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Read Ebook {PDF EPUB} Pseudo by Dysonrules Read Ebook {PDF EPUB} Pseudo by dysonrules Pseudoreplication: choose your data wisely¶ Many studies strive to collect more data through replication: by repeating their measurements with additional patients or samples, they can be more certain of their numbers and discover subtle relationships that aren’t obvious at first glance. We’ve seen the value of additional data for improving statistical power and detecting small differences. But what exactly counts as a replication? Let’s return to a medical example. I have two groups of 100 patients taking different medications, and I seek to establish which medication lowers blood pressure more. I have each group take the medication for a month to allow it to take effect, and then I follow each group for ten days, each day testing their blood pressure. I now have ten data points per patient and 1,000 data points per group. Brilliant! 1,000 data points is quite a lot, and I can fairly easily establish whether one group has lower blood pressure than the other. When I do calculations for statistical significance I find significant results very easily. But wait: we expect that taking a patient’s blood pressure ten times will yield ten very similar results. If one patient is genetically predisposed to low blood pressure, I have counted his genetics ten times. Had I collected data from 1,000 independent patients instead of repeatedly testing 100, I would be more confident that differences between groups came from the medicines and not from genetics and luck. I claimed a large sample size, giving me statistically significant results and high statistical power, but my claim is unjustified. This problem is known as pseudoreplication, and it is quite common. 38 After testing cells from a culture, a biologist might “replicate” his results by testing more cells from the same culture. Neuroscientists will test multiple neurons from the same animal, incorrectly claiming they have a large sample size because they tested hundreds of neurons from just two rats. In statistical terms, pseudoreplication occurs when individual observations are heavily dependent on each other. Your measurement of a patient’s blood pressure will be highly related to his blood pressure yesterday, and your measurement of soil composition here will be highly correlated with your measurement five feet away. There are several ways to account for this dependence while performing your statistical analysis: Average the dependent data points. For example, average all the blood pressure measurements taken from a single person. This isn’t perfect, though; if you measured some patients more frequently than others, this won’t be reflected in the averaged number. You want a method that somehow counts measurements as more reliable as more are taken. Analyze each dependent data point separately. You could perform an analysis of every patient’s blood pressure on day 5, giving you only one data point per person. But be careful, because if you do this for every day, you’ll have problems with multiple comparisons , which we will discuss in the next chapter. Use a statistical model which accounts for the dependence, like a hierarchical model or random effects model. It’s important to consider each approach before analyzing your data, as each method is suited to different situations. Pseudoreplication makes it easy to achieve significance, even though it gives you little additional information on the test subjects. Researchers must be careful not to artificially inflate their sample sizes when they retest samples. Pseudomonas. Professional Reference articles are designed for health professionals to use. They are written by UK doctors and based on research evidence, UK and European Guidelines. You may find one of our health articles more useful. Treatment of almost all medical conditions has been affected by the COVID-19 pandemic. NICE has issued rapid update guidelines in relation to many of these. This guidance is changing frequently. Please visit https://www.nice.org.uk/covid-19 to see if there is temporary guidance issued by NICE in relation to the management of this condition, which may vary from the information given below. Pseudomonas. In this article. Pseudomonas spp. are Gram-negative rod bacteria commonly found in soil, ground water, plants and animals. Pseudomonal infection causes a necrotising inflammation. Pseudomonads [1] Pseudomonads include a number of true Pseudomonas species as well as many species formerly classified in the genus. Pseudomonads are natural residents of soil and water. They rarely cause infections in healthy individuals. In immunocompromised patients, systemic infections can occur which may be severe and associated with a high mortality. The genus Pseudomonas once comprised over 100 species but over the period of a decade many of these have been reclassified into different genera. The main groups of pseudomonads of medical interest are: The fluorescent or 'true' Pseudomonas - P. aeruginosa , P. fluorescens and P. putida . Burkholderia spp. - within this genus, there are at least 30 species but the medically important species are B. cepacia , B. pseudomallei and B. mallei , which are are associated with human and animal infection: B. cepacia is an important pathogen of pulmonary infections in people with cystic fibrosis. B. pseudomallei is the causal agent of melioidosis, a life-threatening septic infection prevalent in Southeast Asia and Northern Australia. B. mallei causes glanders, a rare disease in horses and other species. Both B. pseudomallei and B. mallei must be handled in category 3 containment facilities and their exchange between laboratories is restricted. May be clinically significant in severely immunocompromised patients and is increasingly isolated from sputum of patients with cystic fibrosis. The overall incidence in 2017 for S. maltophilia bacteraemia was 0.8 cases/100,000 population in England, Wales and Northern Ireland. The rest of this article is specific for infections caused by P. aeruginosa . Pseudomonas aeruginosa. P. aeruginosa is an opportunistic pathogen that can cause a wide range of infections, especially in immunocompromised people and people with severe burns, diabetes mellitus or cystic fibrosis. P. aeruginosa is relatively resistant to many antibiotics, but effective antibiotics include imipenem, meropenem, ceftazidime, ciprofloxacin, amikacin, gentamicin, tobramycin, and piperacillin combined with tazobactam. Between 2015 and 2016, the resistance patterns for key antimicrobial agents remained broadly stable with small decreases in resistance for gentamicin (4% to 3%) and tobramycin (4% to 3%). Increases in resistance to imipenem (9% to 11%), amikacin (1% to 2%) and piperacillin\tazobactam (6% to 7%) were observed over the same time period [1] . Epidemiology [2] P. aeruginosa is found almost anywhere but rarely affects healthy people. Most community-acquired infections are associated with prolonged contact with contaminated water. In April 2017, the government extended the surveillance of bacteraemias caused by Gram-negative organisms to include P. aeruginosa . Between 2013 and 2017, there was a 26.6% increase in the number of Pseudomonas spp. bacteraemias reported to Public Health England (PHE) compared with a 6% decrease from 2008-2012. The overall incidence in 2017 for Pseudomonas spp. bacteraemias was 8.1 cases/100,000 population in England, Wales and Northern Ireland. P. aeruginosa is the most common cause of pseudomonal infection [1] . Studies suggest that P. aeruginosa may colonise up to one third of patients admitted to hospital. However, whether or not this causes clinical infection depends on the immune status of the host [3] . Pneumonia, urinary tract infections, surgical wound infections and bloodstream infections are the most common pathologies. In hospitals, P. aeruginosa particularly contaminates moist/wet reservoirs such as respiratory equipment and indwelling catheters. P. aeruginosa is also a frequent cause of chronic respiratory infection in patients with cystic fibrosis. As many as 80% of cystic fibrosis patients may be colonised in the lung with P. aeruginosa and, once established, it is very resistant to antibiotic treatment. Presentation [4] Respiratory tract. Pneumonia is seen in patients with immunosuppression and chronic lung disease. There is an increased risk in patients on mechanical ventilation, patients with neutropenia and in patients with HIV infection. Chronic infection of the lower respiratory tract with P. aeruginosa is common in patients with cystic fibrosis. Bacteraemia. There is an increased risk for people in hospitals and nursing homes. In 2017/18, 4,286 cases of P. aeruginosa bacteraemia were reported in England, of which 4,140 (97%) had known fatality outcomes. This equates to a case fatality rate of 27% [5] . Skin shows characteristic skin lesions (ecthyma gangrenosum), which are haemorrhagic and necrotic with surrounding erythema, and most often found in the axilla, groin or perianal area. Endocarditis. May infect heart valves in intravenous drug abusers and also prosthetic heart valves. Thromboembolism may cause widespread infection, including in the central nervous system. Central nervous system. May cause meningitis and intracranial abscesses. Most infections result from direct spread from local structures (eg, the ear, mastoid or sinuses) but blood-borne spread may also occur. Common cause of chronic otitis media. May also cause otitis externa (including malignant otitis externa). In adults: common cause of bacterial keratitis,
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