Psychometric assessment of the patient activation measure short form (PAM-13) in rural settings

Purpose

The patient activation measure short form (PAM-13) assesses patients’ self-reported health management skills, knowledge, confidence, and motivation. We used item response theory to evaluate the psychometric properties of the PAM-13 utilized in rural settings.

Methods

A Rasch partial credit model analysis was conducted on the PAM-13 instrument using a sample of 812 rural patients recruited by providers and our research staff. Specially, we examined dimensionality, item fit, and quality of measures, category response curves, and item differential functioning. Convergent and divergent validities were also examined.

Findings

The PAM-13 instrument has excellent convergent and divergent validities. It is fairly unidimensional, and all items fit the Rasch model well. It has relatively high person and item reliability indices. Majority of the items were free of item differential functioning. There were, however, some issues with ceiling effects. Additionally, there was a lack of responses for category one across all items.

Conclusions

Patient activation measure short form (PAM-13) performs well in some areas, but not all. In general, more items need to be added to cover the upper end of the trait. The four response categories of PAM-13 should be collapsed into three.     

Rosuvastatin use increases plasma fibrinolytic potential: a randomised clinical trial

We conducted a study to assess the effect of rosuvastatin use on fibrinolysis in patients with previous venous thromboembolism (VTE). This was a post hoc analysis within the STAtins Reduce Thrombophilia (START) study (NCT01613794). Plasma fibrinolytic potential, fibrinogen, plasmin inhibitor, plasminogen activator inhibitor-1 (PAI-1) and thrombin-activatable fibrinolysis inhibitor (TAFI) were measured before and after four weeks of rosuvastatin or no treatment in participants with prior confirmed VTE, after ending anticoagulant therapy. In the non-rosuvastatin group (n = 121), plasma fibrinolytic potential and individual fibrinolysis parameters did not change at the end of the study versus the baseline, whereas in the rosuvastatin group (n = 126), plasma fibrinolytic potential increased: the mean clot lysis time decreased by 8·75 min (95% CI −13·8 to −3·72), and plasmin inhibitor levels and TAFI activity were lower at the end of the study (−0·05 U/ml; 95% CI −0·07 to −0·02 and −4·77%; 95% CI −6·81 to −2·73, respectively). PAI-1 levels did not change and fibrinogen levels were 0·17 g/l (95% CI 0·04–0·29) higher. In participants with prior VTE, rosuvastatin use led to an increased fibrinolytic potential compared with non-statin use. Our findings support the need for further studies on the possible role for statins in the secondary prevention of VTE.     

A concise review of DNA damage checkpoints and repair in mammalian cells

DNA of eukaryotic cells, including vascular cells, is under the constant attack of chemicals, free radicals, or ionizing radiation that can be caused by environmental exposure, by-products of intracellular metabolism, or medical therapy. Damage may be either limited to altered DNA bases and abasic sites or extensive like double-strand breaks (DSBs). Nuclear proteins sense this damage and initiate the attachment of protein complexes at the site of the lesion. Subsequently, signal transducers, mediators, and finally, effector proteins phosphorylate targets (e.g., p53) that eventually results in cell cycle arrest at the G1/S, intra-S, or G2/M checkpoint until the lesion undergoes repair. Defective cell cycle arrest at the respective checkpoints is associated with genome instability and oncogenesis. When cell cycle arrest is accomplished, the DNA repair machinery can become effective. Important pathways in mammalian cells are the following: base excision repair, nucleotide excision repair, mismatch repair, and DSB repair. When repair is successful, the cell cycle arrest may be lifted. If repair is unsuccessful (e.g., by high doses of DNA-damaging agents or genetic defects in the DNA repair machinery), then this may lead to permanent cell cycle arrest (cellular senescence), apoptosis, or oncogenesis.     

Risk-stratification enables accurate single-center outcomes assessment in congenital diaphragmatic hernia (CDH)

BackgroundManagement of CDH is highly variable from center to center, as are patient outcomes. The purpose of this study was to examine risk-stratified survival and extracorporeal membrane oxygenation (ECMO) rates at a single center, and to determine whether adverse outcomes are related to patient characteristics or management.MethodsA retrospective single-center review of CDH patients was performed, and outcomes compared to those reported by the CDH Study Group (CDHSG) registry. Patient demographics, disparities, and clinical characteristics were examined to identify unique features of the cohort. A model derived using the registry that estimates probability of ECMO use or death in CDH newborns was used to risk-stratify patients and assess mortality rates. Observed over expected (O/E) ECMO use rates were calculated to measure whether “excess” or “appropriate” ECMO use was occurring.ResultsThere were 81 CDH patients treated between 2004–2017, and 5034 in the CDHSG registry. Mortality in ECMO-treated patients was higher than the registry. Socioeconomic variables were not significantly associated with outcomes. The strongest predictors of mortality were ECMO use and early blood gas variables. The risk model accurately predicted ECMO use with a c-statistic of 0.79. Compared with the registry, the disparity in mortality rates was greatest for moderate-risk patients. O/E ECMO use was highest in low and moderate-risk patients.ConclusionsECMO use is a more consistent predictor of mortality than CDH severity at a single center, and there is relative overuse of ECMO in lower-risk patients. Risk stratification allows for more accurate institutional assessment of mortality and ECMO use, and other centers could consider such an adjusted analysis to identify opportunities for outcomes improvement.Level of EvidenceIII.     

What's in a Transition? An Integrative Perspective on Transitions in Medical Education

This Conversation Starters article presents a selected research abstract from the 2016 Association of American Medical Colleges Western Region Group on Educational Affairs annual spring meeting. The abstract is paired with the integrative commentary of three experts who shared their thoughts stimulated by the needs assessment study. These thoughts explore how the general theoretical mechanisms of transition may be integrated with cognitive load theory in order to design interventions and environments that foster transition.     

Bummed Out Now,Feeling Sick Later: Weekday versus Weekend Negative Affect and Physical Symptom Reports in High School Freshmen

PurposeThis study examined adolescent negative affect (NA) in daily life on school days and weekend days during the spring and associations with physical symptoms during the following summer.MethodsUsing experience sampling methodology (ESM), participants provided electronic diary (eDiary) reports of NA on weekdays (Thursday and Friday) and weekend days during their 9^th grade year. In telephone interviews during the winter and summer months they reported physical symptoms. Multiple regression analyses were conducted to examine associations between weekday NA, weekend NA, and their interaction and four constellations of physical symptoms reported in summer (pain, respiratory, gastrointestinal, and immune symptoms).ResultsFindings indicated that weekend NA was associated with later reports of pain, respiratory, and immune symptoms. For gastrointestinal symptoms only adolescents who reported low NA on both weekend and school days reported fewer gastric symptoms than other adolescents.ConclusionsMapping the predictors and correlates of weekend NA may be important not only for understanding teenage mood patterns but also for enhancing the interpretation of physical symptom reporting by adolescents     

Global climate evolution during the last deglaciation

Deciphering the evolution of global climate from the end of the Last Glacial Maximum approximately 19 ka to the early Holocene 11 ka presents an outstanding opportunity for understanding the transient response of Earth’s climate system to external and internal forcings. During this interval of global warming, the decay of ice sheets caused global mean sea level to rise by approximately 80 m; terrestrial and marine ecosystems experienced large disturbances and range shifts; perturbations to the carbon cycle resulted in a net release of the greenhouse gases CO₂ and CH₄ to the atmosphere; and changes in atmosphere and ocean circulation affected the global distribution and fluxes of water and heat. Here we summarize a major effort by the paleoclimate research community to characterize these changes through the development of well-dated, high-resolution records of the deep and intermediate ocean as well as surface climate. Our synthesis indicates that the superposition of two modes explains much of the variability in regional and global climate during the last deglaciation, with a strong association between the first mode and variations in greenhouse gases, and between the second mode and variations in the Atlantic meridional overturning circulation.During the interval of global warming from the end of the Last Glacial Maximum (LGM) approximately 19 ka to the early Holocene 11 ka, virtually every component of the climate system underwent large-scale change, sometimes at extraordinary rates, as the world emerged from the grips of the last ice age (Fig. 1). This dramatic time of global change was triggered by changes in insolation, with associated changes in ice sheets, greenhouse gas concentrations, and other amplifying feedbacks that produced distinctive regional and global responses. In addition, there were several episodes of large and rapid sea-level rise and abrupt climate change (Fig. 2) that produced regional climate signals superposed on those associated with global warming. Considerable ice-sheet melting and sea-level rise occurred after 11 ka, but otherwise the world had entered the current interglaciation with near-pre-Industrial greenhouse gas concentrations and relatively stable climates. Here we synthesize well-dated, high-resolution ocean and terrestrial proxy records to describe regional and global patterns of climate change during this interval of deglaciation.Open in a separate windowFig. 1.(A) Climate simulation of the Last Glacial Maximum 21,000 y ago using the National Center for Atmospheric Research Community Climate System Model, version 3.0 (141). Sea-surface temperatures are anomalies relative to the control climate. Also shown are continental ice sheets (1,000-m contours) (149) and leaf-area index simulated by the model (scale bar shown). (B) Same as A except for 11 ka.Open in a separate windowFig. 2.Climate records and forcings during the last deglaciation. The oxygen-isotope (δ¹⁸O) records from Greenland Ice Sheet Project Two (GISP2) (150) (dark-blue line) and Greenland Ice Core Project (GRIP) (151) (light-blue line) Greenland ice cores shown in (A) (placed on the GICC05 timescale; ref. 57) document millennial-scale events that correspond to those first identified in northern European floral and pollen records. LGM, Last Glacial Maximum; OD, Oldest Dryas; BA, Bølling–Allerød; ACR, Antarctic Cold Reversal; YD, Younger Dryas. (B) Oxygen-isotope (δ¹⁸O) record from European Project for Ice Coring in Antarctica (EPICA) Dronning Maud Land (152) (dark-green line) and deuterium (δD) record from Dome C (45) (light-green line) Antarctic ice cores, placed on a common timescale (2). (C) Midmonth insolation at 65°N for July (orange line) and at 65°S for January (light-blue line) (153). (D) The combined radiative forcing (red line) from CO₂ (blue dashed line), CH₄ (green dashed line), and N₂O (purple dashed line) relative to preindustrial levels. CO₂ is from EPICA Dome C ice core (1) on Greenland Ice Core Chronology 05 (GICC05) timescale from ref. 2, CH₄ is from GRIP ice core (154) on the GICC05 timescale, and N₂O is from EPICA Dome C (155) and GRIP (156) ice cores on the GICC05 timescale. Greenhouse gas concentrations were converted to radiative forcings using the simplified expressions in ref. 157. The CH₄ radiative forcing was multiplied by 1.4 to account for its greater efficacy relative to CO₂ (158). (E) Relative sea-level data from Bonaparte Gulf (green crosses) (159), Barbados (gray and dark-blue triangles) (160), New Guinea (light-blue triangles) (161, 162), Sunda Shelf (purple crosses) (163), and Tahiti (green triangles) (164). Also shown is eustatic sea level (gray line) (165). (F) Rate of change of area of Laurentide Ice Sheet (LIS) (166) and Scandinavian Ice Sheet (SIS) (SI Appendix). (G) Freshwater flux to the global oceans derived from eustatic sea level in E. (H) Record of ice-rafted detrital carbonate from North Atlantic core VM23-81 identifying times of Heinrich events 1 and 0 (167). (I) Freshwater flux associated with routing of continental runoff through the St. Lawrence and Hudson rivers (filled blue time series) with age uncertainties (168). Also shown is time series of runoff through the St. Lawrence River during the Younger Dryas (solid blue line) (142).Between the LGM and present, seasonal insolation anomalies arising from the combined effects of eccentricity, precession, and obliquity were generally opposite in sign between hemispheres (Fig. 2C), whereas variations in annual-average insolation were symmetrical about the equator. At the LGM, seasonal insolation was similar to present, whereas subsequent changes in obliquity and perihelion caused Northern-Hemisphere seasonality to reach a maximum in the early Holocene.CO₂ concentrations started to rise from the LGM minimum approximately 17.5 ± 0.5 ka (1). The onset of the CO₂ rise may have lagged the start of Antarctic warming by 800 ± 600 years (1), but this may be an overestimate (2). CO₂ levels stabilized from approximately 14.7–12.9 ka, and then rose again from about 12.9–11.7 ka, reaching near-interglacial maximum levels shortly thereafter. CH₄ concentrations also began to rise starting at approximately 17.5 ka, with a subsequent abrupt increase at 14.7 ka, an abrupt decrease at about 12.9 ka, followed by a rise at approximately 11.7 ka (3). Changes in N₂O concentrations appear to follow changes in CH₄ (4). The combined variations in radiative forcing due to greenhouse gases (GHGs) is dominated by CO₂, but abrupt changes in CH₄ and N₂O modulate the overall structure, accentuating the rapid increase at 14.7 ka and causing a slight reduction from 12.9–11.7 ka (Fig. 2D).Freshwater forcing of the Atlantic meridional overturning circulation (AMOC) is commonly invoked to explain past and possibly future abrupt climate change (5, 6). During the last deglaciation, the AMOC was likely affected by variations in moisture transport across Central America (7), salt and heat transport from the Indian Ocean (8), freshwater exchange across the Bering Strait (9), and the flux of meltwater and icebergs from adjacent ice sheets (6). The first two factors largely represent feedbacks on AMOC variability. Freshwater exchange across the Bering Strait began with initial submergence of the Strait during deglacial sea-level rise. Highly variable fluxes from ice-sheet melting and calving and routing of continental runoff (Fig. 2 E–I) also directly forced the AMOC, but uncertainties in the sources of several key events remain (SI Appendix).