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Effects of Potentially Inappropriate Psychoactive Medications on Falls in US Nursing Home Residents^ Analysis of the 2004 National Nursing Home Survey Database

Neetu Agashivala and Wenchen K. Wu

St John's University, Queens, New York, USA

Abstract Background and Objective: Use of potentially inappropriate psychoactive medications (PIPMs) poses a serious threat of falls among elderly nursing home residents. This study was conducted to identify the effects of PIPMs on falls compared with use of other psychoactive medications among elderly US nursing home residents. Methods: The 2004 National Nursing Home Survey (NNHS) was used as the data source. Logistic regression was performed to ascertain the relationship between elderly residents who fell in the past 30 days and the use of PIPMs as per Beers' criteria in the presence of other risk factors. The data analysis was performed using SAS version 9,1. Results: The 2004 NNHS database includes data concerning 11 940 elderly residents in 1174 facilities. The mean age of the elderly residents was 84,1 ±7,97 years. Residents receiving PIPMs were at an increased risk of falling compared with those receiving other psychoactive medications (odds ratio [OR] = 0.830, p = 0.028) as well as compared with residents not receiving psychoactive medications (OR = 0,624, p< 0.001), In addition, residents' fall risk increased with an increase in the number of impaired activities of daily living (OR = 1,160, p < 0.001). Presence of depressed mood indicators was also identified as an important risk factor (OR= 1,256, p < 0,001). Use of bedrails had a protective effect on residents' fall risk (OR = 0.714, p<0.001). Demo- graphic factors such as male sex and White race were also significant fall-risk factors. Conclusion: Prevention of falls in elderly nursing home residents remains a challenge. Despite the recommendations of prescribing guidelines, PIPMs are still prescribed to elderly nursing home residents. Access to appropriate

t Related presentations: paper presented at the International Society for Pharmacoeeonomics and Outcomes Research (ISPOR) 13th Annual International Meeting; 2008 May 3-7; Toronto (ON), and the abstract published in Value Health 2008; 11 (3): A173.

854 Agashivala & Wu

psychoactive medications should be ensured. Residents with the identified risk factors should be closely monitored. Further research should be pursued to evaluate the impact on falls of potentially inappropriate medications in other therapeutic categories.

Background

Falls are common among elderly nursing home residents and may have harmful con- sequences. Statistics have shown that falls are the key factor in hip fractures and hospitalizations due to traumatic injuries among elderly.t''^' Pre- vious studies have identified psychoactive medi- cations to be the major therapeutic category of medications leading to fall risk among elderly nursing home residents.'̂ '̂ 1 However, not all psychoactive medications are of potential risk to elderly residents. Therefore, we aimed to assess the association of use of potentially inappro- priate psychoactive medications (PIPMs) and falls among elderly US nursing home residents compared with use of other psychoactive medi- cations, taking into consideration the presence of other risk factors.

Methods

The 2004 National Nursing Home Survey (NNHS), a nationally representative multistage sample of nursing homes and their residents, was used as the data source for this study.'̂ ^ All nur- sing homes that participated in the 2004 NNHS had at least three beds and were either certified (by Medicare or Medicaid) or had a state license to operate as a nursing home. The 2004 NNHS was redesigned and expanded to collect many new data items compared with its previous ver- sions. Medication and fall data were included for the first time in the survey. 1174 nursing homes participated in the survey and data were collected for a total of 13 507 residents.

The 2004 NNHS was administered in sampled nursing home facilities using a computer-assisted personal interviewing (CAPI) system. This con- tained two facility-level modules, two sampling modules and four resident-level modules that

were completed for up to 12 current residents in each sampled facility. After completing the re- sident sampling module, the four resident-level modules (health status [HS], health status - non- minimum data set {MDS} (HN), prescribed medications [PM] and sources of payment [PA]) were completed in no particular order for any sampled resident. The HS module collected data about a resident's health status documented in the MDS assessment that is federally mandated of all residents in a Medicare or Medicaid certi- fied nursing home. The HN module collected data about a resident's health status and medical care that were not available from the MDS. In the PM module, the nursing home respondent used the medication administration records to answer medication questions asked about each sampled resident. The questions were related to the medi- cations taken by the resident during the 24 hours the day before the interview and the medications taken regularly but not during the 24 hours the day before interview. A total of up to 50 medi- cations (25 for each question) per patient were allowed to be entered.t^'

Based on the literature review and the pre- liminary bivariate analysis, a fall model was developed to identify the effect of PIPMs on risk of falls among elderly nursing home residents (aged >65 years). To incorporate the effects of recent medications taken by the residents, falls were defined as the number of residents who fell over the past 30 days. Psychoactive medications were identified based on the national drug codes (NDCs) 0626-0635, which included sedatives, hypnotics, antianxiety agents, antipsychotics, antidepressants, anorexiants, antiemetics, sleep- aid products and other medications for CNS and Alzheimer-type dementia. Beers' criteria^ '̂ were used as the source to identify potentially in- appropriate medications among the elderly. Only the psychoactive medications from the updated

PIPMs and Falls in US Nursing Home Residents 855

2003 Beers' criteria based on the NDCs men- tioned above were selected as PIPMs (see Ap- pendix). As the N N H S database does not include dose level data, all the psychoactive medications identified by Beers' criteria were included in the study regardless of dose factor. PIPM was de- fined as a three-level variable with patients re- ceiving psychoactive medications listed in Beers' criteria, patients receiving psychoactive medi- cations not in Beers' criteria and patients not receiving psychoactive medications. The expla- natory variables in the fall model in addition to PIPMs were presence of mental disorders, pre- sence of depressed mood indicators, number of impaired activities of daily living (ADLs), use of bedrails, fall history (fall in the past 31-180 days), age, sex and race. Binary logistic regression was performed to determine the fall risk associated with the use of PIPMs in the presence of other risk factors. The data analysis for this study was performed using SAS version 9.1 for Win- dows (SAS Institute Inc., Cary, NC, USA). The SURVEYLOGISTIC procedure was used to incorporate complex survey sample design with stratification, clustering and unequal weighting. A linear regression model was also run to assess the multicoUinearity of the study variables.

Results

About 90% (n=11940) of the total sampled residents (n= 13 507) were elderly (aged >65 years). Of the 11 940 elderly residents, 4276 (35.81%) had fallen in the past 180 days, including 1845 ( 15.45%) who had fallen in the past 30 days; 701 (5.87%) had fallen in the past 30 days as well as in the past 31-180 days. The mean age of the elderly nursing home residents was 84.1 ±7.97 years. A higher percentage of residents (4.49%) who fell in the past 180 days suffered a hip fracture compared with residents (0.70%; p < 0.001) who did not fall in that period. Table I lists the key baseline characteristics of the residents. Nearly one-fifth (17.04%) of the elderly ntirsing home residents were receiving PIPMs. A hi¿ier proportion of residents who fell in the past 30 days (20.98%) were receiving PIPMs compared with those who did not fall in the past 30 days (16.32%; p<0.001). The individual risk factors

leading to falls and their risk based on the chi- squared (x^) test are summarized in table II.

Table III lists the results of application of the SURVEYLOGISTIC procedure to the fall model. The likelihood ratio test suggested that the model fitted well (p< 0.001). The multicoUinearity results showed that the independent variables were not correlated (results not reported). The results from the logistic regression showed that demographic factors such as male sex and race increased the risk of falling among nursing home residents. PIPMs were an important category of medications leading to increased falls among nursing home residents. The multivariate analysis showed a 20.5% in- creased risk among residents taking PIPMs com- pared with those taking other psychoactive medications, and a 60.3% increased risk compared with those taking non-psychoactive medications. Advancing age had no significant effect. Male sex was associated with a 48.4% increased risk of fall- ing compared with female sex. Ethnicity was also an important risk factor. White individuals had a 43.0% increased risk of falling compared with non- Whites. In addition, increased number of impaired ADLs and fall history were also significant fall-risk factors. Use of bedrails reduced the risk of falling by 28.6%. Presence of mental disorders did not have any significant effect. However, presence of depressed mood indicators was associated with a 25.6% increased risk.

Discussion

The literature has identified both an increase in the risk of adverse outcomes among elderly pa- tients using potentially inappropriate medica- tions'^"' 'Í and an extensive fall risk associated with the use of psychoactive medications.''*! Despite current knowledge of the effects of these medica- tions, the NNHS data revealed that a number of elderly nursing home residents were prescribed and receiving PIPMs (table I). This study evaluated the risk associated with use of PIPMs on falls compared with other psychoactive medications in elderly nursing home residents. Beers' criteria'^l were used as the reference guide to identify use of PIPMs in nursing home residents. Beers' criteria are increasingly being used as the quality of care

856 Agashivala & Wu

Table I. Baseline characteristics of elderly nursing home residents

Resident characteristics

Sex

female

male

Race

Whites

non-Whites

Living alone before entering facility

Ail psychoactive medications

PIPMs

other psychoactive medications

Mental disorders"

dementia*"

depression"

All residents [n (%)]

11940

8879(74,4)

3061 (25,6)

10668(89,4)

1272(10,6)

1 669 (14,0)

8198(68,7)

2035(17,0)

6164(51,6)

7880(66,0)

4233(35,5)

4247(35,6)

Decision-making ability regarding tasks of daiiy iife

independent or modified independent

moderateiy or severely impaired

Depressed mood indicators

no mood indicators

indicators present

Impairment in ADLs

transfer (move between surfaces)

walking in room or corridor

locomotion on/off unit

bathing

dressing

toilet use

5083(42,6)

6857(57,4)

6809(57,0)

5131 (43,0)

8477(71,0)

4115(34,5)

7626(63,9)

11040(92,5)

9839(82,4)

9215(77,2)

Residents who fell in past 30 days [n (%)]

1845

1275(69,1)

570 (30,9)

1 721 (93,3)

124(6,7)

264 (14,3)

1 388 (75,2)

387(21,0)

1 001 (54,3)

1 224 (66,3)

663 (35,9)

668 (36,2)

733 (39,7)

1112(60,3)

930 (50,4)

915(49,6)

1416(76,8)

919(49,8)

1 278 (69,3)

1 735 (94,0)

1 623 (88,0)

1 530 (82,9)

Residents who did not fall in past 30 days [n (%)]

10095

7604(75,3)

2491 (24,7)

8947(88,6)

1148(11,4)

1405(13,9)

6810(67,5)

1648(16,3)

5163(51,1)

6656(65,9)

3570(35,4)

3579(35,5)

4350(43,1)

5745(56,9)

5894(58,4)

4201 (41,6)

7061 (70,0)

3196(31,7)

6348(62,9)

9305(92,2)

8216(81.4)

7685(76.1)

a Mental disorders include ICD-9 codes 290,-319.

b Dementia includes ICD-9 codes 290-294,

c Depression includes ICD-9 codes 296 and 311.

ADLs = activities of daiiy iiving; ICD-9 = International Classification psychoactive medications.

of Diseases, Ninth Revision; PIPMs = potentially inappropriate

measure in the elderly. The Health Plan Employer Data and Information Set (HEDIS) measures in- cludes a list of inappropriate medications based on Beers' criteria to assess quality of care in managed healthcare plans.''^' The results of this analysis showed that use of PIPMs as per Beers' criteria among elderly nursing home residents increased the risk of falling significantly. This increased risk was sustained in the study model even after adjust- ing for other confounding factors (table III). The effects of PIPMs demonstrated in this study

were consistent with those of previous studies as- sessing the risk of the whole therapeutic class of psychoactive medications on falls among nursing home residents. For example, a study of commu- nity-dwelling older people by Landi et al.''*' reported an increased risk of falls of nearly 47% associated with the use of psychoactive medica- tions after adjustment for potential confounders. The effects of PIPMs in the current study were also consistent with those of previous studies assessing the effect of potentially inappropriate medications

PIPMs and Falls in US Nursing Home Residents 857

on adverse health outcomes among the elderly. However, none of the previous studies focused specifically on the risk of these medications on the most severe adverse outcome, namely, falls. The study by Chang et al.I'̂ l reported a 15.3% increased risk of adverse drug reactions if potentially in- appropriate medications were prescribed. Fur- thermore, the results of the study by Perri et al.'"' showed that inappropriate medication use in- creased the likelihood of experiencing at least one adverse health outcome more than 2-fold. However, these studies monitored the correlation of potentially inappropriate medications with ad- verse health outcomes such as hospitalization, emergency room visits or death.

Impairment of ADLs is also one of the most important risk factors for falling.''^'''*' Impaired ADLs were included as a continuous variable in the study model, with only those ADLs that had been linked with falls in nursing home residents in previous studies being included. This study showed that the risk of falling increased significantly with an increase in the number of impaired ADLs. These results confirmed previous study results showing that impaired ADLs can be a significant risk factor for falling, and that residents with impairments in ADLs should be closely mon- itored. Fall history has been identified as a major fall concern in the literature;''^''^''^] this study also confirmed that fall history can be an im- portant factor in identifying high-risk residents. Residents with a history of falls should be given special attention and the necessary precautionary measures to prevent subsequent falls.

Fall prevention studies have identified that physical restraints are not an important factor in controlling the fall rate among nursing home re- sidents.t'''-'^' However, use of bedraiis was in- cluded as an independent variable in the study model and was found to confer a significant pro- tective effect against fall risk among the residents. The reason for this disparity might be that the fall risk was not adjusted for propensity of falling in previous studies or in the present study. There might have been selection bias, whereby residents who were already at an increased risk of falls were subjected to physical restraints. However, this drawback was partly overcome in the present study by use of a national database. Nevertheless, further analysis is warranted with risk adjustment for propensity of falling. The results of this study also showed that there was a higher incidence of hip fractures among patients who fell, an im- portant finding given the high cost of hip fracture management.

Contrary to our expectation, elderly residents with mental disorders were at no greater risk of falls than other nursing home residents. Mental disorders included Alzheimer's disease and other dementias, depression and other disorders related to the CNS (table I). Although previous studies have reported that fall risk is higher among re- sidents with dementiat'^-'^i and depression,!^"- '̂' our analysis of the NNHS data suggested that mental disorders are not an important or likely risk factor for falling. Such an unexpected result might be due to methodological shortcomings of previous studies; for example, no comparison

Table II. Individual risk factors for falis in the past 30 days based on the chi-squared (x^) test

Risi< factor

Sex (1 = maie, O=femaie)

Race (1 =Whites, O = non-Whites)

Ail psychoactive medications

PIPMs

Mental disorders"

Mood indicators

Bedraiis

Fali history (faii in past 31-180 days)

a Mental disorders inciudes ICD-9 codes 290-319.

Odds ratio

1.349

1.799

1.507

1.349

1.086

1.424

0.735

1.923

95% CI

1.335, 1.363

1.768,1.830

1.491, 1.524

1.333, 1.366

1.075, 1.097

1.411, 1.438

0.724, 0.747

1.904,1.943

p-Vaiue

<0.001

ICD-9 = lnternationai Classification of Diseases, Ninth Revision; PIPMs=potentially inappropriate psychoactive medications.

858 Agashivala & Wu

Table III. Logistic regression analysis ot relationship between tail in past 30 days and use ot potentiaily inappropriate psychoactive medications (PIPMs)

Risk tactor

Age

Sex (1 = male, O=teniiale)

Race (1 = Whites, 0=non-Whites)

Medications

PIPMs

other psychoactive medications

non-psychoactive medications

Mental disorders'*

Mood indicators

Number ot impaired ADLs"

Bedraiis

Fall history (tall in past 31-180 days)

Odds ratio

1,007

1,484

1,430

1,000»

0,830

0,624

0,879

1,256

1,160

0,714

1,697

95% CI

1,000, 1,015

1,294,1,701

1,159,1,764

0,702, 0,980

0,516,0,754

0,763,1.012

1,108,1,423

1,113,1,209

0,593, 0,860

1,475, 1,953

Standard error

0,0039

0,0697

0,1071

0,0851

0,0967

0,0719

0,0637

0,0211

0,0947

0,0717

p-Value

0.064

<0,001

0,028

<0,001

0,073

<0,001

a Reterence standard,

b Mental disorders inciude ICD-9 codes 290-319,

c Impaired ADLs include walking in room/corridor, iocomotion on/ott unit, transter, bathing, dressing and using the toilet,

ADLs == Activities ot Daiiy Living; ICD-9 = International Classitication ot Diseases, Ninth Revision,

group, limited data sources and less general- izabiiity. These limitations have been overcome in the current study through the use of multi- variate analysis and a national database. Also, the residents diagnosed with mental disorders may have received special care for fall risk pre- vention in the nursing home. Future research should be conducted to explore the factors that may have an impact on the propensity of receiv- ing fall risk preventive care for nursing home re- sidents.

The variable 'mood indicators' was defined as presence of subjective signs and symptoms of depression and sad mood. This category differs from the 'mental disorders' variable in that pa- tients in the 'mental disorders' category had a clinical diagnosis of depression, while the 'mood indicators' category includes patients showing signs of, but not necessarily diagnosed with, depression. Furthermore, the multicollinearity results found no correlation between mental dis- orders and mood indicators. Presence of mood indicators posed a serious risk of falling in elderly nursing home residents; the findings in our study showed about a 25% increased risk for residents who had indicators of depression, anxiety or sad mood. These results suggest that these patients

might not have been diagnosed as having a mental or mood disorder and would have re- mained untreated, thereby increasing their risk of falling.

Most previous studies of falls in US nursing homes have been conducted in individual nursing homes or in a small number of nursing homes, whereas a nationally representative sample of nursing homes and nursing home residents with medication use profiles was used in this study. This confers the advantage of better general- izability of the results arising from the study. However, there were certain limitations pertain- ing to the fall data in the NNHS database. The NNHS database contains fall information for the past 30 days at the time of interview, but has information only on the medications being taken at the time of interview - it does not provide information on the medications taken by the residents over previous months. However, nursing home residents are usually prescrib- ed medications every 30 days, and it was accord- ingly assumed that any changes in prescribed medications during the past 30 days might have an effect on falls. The files included information only on the residents who had fallen in the past 30 days and the past 31-180 days; the total

PIPMs and Falls in US Nursing Home Residents 859

number of falls was not included. Information on the circumstances and severity of fall was also not available. Because of the limitations of the data- base, all psychoactive medications listed in the Beers' criteria were included in the study model regardless of dose factor. The class of short- acting benzodiazepines (including lorazepam, oxazepam, alprazolam, temazepam and triazo- 1am) is listed as potentially inappropriate only above a particular dose in the Beers' criteria, whereas the model used in this analysis included these medications regardless of dose. Excluding these medications from the PIPM list still meant the risk of falling was increased, but the risk was a little lower compared with the current results.

Based on the results of this analysis of a nationally representative sample of nursing home residents, we recommend that use of PIPMs should be avoided in elderly subjects. However, there are some issues surrounding the prescribing of these medications. These PIPMs include many anti- depressants such as selective serotonin reuptake inhibitors and tricyclic antidepressants, benzo- diazepines and certain antipsychotics, which also have an inherent risk of increasing falls (see Ap- pendix). Although these medications have been listed as potentially inappropriate in the Beers' criteria, in practice, physicians continue to pre- scribe them to elderly patients. Indeed, some of these medications are considered the first-line choice in elderly patients. While it is possible that these medications are being prescribed at lower doses in the elderly, caution still needs to be ex- ercised when prescribing them to elderly nursing home residents until newer and safer medications have been developed to replace these potentially inappropriate medications in this population.

Conclusions

The current study is the first to identify the risk of PIPMs among elderly nursing home residents using a nationally sampled database. PIPMs were identified as an important risk factor for falls and should be avoided among elderly nursing home residents. Although there are other factors (such as patient requests, preferred drug lists and

direct-to-consumer advertising) that may infiu- ence the decision-making process for prescribing medications, the statistically significant associa- tion between PIPMs and falls demonstrated in this study should encourage healthcare providers to re-examine the use of these medications among elderly nursing home residents. Furthermore, newer medications with low fall risk should also be developed.

Acknowledgements

No sources of funding were used to assist in the prepara- tion of this study. The authors have no conflicts of interest that are directly relevant to the contents of this study.

Appendix

List of PIPMs as per Beers' criteria! '̂ and ICD-9 codes 0626-0635:

Flurazepam Amitriptyline Chlordiazepoxide/amitriptyline Perphenazine/amitriptyline Doxepin Meprobamate Lorazepam Oxazepam Alprazolam Temazepam Triazolam Chlordiazepoxide Clidinium/chlordiazepoxide Diazepam Quazepam Halazepam Chlorazepate Hydroxyzine Amphetamines and anorexic agents Daily fiuoxetine Thioridazine Mesoridazine.

References 1. Fuller GF. Falls in the elderly. Am Fam Physician 2000; 61

(7): 2159-68 2. Marin PP. Latin-American regional review on falls in older

people [online]. Available from URL: http://www.who.int/ ageing/projects/AMRO-Chile.pdf [Accessed 2007 Nov 18]

860 Agashivala & Wu

3. Cooper JW, Freeman MH, Cook CL, et al. Assessment of psychotropic and psychoactive drug loads and falls in nursing facility residents. Consult Pharm 2007; 22 (6): 483-9

4. Landi F, Onder G, Cesad M, et al. Psychotropic medica- tions and risk for falls among community-dwelling frail older people: an observational study. J Gerontol A Biol Sei Med Sei 2005; 60 (5): 622-6

5. Souchet E, Lapeyre-Mestre M, Montastruc JL. Drug related falls: a study in the French Pharmacovigilanee Database. Pharmacoepidemiol Drug Saf 2005; 14 (1): 11-6

6. US Department of Health and Human Services, National Center for Health Statistics. National Nursing Home Survey, 2004 [online]. Available from URL: ftp://ftp.cdc.gov/puly Health_Statistics/NCHS/Datasets/NNHS/nnhsO4/[Ac- cessed 2007 Apr 13]

7. US Department of Health and Human Services, National Center for Health Statistics. National Nursing Home Survey (NNHS) [online]. Available from URL: http:// www.cdc.gov/nchs/nnhs.htm [Accessed 2009 Feb 1]

8. Fick DM, Cooper JW, Wade WE, et al. Updating the Beers criteria for potentially inappropriate medication use in older adults. Arch Intern Med 2003; 163 (22): 2716-24

9. Fu AZ, Liu GG, Christensen DB. Inappropriate medication use and health outcomes in the elderly. J Am Geriatr Soc 2004; 52 (11): 1934-9

10. Chang CM, Liu PY, Yang YH, et al. Use of the Beers criteria to predict adverse drug reactions among first-visit elderly outpatients. Pharmacotherapy 2005; 25 (6): 831-8

11. Perd 3rd M, Menon AM, Deshpande AD, et al. Adverse outcomes associated with inappropdate drug use in nursing homes. Ann Pharmacother 2005; 39 (3): 405-11

12. National Committee for Quality Assurance. HEDIS 2008 fmal NDC lists [online]. Available from URL: http:// www.ncqa.org/tabid/598/Default.aspx [Accessed 2008 Aug 12]

13. Kiely DK, Kiel DP, Burrows AB, et al. Identifying nursing home residents at dsk for falling. J Am Gedatr Soc 1998; 46 (5): 551-5

14. Cigolle CT, Langa KM, Kabeto MU, et al. Gedatric con- ditions and disability: the Health and Retirement Study. Ann Intern Med 2007; 147 (3): 156-64

15. Van DC, Gruber-Baldini AL, Zimmerman S. Dementia as a dsk factor for falls and fall injudes among nursing home residents. J Am Gedatr Soc 2003; 51 (9): 1213-8

16. Lowery K, Bud H, Ballard C. What is the prevalence of environmental hazards in the homes of dementia sufferers and are they associated with falls? Int J Geriatr Psychiatry 2000; 15 (10): 883-6

17. Capezuti E, Strumpf NE, Evans LK, et al. The relationship between physical restraint removal and falls and injudes among nursing home residents. J Gerontol A Biol Sei Med Sei 1998; 53A(l):M47-52

18. Tinetti ME, Wen-Liang L, Ginter SF. Mechanical restraint use and fall-related injudes among residents of skilled nursing facilities. Ann Intern Med 1992; 116 (5): 369-74

19. French DD, Werner DC, Campbell RR, et al. A multivadate fall dsk assessment model for VHA nursing homes using the minimum data set. J Am Med Dir Assoc 2007; 8 (2): 115-22

20. Kose N, Cuvalci S, Ekici G, et al. The dsk factors of fall and their correlation with balance, depression, cognitive im- pairment and mobility skills in elderly nursing home residents. Saudi Med J 2005; 26 (6): 978-81

21. Jantti PO, Pyykko I, Laippala P. Prognosis of falls among el- derly nursing home residents. Aging (Milano) 1995; 7 (1): 23-7

Correspondence: Neetu Agashivala, Outcomes Research Fellow, Novartis Pharmaceuticals/Rutgers University, 60 Johnson Ave, Cranford, NJ 07016, USA. E-mail: [email protected] Alternative correspondence: Dr Wenchen K. Wu, St John's University, Department of Pharmacy and Administrative Sciences, 8000 Utopia Parkway, Queens, NY 11432, USA. E-mail: [email protected]

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