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International Journal of Environmental... Nov 2022COVID-19 is a public health emergency all around the world. Severe illness occurred in about 14% of patients and 5% of patients developed critical illness, but the... (Meta-Analysis)
Meta-Analysis
INTRODUCTION
COVID-19 is a public health emergency all around the world. Severe illness occurred in about 14% of patients and 5% of patients developed critical illness, but the prognosis for these patients remains unclear.
OBJECTIVE
To describe the prognosis in hospitalized adults with COVID-19.
METHODS
The MEDLINE, EMBASE, AMED, and COCHRANE databases were searched for studies published up to 28 June 2021 without language restrictions. Descriptors were related to "COVID-19" and "prognosis". Prospective inception cohort studies that assessed morbidity, mortality and recovery in hospitalized people over 18 years old with COVID-19 were included. Two independent reviewers selected eligible studies and extracted the available data. Acute respiratory distress syndrome (ARDS) and multiple organ failure (MOFS) were considered as outcomes for morbidity and discharge was considered for recovery. The Quality in Prognosis Studies (QUIPS) tool was used to assess risk of bias. Analyses were performed using Comprehensive Meta-Analysis (version 2.2.064).
RESULTS
We included 30 inception cohort studies investigating 13,717 people hospitalized with COVID-19 from different countries. The mean (SD) age was 60.90 (21.87) years, and there was high proportion of males (76.19%) and people with comorbidities (e.g., 49.44% with hypertension and 29.75% with diabetes). Findings suggested a high occurrence of morbidity, mainly related to ARDS. Morbidity rates varied across studies from 19% to 36% in hospital wards, and from 13% to 90% in Intensive Care Units-ICU. Mortality rates ranged from 4% to 38% in hospital wards and from 8% to 51% in ICU. Recovery rates ranged up to 94% and 65% in hospital wards and ICU, respectively. The included studies had high risk of bias in the confounding domain.
CONCLUSIONS
The prognosis of people hospitalized with COVID-19 is an issue for the public health system worldwide, with high morbidity and mortality rates, mainly in ICU and for patients with comorbidities. Its prognosis emphasizes the need for appropriate prevention and management strategies.
Topics: Male; Adult; Humans; Middle Aged; Adolescent; COVID-19; SARS-CoV-2; Prospective Studies; Respiratory Distress Syndrome; Intensive Care Units
PubMed: 36361488
DOI: 10.3390/ijerph192114609 -
Journal of Medical Virology Jan 2023The postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC), also known as post-acute coronavirus disease 19 (COVID-19) or... (Review)
Review
The postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC), also known as post-acute coronavirus disease 19 (COVID-19) or the long COVID syndrome (long COVID) is an emerging public health concern. A substantial proportion of individuals may remain symptomatic months after initial recovery. An updated review of published and ongoing trials focusing on managing long COVID will help identify gaps and address the unmet needs of patients suffering from this potentially debilitating syndrome. A comprehensive literature search was conducted on the international databases and clinical trial registries from inception to 31 July 2022. This review included 6 published trials and 54 trial registration records. There is significant heterogeneity in the characterization of long COVID and ascertainment of primary outcomes. Most of the trials are focused on individual symptoms of long COVID or isolated organ dysfunction, classified according to cardiovascular, respiratory and functional capacity, neurological and psychological, fatigue, and olfactory dysfunction. Most of the interventions are related to the mechanisms causing the individual symptoms. Although the six published trials showed significant improvement in the symptoms or organ dysfunction studied, these initial studies lack internal and external validity limiting the generalizability. This review provides an update of the pharmacological agents that could be used to treat long COVID. Further standardization of the diagnostic criteria, inclusion of participants with concomitant chronic cardiometabolic diseases and standardization of outcomes will be essential in future clinical trials.
Topics: Humans; COVID-19; SARS-CoV-2; Post-Acute COVID-19 Syndrome; Multiple Organ Failure
PubMed: 36349400
DOI: 10.1002/jmv.28289 -
The Cochrane Database of Systematic... Feb 2022Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with ongoing transmission (WHO 2020). The World Health Organization (WHO) estimated that, in 2019, approximately 229 million cases of malaria occurred worldwide, with 94% occurring in the WHO's African region (WHO 2020). Of these malaria cases, an estimated 409,000 deaths occurred globally, with 67% occurring in children under five years of age (WHO 2020). Malaria also negatively impacts the health of women during pregnancy, childbirth, and the postnatal period (WHO 2020). Sulfadoxine/pyrimethamine (SP), an antifolate antimalarial, has been widely used across sub-Saharan Africa as the first-line treatment for uncomplicated malaria since it was first introduced in Malawi in 1993 (Filler 2006). Due to increasing resistance to SP, in 2000 the WHO recommended that one of several artemisinin-based combination therapies (ACTs) be used instead of SP for the treatment of uncomplicated malaria caused by Plasmodium falciparum (Global Partnership to Roll Back Malaria 2001). However, despite these recommendations, SP continues to be advised for intermittent preventive treatment in pregnancy (IPTp) and intermittent preventive treatment in infants (IPTi), whether the person has malaria or not (WHO 2013). Description of the intervention Folate (vitamin B9) includes both naturally occurring folates and folic acid, the fully oxidized monoglutamic form of the vitamin, used in dietary supplements and fortified food. Folate deficiency (e.g. red blood cell (RBC) folate concentrations of less than 305 nanomoles per litre (nmol/L); serum or plasma concentrations of less than 7 nmol/L) is common in many parts of the world and often presents as megaloblastic anaemia, resulting from inadequate intake, increased requirements, reduced absorption, or abnormal metabolism of folate (Bailey 2015; WHO 2015a). Pregnant women have greater folate requirements; inadequate folate intake (evidenced by RBC folate concentrations of less than 400 nanograms per millilitre (ng/mL), or 906 nmol/L) prior to and during the first month of pregnancy increases the risk of neural tube defects, preterm delivery, low birthweight, and fetal growth restriction (Bourassa 2019). The WHO recommends that all women who are trying to conceive consume 400 micrograms (µg) of folic acid daily from the time they begin trying to conceive through to 12 weeks of gestation (WHO 2017). In 2015, the WHO added the dosage of 0.4 mg of folic acid to the essential drug list (WHO 2015c). Alongside daily oral iron (30 mg to 60 mg elemental iron), folic acid supplementation is recommended for pregnant women to prevent neural tube defects, maternal anaemia, puerperal sepsis, low birthweight, and preterm birth in settings where anaemia in pregnant women is a severe public health problem (i.e. where at least 40% of pregnant women have a blood haemoglobin (Hb) concentration of less than 110 g/L). How the intervention might work Potential interactions between folate status and malaria infection The malaria parasite requires folate for survival and growth; this has led to the hypothesis that folate status may influence malaria risk and severity. In rhesus monkeys, folate deficiency has been found to be protective against Plasmodium cynomolgi malaria infection, compared to folate-replete animals (Metz 2007). Alternatively, malaria may induce or exacerbate folate deficiency due to increased folate utilization from haemolysis and fever. Further, folate status measured via RBC folate is not an appropriate biomarker of folate status in malaria-infected individuals since RBC folate values in these individuals are indicative of both the person's stores and the parasite's folate synthesis. A study in Nigeria found that children with malaria infection had significantly higher RBC folate concentrations compared to children without malaria infection, but plasma folate levels were similar (Bradley-Moore 1985). Why it is important to do this review The malaria parasite needs folate for survival and growth in humans. For individuals, adequate folate levels are critical for health and well-being, and for the prevention of anaemia and neural tube defects. Many countries rely on folic acid supplementation to ensure adequate folate status in at-risk populations. Different formulations for folic acid supplements are available in many international settings, with dosages ranging from 400 µg to 5 mg. Evaluating folic acid dosage levels used in supplementation efforts may increase public health understanding of its potential impacts on malaria risk and severity and on treatment failures. Examining folic acid interactions with antifolate antimalarial medications and with malaria disease progression may help countries in malaria-endemic areas determine what are the most appropriate lower dose folic acid formulations for at-risk populations. The WHO has highlighted the limited evidence available and has indicated the need for further research on biomarkers of folate status, particularly interactions between RBC folate concentrations and tuberculosis, human immunodeficiency virus (HIV), and antifolate antimalarial drugs (WHO 2015b). An earlier Cochrane Review assessed the effects and safety of iron supplementation, with or without folic acid, in children living in hyperendemic or holoendemic malaria areas; it demonstrated that iron supplementation did not increase the risk of malaria, as indicated by fever and the presence of parasites in the blood (Neuberger 2016). Further, this review stated that folic acid may interfere with the efficacy of SP; however, the efficacy and safety of folic acid supplementation on these outcomes has not been established. This review will provide evidence on the effectiveness of daily folic acid supplementation in healthy and malaria-infected individuals living in malaria-endemic areas. Additionally, it will contribute to achieving both the WHO Global Technical Strategy for Malaria 2016-2030 (WHO 2015d), and United Nations Sustainable Development Goal 3 (to ensure healthy lives and to promote well-being for all of all ages) (United Nations 2021), and evaluating whether the potential effects of folic acid supplementation, at different doses (e.g. 0.4 mg, 1 mg, 5 mg daily), interferes with the effect of drugs used for prevention or treatment of malaria.
OBJECTIVES
To examine the effects of folic acid supplementation, at various doses, on malaria susceptibility (risk of infection) and severity among people living in areas with various degrees of malaria endemicity. We will examine the interaction between folic acid supplements and antifolate antimalarial drugs. Specifically, we will aim to answer the following. Among uninfected people living in malaria endemic areas, who are taking or not taking antifolate antimalarials for malaria prophylaxis, does taking a folic acid-containing supplement increase susceptibility to or severity of malaria infection? Among people with malaria infection who are being treated with antifolate antimalarials, does folic acid supplementation increase the risk of treatment failure?
METHODS
Criteria for considering studies for this review Types of studies Inclusion criteria Randomized controlled trials (RCTs) Quasi-RCTs with randomization at the individual or cluster level conducted in malaria-endemic areas (areas with ongoing, local malaria transmission, including areas approaching elimination, as listed in the World Malaria Report 2020) (WHO 2020) Exclusion criteria Ecological studies Observational studies In vivo/in vitro studies Economic studies Systematic literature reviews and meta-analyses (relevant systematic literature reviews and meta-analyses will be excluded but flagged for grey literature screening) Types of participants Inclusion criteria Individuals of any age or gender, living in a malaria endemic area, who are taking antifolate antimalarial medications (including but not limited to sulfadoxine/pyrimethamine (SP), pyrimethamine-dapsone, pyrimethamine, chloroquine and proguanil, cotrimoxazole) for the prevention or treatment of malaria (studies will be included if more than 70% of the participants live in malaria-endemic regions) Studies assessing participants with or without anaemia and with or without malaria parasitaemia at baseline will be included Exclusion criteria Individuals not taking antifolate antimalarial medications for prevention or treatment of malaria Individuals living in non-malaria endemic areas Types of interventions Inclusion criteria Folic acid supplementation Form: in tablet, capsule, dispersible tablet at any dose, during administration, or periodically Timing: during, before, or after (within a period of four to six weeks) administration of antifolate antimalarials Iron-folic acid supplementation Folic acid supplementation in combination with co-interventions that are identical between the intervention and control groups. Co-interventions include: anthelminthic treatment; multivitamin or multiple micronutrient supplementation; 5-methyltetrahydrofolate supplementation. Exclusion criteria Folate through folate-fortified water Folic acid administered through large-scale fortification of rice, wheat, or maize Comparators Placebo No treatment No folic acid/different doses of folic acid Iron Types of outcome measures Primary outcomes Uncomplicated malaria (defined as a history of fever with parasitological confirmation; acceptable parasitological confirmation will include rapid diagnostic tests (RDTs), malaria smears, or nucleic acid detection (i.e. polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), etc.)) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Severe malaria (defined as any case with cerebral malaria or acute P. falciparum malaria, with signs of severity or evidence of vital organ dysfunction, or both) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Parasite clearance (any Plasmodium species), defined as the time it takes for a patient who tests positive at enrolment and is treated to become smear-negative or PCR negative. This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Treatment failure (defined as the inability to clear malaria parasitaemia or prevent recrudescence after administration of antimalarial medicine, regardless of whether clinical symptoms are resolved) (WHO 2019). This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Secondary outcomes Duration of parasitaemia Parasite density Haemoglobin (Hb) concentrations (g/L) Anaemia: severe anaemia (defined as Hb less than 70 g/L in pregnant women and children aged six to 59 months; and Hb less than 80 g/L in other populations); moderate anaemia (defined as Hb less than 100 g/L in pregnant women and children aged six to 59 months; and less than 110 g/L in others) Death from any cause Among pregnant women: stillbirth (at less than 28 weeks gestation); low birthweight (less than 2500 g); active placental malaria (defined as Plasmodium detected in placental blood by smear or PCR, or by Plasmodium detected on impression smear or placental histology). Search methods for identification of studies A search will be conducted to identify completed and ongoing studies, without date or language restrictions. Electronic searches A search strategy will be designed to include the appropriate subject headings and text word terms related to each intervention of interest and study design of interest (see Appendix 1). Searches will be broken down by these two criteria (intervention of interest and study design of interest) to allow for ease of prioritization, if necessary. The study design filters recommended by the Scottish Intercollegiate Guidelines Network (SIGN), and those designed by Cochrane for identifying clinical trials for MEDLINE and Embase, will be used (SIGN 2020). There will be no date or language restrictions. Non-English articles identified for inclusion will be translated into English. If translations are not possible, advice will be requested from the Cochrane Infectious Diseases Group and the record will be stored in the "Awaiting assessment" section of the review until a translation is available. The following electronic databases will be searched for primary studies. Cochrane Central Register of Controlled Trials. Cumulative Index to Nursing and Allied Health Literature (CINAHL). Embase. MEDLINE. Scopus. Web of Science (both the Social Science Citation Index and the Science Citation Index). We will conduct manual searches of ClinicalTrials.gov, the International Clinical Trials Registry Platform (ICTRP), and the United Nations Children's Fund (UNICEF) Evaluation and Research Database (ERD), in order to identify relevant ongoing or planned trials, abstracts, and full-text reports of evaluations, studies, and surveys related to programmes on folic acid supplementation in malaria-endemic areas. Additionally, manual searches of grey literature to identify RCTs that have not yet been published but are potentially eligible for inclusion will be conducted in the following sources. Global Index Medicus (GIM). African Index Medicus (AIM). Index Medicus for the Eastern Mediterranean Region (IMEMR). Latin American & Caribbean Health Sciences Literature (LILACS). Pan American Health Organization (PAHO). Western Pacific Region Index Medicus (WPRO). Index Medicus for the South-East Asian Region (IMSEAR). The Spanish Bibliographic Index in Health Sciences (IBECS) (ibecs.isciii.es/). Indian Journal of Medical Research (IJMR) (journals.lww.com/ijmr/pages/default.aspx). Native Health Database (nativehealthdatabase.net/). Scielo (www.scielo.br/). Searching other resources Handsearches of the five journals with the highest number of included studies in the last 12 months will be conducted to capture any relevant articles that may not have been indexed in the databases at the time of the search. We will contact the authors of included studies and will check reference lists of included papers for the identification of additional records. For assistance in identifying ongoing or unpublished studies, we will contact the Division of Nutrition, Physical Activity, and Obesity (DNPAO) and the Division of Parasitic Diseases and Malaria (DPDM) of the CDC, the United Nations World Food Programme (WFP), Nutrition International (NI), Global Alliance for Improved Nutrition (GAIN), and Hellen Keller International (HKI). Data collection and analysis Selection of studies Two review authors will independently screen the titles and abstracts of articles retrieved by each search to assess eligibility, as determined by the inclusion and exclusion criteria. Studies deemed eligible for inclusion by both review authors in the abstract screening phase will advance to the full-text screening phase, and full-text copies of all eligible papers will be retrieved. If full articles cannot be obtained, we will attempt to contact the authors to obtain further details of the studies. If such information is not obtained, we will classify the study as "awaiting assessment" until further information is published or made available to us. The same two review authors will independently assess the eligibility of full-text articles for inclusion in the systematic review. If any discrepancies occur between the studies selected by the two review authors, a third review author will provide arbitration. Each trial will be scrutinized to identify multiple publications from the same data set, and the justification for excluded trials will be documented. A PRISMA flow diagram of the study selection process will be presented to provide information on the number of records identified in the literature searches, the number of studies included and excluded, and the reasons for exclusion (Moher 2009). The list of excluded studies, along with their reasons for exclusion at the full-text screening phase, will also be created. Data extraction and management Two review authors will independently extract data for the final list of included studies using a standardized data specification form. Discrepancies observed between the data extracted by the two authors will be resolved by involving a third review author and reaching a consensus. Information will be extracted on study design components, baseline participant characteristics, intervention characteristics, and outcomes. For individually randomized trials, we will record the number of participants experiencing the event and the number analyzed in each treatment group or the effect estimate reported (e.g. risk ratio (RR)) for dichotomous outcome measures. For count data, we will record the number of events and the number of person-months of follow-up in each group. If the number of person-months is not reported, the product of the duration of follow-up and the number of children evaluated will be used to estimate this figure. We will calculate the rate ratio and standard error (SE) for each study. Zero events will be replaced by 0.5. We will extract both adjusted and unadjusted covariate incidence rate ratios if they are reported in the original studies. For continuous data, we will extract means (arithmetic or geometric) and a measure of variance (standard deviation (SD), SE, or confidence interval (CI)), percentage or mean change from baseline, and the numbers analyzed in each group. SDs will be computed from SEs or 95% CIs, assuming a normal distribution of the values. Haemoglobin values in g/dL will be calculated by multiplying haematocrit or packed cell volume values by 0.34, and studies reporting haemoglobin values in g/dL will be converted to g/L. In cluster-randomized trials, we will record the unit of randomization (e.g. household, compound, sector, or village), the number of clusters in the trial, and the average cluster size. The statistical methods used to analyze the trials will be documented, along with details describing whether these methods adjusted for clustering or other covariates. We plan to extract estimates of the intra-cluster correlation coefficient (ICC) for each outcome. Where results are adjusted for clustering, we will extract the treatment effect estimate and the SD or CI. If the results are not adjusted for clustering, we will extract the data reported. Assessment of risk of bias in included studies Two review authors (KSC, LFY) will independently assess the risk of bias for each included trial using the Cochrane 'Risk of bias 2' tool (RoB 2) for randomized studies (Sterne 2019). Judgements about the risk of bias of included studies will be made according to the recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). Disagreements will be resolved by discussion, or by involving a third review author. The interest of our review will be to assess the effect of assignment to the interventions at baseline. We will evaluate each primary outcome using the RoB2 tool. The five domains of the Cochrane RoB2 tool include the following. Bias arising from the randomization process. Bias due to deviations from intended interventions. Bias due to missing outcome data. Bias in measurement of the outcome. Bias in selection of the reported result. Each domain of the RoB2 tool comprises the following. A series of 'signalling' questions. A judgement about the risk of bias for the domain, facilitated by an algorithm that maps responses to the signalling questions to a proposed judgement. Free-text boxes to justify responses to the signalling questions and 'Risk of bias' judgements. An option to predict (and explain) the likely direction of bias. Responses to signalling questions elicit information relevant to an assessment of the risk of bias. These response options are as follows. Yes (may indicate either low or high risk of bias, depending on the most natural way to ask the question). Probably yes. Probably no. No. No information (may indicate no evidence of that problem or an absence of information leading to concerns about there being a problem). Based on the answer to the signalling question, a 'Risk of bias' judgement is assigned to each domain. These judgements include one of the following. High risk of bias Low risk of bias Some concerns To generate the risk of bias judgement for each domain in the randomized studies, we will use the Excel template, available at www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2. This file will be stored on a scientific data website, available to readers. Risk of bias in cluster randomized controlled trials For the cluster randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 1b (bias arising from the timing of identification or recruitment of participants) and its related signalling questions. To generate the risk of bias judgement for each domain in the cluster RCTs, we will use the Excel template available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-cluster-randomized-trials. This file will be stored on a scientific data website, available to readers. Risk of bias in cross-over randomized controlled trials For cross-over randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 2 (bias due to deviations from intended interventions), and Domain 3 (bias due to missing outcome data), and their respective signalling questions. To generate the risk of bias judgement for each domain in the cross-over RCTs, we will use the Excel template, available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-crossover-trials, for each risk of bias judgement of cross-over randomized studies. This file will be stored on a scientific data website, available to readers. Overall risk of bias The overall 'Risk of bias' judgement for each specific trial being assessed will be based on each domain-level judgement. The overall judgements include the following. Low risk of bias (the trial is judged to be at low risk of bias for all domains). Some concerns (the trial is judged to raise some concerns in at least one domain but is not judged to be at high risk of bias for any domain). High risk of bias (the trial is judged to be at high risk of bias in at least one domain, or is judged to have some concerns for multiple domains in a way that substantially lowers confidence in the result). The 'risk of bias' assessments will inform our GRADE evaluations of the certainty of evidence for our primary outcomes presented in the 'Summary of findings' tables and will also be used to inform the sensitivity analyses; (see Sensitivity analysis). If there is insufficient information in study reports to enable an assessment of the risk of bias, studies will be classified as "awaiting assessment" until further information is published or made available to us. Measures of treatment effect Dichotomous data For dichotomous data, we will present proportions and, for two-group comparisons, results as average RR or odds ratio (OR) with 95% CIs. Ordered categorical data Continuous data We will report results for continuous outcomes as the mean difference (MD) with 95% CIs, if outcomes are measured in the same way between trials. Where some studies have reported endpoint data and others have reported change-from-baseline data (with errors), we will combine these in the meta-analysis, if the outcomes were reported using the same scale. We will use the standardized mean difference (SMD), with 95% CIs, to combine trials that measured the same outcome but used different methods. If we do not find three or more studies for a pooled analysis, we will summarize the results in a narrative form. Unit of analysis issues Cluster-randomized trials We plan to combine results from both cluster-randomized and individually randomized studies, providing there is little heterogeneity between the studies. If the authors of cluster-randomized trials conducted their analyses at a different level from that of allocation, and they have not appropriately accounted for the cluster design in their analyses, we will calculate the trials' effective sample sizes to account for the effect of clustering in data. When one or more cluster-RCT reports RRs adjusted for clustering, we will compute cluster-adjusted SEs for the other trials. When none of the cluster-RCTs provide cluster-adjusted RRs, we will adjust the sample size for clustering. We will divide, by the estimated design effects (DE), the number of events and number evaluated for dichotomous outcomes and the number evaluated for continuous outcomes, where DE = 1 + ((average cluster size 1) * ICC). The derivation of the estimated ICCs and DEs will be reported. We will utilize the intra-cluster correlation coefficient (ICC), derived from the trial (if available), or from another source (e.g., using the ICCs derived from other, similar trials) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). If this approach is used, we will report it and undertake sensitivity analysis to investigate the effect of variations in ICC. Studies with more than two treatment groups If we identify studies with more than two intervention groups (multi-arm studies), where possible we will combine groups to create a single pair-wise comparison or use the methods set out in the Cochrane Handbook to avoid double counting study participants (Higgins 2021). For the subgroup analyses, when the control group was shared by two or more study arms, we will divide the control group (events and total population) over the number of relevant subgroups to avoid double counting the participants. Trials with several study arms can be included more than once for different comparisons. Cross-over trials From cross-over trials, we will consider the first period of measurement only and will analyze the results together with parallel-group studies. Multiple outcome events In several outcomes, a participant might experience more than one outcome event during the trial period. For all outcomes, we will extract the number of participants with at least one event. Dealing with missing data We will contact the trial authors if the available data are unclear, missing, or reported in a format that is different from the format needed. We aim to perform a 'per protocol' or 'as observed' analysis; otherwise, we will perform a complete case analysis. This means that for treatment failure, we will base the analyses on the participants who received treatment and the number of participants for which there was an inability to clear malarial parasitaemia or prevent recrudescence after administration of an antimalarial medicine reported in the studies. Assessment of heterogeneity Heterogeneity in the results of the trials will be assessed by visually examining the forest plot to detect non-overlapping CIs, using the Chi2 test of heterogeneity (where a P value of less than 0.1 indicates statistical significance) and the I2 statistic of inconsistency (with a value of greater than 50% denoting moderate levels of heterogeneity). When statistical heterogeneity is present, we will investigate the reasons for it, using subgroup analysis. Assessment of reporting biases We will construct a funnel plot to assess the effect of small studies for the main outcome (when including more than 10 trials). Data synthesis The primary analysis will include all eligible studies that provide data regardless of the overall risk of bias as assessed by the RoB2 tool. Analyses will be conducted using Review Manager 5.4 (Review Manager 2020). Cluster-RCTs will be included in the main analysis after adjustment for clustering (see the previous section on cluster-RCTs). The meta-analysis will be performed using the Mantel-Haenszel random-effects model or the generic inverse variance method (when adjustment for clustering is performed by adjusting SEs), as appropriate. Subgroup analysis and investigation of heterogeneity The overall risk of bias will not be used as the basis in conducting our subgroup analyses. However, where data are available, we plan to conduct the following subgroup analyses, independent of heterogeneity. Dose of folic acid supplementation: higher doses (4 mg or more, daily) versus lower doses (less than 4 mg, daily). Moderate-severe anaemia at baseline (mean haemoglobin of participants in a trial at baseline below 100 g/L for pregnant women and children aged six to 59 months, and below 110 g/L for other populations) versus normal at baseline (mean haemoglobin above 100 g/L for pregnant women and children aged six to 59 months, and above 110 g/L for other populations). Antimalarial drug resistance to parasite: known resistance versus no resistance versus unknown/mixed/unreported parasite resistance. Folate status at baseline: Deficient (e.g. RBC folate concentration of less than 305 nmol/L, or serum folate concentration of less than 7nmol/L) and Insufficient (e.g. RBC folate concentration from 305 to less than 906 nmol/L, or serum folate concentration from 7 to less than 25 nmol/L) versus Sufficient (e.g. RBC folate concentration above 906 nmol/L, or serum folate concentration above 25 nmol/L). Presence of anaemia at baseline: yes versus no. Mandatory fortification status: yes, versus no (voluntary or none). We will only use the primary outcomes in any subgroup analyses, and we will limit subgroup analyses to those outcomes for which three or more trials contributed data. Comparisons between subgroups will be performed using Review Manager 5.4 (Review Manager 2020). Sensitivity analysis We will perform a sensitivity analysis, using the risk of bias as a variable to explore the robustness of the findings in our primary outcomes. We will verify the behaviour of our estimators by adding and removing studies with a high risk of bias overall from the analysis. That is, studies with a low risk of bias versus studies with a high risk of bias. Summary of findings and assessment of the certainty of the evidence For the assessment across studies, we will use the GRADE approach, as outlined in (Schünemann 2021). We will use the five GRADE considerations (study limitations based on RoB2 judgements, consistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence as it relates to the studies which contribute data to the meta-analyses for the primary outcomes. The GRADEpro Guideline Development Tool (GRADEpro) will be used to import data from Review Manager 5.4 (Review Manager 2020) to create 'Summary of Findings' tables. The primary outcomes for the main comparison will be listed with estimates of relative effects, along with the number of participants and studies contributing data for those outcomes. These tables will provide outcome-specific information concerning the overall certainty of evidence from studies included in the comparison, the magnitude of the effect of the interventions examined, and the sum of available data on the outcomes we considered. We will include only primary outcomes in the summary of findings tables. For each individual outcome, two review authors (KSC, LFY) will independently assess the certainty of the evidence using the GRADE approach (Balshem 2011). For assessments of the overall certainty of evidence for each outcome that includes pooled data from included trials, we will downgrade the evidence from 'high certainty' by one level for serious (or by two for very serious) study limitations (risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates, or potential publication bias).
Topics: Child; Infant; Pregnancy; Infant, Newborn; Female; Humans; Child, Preschool; Antimalarials; Sulfadoxine; Pyrimethamine; Folic Acid Antagonists; Birth Weight; Parasitemia; Vitamins; Folic Acid; Anemia; Neural Tube Defects; Dietary Supplements; Iron; Recurrence
PubMed: 36321557
DOI: 10.1002/14651858.CD014217 -
International Journal of Molecular... Aug 2022Sepsis is a critical condition characterized by increased levels of pro-inflammatory cytokines and proliferating cells such as neutrophils and macrophages in response to... (Review)
Review
Sepsis is a critical condition characterized by increased levels of pro-inflammatory cytokines and proliferating cells such as neutrophils and macrophages in response to microbial pathogens. Such processes lead to an abnormal inflammatory response and multi-organ failure. MicroRNAs (miRNA) are single-stranded non-coding RNAs with the function of gene regulation. This means that miRNAs are involved in multiple intracellular pathways and thus contribute to or inhibit inflammation. As a result, their variable expression in different tissues and organs may play a key role in regulating the pathophysiological events of sepsis. Thanks to this property, miRNAs may serve as potential diagnostic and prognostic biomarkers in such life-threatening events. In this narrative review, we collect the results of recent studies on the expression of miRNAs in heart, blood, lung, liver, brain, and kidney during sepsis and the molecular processes in which they are involved. In reviewing the literature, we find at least 122 miRNAs and signaling pathways involved in sepsis-related organ dysfunction. This may help clinicians to detect, prevent, and treat sepsis-related organ failures early, although further studies are needed to deepen the knowledge of their potential contribution.
Topics: Gene Expression Regulation; Humans; Macrophages; MicroRNAs; Multiple Organ Failure; Sepsis
PubMed: 36012630
DOI: 10.3390/ijms23169354 -
Critical Care (London, England) Aug 2022Clinical research on nutritional and metabolic interventions in critically ill patients is heterogenous regarding time points, outcomes and measurement instruments used,...
Core outcome measures for clinical effectiveness trials of nutritional and metabolic interventions in critical illness: an international modified Delphi consensus study evaluation (CONCISE).
BACKGROUND
Clinical research on nutritional and metabolic interventions in critically ill patients is heterogenous regarding time points, outcomes and measurement instruments used, impeding intervention development and data syntheses, and ultimately worsening clinical outcomes. We aimed to identify and develop a set of core outcome domains and associated measurement instruments to include in all research in critically ill patients.
METHODS
An updated systematic review informed a two-stage modified Delphi consensus process (domains followed by instruments). Measurement instruments for domains considered 'essential' were taken through the second stage of the Delphi and a subsequent consensus meeting.
RESULTS
In total, 213 participants (41 patients/caregivers, 50 clinical researchers and 122 healthcare professionals) from 24 countries contributed. Consensus was reached on time points (30 and 90 days post-randomisation). Three domains were considered 'essential' at 30 days (survival, physical function and Infection) and five at 90 days (survival, physical function, activities of daily living, nutritional status and muscle/nerve function). Core 'essential' measurement instruments reached consensus for survival and activities of daily living, and 'recommended' measurement instruments for physical function, nutritional status and muscle/nerve function. No consensus was reached for a measurement instrument for Infection. Four further domains met criteria for 'recommended,' but not 'essential,' to measure at 30 days post-randomisation (organ dysfunction, muscle/nerve function, nutritional status and wound healing) and three at 90 days (frailty, body composition and organ dysfunction).
CONCLUSION
The CONCISE core outcome set is an internationally agreed minimum set of outcomes for use at 30 and 90 days post-randomisation, in nutritional and metabolic clinical research in critically ill adults.
Topics: Activities of Daily Living; Adult; Critical Illness; Delphi Technique; Humans; Multiple Organ Failure; Outcome Assessment, Health Care; Research Design; Treatment Outcome
PubMed: 35933433
DOI: 10.1186/s13054-022-04113-x -
Vaccines Jun 2022COVID-19, caused by SARS-CoV-2, is one of the longest viral pandemics in the history of mankind, which have caused millions of deaths globally and induced severe... (Review)
Review
COVID-19, caused by SARS-CoV-2, is one of the longest viral pandemics in the history of mankind, which have caused millions of deaths globally and induced severe deformities in the survivals. For instance, fibrosis and cavities in the infected lungs of COVID-19 are some of the complications observed in infected patients post COVID-19 recovery. These health abnormalities, including is multiple organ failure-the most striking pathological features of COVID-19-have been linked with diverse distribution of ACE2 receptor. Additionally, several health complications reports were reported after administration of COVID-19 vaccines in healthy individuals, but clinical or molecular pathways causing such complications are not yet studied in detail. Thus, the present systematic review established the comparison of health complication noted in vaccinated and non-vaccinated individuals (COVID-19 infected patients) to identify the association between vaccination and the multiorgan failure based on the data obtained from case studies, research articles, clinical trials/Cohort based studies and review articles published between 2020-2022. This review also includes the biological rationale behind the COVID-19 infection and its subsequent symptoms and effects including multiorgan failure. In addition, multisystem inflammatory syndrome (MIS) has been informed in individuals post vaccination that resulted in multiorgan failure but, no direct correlation of vaccination with MIS has been established. Similarly, hemophagocytic lymphohistiocytosis (HLH) also noted to cause multiorgan failure in some individuals following full vaccination. Furthermore, severe complications were recorded in elderly patients (+40 years of age), indicates that older age individuals are higher risk by COVID-19 and post vaccination, but available literature is not sufficient to comply with any conclusive statements on relationship between vaccination and multiorgan failure.
PubMed: 35891149
DOI: 10.3390/vaccines10070985 -
Annals of Medicine Dec 2022Critical illness may lead to activation of the sympathetic system. The sympathetic stimulation may be further increased by exogenous catecholamines, such as vasopressors... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Critical illness may lead to activation of the sympathetic system. The sympathetic stimulation may be further increased by exogenous catecholamines, such as vasopressors and inotropes. Excessive adrenergic stress has been associated with organ dysfunction and higher mortality. -Blockers may reduce the adrenergic burden, but they may also compromise perfusion to vital organs thus worsening organ dysfunction. To assess the effect of treatment with -blockers in critically ill adults, we conducted a systematic review and meta-analysis of randomized controlled trials.
MATERIALS AND METHODS
We conducted a search from three major databases: Ovid Medline, the Cochrane Central Register for Controlled Trials and Scopus database. Two independent reviewers screened, selected, and assessed the included articles according to prespecified eligibility criteria. We assessed risk of bias of eligible articles according to the Cochrane guidelines. Quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.
RESULTS
Sixteen randomized controlled trials comprising 2410 critically ill patients were included in the final review. A meta-analysis of 11 trials including 2103 patients showed a significant reduction in mortality in patients treated with -blockers compared to control (risk ratio 0.65, 95%CI 0.53-0.79; < .0001). There was no significant difference in mean arterial pressure or vasopressor load. Quality of life, biventricular ejection fraction, blood lactate levels, cardiac biomarkers and mitochondrial function could not be included in meta-analysis due to heterogenous reporting of outcomes.
CONCLUSIONS
In this systematic review we found that -blocker treatment reduced mortality in critical illness. Use of -blockers in critical illness thus appears safe after initial hemodynamic stabilization. High-quality RCT's are needed to answer the questions concerning optimal target group of patients, timing of -blocker treatment, choice of -blocker, and choice of physiological and hemodynamic parameters to target during -blocker treatment in critical illness.KEY MESSAGESA potential outcome benefit of -blocker treatment in critical illness exists according to the current review and meta-analysis. Administration of -blockers to resuscitated patients in the ICU seems safe in terms of hemodynamic stability and outcome, even during concomitant vasopressor administration. However, further studies, preferably large RCTs on -blocker treatment in the critically ill are needed to answer the questions concerning timing and choice of -blocker, patient selection, and optimal hemodynamic targets.
Topics: Adrenergic beta-Antagonists; Adult; Critical Illness; Humans; Multiple Organ Failure; Quality of Life; Randomized Controlled Trials as Topic; Respiration, Artificial
PubMed: 35838226
DOI: 10.1080/07853890.2022.2098376 -
Stem Cell Research & Therapy May 2022Intestinal ischemia-reperfusion injury (IRI) causes localized and distant tissue lesions. Multiple organ failure is a common complication of severe intestinal IRI,... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Intestinal ischemia-reperfusion injury (IRI) causes localized and distant tissue lesions. Multiple organ failure is a common complication of severe intestinal IRI, leading to its high rates of morbidity and mortality. Thus far, this is poorly treated, and there is an urgent need for new more efficacious treatments. This study evaluated the beneficial effects of mesenchymal stem cells (MSCs) therapy on intestinal IRI using many animal experiments.
METHODS
We conducted a comprehensive literature search from 4 databases: Pubmed, Embase, Cochrane library, and Web of science. Primary outcomes included the survival rate, Chiu's score, intestinal levels of IL-6, TNF-α and MDA, as well as serum levels of DAO, D-Lactate, and TNF-α. Statistical analysis was carried out using Review Manager 5.3.
RESULTS
It included Eighteen eligible researches in the final analysis. We demonstrated that survival rates in animals following intestinal IRI were higher with MSCs treatment compared to vehicle treatment. Besides, MSCs treatment attenuated intestinal injury caused by IRI, characterized by lower Chiu's score (- 1.96, 95% CI - 2.72 to - 1.19, P < 0.00001), less intestinal inflammation (IL-6 (- 2.73, 95% CI - 4.19 to - 1.27, P = 0.0002), TNF-α (- 3.00, 95% CI - 4.74 to - 1.26, P = 0.0007)) and oxidative stress (MDA (- 2.18, 95% CI - 3.17 to - 1.19, P < 0.0001)), and decreased serum levels of DAO (- 1.39, 95% CI - 2.07 to - 0.72, P < 0.0001), D-Lactate (- 1.54, 95% CI - 2.18 to - 0.90, P < 0.00001) and TNF-α (- 2.42, 95% CI - 3.45 to - 1.40, P < 0.00001). The possible mechanism for MSCs to treat intestinal IRI might be through reducing inflammation, alleviating oxidative stress, as well as inhibiting the apoptosis and pyroptosis of the intestinal epithelial cells.
CONCLUSIONS
Taken together, these studies revealed that MSCs as a promising new treatment for intestinal IRI, and the mechanism of which may be associated with inflammation, oxidative stress, apoptosis, and pyroptosis. However, further studies will be required to confirm these findings.
Topics: Animals; Inflammation; Interleukin-6; Lactates; Mesenchymal Stem Cells; Reperfusion Injury; Tumor Necrosis Factor-alpha
PubMed: 35619154
DOI: 10.1186/s13287-022-02896-y -
Computational and Mathematical Methods... 2022One of the leading causes of deaths around the globe is heart disease. Heart is an organ that is responsible for the supply of blood to each part of the body. Coronary...
Machine Learning-Based Automated Diagnostic Systems Developed for Heart Failure Prediction Using Different Types of Data Modalities: A Systematic Review and Future Directions.
One of the leading causes of deaths around the globe is heart disease. Heart is an organ that is responsible for the supply of blood to each part of the body. Coronary artery disease (CAD) and chronic heart failure (CHF) often lead to heart attack. Traditional medical procedures (angiography) for the diagnosis of heart disease have higher cost as well as serious health concerns. Therefore, researchers have developed various automated diagnostic systems based on machine learning (ML) and data mining techniques. ML-based automated diagnostic systems provide an affordable, efficient, and reliable solutions for heart disease detection. Various ML, data mining methods, and data modalities have been utilized in the past. Many previous review papers have presented systematic reviews based on one type of data modality. This study, therefore, targets systematic review of automated diagnosis for heart disease prediction based on different types of modalities, i.e., clinical feature-based data modality, images, and ECG. Moreover, this paper critically evaluates the previous methods and presents the limitations in these methods. Finally, the article provides some future research directions in the domain of automated heart disease detection based on machine learning and multiple of data modalities.
Topics: Algorithms; Arrhythmias, Cardiac; Computational Biology; Coronary Artery Disease; Data Mining; Databases, Factual; Diagnosis, Computer-Assisted; Electrocardiography; Heart Failure; Humans; Image Interpretation, Computer-Assisted; Machine Learning; Neural Networks, Computer
PubMed: 35154361
DOI: 10.1155/2022/9288452 -
Medicine Jan 2022The role of ambroxol hydrochloride combined with fiberoptic bronchoscopy in elderly patients with severe pneumonia remains unclear, we aimed to analyze this issue to... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The role of ambroxol hydrochloride combined with fiberoptic bronchoscopy in elderly patients with severe pneumonia remains unclear, we aimed to analyze this issue to provide evidences into the management of clinical pneumonia.
METHODS
We searched PubMed et al databases up to October 20, 2021 for the randomized controlled trials on the application of ambroxol hydrochloride combined with fiberoptic bronchoscopy in elderly patients with severe pneumonia. Related outcomes were extracted and analyzed. Review Manager 5.3 software was used for data analysis.
RESULTS
A total of 13 randomized controlled trials involving 1317 elderly patients (559 cases in the ambroxol hydrochloride + fiberoptic bronchoscopy group and 658 cases in the fiberoptic bronchoscopy group) with pneumonia were included. Meta-analyses indicated that the blood oxygen partial pressure [mean difference (MD) = 5.75, 95% confidence interval (CI) (3.80, 7.70)], blood oxygen saturation [MD = 6.43, 95% CI (4.39, 8.48)], oxygenation index [MD = 26.75, 95% CI (14.61, 38.89)] of experimental group was significantly higher than that of control group (all P < .001), the incidence of multiple organ failure [odds ratio = 0.42, 95% CI (0.31, 0.56), P < .001], mortality on day 28 [odds ratio = 0.44, 95% CI (0.33, 0.59)] of experimental group was significantly less than that of control group (all P < .001).
CONCLUSIONS
The high-dose ambroxol hydrochloride combined with fiberoptic bronchoscopy is beneficial to improve the patient's blood gas indicators, and reduce mortality in elderly patients with severe pneumonia.
Topics: Aged; Ambroxol; Blood Gas Analysis; Bronchi; Bronchoscopy; Expectorants; Humans; Pneumonia; Treatment Outcome
PubMed: 35089191
DOI: 10.1097/MD.0000000000028535