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Special Anomaly Rules –

 

 

1) Systems

a. No one individual or group can lay claim to a system and tell others to leave. Amount of time spent ratting in the system does not matter.

b. People are encouraged to spread out and make full use of all systems in the territory. However, there are a lot of us sharing this space and if someone else turns up in your system and wants to rat too, they absolutely have the right to do so. 

c. When this happens, you are encouraged to fleet up and work together. If you (or they) decide not to fleet up and work cooperatively, that's fine.

2) Normal Anomalies

a. Normal Anomalies and their loot are the property of the individual or fleet that first enters the anomaly.

b. If you warp into a normal anomaly and it's already being cleared by someone else, ask to fleet up (preferred) or go find an unclaimed one to clear.

3) Special Anomalies (the rare ones)

a. Clearing normal anomalies in hopes of spawning a special anomaly is akin to rolling dice. If you roll the dice 50 times and don't get one and then someone else picks up the dice and gets it on their first roll, it may seem unfair but it's not. That's the nature of RNG. But fear not, for their luck is your luck!

b. Special Anomalies shall be defined as Scouts, Inquisitors, and Deadspace sites, and any event anomaly

c. Those who are ratting in the system and have fully completed at least one anomaly at the time a special anomaly spawns, shall have the right to take part in the special anomaly and earn a share of the loot. Amount of time spent ratting in the system does not matter.

4) To be eligible to participate: You must complete at least 1 anomaly before you can lay claim to any special in system. If a special spawns when you have not completed at least 1 anomaly, other members ratting in system who have completed at least 1 anomaly have priority rights to specials in that system and do not need to include you or share loot.

5) You may only claim or participate in a special anomaly when hopping from system to system, or claim a special without having completed an anomaly if there is no one else ratting in that system. Ratters in system who have completed at least one anomaly at time of special spawn have priority even if you claim it first in local chat.

6) If you and other players have both not completed a full, normal anomaly in system and for whatever reason you arrive in system at the same time, priority is given to the one who claims it first in local chat

7) If you leave a system, upon your return you must complete another normal anomaly to be eligible for a special spawn claim in that system. 

8) You may not be eligible for special spawn claim in more than one system at a time.

9) You may not complete one anomaly and then sit in system waiting for others to spawn a special. You must continue to clear anomalies and contribute towards making a special spawn. Don't be a parasite.

10) Everyone is expected to be flying a ship that can meaningfully contribute to the group. This generally means Tech 6 or higher. Exceptions can be made for special circumstances or new players

11) When a special anomaly spawns, to claim it you must:

a. Have completed at least 1 normal anomaly in that system and been continuing to attempt to clear normal anomalies.

b. Have claimed the special anomaly in local chat by stating the name of the special and "Claimed" (this is not a hard and fast rule, anything posted to claim ownership is acceptable). For example, saying "inquis claimed" is sufficient to claim an Inquisitor Special Anomaly spawn in system.

12) Best practice would be to take screenshot of everyone in local at time of the spawn as well, in the unfortunate event a dispute is to occur

13) All ratters in the system who wish to participate in the special anomaly shall converge on the entrance gate.

14) Message any additional ratters in the system to see if they are coming. Any ratter in the system who is not responsive to messages, and not on gate within 5 minutes will be considered uninterested.

15) Fleet up / combine fleets as needed.

16) Invite others who are eligible as per the rules above.

17) Agree to loot rules and designate a looter if needed.

18) Engage the special anomaly to claim ownership over it for the group and get space rich together.

Querious Ratting Map

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•          The Amgen-Fresenius research initiative: first publications on a large EU dialysis patient cohort (ARO database)

•          Summary of Published Results

•          v2.0 IHQ release 02 March 2011

•          ARO

•          The ARO research initiative

•          ARO-2: new cohort

•          Publications

•          An Epidemiological Study of Hemodialysis Patients Based on the European Fresenius Medical Care Hemodialysis Network: Results of the ARO Study

•          Angel de Francisco, Joseph Kim, Stefan Anker, Vasily Belozeroff, Bernard Canaud, Charles Chazot, Tilman Drüeke, Kai-Uwe Eckardt, Jürgen Floege, Florian Kronenberg, Iain Macdougall, Daniele Marcelli, Bart Molemans, Jutta Passlick-Deetjen, Guntram Schernthaner, Peter Stenvinkel, David Wheeler, Bruno Fouqueray and Pedro Aljama

•          de Francisco et al Nephron Clinical Practice 2011;118:c143-c154

•          Objectives

•          Study population

•          Open-cohort study design

•          Baseline demographics

•          Patient numbers by country

•          CKD aetiology (N=8963)

•          Dialysis parameters during first 6 months of follow up

•          Achieved Hb during the first 6 months of follow-up by dialysis vintage

•          Laboratory parameters during first 6 months of follow up

•          Medication use during first 6 months of follow up

•          Patient outcomes during entire study period

•          Causes of deaths during the entire study period (n=1678)

•          Discussion points raised in analysis

•          The diagnosis of CKD aetiology was inconsistent across countries

•          Mortality rates /1000 pt years ranged from 73-182 (avg 124) vs. 140 (EuroDOPPS), 220 (US DOPPS) and 210 (USRDS)

•          Lower diabetes rates in ARO (25%) vs. DOPPS (36%) and USRDS (55%)

•          Incident patients had higher mortality and ESA use than prevalent patients

•          Study limitations

•          No data from UK or Germany

•          Forty-four centres excluded as a result of inadequate data capture on key dialysis parameters

•          Data from a single dialysis provider (FMC)

•          Summary

•          8963 patients were included in the analysis giving a total of 12,194 patient-years of follow-up.

•          Overall, patient mortality is higher in incident patients than prevalent patients.

•          Patient characteristics and treatment patterns vary widely among the countries in the study owing to varied:

–        Distribution of comorbid conditions

–        Availability of health care resources

–        Physician training

•          Hemoglobin Variability Does Not Predict Mortality in European Hemodialysis Patients

•          Kai-Uwe Eckardt, Joseph Kim, Florian Kronenberg, Pedro Aljama, Stefan D Anker, Bernard Canaud, Bart Molemans, Peter Stenvinkel, Guntram Schernthaner, Elizabeth Ireland, Bruno Fouqueray and Iain C Macdougall

•          Eckardt et al J Am Soc Nephrol 21: 1765–1775, 2010

•          Background and rationale

•          Significant Hb variability in US HD populations

•          Unclear whether associated with mortality

•          So far, no data in European dialysis cohorts

•          Objectives

•          Describe and characterize Hb variability in a European population of HD patients

•          Identify predictors of high Hb variability

•          Evaluate the association between Hb variability and all-cause and cardio-vascular mortality

•          Study population

•          Methods

•          Exposure period: 6 months

•          Observation period: up to 18 months, immediately following exposure

•          Measures of Hb variability

–        Standard deviation (SD)

–        Residual SD

–        Time spent in target (11-12.5 g/dL)

–        Fluctuations across thresholds (CL, CT, CH, LAL, LAH, HA)

–        Area under the Curve (AUC)

•          Predictors of high variability were evaluated using logistic regression

•          Cox regression was used to examine the association between Hb variability and mortality

•          Methods
Area Under the Curve (AUC)

•          To capture both deviations of Hb from the mean and frequencies of fluctuations across time in a single quantitative index

•          AUC was calculated for each individual patient’s 6-month Hb profile

•          Incident patients had greater Hb variability and spent less time in target

•          Categories of Hb fluctuation across thresholds

•          Incident patients more likely to be in consistently low or high-amplitude Hb categories

•          Predictors of Hb variability

•          Hb variability expressed using SD, residual SD, time in target, and AUC is not associated with an increased risk of mortality after multivariable adjustment

•          Categories of Hb fluctuation across thresholds

•          Patients with consistently low Hb levels have the highest risk of mortality

•          Study limitations

•          Observational study:

–        difficult to determine cause-and-effect relationships

–        clinical database was not originally established as a research tool

–        database is from a single private dialysis provider (FMC)

–        generalizability to patients at other providers and countries without FMC centers remains unclear

•          44% of patients excluded from analysis because of open cohort design (52% of these were incident); may have resulted in selection bias.

•          Absence of information on iron therapy which may influence Hb variability or survival.

•          Median observation period ~1 year; precludes conclusions on longer-term mortality.

•          Although N>5000, numbers of events in subgroups were relatively small.

•          DOPPS: Risk of mortality is higher in facilities with higher Hb variability

•          Discussion of findings on Hb variability in DOPPS and Medicare analyses

•          Inter-facility Hb variability:¹

–        seen to be reduced between 1996-2008 in most countries assessed

–        mainly dependent on practice patterns

–        may be proposed as an indicator of care

•          Inter-patient ESA dose increases and younger age were linked with raised mortality risk and increased Hb variability¹

•          Intra-patient Hb variability association with mortality risk was weak, and inconsistent after adjustment for concurrent disease severity²

•       It remains to be seen whether decrease in Hb variability in an individual facility over time will translate into improved outcomes³

Ø  Hb variability may indicate disease severity and difference in quality of practice patterns, but by itself is not a good indicator of risk^1-3

•          Summary and conclusions

•          Hb variability occurs in the European HD population to a similar extent as in US HD populations

•          It is related to various patient characteristics, comorbidities, and hospitalizations but is not an independent risk factor for all-cause or cardio-vascular mortality

•          However, patients with consistently low Hb levels have the highest risk of mortality

•          Backup

•          Variables of adjustment

•          Demographics

–        age, gender, country, BMI, smoking status

•          Medical history

–        CKD aetiology, history of diabetes, history of CVD, history of Cancer

•          Dialysis parameters

–        Vintage, vascular access type, Kt/V, blood flow

•          Markers of inflammation

–        Serum albumin, CRP

•          CVD medications

–        Antihypertensive drugs, ACE inhibitors, oral anticoagulants, anti-aggregants

•          BMM medications

–        Vitamin D, phosphate binders

•          Other lab parameters

–        PTH, calcium, phosphate, Hb, ferritin, cholesterol, blood leucocytes

•          Miscellaneous

–        Hospitalization, change in vascular access type

•          AUC is highly correlated with within-person SD but not with time spent in target

•          Distribution of AUC is consistent with categories of fluctuation across thresholds

•          Serum iPTH, Calcium and Phosphate, and the Risk of Mortality in a European Haemodialysis Population

•          Jürgen Floege, Joseph Kim,  Elizabeth Ireland, Charles Chazot, Tilman Drueke, Angel de Francisco, Florian Kronenberg,  Daniele Marcelli, Jutta Passlick-Deetjen,  Guntram Schernthaner,  Bruno Fouqueray and David C. Wheeler on behalf of the ARO Investigators

•          Floege J et al. NDT 2010; published online Dec 10: doi: 10.1093/ndt/gfq219

•          Background and rationale

•          A number of US observational studies reported an increased mortality risk with higher intact parathyroid hormone (iPTH), calcium and/or phosphate.

•          The existence of such a link in a European haemodialysis population was explored as part of the Analysing Data, Recognising  Excellence and Optimising Outcomes (ARO) Chronic  Kidney Disease (CKD) Research Initiative.

•          Objectives

•          The aim of the present analysis was to examine the relation between levels of soluble markers of mineral bone disease (MBD: iPTH, total serum calcium and serum phosphate) and long-term mortality in 7970 hemodialysis patients treated at Fresenius Medical Care facilities in Europe.

•          Study population

•          Methods

•          Measurements of iPTH, calcium and phosphate were averaged over first quarter of follow-up, then divided into categories

•          All-cause mortality was the primary outcome of interest

•          Crude and adjusted hazard ratios (HR) for mortality were determined using baseline (i.e. fixed-covariate) Cox regression models

•          Time-dependent Cox analysis was performed to evaluate any potential effects of updating exposure and selected covariates over time

•          Baseline data by iPTH level

•          Baseline medical data by iPTH level

•          Baseline and time-dependent Cox regression for all-cause mortality

•          Adjusted risk for iPTH levels

•          Adjusted risk for calcium levels

•          Adjusted risk for phosphate levels

•          Adjusted risk for iPTH in diabetic vs. non-diabetic patients

•          Summary of the key findings

•          Serum iPTH:

–        In the adjusted baseline Cox analysis, the HR estimates were U-shaped. Patients with iPTH level below or above the 2003 KDOQI target range of 150 to 300 pg/mL had a greater risk of death.

–        The adjusted time-dependent analysis confirmed the U-shaped pattern.

•          Serum calcium:

–        The adjusted baseline analysis showed a higher risk of death in patients with high serum calcium levels (> 2.75 mmol/L) compared to those within the target range.

–        The adjusted time-dependent analysis showed that both patients with low calcium level and high calcium level had increased risk of death.

•          Serum phosphate:

–        The adjusted baseline analysis showed a U-shaped pattern similar to that for iPTH. Both low and high serum phosphate increased risk of death.

–        The adjusted time-dependent analysis showed increased risk of death for low phosphate only.

•          Comparative data from published studies on MBD and mortality in large HD populations

•          CORES study shows similar U-shaped association of mortality with PTH levels in Latin America

•          Study limitations

•          Analyses were based on observational data and no causal inference can be made.

•          Missing data were common among all the MBD markers considered, as were some potentially important confounding factors such as dialysate calcium concentration and intravenous administration of active vitamin D therapy derivatives

•          Results were not stratified by incident vs prevalent patients due to the small number of incident patients.

•          Adjustment for serum 25(OH) vitamin D was not made because this information was not captured in the ARO database.

•          Conclusions

•          Patients with iPTH, calcium and phosphate levels within the KDOQI recommended targets experienced the lowest risk of mortality compared with those outside the respective target ranges

•          The data are consistent with the KDIGO recommendations on CKD-MBD target parameters, although some patients could be at increased risk of mortality compared to those treated within the KDOQI target range

•          Very low or high values of iPTH and phosphate, as well as high values of calcium, should be avoided

•          Backup

•          Variables of adjustment

•          Demographics

–        age, gender, country, BMI, smoking status

•          Medical history

–        CKD aetiology, history of diabetes, history of CVD, history of Cancer

•          Dialysis parameters

–        Vintage, vascular access type, Kt/V, blood flow

•          Markers of inflammation

–        Serum albumin, CRP

•          CVD medications

–        Antihypertensive drugs, ACE inhibitors, oral anticoagulants, anti-aggregants

•          BMM medications

–        Vitamin D, phosphate binders

•          Other lab parameters

–        PTH, calcium, phosphate, Hb, ferritin, cholesterol, blood leucocytes

•          Miscellaneous

–        Hospitalization, change in vascular access type