As new Patient-Reported Outcomes Measurement Information System (PROMIS) instruments are incorporated into clinical practice, determining how large a change on these instruments represents a ...clinically relevant difference is important; the metric that describes this is the minimum clinically important difference (MCID). Prior research on MCIDs of the Neck Disability Index (NDI) and Oswestry Disability Index (ODI) has produced values ranging from 5 to 10 points, but these measures have not been presented in relation to MCID values of PROMIS instruments.
To establish a comprehensive repository of MCID values calculated both with distribution-based and anchor-based methods for four outcomes instruments in spine care, we asked: (1) What are the MCIDs of the PROMIS Physical Function (PF); (2) the PROMIS Pain Interference (PI); (3) the NDI; and (4) the ODI among spine patients?
We conducted a prospective study of previously tested diagnostic measures on 1945 consecutive patients with a reference standard applied. All patients aged 18 years and older visiting an orthopaedic spine clinic between October 2013 and January 2017 completed the PROMIS PF and PI, NDI, and ODI on tablet computers before their clinic visits. Patients were grouped by change level (self-report of meaningful change versus slight or no change) using an anchor question in comparison to baseline. Descriptive statistics, two anchor-based MCID values (mean change and receiver operating characteristic curve), and five distribution-based values (SD at 1/2 and 1/3 values and minimum detectable change MDC at 90%, 95%, and 99%) were analyzed four different times between 3 months and > 6 months of followup. A total of 1945 included patients with a wide range of spine conditions and varying treatments had a mean age of 58 years (SD = 15.5), were 51% (988 of 1945) male, 90% (1754 of 1945) self-identified as white, and 5% (94 of 1945) as Hispanic with 1% to 2% of patients refusing participation.
The PROMIS PF mean change scores in the changed group (much worse, worse, improved, or much improved) ranged between 7 and 8 points. MCID values ranged from 3 to 23 points depending on the method of calculation with a median of 8. For the PROMIS PI, mean change scores ranged from 8 to 9 points and MCID values from 1 to 24 points with a median of 8. For the NDI, mean change scores ranged from 13 to 18 points and MCID values ranged from 6 to 43 points with a median of 18. For the ODI, mean change ranged from 17 to 19 points and MCID values ranged from 7 to 51 points with a median of 24. For each instrument, distribution-based SD yielded the smallest values, followed by anchor-based methods, with MDC yielding the largest MCID values.
This study uses a range of methods for determining MCIDs of the PROMIS PF and PI, NDI, and ODI from anchor-based to distribution-based methods. MCIDs do not have a static value for a given outcome measure, but have a range of values and are dependent on the method calculated. The lowest MCIDs identified for the NDI and ODI are consistent with prior studies, but those at the upper range are much higher. Anchor-based methods are thought to be most relevant in the clinical setting and are more easily understood by clinicians, whereas the distribution-based MCIDs are useful in understanding population breadth. Lower MCID values may be most appropriate for screening purposes or low-risk effects, and the median or higher MCID values should be used for high-risk effects or outcomes.
Level I, diagnostic study.
The Oswestry Disability Index v2.0 (ODI), SF36 Physical Function Domain (SF-36 PFD), and PROMIS Physical Function CAT v1.2 (PF CAT) questionnaires were prospectively collected from 1607 patients ...complaining of back or leg pain, visiting a university-based spine clinic. All questionnaires were collected electronically, using a tablet computer.
The aim of this study was to compare the psychometric properties of the PROMIS PF CAT with the ODI and SF36 Physical Function Domain in the same patient population.
Evidence-based decision-making is improved by using high-quality patient-reported outcomes measures. Prior studies have revealed the shortcomings of the ODI and SF36, commonly used in spine patients. The PROMIS Network has developed measures with excellent psychometric properties. The Physical Function domain, delivered by Computerized Adaptive Testing (PF CAT), performs well in the spine patient population, though to-date direct comparisons with common measures have not been performed.
Standard Rasch analysis was performed to directly compare the psychometrics of the PF CAT, ODI, and SF36 PFD. Spearman correlations were computed to examine the correlations of the three instruments. Time required for administration was also recorded.
One thousand six hundred seven patients were administered all assessments. The time required to answer all items in the PF CAT, ODI, and SF-36 PFD was 44, 169, and 99 seconds. The ceiling and floor effects were excellent for the PF CAT (0.81%, 3.86%), while the ceiling effects were marginal and floor effects quite poor for the ODI (6.91% and 44.24%) and SF-36 PFD (5.97% and 23.65%). All instruments significantly correlated with each other.
The PROMIS PF CAT outperforms the ODI and SF-36 PFD in the spine patient population and is highly correlated. It has better coverage, while taking less time to administer with fewer questions to answer.
2.
To establish minimum clinically important difference (MCID) for measurements in an orthopaedic patient population with joint disorders.
Adult patients aged 18 years and older seeking care for joint ...conditions at an orthopaedic clinic took the Patient-Reported Outcomes Measurement Information System Physical Function (PROMIS
PF) computerized adaptive test (CAT), hip disability and osteoarthritis outcome score for joint reconstruction (HOOS JR), and the knee injury and osteoarthritis outcome score for joint reconstruction (KOOS JR) from February 2014 to April 2017. MCIDs were calculated using anchor-based and distribution-based methods. Patient reports of meaningful change in function since their first clinic encounter were used as an anchor.
There were 2226 patients who participated with a mean age of 61.16 (SD = 12.84) years, 41.6% male, and 89.7% Caucasian. Mean change ranged from 7.29 to 8.41 for the PROMIS
PF CAT, from 14.81 to 19.68 for the HOOS JR, and from 14.51 to 18.85 for the KOOS JR. ROC cut-offs ranged from 1.97-8.18 for the PF CAT, 6.33-43.36 for the HOOS JR, and 2.21-8.16 for the KOOS JR. Distribution-based methods estimated MCID values ranging from 2.45 to 21.55 for the PROMIS
PF CAT; from 3.90 to 43.61 for the HOOS JR, and from 3.98 to 40.67 for the KOOS JR. The median MCID value in the range was similar to the mean change score for each measure and was 7.9 for the PF CAT, 18.0 for the HOOS JR, and 15.1 for the KOOS JR.
This is the first comprehensive study providing a wide range of MCIDs for the PROMIS
PF, HOOS JR, and KOOS JR in orthopaedic patients with joint ailments.
Efficiency of the coastal filter Asmala, Eero; Carstensen, Jacob; Conley, Daniel J. ...
Limnology and oceanography,
November 2017, Letnik:
62, Številka:
S1
Journal Article
Recenzirano
Odprti dostop
An important function of coastal ecosystems is the reduction of the nutrient flux from land to the open sea, the coastal filter. In this study, we focused on the two most important coastal ...biogeochemical processes that remove nitrogen and phosphorus permanently: denitrification and phosphorus burial. We compiled removal rates from coastal systems around the Baltic Sea and analyzed their spatial variation and regulating environmental factors. These analyses were used to scale up denitrification and phosphorus burial rates for the entire Baltic Sea coastal zone. Denitrification rates ranged from non-detectable to 12 mmol N m−2 d−1, and correlated positively with both bottom water nitrate concentration and sediment organic carbon content. The rates exhibited a strong decreasing gradient from land to the open coast, which was likely driven by the availability of nitrate and labile organic carbon, but a high proportion of non-cohesive sediments in the coastal zone decreased the denitrification efficiency relative to the open sea. Phosphorus burial rates varied from 0.21 g P m−2 yr−1 in open coastal systems to 2.28 g P m−2 yr−1 in estuaries. Our analysis suggests that archipelagos are important phosphorus traps and account for 45% of the coastal P removal, while covering only 17% of the coastal areas. High burial rates could partly be sustained by phosphorus import from the open Baltic Sea. We estimate that the coastal filter in the Baltic Sea removes 16% of nitrogen and 53% of phosphorus inputs from land.
Background:
Establishing score points that reflect meaningful change from the patient perspective is important for interpreting patient-reported outcomes. This study estimated the minimum clinically ...important difference (MCID) values of 2 Patient-Reported Outcomes Measurement Information System (PROMIS) instruments and the Foot and Ankle Ability Measure (FAAM) Sports subscale within a foot and ankle orthopedic population.
Methods:
Patients seen for foot and ankle conditions at an orthopedic clinic were administered the PROMIS Physical Function (PF) v1.2, the PROMIS Pain Interference (PI) v1.1, and the FAAM Sports at baseline and all follow-up visits. MCID estimation was conducted using anchor-based and distribution-based methods.
Results:
A total of 3069 patients, mean age of 51 years (range = 18-94), were included. The MCIDs for the PROMIS PF ranged from approximately 3 to 30 points (median = 11.3) depending on the methods being used. The MCIDs ranged from 3 to 25 points (median = 8.9) for the PROMIS PI, and from 9 to 77 points (median = 32.5) for the FAAM Sports.
Conclusions:
This study established a range of MCIDs in the PROMIS PF, PROMIS PI, and FAAM Sports indicating meaningful change in patient condition. MCID values were consistent across follow-up periods, but were different across methods. Values below the 25th percentile of MCIDs may be useful for low-risk clinical decisions. Midrange values (eg, near the median) should be used for high stakes decisions in clinical practice (ie, surgery referrals). The MCID values within the interquartile range should be utilized for most decision making.
Level of Evidence:
Level I, diagnostic study, testing of previously developed diagnostic measure on consecutive patients with reference standard applied.
Objective
This study sought to utilise machine learning methods in artificial intelligence to select the most relevant variables in classifying the presence and absence of root caries and to evaluate ...the model performance.
Background
Dental caries is one of the most prevalent oral health problems. Artificial intelligence can be used to develop models for identification of root caries risk and to gain valuable insights, but it has not been applied in dentistry. Accurately identifying root caries may guide treatment decisions, leading to better oral health outcomes.
Methods
Data were obtained from the 2015‐2016 National Health and Nutrition Examination Survey and were randomly divided into training and test sets. Several supervised machine learning methods were applied to construct a tool that was capable of classifying variables into the presence and absence of root caries. Accuracy, sensitivity, specificity and area under the receiver operating curve were computed.
Results
Of the machine learning algorithms developed, support vector machine demonstrated the best performance with an accuracy of 97.1%, precision of 95.1%, sensitivity of 99.6% and specificity of 94.3% for identifying root caries. The area under the curve was 0.997. Age was the feature most strongly associated with root caries.
Conclusion
The machine learning algorithms developed in this study perform well and allow for clinical implementation and utilisation by dental and nondental professionals. Clinicians are encouraged to adopt the algorithms from this study for early intervention and treatment of root caries for the ageing population of the United States, and for attaining precision dental medicine.
In light of recently-proposed quality measures for carpal tunnel release (CTR), elucidating the minimal clinically important difference (MCID) for selected outcome measures will be important when ...interpreting treatment responses. Our purpose was to estimate the MCID of the Patient-Reported Outcomes Measurement Information System (PROMIS) instruments and the short Disabilities of the Arm, Shoulder, and Hand (QuickDASH) following CTR.
Adult patients undergoing isolated unilateral CTR between July 2014 and October 2016 were identified. Outcomes included the PROMIS Upper Extremity (UE) Computer Adaptive Test (CAT), Physical Function (PF) CAT, QuickDASH, and Pain Interference (PI) CAT. For inclusion, pretreatment baseline (within 60 days of surgery) and postoperative (6–90 days) UE or PF CAT scores were required, as well as a response on a 5-point Likert scale to the question “How much relief and/or improvement do you feel you have experienced as a result of your treatment?” The MCID was calculated using SD and minimum detectable change (MDC) distribution methods.
In response to the Likert scale question, 88.6% of patients reported improvement at a mean of 14.8 days after surgery. The infrequency of patients reporting no change (5 of 44; 11.4%) precluded calculation of a statistically sound anchor-based MCID value. The MCID values, as calculated using the one-half SD method, were 3.6, 4.6, 10.4, and 3.4 for the UE CAT, PF CAT, QuickDASH, and PI CAT, respectively.
We have calculated MCID values for the UE CAT, PF CAT, QuickDASH, and PI CAT for patients undergoing CTR. Although the small number of patients reporting no change and minimal change after surgery precluded an anchor-based MCID calculation, we report estimates using the one-half SD method for the MCID following CTR.
These MCID estimates will be helpful when interpreting CTR clinical outcomes and for powering prospective trials.
The global nitrogen cycle in the twenty-first century Fowler, David; Coyle, Mhairi; Skiba, Ute ...
Philosophical transactions of the Royal Society of London. Series B. Biological sciences,
07/2013, Letnik:
368, Številka:
1621
Journal Article
Recenzirano
Odprti dostop
Global nitrogen fixation contributes 413 Tg of reactive nitrogen (Nr) to terrestrial and marine ecosystems annually of which anthropogenic activities are responsible for half, 210 Tg N. The majority ...of the transformations of anthropogenic Nr are on land (240 Tg N yr−1) within soils and vegetation where reduced Nr contributes most of the input through the use of fertilizer nitrogen in agriculture. Leakages from the use of fertilizer Nr contribute to nitrate (NO3−) in drainage waters from agricultural land and emissions of trace Nr compounds to the atmosphere. Emissions, mainly of ammonia (NH3) from land together with combustion related emissions of nitrogen oxides (NOx), contribute 100 Tg N yr−1 to the atmosphere, which are transported between countries and processed within the atmosphere, generating secondary pollutants, including ozone and other photochemical oxidants and aerosols, especially ammonium nitrate (NH4NO3) and ammonium sulfate (NH4)2SO4. Leaching and riverine transport of NO3 contribute 40–70 Tg N yr−1 to coastal waters and the open ocean, which together with the 30 Tg input to oceans from atmospheric deposition combine with marine biological nitrogen fixation (140 Tg N yr−1) to double the ocean processing of Nr. Some of the marine Nr is buried in sediments, the remainder being denitrified back to the atmosphere as N2 or N2O. The marine processing is of a similar magnitude to that in terrestrial soils and vegetation, but has a larger fraction of natural origin. The lifetime of Nr in the atmosphere, with the exception of N2O, is only a few weeks, while in terrestrial ecosystems, with the exception of peatlands (where it can be 102–103 years), the lifetime is a few decades. In the ocean, the lifetime of Nr is less well known but seems to be longer than in terrestrial ecosystems and may represent an important long-term source of N2O that will respond very slowly to control measures on the sources of Nr from which it is produced.
Purpose The Patient-Reported Outcomes Measurement Information System Upper Extremity Computer Adaptive Test (UE CAT) has recently been made available by the National Institutes of Health to measure ...physical function outcomes in the upper extremity. We hypothesized that the UE CAT would psychometrically outperform the Disabilities of the Arm, Shoulder, and Hand (DASH) and the Patient-Reported Outcomes Measurement Information System Physical Function Computer Adaptive Test (PF CAT) in a hand patient population. Methods The UE CAT, PF CAT, and DASH were each electronically administered to all adult patients who presented to a tertiary hand and upper extremity (nonshoulder) orthopedic clinic. Patient responses were retrospectively studied to determine the validity, reliability, and floor/ceiling effects of all 3 instruments using the Rasch Partial Credit Model. Responder burden and Pearson correlations were calculated for each instrument. Results A total of 379 patients completed the UE CAT, PF CAT, and the DASH. On average, 6 UE CAT, 9 PF CAT, and 30 DASH questions were administered to each patient. All 3 instruments were each highly correlated with each other. Floor effects were low and similar between all instruments; however, ceiling effects were higher in the UE CAT (10.82%) than in the PF CAT (1.32%) or DASH (5.28%). High person reliability (PR) and item reliability (IR) were found for all 3 metrics: UE CAT (α = 0.99; PR = 0.91; IR = 0.94); PF CAT (α = 0.95; PR = 0.89; IR = 0.96); and DASH (α = 0.97; PR = 0.95; IR = 0.99). The UE CAT questions had the best item-fit: only 1 of 15 UE CAT items had poor fit in contrast to 4 of 30 DASH items and 7 of 33 PF CAT items. Conclusions The psychometric properties of the UE CAT compare favorably with the PF CAT and the DASH in nonshoulder upper extremity patients. The relatively large ceiling effect found in the UE CAT could be improved with item bank expansion to include items at the upper end of function. Clinical Relevance The UE CAT is a useful patient-reported outcome measure that merits further investigation.
The ocean's nitrogen cycle is driven by complex microbial transformations, including nitrogen fixation, assimilation, nitrification, anammox and denitrification. Dinitrogen is the most abundant form ...of nitrogen in sea water but only accessible by nitrogen-fixing microbes. Denitrification and nitrification are both regulated by oxygen concentrations and potentially produce nitrous oxide (N2O), a climate-relevant atmospheric trace gas. The world's oceans, including the coastal areas and upwelling areas, contribute about 30 per cent to the atmospheric N2O budget and are, therefore, a major source of this gas to the atmosphere. Human activities now add more nitrogen to the environment than is naturally fixed. More than half of the nitrogen reaches the coastal ocean via river input and atmospheric deposition, of which the latter affects even remote oceanic regions. A nitrogen budget for the coastal and open ocean, where inputs and outputs match rather well, is presented. Furthermore, predicted climate change will impact the expansion of the oceans' oxygen minimum zones, the productivity of surface waters and presumably other microbial processes, with unpredictable consequences for the cycling of nitrogen. Nitrogen cycling is closely intertwined with that of carbon, phosphorous and other biologically important elements via biological stoichiometric requirements. This linkage implies that human alterations of nitrogen cycling are likely to have major consequences for other biogeochemical processes and ecosystem functions and services.
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