laboratory parameters that are significantly different between patients with AKI and patients without AKI. d-dimer level was significantly higher in patients with AKI without kidney function recovery than in patients with AKI and kidney function recovery. A recent study in patients with COVID-19 admitted to the intensive care unit reported d-dimer as predictive of the need for dialysis (5), and it is likely that d-dimer is a predictor of disease severity. We also found a higher IL-6 level in patients with AKI than in patients without AKI. Whether cytokine storm also played a role in kidney injury is unknown. Disease severity may also be linked to men, and further evaluation is needed to understand the relationship between sex and AKI. An important limitation of our study is that the incidence of community-acquired AKI may have been underestimated because only one-third of patients had a baseline creatinine prior to admission. In conclusion, our study identified a high incidence of AKI in hospitalized patients with COVID-19. We found that a significant proportion did not have complete kidney function recovery, supporting the importance of CKD follow-up in patients with COVID-19. Disclosures O. Akchurin reports receiving a grant from the National Institutes of Health and is a recipient of the Clinical Scholar Award from Weill Cornell Medicine. M. Choi reports receiving grants from the National Institutes of Health. D. Dadhania reports receiving advisory board fees from AlloVir Inc., CareDx, and Veloxis Pharm. D. Dadhania, J. Lee, and M. Suthanthiran have filed patent US-2020-0048713-A1 titled "Methods of detecting cell-free DNA in biological samples." J. Lee reports receiving a grant from BioFire Diagnostics LLC, grants from the National Institutes of Health, and a grant from the National Kidney Foundation. F. Liu reports receiving advisory board fees from Accordant and is on the speakers' bureau on Janssen Pharmaceuticals. V. Srivatana reports receiving speakers' fees from Baxter Healthcare. M. Suthanthiran reports receiving grants from CareDx, Inc. and the National Institutes of Health and consultant fees from CareDx, Inc. and Sparks Therapeutics. Y. Zhang reports other from Iris OB Health, Inc. and grants from the Agency for Healthcare Research and Quality, the National Institutes of Health, and the US Department of Transportation, outside the submitted work. All remaining authors have nothing to disclose. Funding This study received support from NewYork-Presbyterian Hospital and Weill Cornell Medical College, including the Clinical and Translational Science Center (National Center for Advancing Translational Sciences grant UL1 TR000457) and Joint Clinical Trials Office.
