network meta-analysis electrical networks and graph theory pdf

Network Meta-analysis Electrical Networks And Graph Theory Pdf

On Wednesday, April 14, 2021 5:39:37 PM

File Name: network meta-analysis electrical networks and graph theory .zip
Size: 24486Kb
Published: 14.04.2021

Either your web browser doesn't support Javascript or it is currently turned off. In the latter case, please turn on Javascript support in your web browser and reload this page.

Metrics details. Network meta-analysis NMA is becoming increasingly popular in systematic reviews and health technology assessments.

Statistics and Its Interface

Line width is proportional to the number of studies comparing every pair of treatments. Size of every circle is proportional to the number of patients. A, network meta-analysis graph of drugs for comparing efficacy of RCTs.

B, network meta-analysis graph of drugs for comparing the defervescence time of RCTs. C, network meta-analysis graph of drugs for comparing safety of RCTs. D, network meta-analysis graph of drugs for comparing efficacy of retrospective studies.

E, network meta-analysis graph of drugs for comparing the defervescence time of retrospective studies. Antibiotics vs azithromycin reference drug. A, comparisons of drugs in RCTs for efficacy. B, comparisons of drugs in RCTs for the defervescence time. C, comparisons of drugs in RCTs for safety. D, comparisons of drugs in retrospective studies for efficacy. E, comparisons of drugs in retrospective studies for the defervescence time. MD indicates mean deviation; OR, odds ratio.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response. Not all submitted comments are published. Please see our commenting policy for details. In retrospective studies, clarithromycin alleviated fever more efficiently than other antibiotics.

The study was conducted from July 12 to September 2, Records of articles in English were considered eligible. Studies were assessed independently by 2 reviewers, with disagreement resolved by consensus.

Of studies initially identified, 10 randomized clinical trials and 4 retrospective study met the criteria for further analysis. Data were independently extracted by 2 reviewers and synthesized with frequentist random-effects network meta-analyses.

Safety, defined as the prevalence of adverse events associated with the antibiotics, was the secondary outcome, and defervescence time was the tertiary outcome. P scores scale of 0 to 1, with 1 indicating superiority to other treatments were used to rank the efficacy, safety, and defeverescence time of the antibiotics. No particular treatment regimen showed a significant advantage or disadvantage with regard to efficacy or safety.

However, clarithromycin might be a better choice than the other drugs for alleviating fever. Orientia tsutsugamushi is a type of gram-negative, obligately intracellular bacillus that belongs to the order Rickettsiales within the family Rickettsiaceae.

Scrub typhus has wide distribution in tropical and subtropical regions, such as the Arabian Peninsula, Chile, and possibly Kenya. However, although almost 1 million new cases are reported every year, scrub typhus is regarded as a neglected tropical disease. The clinical manifestations of scrub typhus differ among individuals. Almost 5 to 14 days after being bitten by Leptotrombidium mites, patients exhibit rash and eschar at the bite site, as well as fever, headache, myalgia, cough, generalized lymphadenopathy, nausea, vomiting, and abdominal pain.

Antibiotics have been used for scrub typhus treatment for many years and, with no vaccine available, are the only way to treat scrub typhus. The most common antibiotics used for treatment are doxycycline, tetracyclines, chloramphenicol, and azithromycin, 13 but their efficacy is disputable. Although studies have compared the efficacy of some antibiotics for curing scrub typhus, 13 - 17 these studies have not been comprehensive or quantitative.

This lack of understanding the varying efficacy of the drugs may lead to patients getting sicker because of inappropriate treatment regimens. Thus, we used a network meta-analysis to systematically analyze data derived from randomized clinical trials RCTs and retrospective studies to evaluate the use of various antibiotics against scrub typhus. In this way, we hope to provide evidence for clinicians to develop therapeutic schedules.

This network meta-analysis was undertaken on the basis of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA extension statement for systematic reviews incorporating network meta-analyses of health care interventions. GRADE provides a system for rating the quality of systematic reviews, meta-analyses, or network meta-analyses.

We searched articles in Embase and PubMed databases from the date of their inception to July 12, , on 3 occasions. In the first search, we used scrub typhus combined with a list of antibiotics.

This list included 11 antibiotics: chloramphenicol , tetracycline , doxycycline , rifampicin , erythromycin , azithromycin , telithromycin , levofloxacin , minocycline , penicillin , and aureomycin. For the second search, the search terms were scrub typhus , therapy , treatment , cure , drug , antibiotic , and antimicrobial. For the final search, we used scrub typhus , randomized controlled trial , controlled clinical trial , random allocation , double-blind , single-blind , survival , treatment , therapy , comparison , comparative , effective , and efficacy as search terms.

All studies had to be RCTs or retrospective studies that compared the efficacy or safety of drugs used to treat scrub typhus and published in English.

In addition, all patients in RCTs or retrospective studies had to have been diagnosed by clinicians in accordance with clinical symptoms and the results of laboratory tests to ascertain whether O tsutsugamushi was present in their body.

Clinicians had to diagnose the disease in those patients using the Weil-Felix test, immunofluorescence assay, bacterial culture, enzyme-linked immunosorbent assay, or polymerase chain reaction test. All included studies were assessed independently by 2 of us L.

Luo and T. Disagreement for a particular assessment was resolved by discussing the issues until a consensus was reached. We extracted data on patients and interventions from each study included in the network meta-analysis. For patient data, we recorded their age and sex. Furthermore, we noted the total number of patients, the number of patients treated using a particular antibiotic, and the number of patients who responded to a particular drug complete recovery from scrub typhus. Fever is the most commonly reported clinical manifestation of scrub typhus and is a strong indicator for evaluating therapeutic effects.

Therefore, we recorded the defervescence time mean [SD] of patients treated with a particular drug. The unit of defervescence time is hours. For studies that did not specify the mean SD defervescence time, we extracted the median range values of the defervescence time and then calculated the mean SD using the method of McGrath and colleagues.

For data on interventions, we recorded the drug name, dose, and duration of therapy. We evaluated all drugs systematically by 3 outcomes: efficacy, safety, and the defervescence time.

Efficacy was the primary study outcome and referred to the response of patients to a particular drug and was measured by the total number of patients who recovered completely. The secondary outcome, safety, referred to the prevalence of adverse reactions of a particular drug and was measured by the total number of patients who developed an adverse reaction during or after treatment.

The third outcome, defervescence time, was the time needed for abatement of fever, as indicated by a decrease in body temperature, after use of antibiotics. All data were extracted by 2 of us L. Li and X. Before we started to analyze extracted data, we assessed the risk of bias of all included studies in accordance with the tool for assessing risk of bias in randomized trials published by the Cochrane Collaboration. Odds ratios ORs were used to report the effect size for assessing efficacy and safety.

Mean deviations MDs were used to report the effect size for assessing the time of defervescence. Inconsistency the difference of estimates of effect between direct evidence and indirect evidence is an important indicator for a network meta-analysis.

We used the back calculation method to assess the inconsistency of this network meta-analysis, which is based on the Z test, and provide the P value to define the inconsistency.

To rank the efficacy, safety, and defervescence time of antibiotics, we used the P score as an indicator. The P score is used to measure the extent of certainty that a treatment is better than other treatments, averaged over all competing treatments. Hence, if one treatment is better than the other treatments, its P score will be larger. All analyses were conducted using the Netmeta package of R, version 3. By excluding duplicate and ineligible studies, we selected 10 RCTs 35 - 44 and 4 retrospective studies 45 - 48 for further analyses Figure 1.

The selected studies were published from to and involved patients patients in retrospective studies and patients in RCTs. In the 10 RCTs, 9 compared drug efficacy, 35 - 38 , 40 - 44 8 compared the defervescence time, 35 , 38 - 44 and 8 compared adverse reactions 36 - 41 , 43 , 44 eTable 2, eTable 3, and eTable 4 in the Supplement. All 4 retrospective studies compared the efficacy of 5 drugs, and 3 of them 45 , 47 , 48 compared the defervescence time eTable 3 and 4 in the Supplement.

The tool for assessing risk of bias in randomized trials examined RCTs according to 7 standards. Network meta-analysis graphs developed for comparison of efficacy, defervescence time, and safety of the RCTs Figure 2 A, B, and C and retrospective studies Figure 2 D and E are provided.

For retrospective studies, we assessed the efficacy of 5 drugs Figure 2 D. We compared the efficacy of all treatment regimens with that of azithromycin reference drug , but a significant difference among them was not observed Figure 3 A and D. Next, we conducted pairwise comparisons of the efficacy of all treatment regimens in RCTs eFigure 2 in the Supplement and retrospective studies Table.

There was no significant difference in efficacy among those treatments. To assess the defervescence time of different drugs, we analyzed separately the data of 7 treatment regimens from RCTs and data on 5 drugs from retrospective studies Figure 2 B and E.

We compared the defervescence time of all treatment regimens with that of azithromycin reference drug. The results of pairwise comparison of all treatment regimens are presented in the Table. There was no significant difference among treatment regimens in RCTs. In retrospective studies, the defervescence time of azithromycin was longer than that of chloramphenicol MD, The defervescence time of chloramphenicol was longer than that of clarithromycin MD, With regard to other comparisons in retrospective studies, there was no significant difference in the defervescence time among them.

All data on drug safety were collected were from RCTs only. A total of patients developed an adverse reaction during or after therapy. The most frequently reported adverse reactions were vomiting, erythematous rash, gastrointestinal reaction, nausea, diarrhea, and increased serum level of alanine aminotransferase. We assessed the safety of 7 treatment regimens Figure 2 C. A forest plot Figure 3 C exhibited the results of comparing the safety of 7 drugs with that of azithromycin reference drug.

In addition, results of pairwise comparison of all drugs are displayed in eFigure 2 in the Supplement.

Estimating the contribution of studies in network meta-analysis: paths, flows and streams

Jump to navigation. The mvmeta command in STATA employs a recent approach to network meta-analysis that handles the different treatment comparisons appeared in studies as different outcomes. The command can perform fixed and random effects network meta-analysis assuming either a common or different between-study variances across comparisons. The command contains also an option that enables the estimation of ranking probabilities. White IR. Multivariate random-effects meta-regression: Updates to mvmeta. Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression.

This website requires Javascript in order to display and function properly. Please enable Javascript in your web browser. SII Home Page. SII Content Home. All SII Volumes. This Volume. This Issue.

Network meta-analysis, electrical networks and graph theory. December ; Research Request Full-text Paper PDF. To read the full-text of.

Graph Theory Electrical Networks Pdf

The conduction and report of network meta-analysis NMA , including the presentation of the network-plot, should be transparent. We aimed to propose metrics adapted from graph theory and social network-analysis literature to numerically describe NMA geometry. A previous systematic review of NMAs of pharmacological interventions was performed. Network-plots were reproduced using Gephi 0. Eleven geometric metrics were tested.

Line width is proportional to the number of studies comparing every pair of treatments. Size of every circle is proportional to the number of patients. A, network meta-analysis graph of drugs for comparing efficacy of RCTs. B, network meta-analysis graph of drugs for comparing the defervescence time of RCTs. C, network meta-analysis graph of drugs for comparing safety of RCTs.

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI:

Было темно. Сьюзан остановилась, собираясь с духом. Звук выстрела продолжал звучать у нее в голове.

Все четко, ясно и. Танкадо зашифровал Цифровую крепость, и только ему известен ключ, способный ее открыть. Но Сьюзан трудно было представить себе, что где-то - например, на клочке бумаги, лежащем в кармане Танкадо, - записан ключ из шестидесяти четырех знаков, который навсегда положит конец сбору разведывательной информации в Соединенных Штатах.

На рубашке расплывалось красное пятно, хотя кровотечение вроде бы прекратилось. Рана была небольшой, скорее похожей на глубокую царапину. Он заправил рубашку в брюки и оглянулся.

Стратмор кивнул: - Танкадо хотел от него избавиться. Он подумал, что это мы его убили. Он почувствовал, что умирает, и вполне логично предположил, что это наших рук. Тут все совпадает.

Приступайте. - Мы не успеем! - крикнула Соши.  - На это уйдет полчаса. К тому времени все уже рухнет.

A Network Meta-Analysis Toolkit

Еще и собственная глупость. Он отдал Сьюзан свой пиджак, а вместе с ним - Скайпейджер.

pdf download pdf free download


  1. Thierry P.

    While social network theory can be readily applied in theoretical research and qualitative empirical studies, there is a general emphasis on the use of software to analyze and visualize network data once they have been collected.

    15.04.2021 at 09:24 Reply
  2. Radahan

    Network topology is a graphical representation of electric circuits.

    19.04.2021 at 19:28 Reply

Leave your comment


Subscribe Now To Get Daily Updates