Dye standards, Part II.5: Pararosaniline (CI 42500)

The names and affiliations of the SRMTS members are cited in Part I: terminology and general principles,Histochem. J. (1992)24, 217–19.     

Radioimmunoassay studies of intestinal calcium-binding protein in the pig. I. Identification of intestinal calcium-binding protein in blood and response to a low calcium diet.

We have developed a radioimmunoassay for porcine intestinal calcium-binding protein (CaBP) and have used it to detect CaBP in pig plasma. Plasma CaBP is identical to intestinal CaBP on the basis of immunological activity, molecular size, and molecular charge properties. The plasma CaBP concentration was greater in the portal blood than in mixed venous blood, suggesting that blood CaBP originates in the gut. Two of four 15-week-old littermate pigs were placed on a low calcium diet (0.15% calcium, 0.65% phosphorus) and two on a control diet (0.65% calcium, 0.65% phosphorus). After 2 weeks, the entire small intestine was removed and divided into nine 1.8-m segments. CaBP was assayed in both plasma and intestinal mucosa. When the two pigs on a low calcium diet were compared with two control pigs, there was a general increase in immunoreactive CaBP in both plasma and intestinal mucosa. However, there was no increment in immunoreactive CaBP in the first 1.8-m segment of small intestine. Seventy-one percent of the increment in CaBP occurred distal to the first two segments. The largest fractional low calcium diet effect occurred in the ileum. The mean CaBP concentration for the total small intestine increased by a factor of 1.9. The plasma CaBP concentration increased by a factor of 2.6. In these pigs, plasma CaBP was a more reliable indicator of change in CaBP status than was the measurement in the proximal gut segment which contained the duodenum. The assay of CaBP in blood is convenient and may obviate the sampling errors inherent in intestinal biopsy.     

Loss to Clinic and Five-Year Mortality among HIV-Infected Antiretroviral Therapy Initiators

Missing outcome data due to loss to follow-up occurs frequently in clinical cohort studies of HIV-infected patients. Censoring patients when they become lost can produce inaccurate results if the risk of the outcome among the censored patients differs from the risk of the outcome among patients remaining under observation. We examine whether patients who are considered lost to follow up are at increased risk of mortality compared to those who remain under observation. Patients from the US Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) who newly initiated combination antiretroviral therapy between January 1, 1998 and December 31, 2009 and survived for at least one year were included in the study. Mortality information was available for all participants regardless of continued observation in the CNICS. We compare mortality between patients retained in the cohort and those lost-to-clinic, as commonly defined by a 12-month gap in care. Patients who were considered lost-to-clinic had modestly elevated mortality compared to patients who remained under observation after 5 years (risk ratio (RR): 1.2; 95% CI: 0.9, 1.5). Results were similar after redefining loss-to-clinic as 6 months (RR: 1.0; 95% CI: 0.8, 1.3) or 18 months (RR: 1.2; 95% CI: 0.8, 1.6) without a documented clinic visit. The small increase in mortality associated with becoming lost to clinic suggests that these patients were not lost to care, rather they likely transitioned to care at a facility outside the study. The modestly higher mortality among patients who were lost-to-clinic implies that when we necessarily censor these patients in studies of time-varying exposures, we are likely to incur at most a modest selection bias.     

Growth Monitoring: A Survey of Current Practices of Primary Care Paediatricians in Europe

Objective

We aimed to study current practices in growth monitoring by European primary care paediatricians and to explore their perceived needs in this field.

Methods

We developed a cross-sectional, anonymous on-line survey and contacted primary care paediatricians listed in national directories in the 18 European countries with a confederation of primary care paediatricians. Paediatricians participated in the survey between April and September 2011.

Results

Of the 1,198 paediatricians from 11 European countries (response rate 13%) who participated, 29% used the 2006 World Health Organization Multicentre Growth Reference Study growth charts, 69% used national growth charts; 61% used software to draw growth charts and 79% did not use a formal algorithm to detect abnormal growth on growth charts. Among the 21% of paediatricians who used algorithms, many used non-algorithmic simple thresholds for height and weight and none used the algorithms published in the international literature. In all, 69% of paediatricians declared that a validated algorithm to monitor growth would be useful in daily practice. We found important between-country variations.

Conclusion

The varied growth-monitoring practices declared by primary care paediatricians reveals the need for standardization and evidence-based algorithms to define abnormal growth and the development of software that would use such algorithms.     

Effects of preconception lifestyle intervention in infertile women with obesity: The FIT-PLESE randomized controlled trial

BackgroundWomen with obesity and infertility are counseled to lose weight prior to conception and infertility treatment to improve pregnancy rates and birth outcomes, although confirmatory evidence from randomized trials is lacking. We assessed whether a preconception intensive lifestyle intervention with acute weight loss is superior to a weight neutral intervention at achieving a healthy live birth.Methods and findingsIn this open-label, randomized controlled study (FIT-PLESE), 379 women with obesity (BMI ≥ 30 kg/m²) and unexplained infertility were randomly assigned in a 1:1 ratio to 2 preconception lifestyle modification groups lasting 16 weeks, between July 2015 and July 2018 (final follow-up September 2019) followed by infertility therapy. The primary outcome was the healthy live birth (term infant of normal weight without major anomalies) incidence. This was conducted at 9 academic health centers across the United States. The intensive group underwent increased physical activity and weight loss (target 7%) through meal replacements and medication (Orlistat) compared to a standard group with increased physical activity alone without weight loss. This was followed by standardized empiric infertility treatment consisting of 3 cycles of ovarian stimulation/intrauterine insemination. Outcomes of any resulting pregnancy were tracked. Among 191 women randomized to standard lifestyle group, 40 dropped out of the study before conception; among 188 women randomized to intensive lifestyle group, 31 dropped out of the study before conception. All the randomized women were included in the intent-to-treat analysis for primary outcome of a healthy live birth. There were no significant differences in the incidence of healthy live births [standard 29/191(15.2%), intensive 23/188(12.2%), rate ratio 0.81 (0.48 to 1.34), P = 0.40]. Intensive had significant weight loss compared to standard (−6.6 ± 5.4% versus −0.3 ± 3.2%, P < 0.001). There were improvements in metabolic health, including a marked decrease in incidence of the metabolic syndrome (baseline to 16 weeks: standard: 53.6% to 49.4%, intensive 52.8% to 32.2%, P = 0.003). Gastrointestinal side effects were significantly more common in intensive. There was a higher, but nonsignificant, first trimester pregnancy loss in the intensive group (33.3% versus 23.7% in standard, 95% rate ratio 1.40, 95% confidence interval [CI]: 0.79 to 2.50). The main limitations of the study are the limited power of the study to detect rare complications and the design difficulty in finding an adequate time matched control intervention, as the standard exercise intervention may have potentially been helpful or harmful.ConclusionsA preconception intensive lifestyle intervention for weight loss did not improve fertility or birth outcomes compared to an exercise intervention without targeted weight loss. Improvement in metabolic health may not translate into improved female fecundity.Trial registrationClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT02432209","term_id":"NCT02432209"}}NCT02432209.

Richard Legro and colleagues investigate the impact of a preconception weight loss intervention on healthy live birth rates in women with obesity and unexplained infertility.     

Proteome-wide Mendelian randomization identifies causal links between blood proteins and severe COVID-19

In November 2021, the COVID-19 pandemic death toll surpassed five million individuals. We applied Mendelian randomization including >3,000 blood proteins as exposures to identify potential biomarkers that may indicate risk for hospitalization or need for respiratory support or death due to COVID-19, respectively. After multiple testing correction, using genetic instruments and under the assumptions of Mendelian Randomization, our results were consistent with higher blood levels of five proteins GCNT4, CD207, RAB14, C1GALT1C1, and ABO being causally associated with an increased risk of hospitalization or respiratory support/death due to COVID-19 (ORs = 1.12–1.35). Higher levels of FAAH2 were solely associated with an increased risk of hospitalization (OR = 1.19). On the contrary, higher levels of SELL, SELE, and PECAM-1 decrease risk of hospitalization or need for respiratory support/death (ORs = 0.80–0.91). Higher levels of LCTL, SFTPD, KEL, and ATP2A3 were solely associated with a decreased risk of hospitalization (ORs = 0.86–0.93), whilst higher levels of ICAM-1 were solely associated with a decreased risk of respiratory support/death of COVID-19 (OR = 0.84). Our findings implicate blood group markers and binding proteins in both hospitalization and need for respiratory support/death. They, additionally, suggest that higher levels of endocannabinoid enzymes may increase the risk of hospitalization. Our research replicates findings of blood markers previously associated with COVID-19 and prioritises additional blood markers for risk prediction of severe forms of COVID-19. Furthermore, we pinpoint druggable targets potentially implicated in disease pathology.     

Number and type of guideline implementation tools varies by guideline,clinical condition,country of origin,and type of developer organization: content analysis of guidelines

Background

Guideline implementation tools (GI tools) can improve clinician behavior and patient outcomes. Analyses of guidelines published before 2010 found that many did not offer GI tools. Since 2010 standards, frameworks and instructions for GI tools have emerged. This study analyzed the number and types of GI tools offered by guidelines published in 2010 or later.

Methods

Content analysis and a published GI tool framework were used to categorize GI tools by condition, country, and type of organization. English-language guidelines on arthritis, asthma, colorectal cancer, depression, diabetes, heart failure, and stroke management were identified in the National Guideline Clearinghouse. Screening and data extraction were in triplicate. Findings were reported with summary statistics.

Results

Eighty-five (67.5%) of 126 eligible guidelines published between 2010 and 2017 offered one or more of a total of 464 GI tools. The mean number of GI tools per guideline was 5.5 (median 4.0, range 1 to 28) and increased over time. The majority of GI tools were for clinicians (239, 51.5%), few were for patients (113, 24.4%), and fewer still were to support implementation (66, 14.3%) or evaluation (46, 9.9%). Most clinician GI tools were guideline summaries (116, 48.5%), and most patient GI tools were condition-specific information (92, 81.4%). Government agencies (patient 23.5%, clinician 28.9%, implementation 24.1%, evaluation 23.5%) and developers in the UK (patient 18.5%, clinician 25.2%, implementation 27.2%, evaluation 29.1%) were more likely to generate guidelines that offered all four types of GI tools. Professional societies were more likely to generate guidelines that included clinician GI tools.

Conclusions

Many guidelines do not include any GI tools, or a variety of GI tools for different stakeholders that may be more likely to prompt guideline uptake (point-of-care forms or checklists for clinicians, decision-making or self-management tools for patients, implementation and evaluation tools for managers and policy-makers). While this may vary by country and type of organization, and suggests that developers could improve the range of GI tools they develop, further research is needed to identify determinants and potential solutions. Research is also needed to examine the cost-effectiveness of various types of GI tools so that developers know where to direct their efforts and scarce resources.