Comparative Analysis of Reported Deaths Cases Associated with the New Coronavirus COVID-19 Pandemic in the South Caucasus Countries (Armenia, Azerbaijan, Georgia) from March 2020 to May 2022

The results of a statistical analysis of daily, total by days of the week and monthly data on officially reported deaths cases from the new coronavirus COVID-19 in the countries of the South Caucasus (Armenia, Azerbaijan, Georgia) from March 12, 2020 to May 31, 2022 are presented. All data are normalized per 1 million populations (mortality rate, hereinafter, this normalization is assumed everywhere). In particular, the following results were obtained. The daily mortality rate in Armenia averaged 3.591 (range: 0-23.622), in Azerbaijan - 1.184 (range: 0-10.969), in Georgia - 5.596 (range: 0-23.189). The total monthly mortality rate in Armenia averaged 107.9 (variability range: 1.01-415.4), in Azerbaijan - 35.6 (variability range: 0.39-122.9), in Georgia - 168.1 (variability range: 0-547.4). A direct linear correlation was observed between the indicated countries in cases of daily and total monthly mortality. An analysis of the intraweek course of mortality showed that in Armenia, on weekdays, the average daily mortality is 4.319, and on weekends - 3.477 (an increase compared to weekends by about 24%); in Azerbaijan, on weekdays and weekends, the average daily mortality is 1.368 and 1.421, respectively (the difference is insignificant); in Georgia on weekdays, the average daily mortality is 7.558, and on weekends - 6.855 (an increase of about 10% compared to weekends).

The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their monthly interval prediction from January 1, 2022 to March 31, 2022

In this work results of the next statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from January 01, 2022 to March 31, 2022 are presented. It also presents the results of the analysis of monthly forecasting of the values of C, D and I. As earlier, the information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained. Georgias ranking in the world for Covid-19 monthly mean values of infection and deaths cases in investigation period (per 1 million population) was determined. Among 157 countries with population [≥] 1 million inhabitants in February 2022 Georgia was in the 4 place on new infection cases, in the 2 place on death. Georgia took the best place in terms of confirmed cases of diseases (thirty fifth) and in mortality (tenth) - in March. A comparison between the daily mortality from Covid-19 in Georgia from January 01, 2022 to March 31, 2022 with the average daily mortality rate in 2015-2019 shows, that the largest share value of D from mean death in 2015-2019 was 43.1 % (January 04, 2022), the smallest 2.12 % (March 23, 2022). As in previous works [10-13] the statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 26320 (February 2, 2022), R = 48486 (February 12, 2022), D = 67 (January 4,2022), I = 41.58 % (February 14, 2022). Maximum mean decade values of investigation parameters are following: C = 22214 (1 Decade of February 2022), R = 23408 (2 Decade of February 2022), D = 45 (2 Decade of February 2022), I = 32.12% (1 Decade of February 2022). It was found that as in spring, summer and from September to December 2021 [10,11,13], in investigation period of time the regression equations for the time variability of the daily values of C, R, D and I have the form of a tenth order polynomial. Mean values of speed of change of confirmed - V(C), recovered - V(R), deaths - V(D) and infection rate V(I) coronavirus-related cases in different decades of months for the indicated period of time were determined. Maximum mean decade values of investigation parameters are following: V(C) = +1079 cases/day (3 Decade of January 2022), V(R) = +1139 cases/day (1 Decade of February 2022), V(D) = +0.8 cases/day (1 Decade of February 2022), V(I) = + 1.16 %/ day (3 decades of January 2022). Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases shows, that from January 1, 2022 to March 31, 2022 the maximum effect of recovery is observed on 3-6 days after infection (CR=0.83-0.84), and deaths - after 2 and 4 days (CR=0.60). The impact of the omicron variant of the coronavirus on people (recovery, mortality) could be up to19 and 16 days respectively. Comparison of daily real and calculated monthly predictions data of C, D and I in Georgia are carried out. It was found that in investigation period of time daily and mean monthly real values of C, D and I mainly fall into the 67% - 99.99% confidence interval of these predicted values. Exception - predicted values of I for January 2022 (alarming deterioration, violation of the stability of a time-series of observations). Traditionally, the comparison of data about C and D in Georgia (GEO) with similar data in Armenia (ARM), Azerbaijan (AZE), Russia (RUS), Turkey (TUR) and in the World (WRL) is also carried out.

The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their monthly interval prediction from September 1, 2021 to December 31, 2021

The lockdown introduced in Georgia on November 28, 2020 contributed to positive trends in the spread of COVID-19 until February - the first half of March 2021. Then, in April-May 2021, the epidemiological situation worsened significantly, and from June to the end of December COVID - situation in Georgia was very difficult. In this work results of the next statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from September 01, 2021 to December 31, 2021 are presented. It also presents the results of the analysis of monthly forecasting of the values of C, D and I. As earlier, the information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained. Georgias ranking in the world for Covid-19 monthly mean values of infection and deaths cases in investigation period (per 1 million population) was determined. Among 157 countries with population [≥] 1 million inhabitants in October 2021 Georgia was in the 4 place on new infection cases, and in September - in the 1 place on death. Georgia took the best place in terms of confirmed cases of diseases (thirteenth) in December, and in mortality (fifth) - in October. A comparison between the daily mortality from Covid-19 in Georgia from September 01, 2021 to December 31, 2021with the average daily mortality rate in 2015-2019 shows, that the largest share value of D from mean death in 2015-2019 was 76.8 % (September 03, 2021), the smallest 18.7 % (November 10, 2021). As in previous work [9,10] the statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 6024 (November 3, 2021), R = 6017 (November 15, 2021), D = 86 (September 3, 2021), I = 12.04 % (November 24, 2021). Maximum mean decade values of investigation parameters are following: C = 4757 (1 Decade of November 2021), R = 4427 (3 Decade of November 2021), D = 76 (2 Decade of November 2021), I = 10.55% (1 Decade of November 2021). It was found that as in spring and summer 2021 [9,10], from September to December 2021 the regression equations for the time variability of the daily values of C, R, D and I have the form of a tenth order polynomial. Mean values of speed of change of confirmed -V(C), recovered - V(R), deaths - V(D) and infection rate V(I) coronavirus-related cases in different decades of months for the indicated period of time were determined. Maximum mean decade values of investigation parameters are following: V(C) = +139 cases/day (1 Decade of October 2021), V(R) = +124 cases/day (3 Decade of October 2021), V(D) = +1.7 cases/day (3 Decade of October 2021), V(I) = + 0.20 %/ day (1 decades of October 2021). Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases shows, that from September 1, 2021 to November 30, 2021 the maximum effect of recovery is observed on 12 and 14 days after infection (CR=0.77 and 0.78 respectively), and deaths - after 7, 9, 11, 13 and 14 days (0.70[≤]CR[≤]0.72); from October 1, 2021 to December 31, 2021 - the maximum effect of recovery is observed on 14 days after infection (RC=0.71), and deaths - after 9 days (CR=0.43). In Georgia from September 1, 2021 to November 30, 2021 the duration of the impact of the delta variant of the coronavirus on people (recovery, mortality) could be up to 28 and 35 days respectively; from October 1, 2021 to December 31, 2021 - up to 21 and 29 days respectively. Comparison of daily real and calculated monthly predictions data of C, D and I in Georgia are carried out. It was found that in investigation period of time daily and mean monthly real values of C, D and I practically fall into the 67% - 99.99% confidence interval of these predicted values. Traditionally, the comparison of data about C and D in Georgia (GEO) with similar data in Armenia (ARM), Azerbaijan (AZE), Russia (RUS), Turkey (TUR) and in the World (WRL) is also carried out.

The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their two-week interval prediction in summer 2021

The lockdown introduced in Georgia on November 28, 2020 brought positive results. There were clearly positive tendencies in the spread of COVID-19 to February - first half of March 2021. However, in April-May 2021 there was a significant deterioration in the epidemiological situation. From June to August 2021, the epidemiological situation with Covid-19 in Georgia became very difficult. In this work results of the next statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from June 01, 2021 to August 31, 2021 are presented. It also presents the results of the analysis of two-week forecasting of the values of C, D and I. As earlier, the information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained. Georgias ranking in the world for Covid-19 monthly mean values of infection and deaths cases in summer 2021 (per 1 million population) was determined. Among 159 countries with population [≥] 1 million inhabitants in August 2021 Georgia was in the 1 place on new infection cases and on Death. A comparison between the daily mortality from Covid-19 in Georgia in summer 2021 with the average daily mortality rate in 2015-2019 shows, that the largest share value of D from mean death in 2015-2019 was 66.0 % (26.08.2021 and 31.08.2021), the smallest 6.0 % (09.07.2021). The statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 6208 (17.08.2021), R = 6177 (29.08.2021), D = 79 (26.08.2021 and 31.08.2021), I = 13.0 % (17.08.2021). Maximum mean decade values of investigation parameters are following: C = 5019 (2 Decade of August 2021), R = 4822 (3 Decade of August 2021), D = 69 (3 Decade of August 2021), I = 10.88 % (2 Decade of August 2021). It was found that as with September 2020 to February 2021 and in spring 2021 [7,8], from June to August 2021 the regression equations for the time variability of the daily values of C, R and D have the form of a tenth order polynomial. Mean values of speed of change of confirmed -V(C), recovered - V(R), deaths - V(D) and infection rate V(I) coronavirus-related cases in different decades of months in the summer 2021 were determined. Maximum mean decade values of investigation parameters are following: V(C) = +134 cases/day (1 Decade of August 2021), V(R) = +134 cases/day (2 Decade of August 2021), V(D) = +2.4 cases/day (3 Decade of August 2021), V(I) = + 0.25 %/ day (1 decades of August 2021). Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases shows, that the maximum effect of recovery is observed 19 days after infection (RC=0.95), and deaths - after 16 and 18 days (RC=0.94). In Georgia in the summer 2021, the duration of the impact of the delta variant of the coronavirus on people (recovery, mortality) could be up to two months. Comparison of real and calculated predictions data of C, D and I in Georgia are carried out. It was found that in summer 2021 two-week daily and mean two-week real values of C, D and I practically fall into the 67% - 99.99% confidence interval of these predicted values. With September 1, 2021, it is started monthly forecasting of C, D and I values. As earlier, the comparison of data about C and D in Georgia (GEO) with similar data in Armenia (ARM), Azerbaijan (AZE), Russia (RUS), Turkey (TUR) and in the World (WRL) is also carried out.

The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their short-term interval prediction in spring 2021

The lockdown introduced in Georgia on November 28, 2020 brought positive results. There are clearly positive tendencies in the spread of COVID-19 to February - first half of March 2021. However, in April-May 2021 there was a significant deterioration in the epidemiological situation. In this work results of the next statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from March 01, 2021 to May 31, 2021 are presented. It also presents the results of the analysis of two-week forecasting of the values of C, D and I. The information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained. Georgias ranking in the world for Covid-19 monthly mean values of infection and deaths cases in spring 2021 (per 1 million population) was determined. Among 156 countries with population [≥] 1 million inhabitants in May 2021 Georgia was in the 11 place on new infection cases and in the 14 place on Death. A comparison between the daily mortality from Covid-19 in Georgia in spring 2021 with the average daily mortality rate in 2015-2019 shows, that the largest share value of D from mean death in 2015-2019 was 25.3 % (22.05.2021), the smallest 1.42 % (15.03.2021). Data about infection rate of the population of Georgia with Covid-19 according to traffic light system shown, that Georgia in April and May 2021 was in the red zone. The statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 2171 (05.05.2021), R = 2038 (17.05.2021), D = 33 (22.05.2021), I = 8.05 % (04.05.2020). Maximum mean decade values of investigation parameters are following: C = 1258 (3 Decade of April 2021), R = 1283 (2 Decade of May 2021), D = 24 (2 Decade of May 2021), I = 6.54 % (1 Decade of May 2021). It was found that as with September 2020 to February 2021 [8], in spring 2021 the regression equations for the time variability of the daily values of C, R and D have the form of a tenth order polynomial. Mean values of speed of change of confirmed -V(C), recovered - V(R), deaths - V(D) and infection rate V(I) coronavirus-related cases in different decades of months in the spring 2021 were determined. Maximum mean decade values of investigation parameters are following: V(C) = +37 cases/day (1 Decade of April 2021), V(R) = +36 cases/day (3 Decade of April 2021), V(D) = +0.6 cases/day (3 Decade of April 2021), V(I) = + 0.17 %/ day (2 and 3 decades of April 2021). Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases shows, that the maximum effect of recovery is observed 9 and 13 days after infection, and deaths - after 12-17 days. Comparison of real and calculated predictions data of C, D and I in Georgia are carried out. It was found that two-week daily and mean two-week real values of C, D and I practically fall into the 67% - 99.99% confidence interval of these predicted values for the specified time periods. The comparison of data about C and D in Georgia (GEO) with similar data in Armenia (ARM), Azerbaijan (AZE), Russia (RUS), Turkey (TUR) and in the World (WRL) is also carried out.

The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their short-term interval prediction from September 2020 to February 2021

In the autumn - winter period of 2020, very difficult situation arose in Georgia with the course of the pandemic of the New Coronavirus COVID-19. In particular, in November-December period of 2020, Georgia eight days was rank a first in the world in terms of COVID-19 infection rate per 1 million populations. In this work results of a statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from September 01, 2020 to February 28, 2021 (for I - from December 05, 2020 to February 28, 2021) are presented. It also presents the results of the analysis of ten-day (decade) and two-week forecasting of the values of C, D and I, the information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained. Georgias ranking in the world for Covid-19 infection and deaths from September 1, 2020 to February 28, 2021 (per 1 million population) was determined. Georgia was in the first place: Infection - November 21, 22, 27, 28 and December 04, 05, 06, 09, 2020; Death - November 22, 2020. A comparison between the daily mortality from Covid-19 in Georgia from September 1, 2020 to February 28, 2021 with the average daily mortality rate in 2015-2019 was made. The largest share value of D from mean death in 2015-2019 was 36.9% (19.12.2020), the smallest - 0.9% (21.09.2020, 24.09.2020 - 26.09.2020). The statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 5450 (05.12.2020), R = 4599 (21.12.2020), D = 53 (19.12.2020), I = 30.1 % (05.12.2020). Maximum mean decade values of investigation parameters are following: C = 4337 (1 Decade of December 2020), R = 3605 (3 Decade of November 2020), D = 44 (2 Decade of December 2020), I = 26.8 % (1 Decade of December 2020). It was found that the regression equations for the time variability of the daily values of C, R and D have the form of a tenth order polynomial. Mean values of speed of change of confirmed -V(C), recovered - V(R) and deaths - V(D) coronavirus-related cases in different decades of months from September 2020 to February 2021 were determined. Maximum mean decade values of investigation parameters are following: V(C) = +104 cases/day (1 Decade of November 2020), V(R) = +94 cases/day (3 Decade of October and 1 Decade of November 2020), V(D) = +0.9 cases/day (1 Decade of November 2020). Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases from 05.12.2020 to 28.02.2021 is carried out. So, the maximum effect of recovery is observed 13-14 days after infection, and deaths - after 13-14 and 17-18 days. The scale of comparing real data with the predicted ones and assessing the stability of the time series of observations in the forecast period in relation to the pre-predicted one was offered. Comparison of real and calculated predictions data of C (23.09.2020-28.02.2021), D (01.01.2021-28.02.2021) and I (01.02.2021-28.02.2021) in Georgia are carried out. It was found that daily, mean decade and two-week real values of C, D and I practically falls into the 67% - 99.99% confidence interval of these predicted values for the specified time periods (except the forecast of C for 13.10.2020-22.10.2020, when a nonlinear process of growth of C values was observed and its real values have exceeded 99.99% of the upper level of the confidence interval of forecast). Alarming deterioration with the spread of coronavirus parameters may arise when their daily values are higher 99.99% of upper level of the forecast confidence interval. Excellent improvement - when these daily values are below 99.99% of the lower level of the forecast confidence interval. The lockdown introduced in Georgia on November 28, 2020 brought positive results. There are clearly positive tendencies in the spread of COVID-19 to February 2021.

Repeatability of 2 swept-source OCT biometers and 1 optical low-coherence reflectometry biometer.

AIM: To compare the repeatability of 2 swept-source optical coherence tomography (SS-OCT) biometers, IOLMaster 700 (biometer A, Carl Zeiss Meditec AG) and ANTERION (biometer B, Heidelberg Engineering GmbH) and 1 optical low-coherence reflectometry (OLCR) device (biometer C, LENSTAR, LS900; Haag-Streit AG). SETTING: Department of Ophthalmology, Hanusch Hospital, Vienna Institute for Research in Ocular Surgery-Karl Landsteiner Institute, Vienna, Austria. DESIGN: Prospective study that included patients scheduled for cataract surgery. METHOD: Three consecutive measurements were performed with 2 SS-OCT devices and 1 OLCR device. The repeatability of the following biometry variables was compared: keratometry, central corneal thickness, anterior chamber depth (ACD), lens thickness (LT), and axial eye length (AL). To assess the repeatability of each parameter, the within-subject SD (Sw) and coefficient of variation (CoV) were calculated. RESULT: Fifty eyes of 50 patients were included. The CoV values were below 0.5 for all variables, except for ACD and LT for biometer C. The Sw values for mean keratometry were 0.018 for biometer A, 0.083 for biometer B, and 0.137 for biometer C. For the ACD, the Sw values were 0.039 and 0.004 for biometer A and biometer B, respectively, and 0.134 for biometer C. For the AL, the values were 0.006 for biometer A, 0.008 for biometer B, and 0.012 for biometer C. CONCLUSIONS: All biometry devices included in the analysis presented a high repeatability. The SS-OCT devices showed a higher repeatability performance compared with the OLCR device.

Comparison of 2 swept-source optical coherence tomography-based biometry devices.

PURPOSE: To compare 2 swept-source optical coherence tomography (SS-OCT) biometers, IOLMaster 700 (biometer A), and ANTERION (biometer B). SETTING: Department of Ophthalmology, Vienna Institute for Research in Ocular Surgery, Karl Landsteiner Institute, Hanusch Hospital, Vienna, Austria. DESIGN: Retrospective study. METHOD: Biometric measurements of cataract patients performed between June and July 2019 were reviewed. Patients scheduled for cataract surgery were measured with both SS-OCT devices on the same day. The following biometry parameters were compared: keratometry, central corneal thickness, anterior chamber depth (ACD), lens thickness (LT), and axial length (AL). RESULT: In total, 389 eyes of 209 subjects were measured with both devices. The mean absolute difference between the keratometry data of the 2 devices was 0.04 ± 0.05 mm (7.80 ± 0.26 mm for biometer A and 7.82 ± 0.26 mm for biometer B; P < .0001) for the steep keratometry readings and 0.04 ± 0.04 mm (7.63 ± 0.26 mm and 7.65 ± 0.25 mm; P < .0001) for the flat keratometry readings. For ACD and LT, the mean absolute difference was 0.07 ± 0.04 mm and 0.07 ± 0.04 mm. The mean absolute difference for AL was 0.02 ± 0.03 mm (23.55 ± 1.18 mm for biometer A and 23.54 ± 1.18 mm for biometer B; P < .0001). CONCLUSIONS: Good agreement was found between the 2 devices, with a minor offset for ACD and LT measurements. Although differences were found to be small, the devices should not be used interchangeably.

Capsular bag performance of a novel hydrophobic acrylic single-piece intraocular lens: Two-year results of a randomised controlled trial.

PURPOSE: To determine the visual outcome, intraocular lens (IOL) stability and posterior capsule opacification (PCO) rate of a hydrophobic acrylic intraocular lens. SETTING: Vienna Institute for Research in Ocular Surgery, Hanusch Hospital, Vienna, Austria. DESIGN: This double-masked randomised study included patients who underwent standard cataract surgery. METHOD: Patients received either the hydrophobic acrylic IOL (iPure, PhysIOL) or the hydrophobic acrylic control IOL (Tecnis ZCB00, Johnson&Johnson). Subjective refraction, uncorrected and corrected distance visual acuity (UDVA, CDVA), IOL tilt and decentration (Purkinje meter) and PCO intensity using retroillumination images with automated image analysis (automated quantification of after-cataract, AQUA), were evaluated for both groups 2 years after surgery. RESULTS: A total number of 31 patients completed the 2-year follow-up, 16 in the study group and 15 in the control group. The CDVA was 0.0 logMAR (standard deviation - SD: 0.1) for the study IOL and 0.1 logMAR (SD: 0.2) for the control IOL, p = 0.001. The AQUA PCO score for the study group was 2.1 and 1.4 for the control group, p = 0.44. Mean IOL tilt was 2.9° (SD: 1.8) in the study group and 5.0° (SD: 4.5) in the control group, whilst the mean decentration was 0.37 mm (SD: 0.18) and 0.45 mm (SD: 0.3), p = 0.610. CONCLUSION: The studied parameters revealed a good performance for both IOLs. Both IOLs had good CDVA, a small amount of tilt and decentration and none of the patients required laser capsulotomies during the follow-up time of 2 years after surgery.Presented at the 37th ESCRS Congress Paris, France, September 2019.

Analysis of twenty-week time-series of confirmed cases of New Coronavirus COVID-19 and their simple short-term prediction for Georgia and Neighboring Countries (Armenia, Azerbaijan, Turkey, Russia) in amid of a global pandemic

Results of a comparative statistical analysis of the daily data associated with New coronavirus COVID-19 infection of confirmed cases ([C]) of the population in Georgia (GEO), Armenia (ARM), Azerbaijan (AZE), Turkey (TUR) and Russia (RUS) amid a global pandemic (WLD) in the period from March 14 to July 31, 2020 are presented. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, a correlation and autocorrelation analysis of the observational data was carried out, the periodicity in the time- series of [C] were revealed, the calculation of the interval prediction values of [C] taking into account the periodicity in the time-series of observations from August 1 to 31, 2020 (ARM, AZE) and from August 1 to September 11, 2020 (WLD, GEO, TUR, RUS) were carried out. Comparison of real and calculated predictions data on [C] in the study sites from August 1 to August 31, 2020 is carried out. It was found that daily, monthly and mean weekly real values of [C] for all the studied locations practically fall into the 99% confidence interval of the predicted values of [C] for the specified time period. A dangerous situation with the spread of coronavirus infection may arise when the mean weekly values of [C] of the 99% upper level of the forecast confidence interval are exceeded within 1-2 weeks. Favorable - when the mean weekly values of [C] decrease below 99% of the lower level of the forecast confidence interval.

Is your drinking-water safe? A rotavirus outbreak linked to water refilling stations in the Philippines, 2016.

INTRODUCTION: In April 2016, the Department of Health in Zamboanga Peninsula reported an increase in the number of acute gastroenteritis cases reported from Zamboanga City. An epidemiologic investigation was conducted to verify the existence of an outbreak, determine source/mode of transmission and recommend control measures. METHODS: A line list of cases was compiled from the 11 hospitals within Zamboanga City and a case-series study was conducted. Suspected cases were any persons from Zamboanga City who had three or more episodes of acute diarrhoea within 24 hours from 15 March to 29 May 2016. Confirmed cases were suspected cases with active symptoms during the investigation who had a stool sample collected with rotavirus detected. Water samples were also collected for viral detection. RESULTS: There were 2936 suspected cases with 22 deaths (case fatality rate: 0.75%), an age range of 8 days to 89 years (median: 2 years), with those aged less than 5 years the most affected age group (1903/2936, 65%). The majority were males (1549/2936, 53%). From the 138 active case patients included in the case-series study, the majority reported contact with a family member who had diarrhoea (89/138, 64%) and using water refilling stations as their major source of drinking-water (88/134, 64%). Of the 93 stool specimens collected, 56 (60%) were positive for rotavirus. Five samples from water refilling stations where case patients reported collecting drinking-water were all positive for rotavirus. DISCUSSION: Strict regulation of water refilling stations and boiling drinking-water in households were implemented, immediately controlling the outbreak. After complying with all the requirements set by the Department of Health, a water safety certificate was awarded to Zamboanga City in September 2018.

The SOS Chromotest applied for screening plant antigenotoxic agents against ultraviolet radiation.

In this work, we investigated the usefulness of the SOS Chromotest for screening plant antigenotoxic agents against ultraviolet radiation (UV). Fifty Colombian plant extracts obtained by supercritical fluid (CO2) extraction, twelve plant extract constituents (apigenin, carvacrol, ß-caryophyllene, 1,8-cineole, citral, p-cymene, geraniol, naringenin, pinocembrin, quercetin, squalene, and thymol) and five standard antioxidant and/or photoprotective agents (curcumin, epigallocatechin gallate, resveratrol, α-tocopherol, and Trolox®) were evaluated for their genotoxicity and antigenotoxicity against UV using the SOS Chromotest. None of the plant extracts, constituents or agents were genotoxic in the SOS Chromotest at tested concentrations. Based on the minimal extract concentration that significantly inhibited UV-genotoxicity (CIG), five plant extracts were antigenotoxic against UV as follows: Baccharis nítida (16 µg mL-1) = Solanum crotonifolium (16 µg mL-1) > Hyptis suaveolens (31 µg mL-1) = Persea caerulea (31 µg mL-1) > Lippia origanoides (62 µg mL-1). Based on CIG values, the flavonoid compounds showed the highest antigenotoxic potential as follows: apigenin (7 µM) > pinocembrin (15 µM) > quercetin (26 µM) > naringenin (38 µM) > epigallocatechin gallate (108 µM) > resveratrol (642 µM). UV-genotoxicity inhibition with epigallocatechin gallate, naringenin and resveratrol was related to its capability for inhibiting protein synthesis. A correlation analysis between compound antigenotoxicity estimates and antioxidant activity evaluated by the oxygen radical absorbance capacity (ORAC) assay showed that these activities were not related. The usefulness of the SOS Chromotest for bioprospecting of plant antigenotoxic agents against UV was discussed.

Alcohol metabolism is not affected by sleeve gastrectomy.

INTRODUCTION: It has been published that patients who underwent gastric bypass surgery have impaired alcohol metabolism, predisposing them to higher rates of intoxication and DUI arrests. Yet the impact of laparoscopic sleeve gastrectomy (LSG) on alcohol metabolism and in particular the long-term effects are still unclear. We hypothesized that LSG does not alter alcohol metabolism. METHODS: A prospective cohort study of patients undergoing LSG was evaluated. Blood alcohol concentration (BAC) was extrapolated using a Breathalyzer(®). Alcohol metabolism was evaluated by determining BAC every 5 min after a single dose of alcohol (5 oz. glass of 14% v/v Malbec wine), until BAC was equal to zero. Subjects were queried about alcohol intoxication symptoms. All parameters were obtained and analyzed preoperatively and at 3 and 12 months postoperatively. RESULTS: Our study consisted of 10 patients (9 female) with a mean age of 46.6 ± 2.2 years and BMI of 43.5 ± 2.2 kg/m(2). The mean percentage excess weight loss was 39.5 ± 3.3 at 3 months and 55.6 ± 4.4 at 12 months. Peak BAC at 20 min was not different at 3 months (0.068 ± 0.007, p = 0.77) or at 12 months (0.047 ± 0.008, p = 0.19) when compared to the preoperative assessment (0.059 ± 0.014). In addition, the time to BAC equal to zero was not significantly different between baseline and the follow-up values (preoperative: 70 ± 9 min, 3 months: 95 ± 18 min, and 12 months: 57 ± 8 min, (p > 0.05). Symptoms of intoxication were not significantly different in patients before and after surgery. CONCLUSIONS: Our study suggests that LSG does not alter alcohol metabolism. Patients who undergo LSG do not have higher levels of intoxication following alcohol consumption and are therefore not prone to higher rates of DUI charges than the general public, in contrast to that previously reported following in patients who undergo gastric bypass surgery.

Atropine treatment modifies LPS-induced inflammatory response and increases survival.

OBJECTIVE: To explore the effect that Atropine, a competitive antagonist for the muscarinic acetylcholine receptor (mAChR), has on the response to LPS. SUBJECTS: Eight-week-old, male, B6 mice. TREATMENT: Mice were treated with Atropine prior to, or after LPS challenge. METHODS: Survival was monitored and analyzed via Kaplan-Meier analysis using the log-rank test. The effects of atropine on the inflammatory response (TNF-alpha, IL-6 and IL-10) were monitored at various time intervals following LPS injection in mice that were treated and not treated with atropine. RESULTS: Atropine administration prior to LPS induction of the inflammatory response resulted in reduced TNF-alpha and elevated IL-10 plasma levels without affecting the production of IL-6. This reduction in TNF-alpha levels was independent of the increase in IL-10 production. Atropine pretreatment improved the rate of survival from endotoxic shock in mice. The improved survival of mice after endotoxic shock could still be observed when atropine was administered several hours after LPS injection. CONCLUSION: The administration of atropine after injury may have a beneficial clinical effect.

Refractory hypotension and edema caused by right atrial compression in a woman with polycystic kidney disease.

We present the case of a 60-year-old woman with a history of autosomal dominant polycystic kidney disease and long-standing hypertension who developed persistent hypotension. While in the hospital for the treatment of bacteriemia, the patient had low systolic blood pressures (90 to 100 mm Hg), which was thought to be the consequence of infection. After the infection was adequately controlled and the blood pressure did not improve, an echocardiogram was done to further elucidate her hypotension. It was nondiagnostic and revealed an ejection fraction of 70% with left ventricular hypertrophy. Shortly after discharge, she developed significant lower extremity edema and her blood pressure remained low. Due to the low blood pressure it was not possible to mobilize the fluid with her dialysis treatments. A repeat transthoracic echocardiogram at that time revealed that the right atrium was partially compressed throughout the cardiac cycle by polycystic hepatic tissue. This tissue invaginated up through the right hemidiaphragm. A partial liver resection was considered for the patient. Instead, right nephrectomy was performed and the blood pressure improved.

Immunization against influenza: comparison of various topical and parenteral regimens containing inactivated and/or live attenuated vaccines in healthy adults.

Methods for enhancing immune responses to influenza were explored in 2 double-blind, placebo-controlled trials. Intranasal (inl) immunization with monovalent, live attenuated, cold-adapted recombinant (CR) or inactivated influenza virus (MIV) vaccine and intramuscular (im) immunization with MIV were evaluated in various combinations. Healthy susceptible adults were assigned randomly to receive 10(7.1) TCID(50) of CR (A/H1N1 or A/H3N2), homologous MIV (15 microg), or placebo inl and placebo or homologous MIV im (6 groups in each study). Serum antibody responses were greatest in groups given im vaccine (with or without inl vaccine). A 2-fold increase in nasal wash antibody response frequencies was seen in groups given combined inl (CR or MIV) and im vaccine, compared with subjects given a single im (MIV) or inl (CR or MIV) vaccine. Combined inl and im immunization is a promising approach for enhancing both local and systemic immune responses against influenza.

Regulation of endochondral cartilage growth in the developing avian limb: cooperative involvement of perichondrium and periosteum.

The perichondrium and periosteum have recently been suggested to be involved in the regulation of limb growth, serving as potential sources of signaling molecules that are involved in chondrocyte proliferation, maturation, and hypertrophy. Previously, we observed that removal of the perichondrium and periosteum from tibiotarsi in organ culture resulted in an overall increase in longitudinal cartilage growth, suggesting negative regulation originating from these tissues. To determine if the perichondrium and periosteum regulate growth through the production of diffusible factors, we have tested various conditioned media from these tissues for the ability to modify cartilage growth in tibiotarsal organ cultures from which these tissues have been removed. Both negative and positive regulatory activities were detected. Negative regulation was observed with conditioned medium from (1) cell cultures of the region bordering both the perichondrium and the periosteum, (2) co-cultures of perichondrial and periosteal cells, and (3) a mixture of conditioned media from perichondrial cell cultures and periosteal cell cultures. The requirement for regulatory factors from both the perichondrium and periosteum suggests a novel mechanism of regulation. Positive regulation was observed with conditioned media from several cell types, with the most potent activity being from articular perichondrial cells and hypertrophic chondrocytes.

Incidence and susceptibility of pathogenic bacteria vary between intensive care units within a single hospital: implications for empiric antibiotic strategies.

BACKGROUND: The purpose of this study was to determine whether the incidence of recovery and patterns of antibiotic susceptibility of pathogenic bacteria vary between intensive care units (ICUs) in a single teaching hospital. METHODS: Culture and susceptibility results were collected prospectively for a 3-month period (April through June 1999) in each of the surgical, trauma, and medical ICUs. The number of unique isolates and susceptibility patterns were determined. Susceptibility of isolates among ICUs was compared with chi2. RESULTS: Statistically significant differences between ICUs in susceptibility to various antibiotics were found for Staphylococcus aureus, Enterococcus sp, Acinetobacter sp, Enterobacter sp, Klebsiella sp, and Pseudomonas sp. Notably, vancomycin-resistant Enterococcus was not seen in the medical ICU, whereas it was seen in both the surgical and trauma ICUs. Klebsiella spp resistant to ceftazidime were seen only in the trauma ICU. The aminoglycosides and quinolones had attenuated activity against Pseudomonas sp in the surgical ICU, whereas they remained highly effective in the trauma ICU. Cefazolin had no activity against the Enterobacter sp in either of the surgical ICUs, but was highly effective in the medical ICU. CONCLUSION: Although the microbiologic results of this study should not be extrapolated to other institutions, the principle is of value. There is variability between ICUs in a single large teaching hospital in susceptibility of bacterial pathogens to various antibiotics. This may have implications in the design of empiric antibiotic strategies and the planning of the hospital formulary. Hospital wide or composite ICU antibiograms are inadequate for planning empiric therapy in the ICU.

Increasing doses of purified influenza virus hemagglutinin and subvirion vaccines enhance antibody responses in the elderly.

The reactogenicities and immunogenicities of two influenza virus vaccines were compared in a placebo-controlled clinical trial among healthy ambulatory persons > or = 65 years old (mean age, 72 years). Volunteers were assigned randomly to receive 15-, 45-, or 135-micrograms doses of monovalent influenza A/Taiwan (H1N1) hemagglutinin (HA) or subvirion (SV) vaccine intramuscularly or a placebo. Increasing doses of SV vaccine were associated with a higher rate of injection site discomfort (P < 0.05; chi-square test for linear trend), but all doses of both vaccines were well tolerated. Increasing the dose of the HA or the SV vaccine resulted in increasingly higher postimmunization levels of serum hemagglutination inhibition and neutralizing antibody levels (P < 0.001; multiple linear regression). Mean serum antibody titers at 1 month increased two- to threefold with a ninefold increase in dose; the frequencies of fourfold or greater rises in titer likewise increased. An increase in the dose of the HA or the SV vaccine also resulted in increased frequencies of rises in immunoglobulin A or G antibody titers in nasal wash specimens. The frequencies increased approximately twofold for each vaccine with a ninefold increase in the dose. These data suggest that increasing the HA vaccine dose is a promising approach to the development of improved influenza virus vaccines for use in elderly people.