A comparative study between magnesium sulphate and dexmedetomidine for deliberate hypotension during middle ear surgery

AbstractBackgroundThis study was designed to compare magnesium sulphate with dexmedetomidine, regarding their efficiency in inducing deliberate hypotension and providing a better surgical field exposure during middle ear surgery. It also compared the influence of their use on postoperative pain and recovery time.MethodsEighty-eight adult patients undergoing middle ear surgery were included. Patients were randomly divided into two equal groups. Patients were assigned to receive either magnesium sulphate (M group) or dexmedetomidine (D group). Anaesthesia was induced by propofol 2mg/kg iv and fentanyl 1μg/kg. Patients in the M group received an iv bolus of magnesium sulphate 50mg/kg in a total of 100ml saline over 10min followed by infusion of 15mg/kg/h until the end of surgery. Similarly, patients in the D group received dexmedetomidine 1μg/kg over 10min followed by 0.4–0.8μg/kg/h until the end of operation. The target MAP during operation was between 60 and 70mmHg. The surgeon who was blinded of the selected hypotensive agent was asked to assess the quality of the surgical field. In the postanaesthesia care unit (PACU), postoperative pain was assessed and recovery time was recorded.ResultsBoth study drugs succeeded to reach the target MAP. The quality of the surgical field was not different between the two groups. Postoperative pain was not different between the two group and only eight patients in the M group and seven patients in the D group required analgesics. Recovery time was significantly longer for the patients in group D (p<0.05).ConclusionWe concluded that both magnesium sulphate and dexmedetomidine successfully induced deliberate hypotension in patients undergoing middle ear surgery but magnesium sulphate was associated with shorter recovery time and earlier discharge from the PACU

Hearing Loss After COVID-19 Vaccines: A Systematic Review and Meta-Analysis

ABSTRACT. Background: Hearing loss is generally classified as conductive hearing loss (CHL) and sensory-neural hearing loss (SNHL). It has been reported that COVID-19 infection may affect the vestibular-hearing system causing dizziness, tinnitus, vertigo, and hearing impairment. However, other studies reported that COVID-19 did not lead to significant hearing impairment. Many studies in the literature have reported hearing loss as a complication of COVID-19 vaccines. However, no systematic review or meta-analysis summarizes the literature on this topic. &nbsp; Method: We performed a comprehensive search for the following databases: PubMed, Cochrane (Medline), Web of Science, and Scopus. All studies published in English till October 2022 were included. These include case reports, case series, prospective and retrospective observational studies, and clinical trials reporting hearing loss following COVID-19 vaccines. Newcastle Ottawa scale (NOS) was used to assess the risk of bias for observational studies. NIH tools were used for non-controlled before and after clinical trials and case reports and case series. A third author solved any disagreements. We analyzed the data using SPSS Software version 26. &nbsp; Results: A total of 630 patients were identified, with a mean age of 57.3 that ranged from 15 to 93 years old. The majority of the patients were females, 339 (53.8%). In addition, 328 out of 609 vaccinated patients took the Pfizer-BioNTech BNT162b2 vaccine, while 242 (40%) took the Moderna COVID-19 vaccine. The mean time from vaccination to hearing impairment was 6.2, ranging from a few hours to one month after the last dose. Most patients reported unilateral sensorineural hearing loss post-vaccination 593 (94.1%). In order to report the fate of cases, a follow-up was initiated with a mean of 15.6 and a range of 2 to 63 days after the initiation of the treatment. A total of 20 patients were fully recovered, and 11 reported no response. Three out of 328 patients who took the Pfizer-BioNTech BNT162b2 vaccine fully recovered, while five reported partial recovery. According to the chi-squared test, there is a statistically significant difference between patients in terms of fate and the type of COVID-19 vaccination (P-value = 0.001) while reporting no significant difference in dose number prior to the onset of the symptoms (P-value = 0.65) and gender (P-value = 0.4). The ANOVA test was conducted to compare vaccine types and the number of doses in terms of mean time from vaccination to hearing impairment onset. The results found a significant difference between vaccine types (P-value &lt; 0.000) while showing no significance in terms of the number of doses prior to the onset (P-value = 0.6). &nbsp; Conclusion: There is a statistically significant difference between patients in terms of fate and the type of COVID-19 vaccination while reporting no significant difference in dose number prior to the onset of the symptoms and gender. Further, we concluded that there is a significant difference between vaccine types while showing no significance in terms of the number of doses prior to the onset

Availability of PEth testing is associated with reduced eligibility for liver transplant among patients with alcohol-related liver disease

BACKGROUND: Serum phosphatidylethanol (PEth) is a highly sensitive test to detect alcohol use. We evaluated whether the availability of PEth testing impacted rates of liver transplant evaluation terminations and delistings. METHODS: Medical record data were collected for patients who initiated transplant evaluation due to alcohol-related liver disease in the pre-PEth (2017) or PEth (2019) eras. Inverse probability weighting (IPW) was used to balance baseline patient characteristics. Outcomes included termination of evaluation or delisting due to alcohol use; patients were censored at receipt of transplant; death was considered a competing risk. The Fine-Gray method was performed to determine whether PEth testing affected risk of evaluation termination/ delisting due to alcohol use. RESULTS: Three hundred and seventy-five patients with alcohol-related indications for transplant (157 in 2017; 210 in 2019) were included. The final IPW-adjusted model for the composite outcome of terminations/delisting due to alcohol use retained two significant variables (P \u3c .05): PEth era and BMI category. Patients evaluated during the PEth era were almost three times more likely to experience an alcohol-related termination/delisting than those in the pre-PEth era (sHR = 2.86; 95%CI 1.67-4.97). CONCLUSION: We found that availability of PEth testing at our institution was associated with a higher rate of exclusion of patients from eligibility for liver transplant. Use of PEth testing has significant potential to inform decisions regarding transplant candidacy for patients with alcohol-related liver disease

Health-related quality of life following TAVI or cardiac surgery in patients at intermediate and low risk: a systematic review and meta-analysis.

Recent randomised trials have shown that clinical outcomes with transcatheter aortic valve implantation (TAVI) are non-inferior to surgical aortic valve replacement (SAVR) in patients with symptomatic aortic stenosis at intermediate to low risk. Health-related quality of life (HrQoL) outcomes in these patient groups remain uncertain. A systematic search of the literature was conducted that included nine trials and 11,295 patients. Kansas City Cardiomyopathy Questionnaire (KCCQ), a heart-failure-specific measure and EuroQol-5D (EQ-5D) (a generic health status tool) changes were the primary outcomes. New York Heart Association (NYHA) classification was the secondary outcome. Improvement in KCCQ scores was greater with TAVI (mean difference (MD)=13.56, 95% confidence interval (CI) 11.67-15.46, p<0.001) at 1 month, as was the improvement in EQ-5D (MD=0.07, 95% CI 0.05-0.08, p<0.001). There was no difference in KCCQ (MD=1.05, 95% CI -0.11 to 2.21, p=0.08) or EQ-5D (MD=-0.01, 95% CI -0.03 to 0.01), p=0.37) at 12 months. NYHA functional class 3/4 was lower in patients undergoing TAVI at 1 month (MD=0.51, 95% CI 0.34-0.78, p=0.002), but there was no difference at 12 months (MD=1.10; 95% CI 0.87-1.38, p=0.43). Overall, TAVI offers early benefit in HRQoL outcomes compared with SAVR, but they are equivalent at 12 months

Association of serum leptin and ghrelin levels with smoking status on body weight: a systematic review and meta-analysis

Background and aimsSmoking cigarettes is a major global health problem that affects appetite and weight. The aim of this systematic review was to determine how smoking affected plasma leptin and ghrelin levels.MethodsA comprehensive search of PubMed, Scopus, Web of Science, and Ovid was conducted using a well-established methodology to gather all related publications.ResultsA total of 40 studies were included in the analysis of 11,336 patients. The overall effect showed a with a mean difference (MD) of −1.92[95%CI; −2.63: −1.20] and p = 0.00001. Subgroup analysis by study design revealed significant differences as well, but with high heterogeneity within the subgroups (I2 of 82.3%). Subgroup by sex showed that there was a significant difference in mean difference between the smoking and non-smoking groups for males (MD = −5.75[95% CI; −8.73: −2.77], p = 0.0002) but not for females (MD = −3.04[95% CI; −6.6:0.54], p = 0.10). Healthy, pregnant, diabetic and CVD subgroups found significant differences in the healthy (MD = −1.74[95% CI; −03.13: −0.35], p = 0.01) and diabetic (MD = −7.69[95% CI, −1.64: −0.73], p = 0.03). subgroups, but not in the pregnant or cardiovascular disease subgroups. On the other hand, the meta-analysis found no statistically significant difference in Ghrelin serum concentration between smokers and non-smokers (MD = 0.52[95% CI, −0.60:1.63], p = 0.36) and observed heterogeneity in the studies (I2 = 68%).ConclusionThis study demonstrates a correlation between smoking and serum leptin/ghrelin levels, which explains smoking’s effect on body weight.Systematic review registrationhttps://www.crd.york.ac.uk/ prospero/display_record.php, identifier (Record ID=326680)

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere