This document discusses common statistical fallacies and errors that occur in medical research. It identifies 10 categories of issues: 1) biased samples, 2) inadequate sample sizes, 3) incomparable groups, 4) mixing of groups, 5) ignoring reality, 6) choice of inappropriate analysis, 7) misuse of statistical packages, 8) errors in data presentation, 9) misinterpretation of results, and 10) overreliance on P-values and correlation without considering causation. The author emphasizes the importance of using statistics correctly and with common sense to truthfully represent medical uncertainties.
Various designs of observational studies (prospective, retrospective, and cross-sectional) and analytical studies (clinical trials and laboratory experiments), and guidelines to choose appropriate sample size
This document provides an overview of critical appraisal of randomized controlled trials (RCTs). It defines critical appraisal as carefully examining research to assess its trustworthiness and relevance. RCTs are described as the gold standard for clinical trials, where participants are randomly allocated to groups that receive either a treatment or a control. Key factors to examine in appraising an RCT are described, including sample size, eligibility criteria, baseline characteristics, randomization, blinding, follow-up of participants, data collection, presentation of results, and applicability to local populations. Advantages of critical appraisal and RCTs include providing a systematic way to assess research validity and improving practice, while disadvantages include taking time and not always finding clear answers.
This document provides information about conducting and appraising a meta-analysis on the use of prophylactic antibiotics for pancreatic necrosis. It outlines the steps of formulating the clinical question using PICO, acquiring relevant studies through database searches and hand searches, appraising study quality, collecting and recording study data, analyzing results using both individual and pooled treatment effects, and reporting findings in a forest plot. Key aspects of meta-analysis methodology are discussed including biases that can affect results.
What is the best evidence in medicine?Samir Haffar
This document discusses the hierarchy of evidence and types of medical studies used to evaluate evidence. It begins by defining evidence-based medicine as integrating the best research evidence, clinical expertise, and patient values. It then outlines the different types of studies from case reports and case series up to systematic reviews and meta-analyses. Randomized controlled trials are considered the gold standard but all study types have strengths and limitations. The document emphasizes finding the highest quality evidence available and assessing it critically to inform clinical decision making.
Critical appraisal of randomized clinical trialsSamir Haffar
The document discusses key concepts in randomized clinical trials (RCTs), including:
1) RCTs are considered the gold standard for evaluating the effectiveness of interventions due to their ability to minimize bias through randomization and blinding.
2) Proper randomization aims to create comparable treatment and control groups, conceal allocation to prevent bias, and may involve simple, stratified or blocked methods.
3) Blinding (masking) of participants, investigators and assessors can decrease observation bias and is important for RCT validity, though full blinding is not always possible.
4) Intention-to-treat analysis includes all randomized patients to preserve comparable groups and prevent bias from non-compliance.
1. This study was a cluster randomized controlled trial that assessed the effects of periodic vitamin A supplementation and deworming on child mortality in 1 million preschool children in North India.
2. The study had a 5-year study period from 1999-2004 and used a 2x2 factorial design to examine the effects of 6-monthly vitamin A supplementation, 6-monthly deworming with albendazole, and their combination on mortality in children aged 1-6 years.
3. The results found that vitamin A supplementation alone did not reduce child mortality as much as expected based on previous trials, reducing mortality by only 4%. However, meta-analysis of this study combined with previous trials still showed an average
This document discusses critical appraisal of published medical research. It notes that thousands of new medical articles are published daily, making it difficult for clinicians to keep up-to-date. Critical appraisal involves assessing the validity, reliability, and applicability of a study rather than just dismissing it or looking only at the results. Key aspects of critical appraisal include describing the evidence, assessing internal validity by examining potential biases and confounding factors, evaluating external validity and whether results can apply to other populations, and comparing results to other evidence. The document provides guidance on how to critically appraise studies and lists resources for further information.
This document discusses common statistical fallacies and errors that occur in medical research. It identifies 10 categories of issues: 1) biased samples, 2) inadequate sample sizes, 3) incomparable groups, 4) mixing of groups, 5) ignoring reality, 6) choice of inappropriate analysis, 7) misuse of statistical packages, 8) errors in data presentation, 9) misinterpretation of results, and 10) overreliance on P-values and correlation without considering causation. The author emphasizes the importance of using statistics correctly and with common sense to truthfully represent medical uncertainties.
Various designs of observational studies (prospective, retrospective, and cross-sectional) and analytical studies (clinical trials and laboratory experiments), and guidelines to choose appropriate sample size
This document provides an overview of critical appraisal of randomized controlled trials (RCTs). It defines critical appraisal as carefully examining research to assess its trustworthiness and relevance. RCTs are described as the gold standard for clinical trials, where participants are randomly allocated to groups that receive either a treatment or a control. Key factors to examine in appraising an RCT are described, including sample size, eligibility criteria, baseline characteristics, randomization, blinding, follow-up of participants, data collection, presentation of results, and applicability to local populations. Advantages of critical appraisal and RCTs include providing a systematic way to assess research validity and improving practice, while disadvantages include taking time and not always finding clear answers.
This document provides information about conducting and appraising a meta-analysis on the use of prophylactic antibiotics for pancreatic necrosis. It outlines the steps of formulating the clinical question using PICO, acquiring relevant studies through database searches and hand searches, appraising study quality, collecting and recording study data, analyzing results using both individual and pooled treatment effects, and reporting findings in a forest plot. Key aspects of meta-analysis methodology are discussed including biases that can affect results.
What is the best evidence in medicine?Samir Haffar
This document discusses the hierarchy of evidence and types of medical studies used to evaluate evidence. It begins by defining evidence-based medicine as integrating the best research evidence, clinical expertise, and patient values. It then outlines the different types of studies from case reports and case series up to systematic reviews and meta-analyses. Randomized controlled trials are considered the gold standard but all study types have strengths and limitations. The document emphasizes finding the highest quality evidence available and assessing it critically to inform clinical decision making.
Critical appraisal of randomized clinical trialsSamir Haffar
The document discusses key concepts in randomized clinical trials (RCTs), including:
1) RCTs are considered the gold standard for evaluating the effectiveness of interventions due to their ability to minimize bias through randomization and blinding.
2) Proper randomization aims to create comparable treatment and control groups, conceal allocation to prevent bias, and may involve simple, stratified or blocked methods.
3) Blinding (masking) of participants, investigators and assessors can decrease observation bias and is important for RCT validity, though full blinding is not always possible.
4) Intention-to-treat analysis includes all randomized patients to preserve comparable groups and prevent bias from non-compliance.
1. This study was a cluster randomized controlled trial that assessed the effects of periodic vitamin A supplementation and deworming on child mortality in 1 million preschool children in North India.
2. The study had a 5-year study period from 1999-2004 and used a 2x2 factorial design to examine the effects of 6-monthly vitamin A supplementation, 6-monthly deworming with albendazole, and their combination on mortality in children aged 1-6 years.
3. The results found that vitamin A supplementation alone did not reduce child mortality as much as expected based on previous trials, reducing mortality by only 4%. However, meta-analysis of this study combined with previous trials still showed an average
This document discusses critical appraisal of published medical research. It notes that thousands of new medical articles are published daily, making it difficult for clinicians to keep up-to-date. Critical appraisal involves assessing the validity, reliability, and applicability of a study rather than just dismissing it or looking only at the results. Key aspects of critical appraisal include describing the evidence, assessing internal validity by examining potential biases and confounding factors, evaluating external validity and whether results can apply to other populations, and comparing results to other evidence. The document provides guidance on how to critically appraise studies and lists resources for further information.
This document provides an overview of key concepts in biostatistics for clinical research. It discusses study design considerations including descriptive versus analytical studies, and observational versus experimental designs. It also covers topics like clinical trial methodology, ethics, and sample size calculation. Sample size depends on the statistical parameter, design, hypothesis being tested, and is neither too small to lack power nor too large to waste resources. Resource limitations may require adjusting the target sample size or power. Planned statistical analyses should be tailored to the research objectives.
This document discusses meta-analysis techniques for systematically reviewing and statistically combining results from multiple clinical trials. It covers the history of meta-analysis, methodology for combining test statistics and assessing heterogeneity, software for conducting meta-analyses, and current issues including how to handle different study designs. Examples are provided to illustrate meta-analysis of randomized controlled trials comparing treatments for stroke, myocardial infarction, and other conditions.
Deciding on a medical research topic: your first challengeAzmi Mohd Tamil
This document provides guidance on choosing a research topic for a research project. It recommends asking your supervisor if they have a topic of interest. If not, you should choose a topic that interests you by considering who or what will benefit from the research, current issues in the field, and when and where the topic is relevant. The document provides examples of how to narrow a topic and define outcomes of interest, conceptual frameworks, and appropriate study designs. It stresses the importance of clearly defining concepts and outcomes and warns against using scales without validating cut-off points for the target population.
This document provides an overview of evidence-based medicine and how to critically appraise clinical papers. It discusses how evidence-based medicine involves using both clinical expertise and the best available external evidence in decision making. The origins of evidence-based medicine in the 1970s and 1990s are also reviewed. The document then focuses on how to critically read clinical papers, including the key things to assess for diagnostic tests, clinical course/prognosis, causation, and therapy papers. It provides guidance on an appraisal format and emphasizes the need to both evaluate the study and summarize what it was about. Evidence-based medicine is positioned as an important guide but not a replacement for clinical expertise and judgment.
The document provides an overview of critical appraisal of medical research. It discusses study designs such as randomized controlled trials, observational studies, systematic reviews and meta-analyses. It also covers topics like developing PICO(T) questions to frame clinical questions, different types of study questions, evaluating studies using the FRISBE mnemonic, calculating measures of clinical importance, and resources for evidence-based practice.
A retrospective cohort study examines existing data to investigate associations between exposures and outcomes without prospective follow-up. The document discusses:
1) Retrospective cohort studies identify exposed and unexposed groups from past data and determine current disease status, requiring less time than prospective studies.
2) Limitations include potential for poor quality or incomplete past data, and lack of information on confounding factors.
3) As an example, a study used employee health records to retrospectively examine the association between chemical exposure in tire manufacturing and mortality. However, past data may not fully account for smoking, diet, or other risk factors.
The document provides guidance on writing introductions and outlines their typical structure. It discusses that introductions should funnel down from general to specific topics and introduce the research problem and plan to address it. Introductions typically have three paragraphs covering: 1) background on the problem, 2) importance and unresolved issues, and 3) rationale and research question/hypothesis. The document also provides tips for writing materials and methods sections, including describing the study design, sample, data collection and analysis procedures.
What Are the Different Types of Clinical Research or who can participate in it?Vial Trials
Participation in a clinical trial is an option for many people with serious illnesses, especially when no suitable treatments are available. Please read this blog here to know about the different types of clinical research or who can participate in it!
Imran rizvi statistics in meta analysisImran Rizvi
This document discusses statistics used in meta-analyses. It explains that meta-analyses statistically combine results from multiple studies on a topic. Effect measures are calculated for individual studies and then combined to find an overall effect. For dichotomous outcomes, common effect measures are risk ratio, odds ratio, and absolute risk reduction. Random effects models account for heterogeneity between studies, while fixed effect models assume one true effect. Forest plots visually display individual study results and the overall effect, allowing readers to assess consistency and precision.
This document outlines the steps involved in conducting a systematic review and meta-analysis on the prevalence of elder abuse. It discusses how 52 studies from around the world were analyzed using comprehensive meta-analysis software. The key findings were that the pooled prevalence of elder abuse was 15.7%. While systematic reviews have strengths like being comprehensive and transparent, they also have limitations such as reliance on the quality of primary studies and risk of publication bias.
Critical appraisal of published medical research (2)Tarek Tawfik Amin
This document outlines 8 steps for critically appraising published medical research: 1) consider the research hypothesis, 2) study design, 3) outcome variable, 4) predictor variables, 5) methods of analysis, 6) potential sources of bias, 7) interpretation of results, and 8) utility of results. For each step, it provides questions to consider when evaluating if a study has addressed that aspect appropriately and rigorously. The goal is to systematically evaluate the strengths and limitations of a published study.
HEALTHCARE RESEARCH METHODS: Experimental Studies and Qualitative StudiesDr. Khaled OUANES
The document provides an overview of various healthcare research methods including experimental studies, qualitative studies, consensus methods, program evaluation, and screening/diagnostic tests. Experimental studies examine the effects of interventions by randomly assigning participants to intervention and control groups. Key aspects of experimental studies discussed are defining outcomes, selecting appropriate controls, blinding participants, randomization techniques, and analyzing results. Qualitative research aims to understand participant perspectives and experiences through techniques like interviews and focus groups. The document also outlines consensus methods such as the Delphi Method, program evaluation frameworks, and considerations for evaluating diagnostic tests.
This document provides guidance on how to critically appraise a randomized controlled trial (RCT) by considering questions related to internal and external validity. Key points to evaluate include whether the trial addressed a clear question, used an appropriate RCT design, properly randomized and accounted for all participants, minimized biases, had sufficient statistical power, and presented results precisely. The value of the results should be determined by considering benefits versus harms and whether findings can be applied to local context.
This document provides an overview of key concepts for collecting and managing data in research studies. It discusses sampling methods, types of variables, data collection techniques including using existing records, observation, interviews and questionnaires. It also covers ensuring quality of data through accuracy, reliability, data handling, data processing including coding, data entry and verification. The goal is to choose appropriate methods to obtain high quality representative data for analysis and drawing valid conclusions.
This document provides an overview of how to conduct a systematic review and meta-analysis. It describes the key steps: (1) asking a focused clinical question using PICO, (2) acquiring relevant studies through database searches, (3) appraising the quality of included studies, (4) analyzing the data using statistical methods to obtain an overall treatment effect size, and (5) reporting results typically in a forest plot. Meta-analyses provide increased statistical power over individual studies but are not without limitations such as potential bias that must be considered when interpreting results.
How to search the medical literature on the netSamir Haffar
This document provides an overview of how to search the medical literature on the internet. It discusses the large volume of published literature, challenges in finding high-quality evidence, and resources that can help. Key points include:
- Over 50,000 new biomedical articles are published each year, making it difficult to find relevant information.
- Formulating focused clinical questions using PICO/PIO criteria can help target searches.
- Resources like PubMed, textbooks, and synthesis sources like Cochrane Reviews can help filter the literature to find the most valid and applicable evidence.
- The Cochrane Collaboration established a standard for compiling systematic reviews and meta-analyses to synthesize the best evidence on various clinical topics.
Dr. Amin Bredan - Highlights on some aspects of research/ Writing research pa...SCMRteam
The document discusses strategies for medical student research, including integrating research methodology training into the curriculum, conducting workshops on research methods, and requiring research assignments. It also examines barriers to student research such as a lack of training courses and difficulty obtaining funding or samples. Finally, it provides an overview of common study designs used in medical student research projects.
This document provides an introduction to critical appraisal of literature. It discusses the importance of critically evaluating research to separate reliable evidence from unreliable evidence. It outlines the process of critical appraisal, including asking a focused question, finding relevant evidence, and using appraisal tools to systematically examine research quality, validity, and relevance. The document also introduces some key statistical concepts used in research, such as p-values, confidence intervals, risk reduction, and number needed to treat. The goal of critical appraisal is to make informed decisions about integrating research findings into clinical practice and policy.
1. The document provides an overview of evidence-based medicine (EBM) and the process of critically appraising research evidence. EBM involves integrating the best available research evidence with clinical expertise and patient values and preferences.
2. The key steps of EBM are outlined, including formulating a clear clinical question using PICO (population, intervention, comparison, outcome), searching for and appraising the evidence, and applying the results to the clinical problem.
3. Users' guides are provided for critically appraising different study designs, focusing on whether the results are valid and assessing the magnitude and precision of the treatment effect. Factors like randomization, blinding, follow-up, and equal treatment of groups
This document provides an overview of evidence-based medicine (EBM). It defines EBM as integrating the best available research evidence with clinical expertise and patient values. The key steps of EBM are outlined as formulating a clinical question using PICO (population, intervention, comparison, outcome), searching for evidence, appraising research studies, and applying the evidence to clinical problems. Study designs such as randomized controlled trials and systematic reviews are discussed. Methods for critically appraising studies including assessing validity and determining the clinical importance of results are also summarized.
This document provides an overview of key concepts in biostatistics for clinical research. It discusses study design considerations including descriptive versus analytical studies, and observational versus experimental designs. It also covers topics like clinical trial methodology, ethics, and sample size calculation. Sample size depends on the statistical parameter, design, hypothesis being tested, and is neither too small to lack power nor too large to waste resources. Resource limitations may require adjusting the target sample size or power. Planned statistical analyses should be tailored to the research objectives.
This document discusses meta-analysis techniques for systematically reviewing and statistically combining results from multiple clinical trials. It covers the history of meta-analysis, methodology for combining test statistics and assessing heterogeneity, software for conducting meta-analyses, and current issues including how to handle different study designs. Examples are provided to illustrate meta-analysis of randomized controlled trials comparing treatments for stroke, myocardial infarction, and other conditions.
Deciding on a medical research topic: your first challengeAzmi Mohd Tamil
This document provides guidance on choosing a research topic for a research project. It recommends asking your supervisor if they have a topic of interest. If not, you should choose a topic that interests you by considering who or what will benefit from the research, current issues in the field, and when and where the topic is relevant. The document provides examples of how to narrow a topic and define outcomes of interest, conceptual frameworks, and appropriate study designs. It stresses the importance of clearly defining concepts and outcomes and warns against using scales without validating cut-off points for the target population.
This document provides an overview of evidence-based medicine and how to critically appraise clinical papers. It discusses how evidence-based medicine involves using both clinical expertise and the best available external evidence in decision making. The origins of evidence-based medicine in the 1970s and 1990s are also reviewed. The document then focuses on how to critically read clinical papers, including the key things to assess for diagnostic tests, clinical course/prognosis, causation, and therapy papers. It provides guidance on an appraisal format and emphasizes the need to both evaluate the study and summarize what it was about. Evidence-based medicine is positioned as an important guide but not a replacement for clinical expertise and judgment.
The document provides an overview of critical appraisal of medical research. It discusses study designs such as randomized controlled trials, observational studies, systematic reviews and meta-analyses. It also covers topics like developing PICO(T) questions to frame clinical questions, different types of study questions, evaluating studies using the FRISBE mnemonic, calculating measures of clinical importance, and resources for evidence-based practice.
A retrospective cohort study examines existing data to investigate associations between exposures and outcomes without prospective follow-up. The document discusses:
1) Retrospective cohort studies identify exposed and unexposed groups from past data and determine current disease status, requiring less time than prospective studies.
2) Limitations include potential for poor quality or incomplete past data, and lack of information on confounding factors.
3) As an example, a study used employee health records to retrospectively examine the association between chemical exposure in tire manufacturing and mortality. However, past data may not fully account for smoking, diet, or other risk factors.
The document provides guidance on writing introductions and outlines their typical structure. It discusses that introductions should funnel down from general to specific topics and introduce the research problem and plan to address it. Introductions typically have three paragraphs covering: 1) background on the problem, 2) importance and unresolved issues, and 3) rationale and research question/hypothesis. The document also provides tips for writing materials and methods sections, including describing the study design, sample, data collection and analysis procedures.
What Are the Different Types of Clinical Research or who can participate in it?Vial Trials
Participation in a clinical trial is an option for many people with serious illnesses, especially when no suitable treatments are available. Please read this blog here to know about the different types of clinical research or who can participate in it!
Imran rizvi statistics in meta analysisImran Rizvi
This document discusses statistics used in meta-analyses. It explains that meta-analyses statistically combine results from multiple studies on a topic. Effect measures are calculated for individual studies and then combined to find an overall effect. For dichotomous outcomes, common effect measures are risk ratio, odds ratio, and absolute risk reduction. Random effects models account for heterogeneity between studies, while fixed effect models assume one true effect. Forest plots visually display individual study results and the overall effect, allowing readers to assess consistency and precision.
This document outlines the steps involved in conducting a systematic review and meta-analysis on the prevalence of elder abuse. It discusses how 52 studies from around the world were analyzed using comprehensive meta-analysis software. The key findings were that the pooled prevalence of elder abuse was 15.7%. While systematic reviews have strengths like being comprehensive and transparent, they also have limitations such as reliance on the quality of primary studies and risk of publication bias.
Critical appraisal of published medical research (2)Tarek Tawfik Amin
This document outlines 8 steps for critically appraising published medical research: 1) consider the research hypothesis, 2) study design, 3) outcome variable, 4) predictor variables, 5) methods of analysis, 6) potential sources of bias, 7) interpretation of results, and 8) utility of results. For each step, it provides questions to consider when evaluating if a study has addressed that aspect appropriately and rigorously. The goal is to systematically evaluate the strengths and limitations of a published study.
HEALTHCARE RESEARCH METHODS: Experimental Studies and Qualitative StudiesDr. Khaled OUANES
The document provides an overview of various healthcare research methods including experimental studies, qualitative studies, consensus methods, program evaluation, and screening/diagnostic tests. Experimental studies examine the effects of interventions by randomly assigning participants to intervention and control groups. Key aspects of experimental studies discussed are defining outcomes, selecting appropriate controls, blinding participants, randomization techniques, and analyzing results. Qualitative research aims to understand participant perspectives and experiences through techniques like interviews and focus groups. The document also outlines consensus methods such as the Delphi Method, program evaluation frameworks, and considerations for evaluating diagnostic tests.
This document provides guidance on how to critically appraise a randomized controlled trial (RCT) by considering questions related to internal and external validity. Key points to evaluate include whether the trial addressed a clear question, used an appropriate RCT design, properly randomized and accounted for all participants, minimized biases, had sufficient statistical power, and presented results precisely. The value of the results should be determined by considering benefits versus harms and whether findings can be applied to local context.
This document provides an overview of key concepts for collecting and managing data in research studies. It discusses sampling methods, types of variables, data collection techniques including using existing records, observation, interviews and questionnaires. It also covers ensuring quality of data through accuracy, reliability, data handling, data processing including coding, data entry and verification. The goal is to choose appropriate methods to obtain high quality representative data for analysis and drawing valid conclusions.
This document provides an overview of how to conduct a systematic review and meta-analysis. It describes the key steps: (1) asking a focused clinical question using PICO, (2) acquiring relevant studies through database searches, (3) appraising the quality of included studies, (4) analyzing the data using statistical methods to obtain an overall treatment effect size, and (5) reporting results typically in a forest plot. Meta-analyses provide increased statistical power over individual studies but are not without limitations such as potential bias that must be considered when interpreting results.
How to search the medical literature on the netSamir Haffar
This document provides an overview of how to search the medical literature on the internet. It discusses the large volume of published literature, challenges in finding high-quality evidence, and resources that can help. Key points include:
- Over 50,000 new biomedical articles are published each year, making it difficult to find relevant information.
- Formulating focused clinical questions using PICO/PIO criteria can help target searches.
- Resources like PubMed, textbooks, and synthesis sources like Cochrane Reviews can help filter the literature to find the most valid and applicable evidence.
- The Cochrane Collaboration established a standard for compiling systematic reviews and meta-analyses to synthesize the best evidence on various clinical topics.
Dr. Amin Bredan - Highlights on some aspects of research/ Writing research pa...SCMRteam
The document discusses strategies for medical student research, including integrating research methodology training into the curriculum, conducting workshops on research methods, and requiring research assignments. It also examines barriers to student research such as a lack of training courses and difficulty obtaining funding or samples. Finally, it provides an overview of common study designs used in medical student research projects.
This document provides an introduction to critical appraisal of literature. It discusses the importance of critically evaluating research to separate reliable evidence from unreliable evidence. It outlines the process of critical appraisal, including asking a focused question, finding relevant evidence, and using appraisal tools to systematically examine research quality, validity, and relevance. The document also introduces some key statistical concepts used in research, such as p-values, confidence intervals, risk reduction, and number needed to treat. The goal of critical appraisal is to make informed decisions about integrating research findings into clinical practice and policy.
1. The document provides an overview of evidence-based medicine (EBM) and the process of critically appraising research evidence. EBM involves integrating the best available research evidence with clinical expertise and patient values and preferences.
2. The key steps of EBM are outlined, including formulating a clear clinical question using PICO (population, intervention, comparison, outcome), searching for and appraising the evidence, and applying the results to the clinical problem.
3. Users' guides are provided for critically appraising different study designs, focusing on whether the results are valid and assessing the magnitude and precision of the treatment effect. Factors like randomization, blinding, follow-up, and equal treatment of groups
This document provides an overview of evidence-based medicine (EBM). It defines EBM as integrating the best available research evidence with clinical expertise and patient values. The key steps of EBM are outlined as formulating a clinical question using PICO (population, intervention, comparison, outcome), searching for evidence, appraising research studies, and applying the evidence to clinical problems. Study designs such as randomized controlled trials and systematic reviews are discussed. Methods for critically appraising studies including assessing validity and determining the clinical importance of results are also summarized.
This document discusses various types of errors and biases that can occur in epidemiological studies. It defines error as a phenomenon where a study's results do not reflect the true facts. There are two basic types of error: random error, which occurs by chance and makes observed values differ from true values; and systematic error or bias, which is due to factors in the study design that cause results to depart from the truth. Types of bias discussed include selection bias, information bias, and confounding. Strategies for controlling biases such as randomization, restriction, matching, and statistical modeling are also outlined.
Quick introduction to critical appraisal of quantitative researchAlan Fricker
1) The document provides an introduction to critically appraising quantitative research for healthcare. It discusses key concepts such as levels of evidence, validity, reliability, and transferability.
2) Critical appraisal involves assessing a study's validity, rigor, and relevance through a structured process using checklists to evaluate aspects like research design, sample size, randomization, and potential for bias.
3) Statistical measures like p-values, confidence intervals, and effect sizes are important to consider, but clinical significance is also key when determining if results can be applied to practice.
P-values the gold measure of statistical validity are not as reliable as many...David Pratap
This is an article that appeared in the NATURE as News Feature dated 12-February-2014. This article was presented in the journal club at Oman Medical College , Bowshar Campus on December, 17, 2015. This article was presented by Pratap David , Biostatistics Lecturer.
David Moher - MedicReS World Congress 2012MedicReS
This document discusses sources of bias in medical research and means to assess bias. It acknowledges the Cochrane Collaboration's Bias Methods Group and provides an overview of the impact of bias. Sources of bias can occur in the production and dissemination of evidence, including reporting biases like publication bias. Meta-epidemiological studies have found empirical evidence of biases in randomized controlled trials. Methods have been developed to assess bias in primary studies. While registration of clinical trials and systematic review protocols are attempts to minimize bias, bias remains an issue and further efforts are still needed.
This document discusses different types of study designs used in medical research, including qualitative and quantitative methods. It covers observational studies like cohort and case-control studies, as well as experimental designs like randomized controlled trials. For each study type, it outlines their purpose, strengths, weaknesses and the types of research questions they can help answer. The goal is to help researchers choose the most appropriate design based on their specific research question and aims.
Zsolt Nagykaldi: Shifting the focus from disease to healthaimlabstanford
In this talk from Stanford Medicine X 2013, the University of Oklahoma's Dr. Zsolt Nagykaldi, PhD, discusses a paradigm shift at the heart of patient-centered care, from treating the unwell to maintaining the healthy.
The document discusses different types of epidemiological studies, including descriptive studies like case reports and case series that focus on person, place and time to create hypotheses. Analytical studies like case-control and cohort studies are used to test hypotheses by being either observational or interventional. Randomized controlled trials are the gold standard for comparing new interventions. Observational analytical studies include cross-sectional, cohort and case-control designs, while interventional analytical studies are clinical trials. The appropriate study design depends on the research goals and objectives.
Biochemical tests in clinical medicine lect1MUDASSAR ANWER
This document discusses biochemical tests in clinical medicine. It covers topics such as the role of clinical biochemistry laboratories in disease diagnosis and treatment monitoring, common analyses performed, and diseases investigated using these tests. It also addresses the uses of biochemical tests in diagnosis, screening, prognosis, and treatment, as well as factors that can affect test results and their interpretation.
This document discusses refractory dyslipoproteinemia, which refers to abnormal levels of lipids like cholesterol and triglycerides in the blood that are resistant to standard treatment approaches. It notes that refractory dyslipoproteinemia is challenging to manage and may require combination drug therapy or specialized treatments like LDL apheresis to effectively lower lipid levels and reduce cardiovascular risk. The document provides an overview of different lipid-lowering drug classes and combination strategies, as well as advanced treatment options like apheresis that can directly remove LDL cholesterol from the bloodstream.
This document discusses meta-analysis of ordinal data and some of the challenges involved. It notes that ordinal outcomes are common in Cochrane reviews of stroke interventions, but are typically analyzed as dichotomous or continuous data rather than using methods suited for ordinal scales. Dichotomizing or treating ordinal data as continuous can discard important information. The document recommends using proportional odds modeling for ordinal data, which makes no distributional assumptions and can provide a single odds ratio summarizing the treatment effect across the full ordinal scale. It provides examples of how this method can be applied and discusses some remaining challenges like assessing model assumptions.
Lessons learned in polygenic risk research | Grand Rapids, MI 2019Cecile Janssens
1. Fifteen years of polygenic risk research has shown that while polygenic risk scores can statistically significantly associate with complex diseases, the association does not necessarily predict disease risk well enough to be useful in healthcare.
2. To improve prediction, both data and models need to be improved to better reflect the underlying biological complexity. Additionally, predictive performance must be properly evaluated in the intended population and clinical utility determined.
3. Complex diseases are too complex and influenced by many factors to be perfectly predicted by current polygenic risk models. However, prediction does not need to be perfect to be useful, depending on the intended clinical application.
This document provides an introduction to biostatistics. It discusses key concepts like study populations, samples, systematic error, confounding, and true associations. It also outlines 9 common research questions and the PICOT framework for defining analytical studies. The document reviews variables, steps in data analysis including descriptive and inferential statistics, and statistical tests for different study designs. It discusses factors to consider when choosing a statistical test like the combination of variables, normality, number of groups, and independence. Finally, it briefly introduces concepts like type I error, power, p-values, and regression analysis.
This document provides an overview of different types of clinical study designs, including observational studies and experimental studies. It discusses the key aspects and objectives of different phases of clinical trials, including:
1. Phase I trials which aim to determine safety and maximum tolerated dose of new therapies.
2. Phase II trials which provide preliminary evidence of efficacy through surrogate endpoints and further evaluate safety.
3. Phase III trials which are comparative effectiveness trials that use clinical outcomes like survival to compare new treatments to standard of care through randomized controlled designs.
Study of the distribution and determinants of
health-related states or events in specified populations and the application of this study to control health problems.
John M. Last, Dictionary of Epidemiology
COMMON BIASES IN PHARMACOEPIDEMIOLOGICAL RESEARCH.pdfsamthamby79
Major biases in pharmacoepidemiological research include selection bias, information bias, and confounding. Selection bias can occur through referral bias, self-selection bias, prevalence study bias, and protopathic bias. Information bias includes non-differential and differential misclassification. Differential misclassification involves recall bias and detection bias. Confounding involves covariates related to disease development that may incorrectly attribute an effect to drug exposure. Accurately defining exposure timing and avoiding these biases is important for valid pharmacoepidemiological research.
basic lecture on literature types, importance of primary literature (papers,article) , study designs, and organization of scientific paper. p value and assessment of a new test is additional topic.
Similar to Statistical errors can cause deaths (20)
These lecture slides, by Dr Sidra Arshad, offer a simplified look into the mechanisms involved in the regulation of respiration:
Learning objectives:
1. Describe the organisation of respiratory center
2. Describe the nervous control of inspiration and respiratory rhythm
3. Describe the functions of the dorsal and respiratory groups of neurons
4. Describe the influences of the Pneumotaxic and Apneustic centers
5. Explain the role of Hering-Breur inflation reflex in regulation of inspiration
6. Explain the role of central chemoreceptors in regulation of respiration
7. Explain the role of peripheral chemoreceptors in regulation of respiration
8. Explain the regulation of respiration during exercise
9. Integrate the respiratory regulatory mechanisms
10. Describe the Cheyne-Stokes breathing
Study Resources:
1. Chapter 42, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 36, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 13, Human Physiology by Lauralee Sherwood, 9th edition
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
Does Over-Masturbation Contribute to Chronic Prostatitis.pptxwalterHu5
In some case, your chronic prostatitis may be related to over-masturbation. Generally, natural medicine Diuretic and Anti-inflammatory Pill can help mee get a cure.
8 Surprising Reasons To Meditate 40 Minutes A Day That Can Change Your Life.pptxHolistified Wellness
We’re talking about Vedic Meditation, a form of meditation that has been around for at least 5,000 years. Back then, the people who lived in the Indus Valley, now known as India and Pakistan, practised meditation as a fundamental part of daily life. This knowledge that has given us yoga and Ayurveda, was known as Veda, hence the name Vedic. And though there are some written records, the practice has been passed down verbally from generation to generation.
Our backs are like superheroes, holding us up and helping us move around. But sometimes, even superheroes can get hurt. That’s where slip discs come in.
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...Oleg Kshivets
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
Osteoporosis - Definition , Evaluation and Management .pdfJim Jacob Roy
Osteoporosis is an increasing cause of morbidity among the elderly.
In this document , a brief outline of osteoporosis is given , including the risk factors of osteoporosis fractures , the indications for testing bone mineral density and the management of osteoporosis
2. Medical Errors
• Surgeon is trained for years but is held
responsible for just one death on table
• Physicians are punished for wrong
diagnosis or wrong treatment in just one
case
3. Statistical Errors – 1
• Wrong statistical methods can lead to
wrong conclusions
• Use of wrong results on a large section of
upcoming patients can kill many or
jeopardise their health but none is
punished
• Ineffective treatment is widely used
(killing many) and effective treatment is
missed (killed, but could have been
saved)
4. Statistical Errors – 2
• Results wrong by just 1%, when used on
millions, can threaten life and health of
many
• We need to be extra careful in our
statistical help to medical research
5. Funny Examples
• Almost all of us have more legs than the
world average
• Head in an oven and leg in a freezer, the
person is comfortable on AVERAGE
• In a trial on two persons, one cured, the
other didn’t. The efficacy is 50%.
• Duration of hospital stay for 5 patients is
(days) 3, 5, 41, 6, 5. The mean is 12 days
and the SD is 16.25 days.
6. Real Examples – 1
• Mean survival period of patients with
prostate cancer is 4 years and of lung
cancer is 12 years (age, treatment)
• Area under the concentration curves –
same area but different curves. Same for
ROC curves
7. Real Examples – 2
Response Rate in Mild and Severe Hyperthyroid Cases
Group
Number
of Subjects
Number
Responded
Response
Rate (%)
I. Treatment
group
40 80.0
Mild 86.7
Severe 60.0
II. Control
group
40 62.5
Mild 87.5
Severe 56.2
Response rate nearly same in mild and severe cases
but different overall??
8. Real Examples – 2 contd.
• Severe cases more in control group
Response Rate in Mild and Severe Hyperthyroid Cases
Group
Number
of Subjects
Number
Responded
Response Rate
(%)
I. Treatment
group
40 32 80.0
Mild 30 26 86.7
Severe 10 6 60.0
II. Control
group
40 25 62.5
Mild 8 7 87.5
Severe 32 18 56.2
9. Real Examples – 3
• Mean vs. Proportion: Iron supplementation
Rise in Hb level(g/dL)
0.4, 0.7, -0.9, 0.3, 0.1, 0.5, 0.9, 0.2
Mean rise = 0.275 g/dL (P > 0.05, NS)
7 out of 8 show rise: P(x ≥ 7) = 0.035 Sig.
• One outlier can yield
a significant relationship
10. Problems with Sample
• Biased: Survivors, Volunteers, Clinic
subjects
• Size: Too small – medically significant
effect missed, Too big – overpowered,
trivial effect significant
• Selection: Random – rarely adopted,
Nonrandom – statistical methods not
applicable
• Informed consent, inclusion/exclusion
criteria
11. Problems with Data
• Errors in elicitation (interview),
recording, suspicious lab. results
• Missing values, incomplete info, dropouts
• Outliers
• Correct assessment (pain, stress/anxiety,
family support) – nonavailabilty of
appropriate scales
• Data manipulation
12. Problems with Analysis – 1
• Mean or proportion, mean or median
• Sensitivity or predictivity
• Looking for linearity
• Ignoring assumptions (Gaussian,
independence, homoscedasticity)
• Confounding, multicollinearity
13. Problems with Analysis – 2
• Categories of continuous variables
• Cherry picking variables and statistical
methods
• Forgetting baseline values
• Analysis done by semi-killed
professionals using software (everyone is
a statistician)
• Statisticians’ complicity
14. Problems with P-values
• Multiple P-values, multiple comparisons
• Accumulation of Type-I error
• Data dredging (torture till confess)
• Accepting a null
• Null not medically significant effect
• Probability statement –results remain inexact
• P-values are only for sampling fluctuations but
generally incorporate chance of errors due to
faulty design and faulty data by default
15. Problems with Interpretation
• Over-dependence on P-values
• Data skills not as much widely available
as the data
• Ignoring biological plausibility,
corroborative evidence
• Medically significant effect
• Association/correlation as cause-effect
• Probabilities work in the long run and
may miserably fail in individual cases
16. Conclusion
• Medical biostatisticians too are in the
profession of saving lives and reduce
suffering
• Need to extremely cautious and
professional in analysis, interpretation
and advice