The authors have declared that no competing interests exist.
The rapid and ongoing spread of antimicrobial-resistant organisms threatens the ability to successfully prevent, control, or treat a growing number of infectious diseases in developed and developing countries. This study was designed to convey more insight on the profile of antimicrobial resistance and the capacity of laboratories conducting antimicrobial susceptibility testing in Cameroon.
A multicentre cross-sectional study was conducted from October 2019 to March 2020 in the Deido Health District. Laboratories that carry out culture and sensitivity testing within the Deido Health District were identified and assessed to determine their capacity as well as the quality of results from microbiological investigations. Information on antimicrobial susceptibility of various isolates was collected using tablet phones in which the study questionnaires had been incorporated.
Gaps identified in antimicrobial susceptibility testing that cut across laboratories included; insufficient standard operating procedures, inadequate records on personnel training and competency assessment, lack of safety equipment such as biosafety cabinet, stock out and non-participation in external quality assurance program. The turnaround time for antimicrobial susceptibility testing ranged from 3 – 7 days. Out of the 1797 samples cultured, 437(24.3%) had at least one isolate. A total of 15 different isolates were identified with
This study has shown the need to develop a coordinated national approach to fight antimicrobial resistance. Scaling-up of antimicrobial susceptibility testing will, therefore, require strengthening the microbiology units of laboratory systems as well as ensuring the use of laboratory data for decision making.
Antimicrobial resistance is a major public health problem. The rapid and ongoing spread of antimicrobial-resistant organisms threatens the ability to successfully prevent, control, or treat a growing number of infectious diseases in developed and developing countries
WHO underscored in the global action plan the need to continue to raise awareness of AMR through research, surveillance, and monitoring in different countries
The impact of AMR is already overwhelming on several health systems worldwide. In the USA, AMR is estimated to be responsible for more than 2 million of infectious diseases and accounts for about 23,000 annual deaths
Studies on antimicrobial resistance in different parts of Cameroon indicate that antimicrobial drugs top the list of commonly prescribed drugs in hospitals following the high burden of infectious diseases
This was a multicentre cross-sectional study conducted from October 2019 to March 2020 in the Deido Health District. Laboratories that carry out culture and antimicrobial susceptibility testing (AST) within the Deido Health District were identified and assessed to determine their capacity as well as the quality of results from microbiological investigations using the Modified WHO Antimicrobial Resistance Surveillance Questionnaire
The laboratory staff working on the microbiology bench were trained on how to collect information using a structured questionnaire incorporated in tablet phones. Information on antimicrobial susceptibility of various isolates was collected using tablet phones in which the study questionnaires had been incorporated.
Participants included in this study were individuals of all ages and sex who visited any of the three (Deido District Hospital, St Padre Pio Hospital and Daniel Muna Memorial Clinic) main hospitals in the Deido Health District for culture and sensitivity tests between October 2019 and March 2020.
Antimicrobial susceptibility of the isolates was determined using the disc diffusion technique on Mueller Hinton agar for bacteria isolates and Sabouraud dextrose agar for fungi isolates as described in the guidelines of the Clinical and Laboratory Standard Institute (CLSI) and the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints
After inoculating the isolates and placing the antimicrobial discs, the plates were incubated for 24h against Staphylococcus isolates and 16–18h for other isolates. The diameters of the zones of complete inhibition (as qualified with the eye) were measured, the diameter of the antimicrobial disk was also measured. The measured diameter was compared to the critical values of each antimicrobial disc to determine whether the target isolate was sensitive, resistant or intermediate. Mindful of the difficulty in obtaining commercial control strains in the country to be used for daily routine, the laboratories had established in house controls that are derived from commercial controls. Control tests were performed with
For mycoplasma susceptibility testing, the specimen was inoculated into the Mycoplasma Susceptibility kit (Autobio Diagnostics Co.,Ltd., Zhengzhou, China) within an hour as described by the manufacturer's guidelines. If there is a growth,
Data on the laboratory capacity and quality of culture and antimicrobial susceptibility testing was collected with the modified WHO Antimicrobial Resistance Surveillance Questionnaire and the SLIPTA Checklist. A structured questionnaire was used to collect demographic information, patient history concerning the usage of antimicrobials. Furthermore, the questionnaire was also designed to capture information on the type of specimen that was cultured, the isolate, and the drugs to which the microbe was resistant as well as the turnaround time for culture and antimicrobial susceptibility testing. Since the questionnaire was incorporated into a tablet phone, an email address was created which was used for weekly backup of the data set.
Data was collected with a questionnaire designed using Epi Info Data software. The data set was exported from Epi Info to excel spreadsheet. Missing variables or discrepancies in data were corrected from the medical records of patient. The data was then exported and analyzed using SPSS version 20 (IBM, Chicago, IL). Descriptive statistics such as the number of microbes isolated, type of specimen cultured were expressed as proportions. The overall resistance of the isolates to a class of antimicrobial agents was calculated as median resistance and inter quarter range. The resistance rate of a specific group of the isolate to the antimicrobial agent was also calculated as median resistance. Comparison of the proportion of antimicrobial resistance between groups was assessed with the chi-square test and the threshold for statistical significance set at p < 0.05.
Ethical approval was obtained from the Faculty of Health Sciences Institutional review board of the University of Buea (N0: 2019/941-01/UB.SG.IRB.FHS). Administrative authorization was obtained from the Littoral Regional Delegation of Public Health and the Deido Health District. Written consent was obtained from the participants after the purpose of the study was orally explained to them. Since the questionnaire was incorporated into the tablet phones, passwords were given for each tablet to avoid unauthorized accessto the database
From the audit results using WHO Antimicrobial Resistance Surveillance and SLIPTA checklist, the methods in use for culture, identification, and antimicrobial susceptibility testing in the laboratories were kit-based (only for mycoplasma) and conventional methods. With respect to personnel, the laboratories were headed by qualified microbiologists and Quality Assurance Officers were present in all the laboratories. The laboratories reported not to be using control strains but they had established in-house quality control isolates. All the laboratories had a backup system for power. The laboratories were using either the “CLSI or the EUCAST” guide for the interpretation of AST.
On the other hand, gaps identified which cut across the three laboratories included; insufficient standard operating procedures, inadequate records on personnel training and competency assessment, lack of safety equipment such as biosafety cabinet, stock out, non-participation in external quality assurance programs, and audits were not regularly performed. The study findings also showed that there are no structures in place to oversee AMR activities in the facilities and at district levels, hence non-utilization of laboratory AST data to inform authorities. Another gap that cut across these laboratories was the non-usage of quality indicators to measure performance.
A total of 1797 samples were cultured in the three laboratories during the study period among which, 424 (23.6%) were female samples. The samples were collected from individuals aged 1 to 94 years, with a mean age of 19.84 years (SD 14.9). The majority of the participants 1199 (66.7) were within the age group 20 – 40 years. Most of the specimens cultured were, urine 731(40.7%) follow by vagina smear 642(35.7%) while the CSF was 2(0.1%). It took the laboratories 3 to 7 days to give out culture and susceptibility testing results. It is important to note that 1164(64.7%) of results were given within 3 working days while 16(0.9%) took more than 5 days (
Out of the 1797 samples cultured, 437(24.3) had at least one isolate. A total of 15 different isolates were identified with
Among the 15 classes of antimicrobial drugs used in this study, the overall resistance of the isolates showed that 5 classes had class median resistance above 40% (Cephalosporins, Penicillins, Beta-lactam, Macrolides and Polyenes). Polyenes had the highest median resistance with Amphotericin B having an overall resistance rate of 89.6 (81.7 – 94.9). The median resistance for Beta-lactam 62.2% with oxacillin being the most resistant in the group 73.0% (95% CI 60.3 – 83.4). On the other hand, the least resistance was observed among the aminoglycosides with a class median of 12.8% with amikacin having the lowest resistance in the group (6.5%, 95% CI 0.8 – 21.4) (
For the resistance of the various isolates to the different antimicrobials tested against, coagulase-negative
Variable | Category | Frequent (%)N= 1797 |
Sex | Male | 424(23.6) |
Female | 1,373(76.4) | |
<5 | 92(5.1) | |
5-10 | 88(4.9) | |
11-19 | 126 (7.0) | |
20-40 | 1199 (66.7) | |
41-60 | 205(11.4) | |
>60 | 87(4.8) | |
Mean | 29.84 (SD,14.9, ) | |
Range | 94 | |
Specimen | US | 55(3.1) |
VS | 642(35.7) | |
Urine | 731(40.7) | |
Stool | 301(16.8) | |
Semen | 11(0.6) | |
Wound | 20(1.1) | |
CSF | 2(0.1) | |
Vulva | 24(1.3) | |
Others body fluid | 11(0.6) | |
Duration of Culture results | 3days | 1164(64.7) |
4-5day | 617(34.3) | |
>5days | 16(0.9) | |
Mean | 3.54 (SD 0.8) | |
Range | 3- 7 |
Isolate | Frequency (%) N = 437 | Specimen |
|
26(5.9) | US (8), VS (5), Urine (9), Semen (1), Wound (3) |
|
10(2.3) | Urine (10) |
|
11(2.5) | Vulva (1), wound (2) Urine (4) VS (4), |
|
1(.2) | US (1) |
|
80(18.3) | VS (17), wound (2) Urine (58) Stool (1), Vulva (1), |
|
22(5.0) | VS (8), Urine (14) |
|
2(.5) | Stool (2) |
|
8(1.8) | Urine (2), Wound (6) |
|
16(3.7) | VS (13), US (2) Semen (1) |
|
24(5.5) | VS (4), US (19) Urine (1) |
|
12(2.7) | VS (1), wound (1) Urine (9), Other body fluid (1), |
|
11(2.5) | VS (6), Urine (5) |
|
12(2.7) | VS (1), US (1) Semen (1) Urine (1) |
CoNS | 24(5.5) | VS (19), US (1) Semen (1) Urine (3) |
|
178(40.7) | VS (97), Stool (79), Vulva (2), |
Total | 437(100.0) | VS (198), US (17), Urine (116), Stool (81), Semen (5), Wound (12), Valve (5) other body fluid (1) |
Antimicrobial Class | Antimicrobial | Resistance (95%CI) | Class Median Resistance (IQR) |
Cephalosporins | Cefuroxime | 50.0 (23.0 – 77.0) | 51(40-53) |
Cefotaxime | 50.6 (39.1 – 62.1) | ||
Ceftazidime | 50.8 (37.5 – 64.1) | ||
Ceftriaxone | 30.1 (20.5 - 41.2) | ||
Cefixime | 54.7(41.7 – 67.2) | ||
Penicillins | Amoxicillin | 37.5(24.9 – 51.5) | 49(39- 68) |
Ampicllin | 65.7(55.6 – 74.8) | ||
Piperacillin | 40.5(29.6 – 52.1) | ||
Cloxacillin | 48.6(36.4 – 60.8) | ||
Amoxiclav | 71.0 (61.5 – 79.4) | ||
Beta-lactam | Aztreonam | 51.4 (34.0 – 68.6) | 62.2 |
oxacillin | 73.0 (60.3 – 83.4) | ||
Quinolones | Ciprofloxacin | 37.7(26.3 – 50.2) | 39(36.8- 49.3) |
Norfloxacin | 39.2 (25.8 – 53.9) | ||
Ofloxacin | 55.9(45.2 – 66.2) | ||
Nalidixic acid | 42.9 (24.5 – 62.8) | ||
Levofloxacin | 32.0(19 – 46.7) | ||
Perfloxacin | 33.3 (23.2 – 44.7) | ||
Macrolides | Josamycin | 31.6 (12.6 – 56.6) | 42(33 - 52) |
Erythromycin | 33.9 (22.1 – 47.4) | ||
Clarithromycin | 42.2 (29.9 – 55.2) | ||
Roxithromycin | 57.9(33.5 – 79.7) | ||
Azithromycin | 62.1 (42.3 – 79.3) | ||
Aminoglycosides | Gentamicin | 17.6 (10.4 – 27.0) | 12.8(ð) |
Amikacin | 6.5 (0.8 – 21.4) | ||
Netilmicin | 12.8 (6.8 – 21.2) | ||
Glycopeptide | Vacomycin | 48.4 (30.2 – 66.9) | - |
Tetracyclines | Tetracycline | 31.3(11.0 – 58.7) | 27.1 |
Doxycycline | 27.1 (15.3 – 41.8) | ||
Monocycline | 38.5 (23.4 55.4) | ||
Antifolate | Trimethoprim | 75.0 (53.3 – 90.2) | - |
Nitrofurans | Nitrofurantoin | 49.3 (36.8 – 1.8) | - |
Antimycobacterial | Rifampicin | 59.4 (46.4 - -71.5) | - |
Chloramphenicol | 23.8 (8.2 – 47.2) | - | |
Antifungals | |||
Azoles | Fluconazole | 56.4 (46.2 – 66.3) | 31(16 - 62) |
Itraconazole | 9.5 (1.2 – 30.4) | ||
Econazol | 21.5 (15.4 – 28.8) | ||
Ketoconazole | 55.8 (47.6 – 63.7) | ||
Miconazole | 10.4(6.2 – 16.1) | ||
Clotrimazole | 41.0(30.0- 52.7) | ||
Polyenes | Nystatin | 68.7 (57.6 – 78.4) | 79.2 (ð) |
Amphotericin B | 89.6 (81.7 – 94.9) | ||
Allyl amines | Terbinafine | 50.0 (29.1 – 70.9) | - |
Others | Grisefulvin | 31.3 (`6.1 – 50.0) | - |
Isolate | Median resistance (IQR) |
|
41.5 (12.8 – 80.0) |
CoNS | 50 (11.0 – 73.0) |
|
29(0.0 – 57.5) |
|
61.0( 2.75 – 82.3) |
|
43.5(29 – 54.8) |
|
33.0 (0.0 – 60.0) |
|
71.0(45.6 – 89.5) |
|
50.0(14.0 - 100) |
|
17.0(0.0 – 61.8) |
|
33.0(0.0 – 51.0) |
|
40.0(20.3 – 59.0) |
Candida albicans | 43.50(19.75 – 70.0) |
Among the cephalosporins, cefixime showed 100% resistance to
Generally, among the 10 classes of drugs tested against the gram-positive bacteria in the study, only clarithromycin (a quinolone) and rifampicin (an antimycobacterial) showed resistance rate with a significant difference across the different category of gram-positive bacteria ( p-value 0.044 and 0.0001 respectively) (
For the resistance of
Antimicrobial Class | Antimicrobial | Isolated bacteriaResistance (%) | P Value | |||
|
CoNS |
|
|
|||
Cephalosporins | Cefuroxime | 0 | 0 | - | ||
Cefotaxime | 18.2 | 66.7 | - | 0.227 | ||
Ceftazidime | - | - | 50 | |||
Ceftriaxone | 75 | 33.3 | 33.3 | 0.510 | ||
Cefixime | 100 | - | 100 | - | - | |
Penicillin | Amoxicillin | 33.3 | 0 | 11.1 | 0.411 | |
Ampicllin | 50.0 | 60.0 | 50.0 | 100 | 0.895 | |
Piperacillin | 21.4 | 0 | 40 | 0 | 0.234 | |
Cloxacillin | 9.1 | 50.0 | 66.7 | 0.131 | ||
Amoxicillin clavulanic acid | 50.0 | 33.3 | 60 | 60 | 0.125 | |
Beta-lactam | Aztreonam | 80 | 66.7 | 0.315 | ||
oxacillin | 100 | 68.8 | 100 | 62.5 | 0.418 | |
Quinolones | Ciprofloxacin | 0 | 75 | 0 | 100 | 0.282 |
Norfloxacin | 100 | 0 | 0 | |||
Ofloxacin | 80.0 | 87.5 | 0 | 83.3 | 0.071 | |
Nalidixic acid | 100 | 73.3 | 100 | 100 | ||
Levofloxacin | - | 0 | - | - | - | |
Perfloxacin | 11.1 | 50 | 0 | 28.6 | 0.063 | |
Macrolides | Erythromycin | 55.6 | 35.3 | - | 50.0 | 0.351 |
Clarithromycin | 33.3 | 60.0 | 0 | 80 | 0.044 | |
Azithromycin | 100 | 80.0 | 0 | 100 | 0.145 | |
Aminoglycosides | Gentamicin | 20.0 | 50 | 0 | 66.7 | 0.199 |
Amikacin | 50.0 | 50.0 | 0 | - | 0.287 | |
Netilmicin | 22.2 | 11.1 | 33.3 | 14.3 | 0.741 | |
Glycopeptide | Vacomycin | 25 | - | - | - | - |
Tetracyclines | Tetracycline | 10.0 | 100 | 0 | 0 | 0.348 |
Doxycycline | 0 | 0 | 100 | 0 | 0.122 | |
Monocycline | ||||||
Antifolate | Trimethoprim | 0 | 35.7 | - | 0 | 0.298 |
Nitrofurans | Nitrofurantoin | 57.1 | 73.3 | 0.0 | 62.5 | 0.133 |
Antimycobacterial | Rifampicin | 91.7 | - | 25.0 | 0.0 | 0.00001 |
Antimicrobial Class | Antimicrobial | Isolated bacteriaResistance (%) | P-Value | ||||
|
|
|
|
|
|||
Cephalosporins | Cefuroxime | 42.9 | 100 | 100 | - | - | 0.582 |
Cefotaxime | 50.0 | 71.4 | 85.7 | 40.0 | 25.0 | 0.158 | |
Ceftazidime | 48.7 | 0 | 50.0 | 80.0 | 50.0 | 0.277 | |
Ceftriaxone | 11.4 | 57.1 | 20.0 | 33.3 | 0 | 0.025 | |
Cefixime | 43.9 | 50.0 | 85.7 | 50.0 | 66.7 | 0.420 | |
Penicillins | Amoxicillin | 33.3 | 60.0 | - | 66.7 | 60.0 | 0.796 |
Ampicllin | 74.5 | 25.0 | 0.0 | 14.3 | 16.7 | 0.011 | |
Piperacillin | 40.0 | 62.5 | 80.0 | 40.0 | 16.7 | 0.111 | |
Cloxacillin | 55.0 | 45.5 | 100 | 66.7 | 42.9 | 0.977 | |
Amoxiclav | 81.2 | 100 | 83.3 | 88.9 | 50.0 | 0.705 | |
Beta-lactam | Aztreonam | 53.8 | 50.0 | 66.7 | 0 | 0 | 0.192 |
oxacillin | 100 | 100 | 100 | 100 | 100 | ||
Quinolones | Ciprofloxacin | 38.7 | 0 | 33.3 | 20.0 | 0 | 0.183 |
Norfloxacin | 28.6 | 25.0 | 50.0 | 60.0 | 42.9 | 0.846 | |
Ofloxacin | 48.4 | 50.0 | 100 | 100 | 0 | 0.462 | |
Nalidixic acid | 71.4 | 0 | - | 100 | 100 | 0.362 | |
Levofloxacin | 40.0 | 0.0 | 60.0 | 0.0 | 0.0 | 0.249 | |
Perfloxacin | 11.8 | 16.7 | 0 | 100 | 100 | 0.111 | |
Macrolides | Erythromycin | 50.0 | 0.0 | - | - | 0.0 | 0.415 |
Clarithromycin | 0 | 0 | - | - | 0 | - | |
Azithromycin | - | - | 100 | - | - | ||
Aminoglycosides | Gentamicin | 10.9 | 33.3 | 50.0 | 0 | 0 | 0.052 |
Amikacin | 0 | 0 | 0 | 0 | - | 0.755 | |
Netilmicin | 4.2 | 5.9 | 50.0 | 25.0 | 0 | 0.200 | |
Glycopeptide | Vacomycin | 100 | 40.0 | - | - | - | 0.090 |
Tetracyclines | Tetracycline | - | |||||
Doxycycline | 40.0 | 0.0 | - | - | 66.7 | 0.090 | |
Antifolate | Trimethoprim | 79.6 | - | 80.0 | 100 | 100 | 0.853 |
Nitrofurans | Nitrofurantoin | 28.6 | 0.0 | - | 0.0 | 0.0 | 0.094 |
Antimycobacterial | Rifampicin | 54.2 | 71.4 | - | 100 | 0.0 | 0.016 |
Chloramphenicol | - | - | 75.0 | - | 0.0 | 0.171 |
Antimicrobial Class | Antimicrobial | Isolated bacteriaResistance (%) | P Value | |
|
|
|||
Beta-lactam | Aztreonam | |||
oxacillin | 0.0 | 56.2 | 0.471 | |
Quinolones | Ciprofloxacin | 50.0 | 0.0 | 0.264 |
Ofloxacin | 33.3 | 40.0 | 0.554 | |
Levofloxacin | 28.6 | 40.0 | 0.647 | |
Perfloxacin | 0.0 | 63.2 | 0.376 | |
Macrolides | Josamycin | 35.7 | 20.0 | 0.516 |
Erythromycin | 0.0 | 21.1 | 0.798 | |
Clarithromycin | 63.6 | 27.3 | 0.128 | |
Roxithromycin | 57.1 | 60.0 | 0.912 | |
Azithromycin | 53.8 | 60.0 | 0.895 | |
Glycopeptide | Vacomycin | 0.0 | 47.1 | 0.516 |
Doxycycline | 33.3 | 20.0 | 0.675 | |
Monocycline | 37.5 | 39.1 | 0.499 | |
Antifolate | Trimethoprim | - | 100 | |
Nitrofurans | Nitrofurantoin | 0.0 | 52.6 | 0.376 |
Among the antifungal agents, the highest resistance of
This study was designed to provide insight on the profile of AMR resistance and the capacity of antimicrobial susceptibility testing laboratories in the Deido Health District. It is worth noting that, the laboratories involved in this study are located within an urban setting were more the 60% of the Cameroon health workforce is concentrated. It has been proven that Antimicrobial resistance is a great threat in treating infectious diseases and it is increasing the cost of medical care
Quality laboratory diagnosis is paramount for containing and enhancing the appropriate usage of antimicrobials
This study showed that it took at least 3days for a culture result to be released. This can be justified by the fact that the laboratories only use conventional identification and AST techniques. The automated methods and point of care kit that provide faster results are not in use in these laboratories.
The findings in this study indicate that there is a need for more commitment to improving laboratory capacities of hospitals in Cameroon. There have been limited commitment by the Government on health care in Cameroon over the past years with only 4.7% of the national GDP currently allocated to health care with just about 8% of this budget allocated to improving health infrastructure and laboratory capacity
In this study, a total of 1797 samples were received by the laboratories for culture from the three hospitals within the study period. This number of cultures done within 5months seems small because these health facilities are secondary level health facilities in the most populated town in Cameroon They can be partially accounted for by the fact that national and local treatment guidelines in many resources limited countries still emphasize on empirical treatment as reported by a study in Tanzania with similar findings
The most frequently isolated pathogens were
Among the different pathogens isolated,
On the other hand, it was also found that, among the gram-positive bacteria isolates,
The antimicrobial resistance situation in the Deido Health District is preoccupying as is the case with other developing countries. Apart from aminoglycosides, pathogens showed an antibiotic class median resistance over 25% of the various antimicrobial agents. Despite the importance of testing in the fight against AMR, the laboratory turnaround time remains long and the laboratories are under-equipped and the quality of AST is seriously affected.
This study has shown there is a need to develop a coordinated national approach by Cameroon's ministry of public health to fight AMR with much priority on antimicrobial susceptibility testing. Scaling-up AST testing will, therefore, require strengthening the microbiology units of laboratory systems and ensuring the use of laboratory data for clinical decision-making.
The authors express sincere gratitude to the Faculty of Science University of Buea, Cameroon, the directors and laboratory staff of the hospitals involved, all the study participants and the littoral Regional Delegation of Public Health
This study was funded by the corresponding author and also received support from the faculty of Science University of Buea, Cameroon. However, the results and conclusions made in this publication are made by the authors and may not represent the official position of the faculty of Science University of Buea, Cameroon
AMR: antimicrobial resistance
AST: antimicrobial susceptibility testing
CLSI: Clinical and Laboratory Standard Institute
CSF: Cerebrospinal fluid
EUCAST: European Committee on Antimicrobial Susceptibility Testing
IRB: Institutional review board
SLIPTA: Stepwise Laboratory Quality Improvement Process towards Accreditation
US: Urethral Smear
VS: Vagina Smear
WHO: World Health Organization
All relevant data are included in this manuscript
This study protocol was reviewed and approved by the Faculty of Health Sciences Institutional Review Board (IRB) of the University of Buea, Cameroon (N0: 2019/941-01/UB.SG.IRB.FHS).
Not applicable
PAN conceived, designed and supervised the study implementation, CN conceived, designed, coordinated the study, analyzed the data and drafted the paper, ETA designed, coordinated the study and participated in drafted the paper, JKTA reviewed and corrected the study proposal and the final manuscript write up and DZ contributed in developing the manuscript. All authors read and approved the final manuscript