Task-sharing interventions for cardiovascular risk reduction and lipid outcomes in low- and middle-income countries: A systematic review and meta-analysis

Journal of Clinical Lipidology (2018) -, -–-

1 2 3 Original Article 4 5 6 7 8 9 10 11 12 13 14 15 Q11 T. N. Anand1, Linju M. Joseph1, A. V. Geetha, Joyita Chowdhury, 16 Q1 17 Q5 Dorairaj Prabhakaran, Panniyammakal Jeemon* 18 19 20 Q2 Public Health Foundation of India, New Delhi, India (Drs Anand, Joseph, Geetha, and Prabhakaran); Centre for Chronic Disease Control, New Delhi, India (Drs Chowdhury and Prabhakaran); and Sree Chitra Tirunal Institute for Medical 21 Sciences and Technology, Trivandrum, Kerala, India (Dr Jeemon) 22 23 24 BACKGROUND: One of the potential strategies to improve health care delivery in understaffed lowKEYWORDS: 25 and middle-income countries (LMICs) is task sharing, where specific tasks are transferred from more Cardiovascular; 26 qualified health care cadre to a lesser trained cadre. Dyslipidemia is a major risk factor for cardiovasDyslipidemia; 27 cular disease but often it is not managed appropriately. LDL-cholesterol; 28 OBJECTIVE: We conducted a systematic review with the objective to identify and evaluate the effect Task shifting; 29 of task sharing interventions on dyslipidemia in LMICs. Task sharing 30 METHODS: Published studies (randomized controlled trials and observational studies) were identi31 fied via electronic databases such as PubMed, Embase, Cochrane Library, PsycINFO, and CINAHL. We searched the databases from inception to September 2016 and updated till 30 June 2017, using 32 search terms related to task shifting, and cardiovascular disease prevention in LMICs. All eligible 33 studies were summarized narratively, and potential studies were grouped for meta-analysis. 34 RESULTS: Although our search yielded 2938 records initially and another 1628 in the updated 35 search, only 15 studies met the eligibility criteria. Most of the studies targeted lifestyle modification 36 and care coordination by involving nurses or allied health workers. Eight randomized controlled tri37 als were included in the meta-analysis. Task sharing intervention were effective in lowering low38 density lipoprotein cholesterol (26.90 mg/dL; 95% CI 211.81 to 21.99) and total cholesterol 39 (29.44 mg/dL; 95% CI 217.94 to 20.93) levels with modest effect size. However, there were no 40 major differences in high-density lipoprotein cholesterol (20.29 mg/dL; 95% CI 20.88 to 1.47) 41 and triglycerides (214.31 mg/dL; 95% CI 233.32 to 4.69). The overall quality of evidence based 42 on Grading of Recommendations Assessment, Development and Evaluation was either ‘‘low’’ or ‘‘very low’’. 43 CONCLUSION: Available data are not adequate to make recommendations on the role of task 44 sharing strategies for the management of dyslipidemia in LMICs. However, the studies conducted 45 in LMICs demonstrate the potential use of this strategy especially in terms of reduction in 46 47 48 1 These authors contributed equally to this article. E-mail address: [email protected] 49 * Corresponding author. Achutha Menon Centre for Health Science Submitted October 17, 2017. Accepted for publication February 13, 50 Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, 2018. Trivandrum, Kerala, India, 695011. 51

Task-sharing interventions for cardiovascular risk reduction and lipid outcomes in low- and middle-income countries: A systematic review and meta-analysis

1933-2874/Ó 2018 Published by Elsevier Inc. on behalf of National Lipid Association. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/). https://doi.org/10.1016/j.jacl.2018.02.008 FLA 5.5.0 DTD  JACL1262_proof  9 March 2018  5:17 pm

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low-density lipoprotein cholesterol and total cholesterol levels. Our review calls for the need of well-designed and large-scale studies to demonstrate the effect of task-sharing strategy on lipid management in LMICs. Ó 2018 Published by Elsevier Inc. on behalf of National Lipid Association. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Q3

Q6

Introduction Consequent to epidemiologic transition, and population ageing, low- and middle-income countries (LMICs) are battling a double burden of disease. For example, LMICs are experiencing a rapid increase in noncommunicable diseases (NCDs), on top of the existing burden of communicable diseases, maternal health conditions, and nutritional disorders.1 The population size of an LMIC is huge, and therefore, nearly 80% of the total 40 million deaths attributable to NCDs in absolute terms occur in these countries.2 Cardiovascular diseases (CVDs) are the leading contributor to NCD mortality and morbidity even in LMICs. Largely CVD comprises of heart attack (myocardial infarction), angina, and stroke. The principal risk factors contributing to CVD are unhealthy diets, physical inactivity, exposure to tobacco smoke, and harmful alcohol consumption. These risk factors may lead to intermediatelevel risk factors such as obesity, elevated levels of blood pressure, blood glucose, and blood lipids.3 Elevated blood lipids along with other risk factors are linked to CVD events, and the risk operates across the range of lipid profile, with moderate reduction at the population level resulting in huge gain in terms of averted mortality and morbidity.4 It has been estimated that, a 10% reduction in serum cholesterol in men aged 40 years is associated with a 50% reduction in heart disease within 5 years; the same serum cholesterol reduction for men aged 70 years may result in an average 20% reduction over the next 5 years.5 Shifting the population distribution of serum cholesterol toward the left of the distribution curve, even marginally, requires a combination of population-wide primary prevention efforts addressing multiple risk factors and high-risk secondary prevention strategies. However, the health workforce available in LMICs to address the dual burden of both communicable diseases and NCDs are very limited. For instance, on an average, there are 0$3, 1$2, and 2 physicians available for 1000 population in low-income countries, LMICs, and upper middle-income countries, respectively.6 In resource constrained settings with nonoptimal skilled workforce, it would be a desirable choice in using the existing nonphysician health care workers (NPHW) for the prevention and control of NCDs. Task shifting or task sharing or task delegation or skills substitution are all referred as the process of engaging NPHW in prevention and control of NCDs in the context of LMICs.7 However, it is not clear whether these strategies would be effective in cholesterol

reduction in individuals and communities. Previous studies demonstrate that task-sharing strategies for hypertension and diabetes management are both viable8,9 and cost-effective10 options in LMICs. The primary focus of the current review is to identify and understand the various task-sharing interventions used in the management of dyslipidemia in LMICs, and their cumulative effect on total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triglycerides (TGs). We aimed to generate evidence to support informed policy decisions on the role of task-sharing strategies for the management of dyslipidemia in LMICs and provide recommendations on the need for future research.

Methods Definitions Task sharing is defined as the rational redistribution of tasks to an existing or new cadre of health workers with either less training in general or lack of disease-/skillspecific training. It involves sharing the delivery of the task from professionals to health workers with fewer qualifications or creating a new workforce with specific training for a specific task.11 Health professionals working together in teams to deliver a task that they may not have undertaken previously is also considered as task sharing.5 We searched the published literature for studies (randomized controlled trials [RCTs], observational studies, and before and after studies) conducted in LMICs that included a task-shared intervention, delivered by nurses or NPHW in primary health centers or hospitals. Outcome measures included were TC, LDL-c, HDL-c, and TGs. Only studies in adult participants were considered.

Exclusions Studies with patient’s knowledge, attitudes, or intentions as outcome variables without measuring any of the relevant lipid outcomes were excluded. Interventions that involve only peer groups were excluded as they would be more likely to be informal support. In addition to these, tasksharing activities that are exclusive to traditional healers and those with just the promotion of self-care management or informal care giver health education were excluded in this review. Studies that do not report change in TC or LDL-c were also excluded.

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159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214

Anand et al 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270

Task sharing interventions and lipids

Search strategy A systematic literature search independent in 5 bibliographic databases (PubMed, Cochrane Library, CINAHL, Embase and PsycINFO) was conducted from inception to September 2016. We adapted a search strategy from a previous review in 2014,8 initially modified it (Appendix 1, online supplement) for PubMed, and further modified appropriately for other databases. Comprehensive search was carried out for studies performed in LMICs classified according to the World Bank Lending Group,12 and then it was updated again in PubMed by adding the search term ‘‘Sub-Saharan Africa’’. No limits on language or publication year were applied during the literature search. The keywords used were categorized into 3: for finding disease, for identifying task-shifted intervention, and for finding studies carried out in LMICs. The keywords were combined using appropriate Boolean operators such as ‘‘cardiovascular disease’’ OR ‘‘hyperlipidemia’’ OR ‘‘diabetes’’ OR ‘‘heart failure’’ AND ‘‘task’’ OR ‘‘shifted’’ OR ‘‘shared’’ OR ‘‘nonphysician health care worker’’ OR ‘‘community care worker’’ AND ‘‘developing countries’’ OR ‘‘low-income countries’’ OR ‘‘resource poor’’. Bibliographies of relevant studies were searched, and cross-referenced to identify any additional studies relevant for inclusion.

Data collection and analysis Selection of studies Two investigators (A.T.N. and L.M.J.) independently reviewed titles and abstract of all relevant articles identified. Those studies that appeared to be on task-sharing interventions for CVD prevention or management in an LMIC were selected for full-text review. A.T.N. and L.M.J. further reviewed these full-text articles independently to identify studies on lipid management. A third investigator (P.J.) served as a tiebreaker, independently reviewing articles to resolve the disagreement between the other 2 investigators. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was followed to report the review process.13

Data management and statistical analysis Data extraction was carried out by 2 investigators (A.T.N. and L.M.J.). Queries regarding data extraction were resolved mutually by returning to the original article and reviewing the data. Studies were grouped in terms of countries of focus, the cadres discussed, the disease focused, and interventions used for control of lipids. The interventions were summarized narratively. After data extraction, task-sharing interventions in all studies were summarized using narrative synthesis. Eligible RCTs were grouped to perform a meta-analysis. The quality of individual studies was appraised using National

3 Heart, Lung, and Blood Institute14 quality assessment scale for nonrandomized before and after studies. This tool contains 12 items on the risk of potential for selection bias, information bias, measurement bias, and confounding. Cochrane Risk of Bias Tool was used for assessing the quality of RCTs. This tool examined randomization procedure, allocation concealment, blinding of outcome assessors, incomplete outcome data, and selective outcome reporting. For the cluster trials, we evaluated recruitment bias, baseline imbalances, loss of clusters, incorrect analysis, and comparability with individual RCT as outlined in the Cochrane Handbook for Systematic Reviews of Interventions.15 Two independent reviewers (A.T.N. and L.M.J.) assessed risk of bias, differences between reviewers were resolved by discussion with a third reviewer (P.J.), and a consensus was reached. Meta-analyses of eligible RCTs were conducted on each outcome of interest independently. Study results were synthesized based on outcome measures of the included studies. We used R version 3.3.2 with ‘‘metaphor and meta’’ packages for meta-analysis. Mean difference (MD) in cholesterol levels between the intervention, and control arm were estimated. Cholesterol values expressed in mmol/ L was converted to mg/dL. Overall effects were calculated by combining the individual study effects using random effects model, and estimates were reported with 95% CI. To detect heterogeneity, we used Q statistics and I2 values. Appropriate subgroup analyses were also conducted. Funnel plots and Egger’s regression test for funnel plot asymmetry were performed. We assessed the quality of the evidence for each outcome across studies included in the meta-analyses according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.16 The quality of evidence was rated as high, moderate, low, or very low after determination of within-study risk of bias (methodological quality), directness of evidence, heterogeneity, the precision of effect estimates, and risk of publication bias.

Results Our search yielded a total of 2938 potential citations from PubMed (n 5 1025), Cochrane Library (n 5 159), Embase (n 5 647), CINAHL (n 5 709), and PsycINFO (n 5 398). Duplicates were removed (n 5 61). Title screening initially removed 2504 articles. All the remaining 373 abstracts were analyzed for eligibility, and 255 abstracts were excluded. Additional 12 articles from hand search (citation and references) were obtained. In total, 130 articles were initially included for full-text reading, and 117 of them were discarded based on the full-text review. The reasons for exclusion of articles during full-text review were nonavailability of outcomes of cardiovascular risk reduction (n 5 9), not being done in LMICs (n 5 8), interventions without task-sharing strategy (n 5 24),

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absence of outcomes related to lipids management (n 5 61), and others such as conference papers, abstracts, and review (n 5 15). We further updated our search in PubMed till 30 June 2017 (n 5 1628). 163 abstracts were

reviewed and 4 full texts were found and finally 2 studies were added. Finally, 15 articles were included in the detailed review, and presented in the PRISMA flow diagram.13 (Fig. 1).

Figure 1 Flow diagram showing literature search and final articles included in the review. SMS, short messaging service; CHW, community health worker; CKD, chronic kidney disease; LMIC, low- and middle-income countries; LDL, low-density lipoprotein; HDL, Q12 high-density lipoprotein; CVD, cardiovascular disease. FLA 5.5.0 DTD  JACL1262_proof  9 March 2018  5:17 pm

383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438

439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 Characteristics of studies included in this review Sample, intervention control

Setting, duration

Intervention and control group

High-risk group such as overweight or obese adults and relatives of patients with type II diabetes mellitus

Nutritionist

104, I 5 51, C553

Primary health centre, 12 mo

I: Individualized dietary counseling C: Routine care

Changes in CVD risk factors (blood pressure, lipids, diabetes, obesity)

RCT

Coronary heart disease

Nurses

167, I 5 83 C 5 84

Tertiary medical centre and home, 12 wk

I: Hospital-based patient/family education and home-based cardiac rehabilitation. C: Routine care

Mollaoglu et al Turkey, 200919

RCT

Diabetes

Nurses

50, I 5 25 C 5 25

Hospital and home

Andryukhin et al Russia, 201020

RCT

Heart failure

Nurses

85, I 5 44 C 5 41

GP Practice and home, 12 mo

I: Predischarge health education for metabolic control and follow-up at home. C: Routine care I: Educational programme for patients with heart failure C: Patients managed with Russian

1. Lifestyle parameters: smoking cessation, walking performance, step II diet adherence 2. Clinical (serum lipids, body weight and blood pressure) Clinical parameters: HbA1c, FBS PPBS, urine glucose, and cholesterol (total cholesterol, TG, HDL-c, and LDL-c). 1. Lifestyle parameters: 6-min walking test New York Heart Association Class of CHF, BMI, WC

Study design

Sartorelli et al Brazil, 200517

RCT

Jiang et al China, 200618

Disease type

Main lipid results from studies

Outcomes measured

At the 6-mo followup, significant difference in total cholesterol (212$3% vs 0$2%) and (LDLc) (215$5% vs 14$0%) (P, .05). At 12-mo follow-up, the reduction in LDL-c levels (213$3%) in the intervention group was significant when compared with baseline. The intervention was successful in reducing TG, TC, and LDL-c at both 3 mo (P , .01, P , .001) and 6 mo (P , .05, P , .001) but no difference was observed for HDL. Total cholesterol and LDL-c were found to have a significant difference after nurse education.

Task sharing interventions and lipids

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Task shifted to/shared with

Author, country, year reported

Anand et al

Table 1

Significant improvement in total cholesterol, low-density lipoprotein, after 6 mo for

5

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551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 6

Table 1

(continued )

Author, country, year reported

Study design

Disease type

Task shifted to/shared with

Sample, intervention control

Setting, duration

Intervention and control group National guidelines.

RCT

Dyslipidemia

Nurse educators

297, I 5 122 C 5 123

Primary care practices, 36 wk

Saffi et al Brazil, 201422

RCT

Coronary heart diseases

Nurses

74, I 5 38 C 5 36

Tertiary referral hospital, 12 mo

I: physician and nurse educator COACH Programme received biweekly telephone followup by trained nurse educators and reinforcement for medication adherence. C: usual care(PCP alone) I: individual counseling sessions and telephone follow-up C: usual care

Main lipid results from studies

Change in HbA1c at 6 mo. Other outcomes were changes in other clinical outcomes (BMI, blood pressure and blood lipids), HbA1c and dietary behaviors at 12 mo.

intervention group. Total cholesterol. mmol/L, Median, IQR Baseline C: 5.53 (5.31–6.13) I: 6.10 (5.72–6.42) At 6 mo C: 5.60 (5.43–6.18) I: 5.30 (5.28–6.05) LDL-c mmol/L, median, IQR Baseline C: 3.57 (3.34–4.03) I: 3.795 (3.58–4.28) At 6 mo C:3.72 (3.62–4.28) I: 3.505 (3.34–4.04) Intervention group showed better improvements in both LDL-c and TC levels when patients were co-managed by nurse educators but was not statistically significant.

Reduction of estimated 10-y CVD risk (Framingham Risk Score). Clinical (lipid profile, blood glucose, HbA1c) and

Total cholesterol mg/dL (mean and SD) at 1 y 175 6 53 vs 173 6 33, P 5 .24, LDL-c mg/dL (mean and SD) at 1 y 99 6 47 vs 96 6 25, P 5 .03, HDL-c

2. Clinical parameters of blood plasma levels of fasting blood glucose, total cholesterol, LDL-c, CRP, (high sensitivity method) and NT-pro BNP

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Selvaraj et al Malaysia, 201221

Outcomes measured

607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662

663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 Cluster RCT

Diabetes

Health promoter

1570 I 5 860 C 5 710

Community health centers, 12 mo

I: group diabetes education led by a health promoter. C: usual care

Muchiri et al South Africa, 201524

RCT

Diabetes

Dietitian

82 I 5 41 C 5 41

Community health centers, 12 mo

I: Nutrition Education programme C: group participants received education materials (pamphlet and wall/fridge poster) and usual medical care.

1. Improved diabetes self-care activities, 5% weight loss, and a 1% reduction in HbA1c level. 2. Secondary outcomes were improved diabetes-specific self-efficacy, locus of control, mean blood pressure, mean weight loss, mean waist circumference, mean HbA1c and mean total cholesterol levels, and quality of life Change in HbA1c, BMI, lipid profile, blood pressure and intakes of macronutrients, vegetables, and fruits

Task sharing interventions and lipids

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Mash R J et al South Africa, 201423

mg/dL (mean and SD) at 1 y 243 6 8 vs 42 6 9, P 5 .06, TG mg/ dL (median and IQR) at 1 y 2145 (9–224) vs 164 (102–223), P 5 .13 No significant improvement was found. Total cholesterol, mmol/mean difference between control and intervention group 20.13 (20.27 to 0.01) (weighted means as per analysis model), P 5 .066

Anand et al

anthropometric parameters (weight, BMI, WC, WHR), BP, capillary blood glucose measurements, and adherence.

No significant results for lipid profile. Post Intervention values: Cholesterol (157.0 [40.2] vs 166.9 [48.4]; P 5 .184), LDL-c (81.0 [20.6] vs 87.3 [29.9]; P 5 .191), HDL-c (42.0 [11.4] vs 38.2 [6.5]; P 5 .042)

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775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 8

Table 1

(continued ) Study design

Xavier et al India, 201625

RCT

Ali et al India and Pakistan, 201626

RCT

Task shifted to/shared with

Sample, intervention control

Acute Coronary Syndrome

Community health workers (CHW)

806, I 5 405, C 5 401

Tertiary hospital and home, 12 mo

I: community health worker–based intervention for adherence to drugs and lifestyle change after acute coronary syndrome. Four in-hospital and 2 home visits for medication adherence C: usual care

Diabetes

Nonphysician care coordinators *nonphysicians with Training in allied health fields (such as dietetics or social work), at least 6 mo of health care experience, and good organizational and basic computing skills.

1146, I 5 575 C 5 571

Outpatient diabetic clinics, 36 mo

I: Multicomponent Quality Improvement strategy comprising nonphysician care coordinators and decision-support electronic health records. C: usual care

Disease type

Setting, duration

Intervention and control group

Outcomes measured Adherence to proven secondary prevention drugs. Others were lifestyle change, including diet, exercise, and tobacco and alcohol use, which were assessed by different scores and clinical risk markers (blood pressure, heart rate, body weight, BMI, and lipids). Primary outcome was the proportion of patients from each group achieving an HbA1c level less than 7% plus a BP less than 130/ 80 mm Hg and/or an LDL-c-Cc level less than 2$59 mmol/L (,100 mg/dL) (,1.81 mmol/L [,70 mg/dL] for patients with a history of CVD).

Main lipid results from studies At 1 y, cholesterol (157.0 [40.2] vs 166.9 [48.4]; P 5 .184), LDL-c (81.0 [20.6] vs 87.3 [29.9]; P 5 .191), HDL-c (42.0 [11.4] vs 38.2 [6.5]; P 5 .042), were lower in the intervention group than in the control group but not statistically significant. Compared with usual care, intervention participants attained LDL-c level (27.86 mg/dL [CI, 210.90 to 24.81 mg/dL]). Initial TG . 1$69 mmol/L (150 mg/dL) I 5 67 (63) C 5 63 (59) not significant; Final TG . 1$69 mmol/L (150 mg/dL) I 5 16 (14) C 5 29 (27) P , .05.

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Author, country, year reported

831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886

887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 Coronary artery disease

Nurses

199 I 5 100 C 5 99

General hospital 7 mo

Nurse led transitional care vs routine care

1. C: SBP, DBP, FBS, TC, triglyceride, HDL-c, LDL-c and BMI. 2. Knowledge scale for CAD 3. SF-36

Pishdad et al Iran, 200828

Before and after

Diabetes

Nurses

214, I 5 107 C 5 107

Private Endocrinology Clinic, 12 mo

NADC model vs usual care

HbA1c, TG, LDL-c, cholesterol, duration of patient’s visit and net clinic’s income for patients under NADC were compared with those of usual care.

CHW

166

9

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Task sharing interventions and lipids

RCT

Anand et al

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Zhang et al China, 201727

Initial LDL-c . 2.58 mmol/L (100 mg/dL) I 5 74 (69%) C 5 70 (65%) not significant Final LDL-c . 2.58 mmol/L (100 mg/dL) 14 (18%) 27 (25%) P , .04 The experimental group showed significant clinical outcome SBP, t 5 5.762, P 5 .000; DBP, t 5 4.250, P 5 .000; FBS, t 5 2.249, P 5 .027; t 5 4.362, P 5 .000; triglyceride, t 5 3.147, P 5 .002, LDL-c, t 5 2.399, P 5 .018; and BMI, t 5 3.166, P 5 .002 and higher knowledge scores for coronary artery disease Significantly smaller proportions of patients had triglyceride levels of . 1.69 mmol/L and LDL-c of . 2.58 mmol/L (both P , .05) in the nurse-assisted group.

943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998

999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 10

Table 1

(continued )

Author, country, year reported

Study design

Denman et al Mexico, 201229

Before and after

Disease type

Task shifted to/shared with

Sample, intervention control

Setting, duration Community health centers, 13 wk

Low-income participants with high risk for developing CVD

Intervention and control group Health education classes by CHW for heart healthy lifestyle vs Pasos Adelante

Before and after

Diabetes

Nurse

40, I 5 20 C 5 20

Two red cross health stations, 12 wk

Nurse coaching vs usual care

Kamran et al 2016, Iran31

Before and after

Individuals with hypertension

Health promotion specialist

138, I 5 68 C 5 70

Rural health center, 6 mo

Nutritional advice by health promotion specialist vs usual care with instructional booklets

Anthropometric waist and hip circumference, weight for calculating BMI (kg/m2); clinical biomarkers fasting blood glucose, HDL-c, LDL-c-C, total cholesterol, and triglycerides and lifestyle questionnaire HbA1c, blood pressure and LDLc-C testing, and satisfaction with nursing intervention questionnaire Mean change in total fat intake, saturated fat, dietary cholesterol and weight. Clinical outcomes such as HDL-c, TC , LDLc, SBP and DBP.

Main lipid results from studies Significant changes from baseline to conclusion in LDLc (7.93 [95% CI, 1.02–14.8] mg/ dL), and triglycerides (226.4 [95% CI, 240.4 to 212.4] mg/dL).

Q10

No significant results for LDL-c.

Intervention group had significant decrease in weight, dietary fat, LDL-c and, TC, SBP and DBP compared with the control group (P , .001).

RCT, randomized controlled trial; I, intervention group; C, control group; LDL, low-density lipoprotein; HDL, high-density lipoprotein; TC, total cholesterol; TG, triglycerides; HbA1c, glycosylated hemoglobin; CVD, cardiovascular disease; BMI, body mass index; WC, waist circumference; WHR, waist-to-hip ratio; IQR, interquartile range; BP, blood pressure; FBS, fasting blood sugar; PPBS, post prandial blood sugar; COACH, counseling and advisory care for health; PCP, primary care physician; CHF, congestive heart failure; GP, general physician; NT-pro BNP, N-terminal pro-brain natriuretic peptide; cRP, C reactive protein; NADC, nurse-assisted diabetes care; SD, standard deviation.

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Navicharern et al, Thailand, 200930

Outcomes measured

1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110

Anand et al 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 Q7 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166

Task sharing interventions and lipids

General characteristics of included studies Of the 15 studies included (Table 1), 1 study was a cluster randomized trial,23 10 individual RCTs,17–22,24–27 and another 4 were before and after studies.28–31 There were 2 studies each from South Africa,23,24 Brazil,17,22 and China,18,27 1 each from India,25 Malaysia,21 Russia,20 and Turkey.19 One study was carried out as a multicenter trial in India and Pakistan.26 The ‘‘before and after’’ studies were carried out 2 each, in Iran,28,31 and 1 each from Mexico29 and Thailand.30 The earliest study in the review was reported in 2005,17 and the most recent study was reported in 2017.27 Participant follow-up ranged from 8 weeks28 to 36 months.26 In total, 6 of 15 studies reported a follow-up of 1 year. Four studies were carried out in the tertiary hospital setting, 1 each in a private clinic and diabetic clinic, and other studies in community health centers or primary care practices. Mean age reported in the studies ranged from 42 to 67 years, and the proportion of female participants ranged from 26% to 98%. Participants included in the studies reported varying past medical histories. Most studies recruited participants with diabetes or CVD. One study exclusively included dyslipidemia participants.21 Other studies included obese participants,17 individuals with hypertension,31 heart failure,20 and acute coronary syndromes.25

Task-sharing interventions in included studies Findings from trial Most of the studies (n 5 6) implemented task-sharing interventions involving nurses (Table 1). In one study each tasks were delegated to dietitian, health promoter, and care coordinator. In addition, 2 studies employed other NPHW to deliver the intervention. The type of task-sharing interventions used markedly varied across studies. Major tasksharing interventions identified were lifestyle modification health education and follow-up using the telephone or home visits. Three studies17,23,24 used lifestyle modification health education as their main intervention. Of the 3 studies, 2

11 studies17,24 focused on counseling by a dietitian on diet and physical activity as their main intervention. Another study used a nurse to impart lifestyle modification education23 and adherence management along with diet and physical activity counseling. Eight trials18–22,25–27 used both lifestyle modification and follow-up. Xavier et al25 employed NPHW to impart lifestyle modification education for patients discharged from hospital after acute coronary syndrome. Ali et al26 employed technology enabled coordinators with decision support system, and they acted as a link between diabetic patients and treating physicians. Two other studies18,26 further stressed the importance of self-monitoring for glucose. Two studies19,21 used nurses for follow-up and counseling. Four trials19,20,23,24 delivered group health education, and other 4 studies17,18,22,25 used individualized face-to-face health education. Four studies used telephone20–22,26 follow-up for the participants, 2 studies19,25 used home visits as follow-up, and Jiang et al18 used both home visit and telephone follow-up alternatively. Most studies reported a training component for the cadre delivering the interventions, although they differed with respect to content, duration, and refresher training availability. The outcome measures and results of the interventions are presented in Table 1. Findings from nonrandomized before and after studies The participants were patients with diabetes visiting a diabetic clinic in Iran,28 2 health stations in Bangkok,30 individuals with hypertension31 referred to rural health center and low-income residents of an urban area of Northern Mexico.29 Of the 4 studies, 2 used nurses28,30 for delivering interventions. The other 2 employed health promotion31 specialists and NPHW29 . Three studies28,29,31 emphasized on lifestyle modification health education. The study with NPHW delivered health education with diet and physical activity, whereas the study with nurses focused on adherence management along with diet and physical activity. Kamran et al31 described how health promotion specialist delivered nutritional education based

Figure 2 Forest plot showing changes in low-density lipoprotein (LDL) levels; comparison of task-sharing interventions with usual care. MD, mean difference; SD, standard deviation; CI, confidence intervals. FLA 5.5.0 DTD  JACL1262_proof  9 March 2018  5:17 pm

1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222

1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 12

Table 2

Summary of findings for main outcomes

Task sharing compared with usual care for dyslipidemia Patient or population: Individuals at risk of developing CVD or CVD related complications. Setting: low and middle income Intervention: Task sharing Comparison: Usual care

Outcomes

Risk with usual care

Risk with task shifting

LDL follow-up: range 2 mo to 24 mo

The mean low-density lipid was 218.47 mg/dL

HDL follow-up: range 2 to 12 mo

The mean high-density lipid was 0.37 mg/dL

TC follow-up: range 2 to 12 mo

The mean total Cholesterol was 216.99 mg/dL

TG follow-up: range 2 to 12 mo

The mean triglycerides were 218.12 mg/dL

The mean low-density lipoprotein in the intervention group was 6.90 mg/dL lower (11.81 lower to 1.99 lower) The mean high-density lipoprotein in the intervention group was 0.29 mg/dL higher (1.12 lower to 1.94 higher) The mean total cholesterol in the intervention group was 9.44 mg/dL lower (17.94 lower to 0.93 lower) The mean triglycerides in the intervention group was 14.31 mg/dL lower (33.32 lower to 4.69 higher)

Relative effect (95% CI)

No of participants (studies)

Quality of the evidence (GRADE)

–

2034 (8 RCTs)

44

Low

–

888 (7 RCTs)

44

Low

–

888 (7 RCTs)

44

Low†,‡,x

–

487 (4 RCTs)

4


Very lowǁ,{,#

Comments

CI, confidence interval; MD, mean difference; LDL, low-density lipoprotein; HDL, high-density lipoprotein; TC, total cholesterol; TG, triglycerides; CVD, cardiovascular disease; RCT, randomized controlled trial. GRADE Working Group grades of evidence. High quality: We are very confident that the true effect lies close to that of the estimate of the effect. Moderate quality: We are moderately confident in the effect estimate: The true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low quality: Our confidence in the effect estimate is limited: The true effect may be substantially different from the estimate of the effect. Very low quality: We have very little confidence in the effect estimate: The true effect is likely to be substantially different from the estimate of effect. *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). †High risk of bias. ‡Wide variation in study population, intervention and task shifting strategies. xFew study participants with wider CI. ǁ High risk of bias characterized by no Random Sequence Generation, Poor outcome assessment. {Variations in interventions and study population. # Fewer study participants with wide variation in features.

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Anticipated absolute effects* (95% CI)

1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334

Anand et al 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390

Task sharing interventions and lipids

13

Figure 3 Forest plot showing changes in high-density lipoprotein (HDL) levels; comparison of task-sharing interventions with usual care. MD, mean difference; SD, standard deviation; CI, confidence intervals.

on Dietary Approach to Stop Hypertension diet. Denman et al29 conducted physical activity sessions 1 to 3 times per week. One study30 had employed nurses for health education and follow-up. Two studies28,30 used individual health education, whereas the other 2 studies29,31 used group health education. Navicharern et al30 used telephone follow-up for their participants. One study compared the same participants before and after intervention without a control group,29 and the other 3 studies had a control group, which received usual care.28,30,31 The outcome measures are presented in Table 1. Kamran et al found that at 6 months after intervention, LDL-c and TC decreased significantly in the intervention group compared with the control group (P , .001). Navicharern et al30 reported no differences in the levels of LDL-c for participants after the intervention. At the end of 3-month follow-up, Denman29 found significant differences from baseline for TC (14.2 mg/dL [95% CI, 6.6–21.8]), HDLc (211.1 mg/dL [95% C, 214.1 to 28.1]), and LDL-c (21.6 mg/dL [95% CI, 14.0–29.2]). At the end of 6-month follow-up, Pishdad28 reported reduction in the proportion of patients with TG concentrations of . 1$69 mmol/L (150 mg/dL) from 63% to 14% (nurse assisted) vs 59% to 27% (usual care) (P , .05). In addition, for LDL-c concentrations of . 2.58 mmol/L (100 mg/dL), proportion of patients decreased from 69% to 18% (nurse assisted) vs 65% to 25% (usual care) (P , .04).

Quality of included studies Overall, some risk of bias was evident in all the studies included in the review (Table S1, online supplement). Eight RCTs18,20–27 clearly described a random sequence generation method (eg, computer generated random number table) and were deemed to be at low risk. Two RCTs17,19 did not report the method of randomization and hence marked as at unclear risk. Allocation concealment was clearly specified in 5 studies,18–20,24,25 and they were assigned low risk. One RCT22 reported no allocation concealment, and in another 4,16,17,21,23 the risk was unclear. Overall, most RCTs17,20–24,26,27 were at risk of performance bias. Some of the studies17,19,21 did not clearly mention about blinding

of outcome assessors. Most of the studies had a relatively lower loss to follow-up and used intention to treat analysis. However, the attrition rate was more than 50% in the cluster RCT.23 Low risk of bias for selective reporting was observed in 4 RCTs,21–23,26 whereas it was difficult to report it based on available information in the remaining studies. Using the National Heart, Lung, and Blood Institute scale, the before and after studies were assessed for methodological quality (Table S2, online supplement). All the before and after studies reported study objectives, although 1 study29 did not clearly mention the eligibility criteria. Three29–31 of 4 studies did report on sample size calculation. All 4 studies28–31 described the intervention and outcome measures. Outcome assessors were not blinded in any reported studies. All 4 studies were relatively of shorter duration, and the loss to follow-up was ,20%. Low-density lipoprotein cholesterol Eight RCTs were included in the meta-analysis of the effect of task-shifting interventions on LDL-c levels. In total, 2034 study participants (intervention group [n 5 1024], control group [n 5 1010]) were included in the final meta-analysis. The intervention period ranged from 2 to 24 months. The pooled MD based on random effects model was 26.90 mg/dL; (95% CI 211.81 to 21.99; P 5 .03; Fig. 2). The chi-square test showed significant heterogeneity (c2 5 15.46, P 5 .03, I2 5 54.7%). Test for funnel plot asymmetry was not significant (P 5 .86) (Fig. S1). The overall quality of evidence based on GRADE was however ‘‘low’’ (Table 2). Subgroup analysis (LDL-c) In individuals with diabetes, the pooled estimate was 24.46 mg/dL (95% CI: 210.40 to 1.48) (Fig. S2), whereas it was 212.79 mg/dL (95% CI: 218.26 to 27.32) in patients with coronary artery disease (CAD) (Fig. S2). Based on the task-sharing group, pooled estimate for nurses was 26.98 mg/dL (95% CI: 214.91 to 0.94), whereas it was 26.56 mg/dL (95% CI: 221.70 to 8.52) in studies involving dietitians (Fig. S3).

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Figure 4 Forest plot showing changes in total cholesterol levels; comparison of task-sharing interventions with usual care. MD, mean difference; SD, standard deviation; CI, confidence intervals.

High-density lipoprotein cholesterol Seven RCTs were included in the meta-analysis of the effect of task-sharing interventions on HDL-c levels. A total of 888 study participants (intervention group [n 5 449], control group [n 5 439]) were included in this metaanalysis. Intervention period ranged from 2 to 12 months. The pooled estimate in the random effects model indicated no additional benefit in the intervention group in comparison with the usual care group (MD 5 20.29 mg/dL; 95% CI 20.88 to 1.47; P 5 .62; Fig. 3). The chi-square test showed no heterogeneity (c2 5 4.06, P 5 .66, I2 5 0.0%). Egger’s regression test for funnel plot asymmetry showed no publication bias with P value .76 (Fig. S4). The overall quality of evidence based on GRADE was ‘‘low’’ (Table 2). Subgroup analysis (HDL-c) The pooled MD of HDL-c levels was 0.17 mg/dL (95% CI: 25.80 to 6.15; Fig. S5) and 0$29 mg/dL (95% CI: 21.12 to 21.70; Fig. S5) in patients with diabetes and CAD, respectively. Interventions with nurses resulted in an MD of 0.65 mg/dL (95% CI: 20.65 to 1.96; Fig. S6), whereas it was 21.24 mg/dL (95% CI: 23.93 to 1.46; Fig. S6) in studies involving dietitians. Total cholesterol Seven RCTs were included in the meta-analysis of the effect of task-sharing interventions on TC levels. A total of 888 study participants (intervention group [n 5 449], control group [n 5 439]) were included in this meta-analysis.

Intervention period ranged from 2 to 12 months. The pooled estimate in the random effects model differ between the intervention and control group (MD 5 29.44; 95% CI 217.94 to 20.93; P 5 .01; Fig. 4). The chi-square test showed statistical heterogeneity (c2 5 20.83, P 5 .00, I2 5 71.2%). There was no publication bias in the Egger’s regression test (P 5 .23; Fig. S7). The overall quality of evidence based on GRADE was ‘‘low’’ (Table 2). Subgroup analysis (TC) Pooled estimates for the effect of interventions on TC levels in patients with diabetes and CAD were 24.13 mg/ dL (95% CI: 217.53 to 9.26; Fig. S8) and 216$57 mg/dL (95% CI: 224.59 to 28.56; Fig. S8), respectively. Interventions involving nurses resulted in an MD of 211.07 mg/dL (95% CI: 222.50 to 0.36; Fig. S9), whereas it was 25.38 mg/dL (95% CI: 216.36 to 5.59; Fig. S9) in studies involving dietitians. Triglycerides Four RCTs were included in the meta-analysis of the effect of task-sharing interventions on TG levels. A total of 487 study participants (intervention group [n 5 248], control group [n 5 239]) were included in this meta-analysis. Intervention period ranged from 2 to 12 months. The pooled estimate, based on random effects model, did not differ between groups (MD 5 214.31 mg/dL; 95% CI 233.32 to 4.69; P 5 .13; Fig. 5). The chi-square test showed no statistical heterogeneity (c2 5 5.90, P 5 .11,

Figure 5 Forest plot showing changes in triglyceride levels; comparison of task-sharing interventions with usual care. MD, mean difference; SD, standard deviation; CI, confidence intervals. FLA 5.5.0 DTD  JACL1262_proof  9 March 2018  5:17 pm

1503 1504 1505 1506 1507 1508 1509 1510 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1556 1557 1558

Anand et al 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614

Task sharing interventions and lipids

I2 5 49.1%). There was no publication bias in the funnel plot asymmetry test (P 5 .81; Fig. S10). The overall quality of evidence based on GRADE was ‘‘very low’’. (Table 2). Complete information of GRADE assessment is provided in supplementary file (Table S3, online supplement). Subgroup analysis (TG) Pooled estimate of intervention effect in patients with CAD was 220.16 mg/dL (95% CI: 245.90 to 5.59; Fig. S11). Pooled estimates for TG based on the interventions implemented by nurses was 220.42 mg/dL (95% CI: 238.80 to 22.03; Fig. S12). Detailed PRISMA check list is provided in the Figure S4, online supplement.

Discussion

15 reasons may be the lack of policy on the eligibility for medicine prescription by NPHW in LMICs. On the contrary, many qualified nonphysician providers who have adequate practice credentials (eg, advanced practice nurses, nurse specialists, and advanced practice pharmacists) under the supervision of a physician can prescribe lipid-lowering medicines in Western Settings.36 For example, the Accreditation Council for Clinical Lipidology in the United States offers a specialization certification for Clinical Lipid Specialists. Therefore, NPHW in LMICs may benefit from additional training and accreditation in lipid management. In addition, most of the interventions included in the task-sharing strategy in LMICs are of nontechnical nature or with clear demarcation of the boundaries from the usual tasks of physicians. Expanding the scope of task-sharing and deeper involvement of NPHW in management of cardiovascular risk may be more effective in LMIC settings.

Summary of main findings Our systematic review identified 15 studies (11 RCTs and 4 quasi-experimental studies) using interventions that are shared with NPHW for managing cardiovascular risk. The results of meta-analysis of RCTs demonstrate that moderate but statistically significant reduction in LDL-c and TC with task-sharing interventions. Efficacy data of task-sharing intervention on HDL-c and TG are however sparse, and the pooled estimates in their respective metaanalyses suggest no difference from usual care in terms of risk reduction. The studies used a range of strategies for task-sharing including one-to-one counseling to group education and follow-up by home visits or by telephone contacts. The overall quality of evidence available is rated as either very low or low based on GRADE criteria.

Comparison of the effect of interventions with previous systematic reviews Task-sharing intervention strategies have been successfully implemented in reproductive and family planning services32 and chronic disease management such as HIV/ AIDS33 The reduction in LDL-c level associated with task-sharing intervention is similar to the findings from pooled effect of multiple interventions on CVD risk reduction in LMICs.34 Chen et al demonstrated no effect of comprehensive lifestyle education program in patients with type II diabetes on lipid profile.35 Nevertheless, in our subgroup analysis, patients with type II diabetes demonstrate a reduction in LDL-c with task-sharing interventions.

Role of NPHW involved in the intervention Despite the involvement of high-risk patients in almost all studies, prescriptions for even the basic medications are not part of the shared interventions. One of the potential

Enablers and barriers of task-sharing interventions Some of the enablers and barriers in implementing tasksharing intervention models as identified in our review are similar to those of Ogedegbe et al8 and Joshi et al.9 The enabling factors are the structured training of NPHW, guidelines- or algorithm-based management, and appropriateness of the intervention model in bridging the gap between hospital- and home-based care. The decisionmaking process of care coordinators with the help of an algorithm is a promising strategy.25 More active involvement of NPHW in disease management, skill building, and structured training and utilization of appropriate technologies may help to improve health outcomes. Although there are attempts to incorporate training component for the NPHW, a formal strategy to align the training with the current regulation and accreditation of trained health care worker are absent even as a policy document in most of the LMICs. Barriers include poor participant retention due to lack of adequate communication between health promoters and patients regarding the timings of health education class, difficulty in accessing care due to distance, and infrastructural limitations such as absence of a suitable space at the health care facility for group health education.

Quality of evidence We assessed the quality of evidence from the systematic review based on GRADE approach. For LDL-c and HDL-c analyses, we assigned the quality of evidence as ‘‘Low’’ because there were serious inconsistencies, indirectness, and imprecision in the pooled analyses. The quality of evidence for TC was downgraded by 2 levels due to serious levels of risk of bias and imprecision with suspected publication bias. For TG, the quality of evidence was downgraded by 3 levels because there were very serious

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levels of risk of bias and imprecision. Although the statistical heterogeneity was within limits, the study population, intervention, and task-sharing group were different across different trials.

Strengths and limitations

our pooled analyses. To support task-sharing policies in LMICs, additional evidence from well-designed and adequately powered RCTs of structured intervention models are required.

Acknowledgments

One of the main strength of the review is the extensive search of literature in multiple databases. The inclusion of studies with different methodologies such as randomized trials and quasi-experimental studies provide more insights into factors influencing NPHW led lipid management. However, one of the limitations is possibility of missing relatively new publications. We have mitigated this by updating the search up to 30 June 2017. We also acknowledge that inclusion of studies in English only must have led to missing of articles especially in Chinese, Spanish, or other foreign languages, which do not provide abstracts in English. We did not restrict the inclusion of studies, which targeted multiple CVD risk factors at the same time rather than managing dyslipidemia alone. Therefore, assessing effectiveness of task-sharing interventions on managing lipids alone may have underestimated the impact of global cardiovascular risk reduction. We acknowledge that this is a limitation as in practice managing lipids is carried out along with managing overall cardiovascular risk.

Completeness and applicability of evidence The study population included in the selected studies is at different levels of CVD risk, and varies from obese individuals to CAD patients. Hence, we cannot confirm whether the effect of interventions can be generalized to a population level. New tasks on lifestyle modification or follow-up are shared with mostly nurses, dietitians, and other NPHW. Lifestyle interventions evaluated mostly are general in nature with a sparse description on the structure and intensity. Detailed descriptions are not available in terms of the training given to the NPHW on lifestyle interventions. Given the low quality of studies available, well-structured task-sharing interventions that are culturally acceptable and contextually relevant need to be developed and tested in LMIC settings.

Conclusion Our study findings highlight scarce data on the widespread implementation and effectiveness of task-sharing strategies, specifically managing dyslipidemia in LMIC settings. Evidence from qualitative and quantitative synthesis is insufficient to state that task-sharing interventions are effective in managing dyslipidemia in LMICs. The risk of bias and small study size affected the overall evidence quality generated from RCTs, even though we demonstrate LDL-c and TC reduction with task-sharing interventions in

P.J. is supported by Clinical and Public Health Intermediate Fellowship from the Wellcome Trust/DBT India Alliance (2015–2020). A.T.N. is an encore fellow of the International Research and Training Fund of the University of Melbourne. This research did not receive any specific grant from funding agencies in the public, commercial, or not-forprofit sectors. Authors’ contributions: G.N , and J.C. did the literature search. A.T.N., L.M.J., and P.J. appraised study quality, extracted, and analyzed the data. A.T.N., L.M.J., P.J., and D.P. interpreted data. A.T.N. and L.M.J. wrote the first draft of the article. P.J., and D.P. critically evaluated the article. A.T.N., L.M.J., G.N., J.C., D.P., and P.J. revised the article. Declaration of interests: All other authors declare no competing interests.

Supplementary data Supplementary data related to this article can be found at https://doi.org/10.1016/j.jacl.2018.02.008.

References

Q8

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